Jurnal Ilmu Komputer dan Sistem Informasi

Implementasi Content-Based Filtering dan Singular Value Decomposition untuk Rekomendasi Film

2026-07-27T12:19:43+07:00

The growth of online video catalogs creates information overload that makes it difficult for users to discover movies matching their preferences. This study develops and evaluates two movie recommender approaches: content-based filtering using TF-IDF and cosine similarity, and collaborative filtering using Singular Value Decomposition (SVD). The dataset includes 4,803 movies with production-credit records and 100,004 user-rating interactions. The research stages comprise data cleaning and integration, content representation, latent-factor modeling, a 75:25 train-test split, and evaluation using Precision and Root Mean Squared Error. The content-based experiment achieved a Precision of 0.70 based on genre overlap, while director- and actor-based recommendations obtained a precision of 1.00 because the ranking features were identical to the relevance criteria. The SVD model achieved an RMSE of 0.9007 and generated personalized recommendations from user-rating patterns. The study contributes an evaluation of two baselines with different objectives, an analysis of potential bias in precision measurement, and an emphasis on consistent movie identifiers across datasets. Content-based filtering is effective for retrieving movies with similar metadata, whereas SVD captures latent user preferences. However, the results of the two approaches must be interpreted using metrics appropriate to their respective objectives.

Analisis Sentimen Berbasis Aspek pada Ulasan Aplikasi JConnect Mobile Menggunakan IndoBERT dan mBERT

2026-07-03T12:20:50+07:00

JConnect Mobile is a mobile banking application developed by Bank Jatim that provides various digital banking transaction services. Although the number of users has continued to increase, the application still receives numerous complaints regarding its interface, features and performance, and service quality, as reflected in user reviews and its relatively low application rating. This study aims to compare the performance of the IndoBERT and mBERT models for aspect-based sentiment classification of JConnect Mobile user reviews. The dataset consists of 4,344 user reviews collected from Google Play Store and App Store between 2021 and 2025. The research methodology includes data collection, data labeling, preprocessing, feature extraction, modeling, and evaluation. The experiments were conducted using 5-fold cross-validation with 24 experimental scenarios involving combinations of hyperparameters, including 5 and 10 epochs, dropout rates of 0.2, 0.4, and 0.6, and batch sizes of 16 and 32. The results of the 5-fold cross-validation show that IndoBERT achieved the best performance, with mean F1-scores of 0.86 for the interface aspect, 0.83 for the features and performance aspect, and 0.74 for the service aspect. Based on these results, IndoBERT was selected as the best-performing model because it consistently outperformed mBERT across all aspects. Evaluation on the test dataset further demonstrated that the best-performing model achieved F1-scores of 0.80 for the interface aspect, 0.83 for the features and performance aspect, and 0.81 for the service aspect.

Implementasi Metode Weighted Moving Average dan Least Square Untuk Persediaan Obat Pada Apotek Kimia Farma

2026-07-23T14:47:47+07:00

Drug inventory management is an important aspect of pharmacy services because it directly affects medicine availability for patients. Inaccurate inventory planning may lead to stock shortages (stockout) or excess inventory (overstock), which can reduce service quality and increase storage costs. This study aims to develop a drug inventory forecasting system for Kimia Farma Pharmacy using the Weighted Moving Average (WMA) and Least Square methods. The research employed the Research and Development (R&D) approach, while the system was developed using the Rapid Application Development (RAD) method. The dataset consisted of historical sales records of ten types of medicines from January to November 2023, collected through observation, interviews, and literature review. The results indicate that the developed system is capable of automatically forecasting future drug inventory based on historical sales data. The Weighted Moving Average method provides forecasts that are more responsive to recent demand changes by assigning greater weights to the latest observations, while the Least Square method generates forecasts based on sales trends. The developed system assists pharmacy staff in determining appropriate inventory levels, thereby reducing the risk of stock shortages and overstock situations. Therefore, the proposed forecasting system can improve the effectiveness of drug inventory management at Kimia Farma Pharmacy.

Desain dan Pengembangan Sistem Informasi Manajemen Proyek Berbasis Web di Apotek Cemara

2026-08-06T21:53:41+07:00

Project management at Cemara Pharmacy faced challenges such as poor team coordination, progress monitoring difficulties, and data inaccuracies, hindering operational efficiency in the pharmaceutical sector. This study aimed to design and develop a web-based project management information system to support real-time planning, execution, and evaluation of projects. The research employed the Waterfall model, with data collection via field observations, interviews with managers and staff, document analysis, and literature review; the population comprised Cemara Pharmacy staff as primary participants, using UML (Use Case, Activity, Sequence, Class Diagrams), WBS, Gantt Chart, and PERT as instruments; data analysis involved functional, integration, and User Acceptance Testing (UAT). Results demonstrated that the Laravel- and MySQL-based system enhanced transparency, reduced administrative errors, and improved efficiency by up to 30%, with user evaluations highlighting interface ease and multi-platform accessibility. The study concludes that the system significantly contributes to professional project management in pharmacy SMEs, implying broader operational digital transformation.

Analisis Sentimen Debat Capres dan Cawapres Indonesia 2024 Menggunakan Metode Bert

2026-08-13T14:54:19+07:00

The 2024 Indonesian Presidential and Vice Presidential Candidate Debate, broadcast on the YouTube channel of the Indonesian General Elections Commission (KPU), generated thousands of public comments reflecting societal sentiment toward the candidates, yet these opinions have not been systematically examined. This study aims to analyze the sentiment of YouTube comments on the debate using the Bidirectional Encoder Representations from Transformers (BERT) method. A total of 2,500 comments were collected via the YouTube Data API from five debate sessions, then cleaned through a pre-processing stage and automatically labeled using the InSetLexicon dictionary into three categories: positive, negative, and neutral. After removing duplicate data, 2,362 clean records were obtained and divided into training and testing data with an 80:20 ratio. The IndoBERT model was then fine-tuned to classify comment sentiment. The results show that the sentiment distribution was dominated by positive comments (1,107), followed by negative (660) and neutral (595) comments. Model evaluation using a confusion matrix yielded an accuracy of 76.5%, with the highest precision, recall, and F1-score values in the positive class at 87.78%, 85.39%, and 86.57%, respectively. These findings indicate that the BERT method is fairly effective in analyzing the sentiment of Indonesian-language comments in the context of political debates on YouTube, while also contributing a mapping of public opinion toward candidates and debate issues that can serve as a reference for future Indonesian-language political sentiment analysis research.

Penerapan Algoritma K-Means Untuk Klasterisasi Pasien Berdasarkan Data Penyakit

2026-08-18T07:54:45+07:00

Sibuhuan Community Health Center (Puskesmas Sibuhuan) experiences a continuous increase in patient visit data every month. However, the utilization of these data is still limited to administrative reporting, resulting in the underutilization of information regarding patient group characteristics. This study aims to implement the K-Means algorithm for patient clustering and to identify patient characteristic patterns based on age, gender, and disease variables. This research employed a quantitative method with a data mining approach. The data used were secondary data consisting of 1,000 patient visit records from Puskesmas Sibuhuan during the January 2026 period. Following data cleaning, 104 records containing missing values were removed, resulting in 896 records used for the clustering process. The research stages included data preprocessing, Min-Max normalization, determining the optimal number of clusters using the Elbow Method, clustering using the K-Means algorithm, and evaluating the clustering results using the Silhouette Coefficient. The results showed that the optimal number of clusters was three, Cluster 0 consisted of 423 patients, predominantly diagnosed with diseases of the respiratory, digestive, and circulatory systems. Cluster 1 comprised 320 patients, with the most prevalent diagnoses involving symptoms, signs, and abnormal clinical findings, as well as pregnancy, childbirth, and the puerperium. Cluster 2 consisted of 153 patients, predominantly diagnosed with infectious and parasitic diseases, endocrine, nutritional and metabolic diseases, and mental and behavioral disorders. The evaluation produced a Silhouette Coefficient value of 0.6384, indicating that the clustering results were of good quality. The findings of this study are expected to provide supporting information for Puskesmas Sibuhuan in identifying patient group characteristics and to assist in planning more targeted healthcare services.

Sistem Informasi Sejarah Peradaban Islam Sebagai Media Literasi Digital dan Moderasi Beragama Berbasis Mobile

2026-09-25T23:18:50+07:00

Islamic Civilization History learning at MAN 1 Medan still relies largely on conventional media, while students' Android smartphones have not been optimally directed toward learning activities. This study aims to design and develop an Android-based learning information system that integrates Islamic Civilization History content, digital literacy, and religious moderation. The study applies a Research and Development approach with Rapid Application Development for software construction. User requirements were identified through observation, interviews, questionnaires, and literature review. The application was developed using Kodular with Airtable as the database. It enables teachers to manage learning materials, videos, quizzes, and scores, while students can access materials, videos, quizzes, and learning results. Functional evaluation through black-box testing covered 12 scenarios across teacher login, learning materials, videos, quizzes, account registration, and student login modules. All scenarios were valid, resulting in a 100% functional success rate. These findings indicate that the prototype satisfies the designed core functional requirements. Nevertheless, its effectiveness in improving digital literacy and religious moderation cannot yet be established because the source manuscript does not report UAT results or experimental testing with students.

Implementasi BERTopic untuk Menganalisis Isu Program Makan Bergizi Gratis pada Media Sosial X

2026-09-28T12:35:27+07:00

The Free Nutritious Meal Program is one of the government policies widely discussed on social media X. The large number of posts makes manual issue identification inefficient; therefore, an automatic topic grouping method is needed. This study aims to implement BERTopic to map issues related to the Free Nutritious Meal Program on social media X. Data were collected through scraping using the keywords “Program Makan Bergizi Gratis” or “MBG” from January 6, 2025, to October 6, 2025. From 37,368 raw posts, 10,637 data remained after filtering. The research stages include text preprocessing, topic modeling using BERTopic, evaluation, visualization, and topic labeling. The best result was obtained with min_cluster_size 40, producing a coherence score of 0.740873, stability score of 0.753521, and final score of 0.747197. BERTopic generated 10 main issues, including child nutrition benefits, policy and budget, school implementation, food safety, supervision, SPPG operations, and food price stability. The results show that BERTopic can representatively map public policy issues from short Indonesian social media texts on X.

Sistem Informasi Monitoring Dan Penjadwalan Proyek Pada Cv. Sahabat Kreasi Nusantara

2026-10-01T11:45:20+07:00

The dynamic nature of the creative industry demands fast and professional project management. CV. Sahabat Kreasi Nusantara faces challenges in monitoring work progress and developing project schedules due to its continued reliance on manual methods such as WhatsApp and Microsoft Excel. Consequently, the Chief Operating Officer (COO) finds it difficult to distribute the team's workload fairly, risking project delays. This research aims to develop a web-based project monitoring and scheduling information system to optimize company operations. The development methodology employed is the Prototype method. The novelty of this research lies in the implementation of the Simple Additive Weighting (SAW) method to determine task priorities based on criteria such as project value, deadlines, difficulty levels, estimated duration, risks, and team workload. The system is developed using the PHP programming language with the Laravel framework and a MySQL database. The result of this research is a platform capable of presenting real-time progress data, facilitating team coordination through a chat feature, and providing objective scheduling recommendations. With this system, the company is expected to improve work efficiency, accelerate decision-making, and minimize the risk of project delays in a structured manner.

Sistem Informasi Absensi Siswa Berbasis Android Menggunakan Location Based Service dan Detect Mock Location

2026-08-18T16:05:14+07:00

SMAS Darussalam Medan is a private high school located at Jl. Darussalam No.26, Sei Sikambing D, Kec. Medan Petisah, Kota Medan, North Sumatra 20119. The student attendance process is still carried out by recording attendance in an attendance book and compiling the attendance data, which has led to several issues, particularly in terms of monitoring attendance by parents. There are still some students who skip school. If parents/guardians want to obtain information about student attendance, they must come directly to the school and check the attendance book and search for attendance data one by one, which requires a lot of time, energy, and money. The purpose of this research is to develop an Android-based information system that can be used for student attendance using location-based services and mock location detection. This feature functions to obtain the student's current location when taking attendance and prevent students from cheating by using the Fake GPS (false location) application. The information system was built using the Kodular framework and Airtable database. The system development method used was the waterfall method. With this information system, it is hoped that parents/guardians can obtain accurate student attendance information via their Android smartphones.

Klasifikasi Kualitas Sinyal Radio FM Berbasis Pengolahan Citra Spektrum pada Berbagai Titik Observasi

2026-07-05T01:23:01+07:00

The quality of FM radio broadcast reception is strongly affected by radio wave propagation characteristics, such as distance, geographical contour, building density, and vegetation, while conventional evaluation methods using a spectrum analyzer are relatively expensive and inflexible. This study aims to develop a simple and economical method for evaluating FM radio signal quality based on spectrum image processing captured through GQRX software and an RTL-SDR Software Defined Radio module. Data were collected at 20 observation points spread across four cardinal directions (North, East, South, West) with five distance variations (2, 4, 6, 8, and 10 km) from the central reference point at the Great Mosque of Palembang, producing 1,424 spectrum images. Each image was processed through spectrum panel detection, power-axis scale reading using Optical Character Recognition (OCR), signal curve extraction, Gaussian filter smoothing, and signal peak detection to calculate the Signal-to-Noise Ratio (SNR), which was then classified according to the TIPHON standard. The results show that the average SNR ranged from 27.06–36.90 dB, with a fluctuating and non-linear distribution pattern with respect to distance. Of the 20 observation points, 18 points obtained a dominant Outstanding category and 2 points obtained an Excellent category, with none falling into the Good, Fair, or Bad categories. These results demonstrate that the RTL-SDR and GQRX-based spectrum image processing approach is effective, economical, and replicable as an FM radio signal quality evaluation method.

Monitoring Radio Frekuensi Berbasis Deep Learning Untuk Klasifikasi Sinyal, Clustering dan Rekomendasi Amplifier

2026-10-02T20:37:57+07:00

Monitoring of radio frequency spectrum is an important activity in managing frequency usage to prevent interference between users. This study proposes a deep learning-based radio frequency monitoring system using SDR# spectrum images with RTL-SDR receiver implemented in MATLAB. The system integrates GoogLeNet with transfer learning to extract visual features from spectrum images, Autoencoder to reduce feature dimensions to a 32-dimensional latent space, and K-Means algorithm to classify spectrum conditions into Cluster A (good signal), Cluster B (moderate signal), and Cluster C (weak signal). AM/FM signal modulation identification is performed using the OCR method on the SDR# image header with FM frequency range 87-108 MHz and AM 109-137 MHz. The system was tested at 20 measurement points in 4 cardinal directions with distance variations of 2 km to 10 km using 909 SDR# spectrum images. Test results show an OCR Success Rate of 16.4% as a measure of frequency text-reading success, indicating that SDR# is not optimal as an image source in this approach. Among the images successfully recognized by OCR, signal modulation classification based on frequency range achieved 100% accuracy, precision, and recall as a measure of classification correctness. The system also produced spectrum condition clustering using K-Means (k=3) with a distribution of Cluster A (56.8%), Cluster B (30.4%), and Cluster C (20.7%), and RF Amplifier recommendation based on FM signal dominance. Future research is recommended to use GQRX to improve system performance.

Implementasi Sistem Informasi Penjualan dan Manajemen Preloved Pada Toko Belipolo.id Berbasis Web

2026-10-02T21:01:22+07:00

The growth of the preloved business, which focuses on selling secondhand items in good condition, has seen a rapid upward trend among young people due to its affordability and support for eco-friendly lifestyles. However, BELIPOLO.ID, a store operating in this sector, still encounters operational challenges because its promotional processes utilize social media such as Instagram and WhatsApp, while transaction records and stock updates have not been systematically maintained. These constraints lead to stock monitoring errors, unstructured product data management, and delayed product information for customers. This study aims to build and implement a web-based sales and management information system specifically tailored for the BELIPOLO.ID. The research uses a Research and Development (R&D) approach with the Waterfall development model, covering requirements analysis, design, implementation, testing, and maintenance. The system was developed using the Laravel framework and MySQL and evaluated using Black Box Testing. The system integrates product, category, stock, sales transaction, payment proof, and owner Dashboard management within a single platform. Testing of 10 functional scenarios showed that all scenarios were successfully executed, resulting in a 100% success rate. The implementation also provides automatic stock updates after transactions and presents sales information based on stored transaction data. These results indicate that the system can support centralized and structured management of product, stock, and transaction data.

Implementasi Sistem Informasi Manajemen Inventori Berbasis Website pada Coffee Shop di SOC Media Group

2026-10-04T09:44:01+07:00

Raw material inventory management is crucial for the operations of Food and Beverage businesses, including the coffee shop units at SOC Media Group. Currently, inventory recording at the two branches—Prasravana Coffee Eatery and Kopi Bahagia—is still performed using conventional methods such as logbooks and spreadsheets, leading to data inaccuracies and a lack of real-time monitoring. This study aims to design a web-based inventory management information system capable of managing raw material data in real-time. The research employs the Research and Development (R&D) methodology using the Waterfall development model. The results demonstrate that the developed system successfully implements recipe management for automatic stock deduction based on Point of Sale (POS) transaction data, critical stock notifications, and inventory reporting. Functionality testing using Black-Box Testing confirmed that all modules operate 100% in accordance with specifications. User Acceptance Testing (UAT) results also indicate excellent system acceptance, with positive responses ("Strongly Agree" and "Agree") reaching 100% across all user levels (Admin, Management, and Owner). Thus, the information system is proven to be valid and reliable for users, while minimizing the risks of data inaccuracy associated with conventional stock tracking. For future development, the addition of a stock requirement forecasting feature based on sales trends is recommended.

Evaluasi Kinerja Pegawai Pengguna Siakad: Studi Simulasi Model Delone & Mclean

2026-06-24T13:35:06+07:00

The era of digital transformation requires higher education institutions to optimize their information technology investments to boost employee productivity. This study aims to examine and analyze the effects of System Quality and Information Quality on Employee Performance, with User Satisfaction serving as a mediating variable within the context of Academic Information System (SIAKAD) utilization. This study employs a quantitative causal approach through a structural simulation study. This step was taken to overcome internal institutional data privacy regulatory restrictions by generating structured data based on empirical parameters. Simulation data were generated to represent a scenario of 116 observation data points adapted to the profile characteristics of administrative and academic staff using SIAKAD at a private higher education institution in Central Java. Model analysis was resolved using Variance-based Structural Equation Modeling (PLS-SEM) via SmartPLS 4.0 software. The evaluation results indicate that System Quality and Information Quality have positive and significant effects on User Satisfaction. Furthermore, User Satisfaction demonstrated a strong direct effect on Employee Performance. Hypothesis testing confirms that User Satisfaction acts as a crucial mediating variable. The novelty of this research lies in testing the stability of technology success theory integration through a controlled computational experiment. Practical implications emphasize the importance of data accuracy and application response time stability to eliminate operational bottlenecks among employees.

Pengembangan Website Profil Desa sebagai Media Informasi dan Promosi Potensi Desa Klambir 5

2026-06-14T19:41:39+07:00

Village information digitalization requires a platform capable of presenting official information in a structured manner while extending the promotion of local potential. This study aims to develop the Klambir 5 Village profile website in Hamparan Perak District, Deli Serdang Regency, as an information and village-potential promotion medium. The study applies a Research and Development approach using the Waterfall model, consisting of requirements analysis, design, development, testing, implementation, and evaluation. Data were collected through observation, interviews, documentation, literature review, and questionnaires. The resulting website provides village profiles, government information, public services, news, galleries, village potential, contact information, and an administrator page. According to the test tables in the research report, all 14 black-box scenarios were recorded as successful, yielding 100% functional success. Responsive testing on five screen sizes showed that the interface adapted appropriately, while compatibility testing indicated successful operation on Google Chrome, Mozilla Firefox, Microsoft Edge, Android browsers, and Safari. However, the user-evaluation table in the report does not yet contain empirical scores; therefore, a questionnaire-based feasibility percentage cannot be reported. Technically, the website fulfills its basic role as a village information center and promotion medium, while user-acceptance validation should be completed before drawing a quantitative feasibility conclusion.

Peningkatan Visibilitas Listing Kos dan Kontrakan Berbasis Web Menggunakan Design Science Research Methodology

2026-06-07T21:51:22+07:00

Web-based information systems have emerged as a primary medium for searching and promoting boarding house and rental accommodations, particularly in campus areas. However, the growing number of listings registered on a single digital platform introduces new challenges concerning information visibility. Accommodations with strategic locations and adequate facilities are often difficult to discover by prospective tenants due to the absence of a systematic mechanism for regulating display priority. This study aims to develop a listing promotion feature integrated within a web-based boarding house and rental information system around the Nusa Putra Sukabumi Campus. The Design Science Research Methodology (DSRM) was employed, emphasizing artifact design and evaluation as the core of the research process. The system was built using the Laravel framework with a MySQL database. Evaluation was conducted through Black Box Testing across 20 functional scenarios and Usability Testing using a Likert Scale 1–5 questionnaire involving 15 respondents (8 boarding house seekers and 7 owners). All system functions performed correctly. Usability Testing yielded an average score of 4.2 out of 5 (good category). Functionally, the listing promotion feature successfully placed promoted properties at the top of the search page with a PROMO badge label, replacing the previous unordered random display. Based on the DSR knowledge contribution matrix, this research is classified as Improvement.

Perancangan Sistem Izin Rekomendasi Penggunaan Jalan Dinas Perhubungan Kota Jambi

2026-07-04T10:43:30+07:00

Indonesia's strategic ports face rising maritime threats like piracy and terrorism, necessitating effective ISPS Code implementation. This study analyzes the application of ISPS Code (X) and its impact on security effectiveness (Y) at the International Bulk Liquid (IBL) Terminal, Gresik Port. Employing a quantitative descriptive-explanatory approach, data were collected via Likert-scale questionnaires from 50 purposive respondents (security personnel, PFSO, operators) during January-June 2025, supported by observations and secondary documents. Instruments were validated (r-hitung > 0.235; sig. <0.05) and reliable (Cronbach's α X=0.848, Y=0.804), analyzed using simple linear regression in SPSS. Results show excellent ISPS implementation (mean 4.46) and security effectiveness (mean 4.68), with significant positive influence (t=11.852 > 1.677; sig=0.000; R²=0.745; Y=17.071+0.641X). In conclusion, ISPS Code substantially enhances port security, recommending intensified training and technology integration.

Sistem Pakar Deteksi Dini Stres Mahasiswa Berdasarkan Gaya Hidup Menggunakan Certainty Factor Berbasis Web

2026-05-11T15:55:19+07:00

Stress is a condition commonly experienced by university students due to academic demands, lifestyle, and daily activities. Poorly managed stress can negatively affect students’ physical and psychological well-being. This study aims to develop a web-based expert system to assist in the early detection of students’ stress levels using the Certainty Factor method. The symptom data were compiled based on Hans Selye’s stress theory under expert guidance, while the expert Certainty Factor values for each symptom were obtained through consultation with a psychologist. The system was developed using PHP programming language and MySQL database. The detection process is performed by processing the users’ confidence levels toward the symptoms along with the expert confidence values using the Certainty Factor method to determine three stress categories: mild, moderate, and severe. The calculation simulation resulted in Certainty Factor values of 0.50 for mild stress, 0.52 for moderate stress, and 0.18 for severe stress, resulting in a moderate stress detection. Black-box testing was conducted using 19 scenarios covering the functions of the user and admin pages, and all scenarios were successfully executed as expected, resulting in a 100% success rate. The system also provides recommendations related to lifestyle based on the detection results. Based on these results, the system can be used as a supporting tool to assist university students in conducting early stress detection independently.

Implementasi Algoritma BERT pada Sistem Analisis Sentimen Berbasis Web terhadap Kebijakan Elektrifikasi Sepeda Listrik

2026-07-07T01:49:20+07:00

The rapid growth of social media has driven a surge in public opinion across digital platforms, including YouTube. The transportation electrification policy, particularly the adoption of electric bicycles in Indonesia, has elicited a wide range of public responses. This study aims to build a web-based sentiment analysis system that classifies YouTube comments related to this policy using the BERT (Bidirectional Encoder Representations from Transformers) algorithm. The system was developed using the waterfall model and covers text preprocessing (text cleaning, case folding, normalization, and tokenization), sentiment classification into positive, neutral, and negative categories, and interactive visualization of the results. The dataset consists of 1,000 comments from 8 YouTube videos collected through web scraping period of 2022, 2023 and 2024. The BERT model achieved an accuracy of 91.50%, with a macro precision of 88.34%, a macro recall of 90.80%, and a macro F1-Score of 89.55%. The classified sentiment distribution comprises 201 positive comments (20.1%), 645 neutral comments (64.5%), and 154 negative comments (15.4%). The web-based system integrates the entire workflow, from dataset upload and preprocessing to sentiment analysis and visualization, and can therefore support data-driven decision-making for policymakers.

Sistem Informasi Arsip Surat Berbasis Website Menggunakan Algoritma Sequential Search Di Mts Baiturrohim Blimbing

2026-05-30T19:32:15+07:00

The management of incoming and outgoing mail archives at Madrasah Tsanawiyah Baiturrohim Blimbing is currently carried out manually using physical ledgers and paper-based storage systems. This conventional method results in several administrative problems, including difficulties in searching and retrieving documents, inconsistent letter numbering, delays in the disposition process, risk of document loss or physical damage, and inefficiency in terms of time and human resources. This study aims to design and develop a web-based information system for managing incoming and outgoing mail archives by applying the Sequential Search algorithm as the main search mechanism. The research uses a qualitative descriptive approach with data collected through observation, interviews, and literature review. The system is developed using the Prototype method through iterative stages: requirement analysis, prototype design and development, and system testing and evaluation. The system is implemented using PHP, SQLite, and Bootstrap. Testing of four algorithm scenarios confirms theoretical time complexity: O(1) in best case (1 iteration), O(n) in average case (5 iterations, T(9)=(9+1)/2=5), worst case (9 iterations), and not found case (9 iterations). Black Box Testing across 8 scenarios shows a 100% success rate. The developed system successfully improves the efficiency and accuracy of mail archive management, reduces manual recording errors, and facilitates timely administrative reporting.

Sistem Pakar Diagnosis Kondisi Koloni Lebah Madu (Apis Cerana) Menggunakan Metode Certainty Factor

2026-06-29T12:30:35+07:00

Apis cerana honey bee cultivation in Indonesia faces a major constraint of limited access to expert apiculturists for fast and accurate colony condition diagnosis. The manual and subjective diagnostic process creates uncertainty because one symptom can indicate multiple possible conditions. This research aims to develop a web-based expert system using the Certainty Factor (CF) method to diagnose Apis cerana honey bee colony conditions. The research methodology follows the Expert System Development Life Cycle (ESDLC) consisting of four stages: intelligence, design, selection, and implementation. The resulting knowledge base consists of 15 symptoms, 5 colony conditions, 5 IF-THEN rules, and a CF value matrix. The results show that the developed expert system achieved 100% accuracy when tested on 20 colony samples compared to expert diagnosis. All system functions performed according to specifications based on black box testing of nine scenarios. The system displays diagnostic ranking with confidence levels in percentages and provides a CF Combine calculation detail feature for diagnostic process transparency. Expert validation results state that the system is feasible for use as a diagnostic tool. This system provides a practical solution for farmers in various locations to diagnose colony conditions independently, quickly, and in a standardized manner.

Pengaruh Usability Aplikasi Portal Analisis Data Berbasis Peta (PANADA) terhadap Transparansi Digital Pemerintah Kota Manado

2026-05-27T19:56:44+07:00

This study is motivated by the importance of digital transparency in government administration, particularly through the use of the Portal Analisis Data Berbasis Peta (PANADA) application in Manado City. The research problem focuses on how much usability influences digital transparency of the Manado City Government. The objective of this study is to determine the extent of the effect of usability on digital transparency as perceived by the public as application users.

This research employs a quantitative approach with data collected through online questionnaires distributed to residents of Manado City who have used the PANADA application. The sampling technique used is Cluster Random Sampling, involving 88 respondents divided into new and experienced users. Data analysis was conducted using a non-parametric statistical method, namely Spearman Rank Correlation, with the assistance of SPSS software.

The results of the study indicate that the Spearman correlation test produced a correlation coefficient of 0.264 with a significance value of 0.013, demonstrating that the usability variable has a positive relationship with digital transparency, where improvements in usability also contribute to enhancing digital transparency. Therefore, improving usability remains necessary to optimally support the effectiveness of digital transparency.

Rancang Bangun Sistem Informasi Poin Keaktifan GenBI UPN "Veteran" Jawa Timur dengan Metode Rapid Application Development dan Gamifikasi

2026-05-03T17:05:57+07:00

Member activity point management at GenBI UPN “Veteran” Jawa Timur remains manual, leading to inefficiency and a lack of transparency. This study aims to design a web-based activity point management information system using Rapid Application Development (RAD) and a gamification approach. The RAD method was implemented through iterative user involvement, while the system was modeled using UML and developed with the Laravel framework. The results indicate that the integrated system effectively manages point data, submissions, and activities, thereby enhancing efficiency, accuracy, and transparency. Furthermore, gamification elements such as leaderboards, progress bars, and badges successfully improved user engagement. Black Box Testing confirmed that all system functions operate correctly, and User Acceptance Testing (UAT) involving 15 respondents yielded a score of 88.13% (Excellent). Consequently, the system is deemed feasible for implementation.

Penerapan Metode Double Diamond dalam Perancangan Desain UI/UX Aplikasi Ternovia Administrasi Kelompok Ternak

2026-05-03T17:17:19+07:00

The administration of livestock farmer groups by farmers in Jombang Regency is still conducted manually via WhatsApp and Google Forms, leading to documentation confusion, unclear submission status, and repeated revisions. This study aims to design the UI/UX of the Ternovia mobile application for farmers using the Double Diamond method with two improvement iterations. The research was conducted through four phases of Discover, Define, Develop, and Deliver involving three Farmer Group Leaders and two Farmer Members. Data was collected through observation and interviews, then analyzed using Empathy Map, User Persona, User Journey, and Pain and Gain Point. Evaluation was performed in two sequential stages: Usability Testing based on ISO 9241-11 as the basis for iteration 1, and Heuristic Evaluation by six evaluators as the basis for iteration 2. Usability Testing results showed success rates of 90.28% (Leaders) and 91.18% (Members), ORE of 84.96% (Leaders) and 91.63% (Members), and SUS scores of 85.83 (Leaders) and 87.50 (Members), all categorized as Excellent. Heuristic Evaluation identified 17 findings with the highest severity rating on the Consistency and Standards heuristic at 1,50. The application of Double Diamond with two iterations is proven effective in producing an interface design that meets farmers’ needs.

Sistem Pendukung Keputusan Penerima Bantuan RUTILAHU Menggunakan Metode ELECTRE

2026-07-07T02:00:35+07:00

Poverty alleviation in Surabaya, which recorded 166.62 thousand residents in 2024, is addressed through various social assistance programs, including the Uninhabitable Housing (RUTILAHU) program. However, the selection process for beneficiaries at the sub-district level often faces challenges such as subjectivity and non-criteria interventions during the nomination phase. This study aims to implement a Decision Support System (DSS) using the Elimination Et Choix Traduisant La Realité (ELECTRE) method to enhance selection objectivity in Alun-Alun Contong Sub-district. The ELECTRE method was selected for its capability to handle pairwise comparisons between alternatives based on predefined criteria to produce accurate priority rankings. The results indicate that the system successfully generates clear ranking recommendations, identifying alternative nine as the primary priority with the highest outranking level. System accuracy testing achieved a validity rate of 87%. It can be concluded that the application of the ELECTRE method is effective in providing transparent and accurate recommendations, while minimizing conflicts of interest among local officials in determining the most deserving residents for assistance.

Smart Health Monitoring Berbasis Machine Learning untuk Prediksi Risiko Stroke sebagai Upaya Pencegahan Dini Kesehatan Masyarakat

2026-10-14T10:32:52+07:00

Stroke is a leading cause of death and disability in Indonesia, with a rising prevalence that extends to the working-age population. Current stroke screening methods which remain largely manual and subjective fail to identify complex risk patterns within patient clinical and lifestyle data. This study develops a machine learning-based Smart Health Monitoring system integrated with a digital clinical dashboard to support early stroke risk detection in primary healthcare facilities, utilizing the Healthcare Stroke Data dataset (Kaggle, 2023) comprising 5,110 patient records. Three algorithms were systematically compared: Random Forest, XGBoost, and a Stacked Ensemble (using Random Forest and XGBoost as base learners and Logistic Regression as the meta-learner). Extreme class imbalance (95.1% vs. 4.9%) was addressed using k-Nearest Neighbors (k=5)-based SMOTE, applied in a leak-free manner across each cross-validation fold. Evaluation metrics included Accuracy, Sensitivity, Specificity, F1-Score, and AUC-ROC. Results indicate that XGBoost achieved the highest AUC-ROC (79.23%) with 99.69% Specificity, while Random Forest yielded the best Sensitivity (22.00%) with an AUC-ROC of 78.74%; the Stacked Ensemble provided a balanced performance (AUC-ROC 78.93%). Model interpretability was assessed via Explainable AI using SHAP value analysis, identifying age, average blood glucose, and BMI as the three most influential features. The study concludes with the development of a Streamlit-based digital clinical dashboard prototype featuring continuous risk prediction capabilities.

Penerapan Data Mining Untuk Analisis Pola Penyakit Pasien Rawat Inap Menggunakan Metode K-Means

2026-06-13T14:43:08+07:00

The management of inpatient medical records generates large volumes of data that are often underutilized for managerial decision-making and data-driven healthcare planning. Hospitals frequently encounter difficulties in identifying patient characteristic patterns associated with healthcare costs, length of stay, intensive care unit (ICU) utilization, and discrepancies between Indonesia’s National Health Insurance (BPJS) reimbursement rates and hospital service charges. This study applied a data mining approach using the K-Means Clustering algorithm to analyze 9,889 inpatient records. The research process involved data cleaning, Z-score normalization, determination of the optimal number of clusters using the Elbow Method and Silhouette Score, and cluster characterization based on BPJS reimbursement rates, hospital charges, length of hospitalization, ICU length of stay, and patient age. The results identified three optimal clusters (k = 3) with a Silhouette Score of 0.3441. Cluster 0 (Critical Patients) consisted of 376 patients (3.8%) and was characterized by the highest healthcare costs and ICU utilization. Cluster 1 (Intermediate Patients) included 6,625 patients (67.0%), predominantly elderly individuals requiring moderate levels of care. Cluster 2 (Low-Acuity Patients) comprised 2,888 patients (29.2%), mainly younger patients with the lowest costs and shortest hospital stays. The analysis also revealed an average discrepancy of IDR 5,602,334 per patient between hospital charges and BPJS reimbursement rates. These findings demonstrate that clustering can effectively identify patient groups with distinct resource-use and financial characteristics, providing valuable insights for resource allocation, ICU capacity planning, geriatric service development, and evaluation of healthcare financing and BPJS reimbursement policies.

Klasifikasi Risiko No-Show Pasien Berdasarkan Karakteristik Penjadwalan dan Sosiodemografi Menggunakan Kombinasi Instance Hardness Threshold dan Symbolic Regression

2026-07-07T01:53:52+07:00

Patient non-attendance at scheduled medical appointments (no-show) places significant burdens on healthcare systems, including resource inefficiency, disrupted care continuity, and substantial financial losses. Medical appointment datasets are inherently imbalanced, making accurate identification of the no-show minority class challenging with conventional classification methods. Moreover, most prior studies have primarily focused on improving predictive accuracy through complex black-box models, while model interpretability for clinical decision-making has received comparatively little attention, leaving such models unable to produce explanations that healthcare personnel can directly act upon in operational settings. This study proposes a two-stage classification pipeline integrating Instance Hardness Threshold (IHT) and genetic programming-based Symbolic Regression (SR), applied to the no-show Appointments dataset from Kaggle (N=110,527 records, Vitória, Brazil) with 14 sociodemographic and scheduling features. IHT selectively eliminates ambiguous majority-class instances, while SR produces explicit mathematical formulas that can be read and translated directly into intervention priority rules without requiring additional interpretability tools. IHT reduced the class imbalance ratio from 3.95:1 to 1.08:1 by removing 44,790 instances. SR identified waiting_days and same_day_appt as the most critical feature pair, generating an explicit symbolic formula that achieved 92% recall, an F1-Score of 0.43, and a ROC-AUC of 0.67 on the test set, competitive against the best-performing Gradient Boosting baseline (F1=0.43, ROC-AUC=0.73) with markedly superior interpretability. The SR formula can be directly operationalized as a reminder dispatch priority rule, patients with longer waiting times who did not book same-day appointments are prioritized for intervention, while same-day appointment patients exhibit near-zero no-show risk. Future work is recommended to explore multi-objective SR, contextual feature integration, and validation on Indonesian clinical datasets.

Monitoring Router Mikrotik CHR Secara Otomatis Menggunakan Telegram Bot Berbasis Python

2026-07-05T01:28:09+07:00

Manual router monitoring is inefficient because network administrators only learn about failures through user complaints rather than automatic system detection. This study aimed to

build an automated monitoring system for Mikrotik CHR Router using a Python-based

Telegram Bot that can detect failures and send automated notifications through periodic monitoring. The system was developed using a prototyping approach and consists of six Python modules running in parallel via threading. Monitoring was performed using the ICMP protocol every 30 seconds, while device information retrieval was done via SSH using the Netmiko library. Testing was conducted through twelve test scenarios simulating router failure using the /disable_interface command through the Telegram bot. The system also includes two network automation features: auto restart interface, which automatically sends the /interface enable command to the router when a failure is detected, and auto backup configuration, which saves the router configuration to a local file each time the router recovers. Test results showed that the failure notification was sent an average of 51 seconds after the interface was disabled in three complete tests. The router was detected as recovered 35 to 44 seconds after the interface was enabled in most events, duplicate alerts were prevented, and 691 log lines were recorded automatically. The results indicate that the system has potential for use in laboratory or small-scale networks.

Pemodelan Sistem Absensi Siswa Berbasis QR Code Dinamis Menggunakan Unified Modeling Language (UML)

2026-04-16T13:32:11+07:00

Pencatatan kehadiran siswa secara manual membutuhkan waktu dan berpotensi menimbulkan kesalahan dalam rekapitulasi data serta praktik titip absen. Penggunaan QR Code statis dapat mempercepat proses absensi, tetapi kode yang sama dapat dibagikan kepada siswa lain sehingga kehadiran aktual siswa sulit dipastikan. Penelitian ini bertujuan memodelkan sistem absensi siswa berbasis QR Code dinamis di SMA Swasta IT Al-Fityah menggunakan Unified Modeling Language (UML). Pengumpulan data dilakukan melalui observasi dan wawancara semi-terstruktur dengan guru atau wali kelas, operator atau petugas piket, serta siswa. Data yang diperoleh digunakan sebagai dasar penyusunan lima diagram UML, yaitu use case diagram, activity diagram, sequence diagram, state machine diagram, dan class diagram. Model sistem mencakup mekanisme pergantian QR Code setiap 20 detik atau setelah dipindai oleh satu siswa. Selain itu, model mempertimbangkan kebijakan penitipan telepon seluler di sekolah dengan menyediakan mekanisme pencatatan kehadiran pada pagi dan sore hari. Pada class diagram, data absensi setiap mata pelajaran dibedakan dari data kehadiran harian, sedangkan hak akses sistem disesuaikan dengan tiga kelompok pengguna yaitu siswa, operator/petugas piket, dan walikelas/guru. Matriks keterlacakan disusun untuk memastikan bahwa setiap kebutuhan fungsional telah terhubung dengan use case, kelas, dan diagram UML yang relevan. Hasil penelitian berupa model UML yang dapat dijadikan acuan dalam pengembangan sistem absensi siswa berbasis QR Code dinamis, khususnya pada jenjang sekolah menengah.

Sistem Monitoring Kualitas Air Limbah Berbasis IoT dengan Thresholding Bertingkat pada UMKM Batik

2026-06-08T21:37:33+07:00

Pesona Batik Jombang SME generates liquid waste from batik dyeing and washing processes that is still monitored manually and non-continuously, risking environmental pollution and violating Indonesian Minister of Environment Regulation No. 5 of 2014. This study designs and develops an IoT-based wastewater quality monitoring system using a multi-level thresholding method that classifies water conditions into three categories: Safe, Caution, and Unsafe. The system integrates an ESP32 Dev Module, a PH4502C pH sensor, a DS18B20 temperature sensor, and a DFRobot Gravity Analog TDS Sensor V1.0 connected via the MQTT protocol to a Node-RED visualization platform. The novelty lies in applying the minimum function K = min(f(pH), f(T), f(TDS)) as a multi-parameter aggregation mechanism based on the worst-case scenario principle, with thresholds derived directly from Indonesian regulations and WHO Guidelines 2022. Sensor calibration yielded a MAPE of 1.86% (pH), 0.37% (temperature), and 2.20% (TDS), all below the 5% tolerance. Field testing on 20 real samples demonstrated a classification accuracy of 100%.

Analisis Sentimen Ulasan Pengguna Aplikasi Duolingo Menggunakan IndoBERT

2026-06-10T15:43:19+07:00

The large volume of user reviews for Duolingo in Indonesia makes the manual evaluation process difficult to conduct. Therefore, this study aims to analyze user sentiment to understand their responses and experiences with the Duolingo application. This study utilizes the IndoBERT model to classify reviews into three sentiment categories: positive, neutral, and negative. The evaluation results demonstrate that the IndoBERT model performs exceptionally well, achieving an Accuracy rate of 92% and a Macro F1-Score of 71%. The majority of the analyzed reviews fall into the positive sentiment category (83.47%), indicating a high level of user satisfaction with the application. The positive sentiment class achieves an F1-Score of 97%, whereas the neutral class yields the lowest Macro F1-Score at 44% due to many neutral reviews being brief and ambiguous. The findings of this study show that IndoBERT is effective and reliable in automatically mapping public opinion and providing an overview of user perception toward the Duolingo application

Sistem Pendukung Keputusan Persediaan Besi Menggunakan Metode Economic Order Quantity Berbasis Web Dengan Validasi Kapasitas Gudang

2026-06-12T14:04:23+07:00

Inventory management that relies solely on the owner's intuition without a mathematical basis often leads to two classic problems: overstock that freezes working capital and stockout that eliminates revenue potential. This problem becomes more complex when the physical warehouse capacity is not considered in procurement decisions. This study aims to design and develop a web-based Decision Support System (DSS) implementing the Economic Order Quantity (EOQ) method to generate optimal order quantity (Q*) and Reorder Point (ROP) recommendations, while integrating the physical warehouse capacity of 504 m³ as a validation parameter. The novelty of this research lies in incorporating physical volume per item unit (m³) as a warehouse capacity constraint within the web-based DSS, differentiating it from conventional EOQ implementations. The system was built using PHP with a MySQL database following the Waterfall development model. Black Box Testing across 21 scenarios on 5 main modules yielded entirely valid results. Manual calculation validation on 15 steel products confirmed that Q* and ROP values produced by the system are identical to theoretical calculations. The system also successfully auto-detects products exceeding warehouse capacity and notifies the user.

Sistem Pendukung Keputusan Rekrutmen Karyawan Berbasis Web Menggunakan Metode Hybrid AHP-SAW pada PT Tribintang Emas Mulia

2026-05-26T16:21:47+07:00

The employee recruitment process often faces the obstacle of subjectivity in candidate assessment, which results in low quality human resources and inefficient decision-making. This study aims to optimize selection objectivity by implementing a hybrid method that integrates Analytic Hierarchy Process (AHP) and Simple Additive Weighting (SAW). The AHP method is used to determine criteria weights consistently and measurably, thereby reducing assessment bias. The results of the pairwise comparison matrix test show a Consistency Ratio (CR) value of 0.02 (<0.1), indicating that the criteria weighting is valid and consistent. Furthermore, the SAW method is implemented to rank alternative applicants efficiently and in real-time. Validity testing is carried out by comparing the system results with the company's manual decisions in the previous period and produces an accuracy level of 100%. These results indicate that the hybrid approach is able to overcome the limitations of AHP in handling many alternatives and reduce the subjectivity of weighting in SAW. Overall, the proposed method produces more accurate, measurable, and efficient recommendations for prioritizing prospective employees compared to conventional methods.

Penerapan Metode Single Moving Average untuk Prediksi Persediaan Voucher Kuota Berbasis Web

2026-05-26T14:23:13+07:00

Manual management of internet voucher inventory may cause recording errors and difficulties in determining stock quantities. This study aims to develop a web-based inventory information system using the Single Moving Average method to assist in forecasting inventory requirements. The research employed a quantitative approach with data collected through observation, interviews, and documentation. The forecasting process was performed using Single Moving Average with 2-period, 3-period, and 4-period windows, and the forecasting accuracy was evaluated using the Mean Absolute Percentage Error (MAPE). The results showed that the 2-period Single Moving Average achieved the best forecasting performance with an average MAPE of 12.29%, outperforming the 3-period model with 13.57% and the 4-period model with 14.06%. The developed system was able to improve inventory management and automate stock forecasting more effectively. Therefore, the implementation of the Single Moving Average method in the inventory information system can support more accurate inventory procurement decisions.

Perancangan UI/UX Manajemen Stok Barang UMKM Mysha Glow Berbasis Mobile dengan Metode Design Thinking

2026-10-18T14:57:30+07:00

The rapid growth of digital technology encourages Micro, Small, and Medium Enterprises (MSMEs) to improve operational efficiency through information systems, particularly in inventory management. However, Mysha Glow MSME still relies on manual stock recording processes, resulting in inaccurate inventory data and difficulties in monitoring stock availability. This study aims to design a mobile-based User Interface and User Experience (UI/UX) for an inventory management application using the Design Thinking method and evaluate its usability. This research employed a descriptive qualitative approach using the Design Thinking framework consisting of empathize, define, ideate, prototype, and test stages. The research population included individuals involved in inventory management activities at Mysha Glow MSME, while the sample was selected through purposive sampling and consisted of the owner and staff members. Data were collected through observation, semi-structured interviews, literature review, and the System Usability Scale (SUS) questionnaire. Qualitative data were analyzed through data reduction, data presentation, and conclusion drawing, while SUS data were analyzed using the standard scoring procedure. The results revealed that the developed prototype achieved an average SUS score of 82.25, indicating an acceptable level of usability with an excellent rating. The study concludes that the proposed UI/UX design effectively addresses user needs and has the potential to enhance the effectiveness and efficiency of inventory management processes at Mysha Glow MSME.

Analisis Tingkat Kapabilit as Website Emis Madrasah Diniyah Kecamatan Cicantayan Menggunakan COBIT 2019 Domain BAI04

2026-10-18T14:32:17+07:00

This study evaluates the capability level of the EMIS website for Madrasah Diniyah in Cicantayan Subdistrict using COBIT 2019 domain BAI04 due to service stability and capacity issues affecting education data management. The objectives are to measure BAI04 capability levels, identify gaps between as‑is and to‑be states, and propose improvement recommendations. The study employs a descriptive quantitative case study. The population includes EMIS managers and users; a purposive sample of five respondents was selected (district admin, DPAC chair, and three madrasah operators). Instruments comprised a COBIT‑based capability assessment questionnaire (Guttman yes/no), observations, semi‑structured interviews, and literature review. Analysis used Goal Cascade, Design Factors, capability percentage calculation, and gap analysis per COBIT 2019. Results: average BAI04 capability is 44.21% (Partially Achieved); findings indicate lack of documented capacity planning, absence of real‑time performance monitoring, informal incident reporting, and weak coordination. Conclusion: BAI04 processes are reactive at Level 2 and require advancement to Level 4 through capacity planning, monitoring metrics (uptime, response time, error rate), integrated ticketing, periodic load testing, formal coordination forums, and operator training.

Perancangan UI/UX Aplikasi Nara Bakery Menggunakan Metode User-Centered Design (UCD)

2026-10-19T08:22:30+07:00

Advances in information technology are driving micro, small, and medium-sized enterprises (MSMEs) to adapt by implementing digital systems to improve the efficiency and accuracy of business management, but in practice, many MSMEs still conduct operational processes manually, leading to issues such as delayed reporting, transaction recording errors, and low management transparency including those experienced by Nara Bakery, where transaction recording, inventory reporting, and employee attendance tracking have not yet been digitally integrated. This research aims to design the User Interface (UI) and User Experience (UX) of the Nara Bakery mobile app centered on user needs to improve operational efficiency and data accuracy, with a design focused on integrating sales transaction recording, inventory reporting, and employee attendance into a single application system that is easy for business owners to use. The method used in this study is User-Centered Design, which consists of four stages: Understanding the context of use, Identifying user needs, Designing solutions, and Evaluating against requirements. Data collection was conducted through direct observation, semi-structured interviews, and a literature review, while the application prototype was designed using Figma software and evaluated through usability testing using the System Usability Scale (SUS) method, involving 10 respondents to measure ease of use and user satisfaction. The research results consist of a prototype design for the Nara Bakery mobile app, which features an intuitive interface, a clear user flow, and key features aligned with the business’s operational needs. The SUS testing yielded an average score of 89.5, falling into the “Excellent” category and Grade A, indicating that the UI/UX design has a very high level of usability and is well-received by users.

Rancang Bangun Sistem Informasi Manajemen Bengkel Menggunakan Metode Rapid Application Development

2026-05-25T19:04:53+07:00

Based on the results of interviews and observations, operational management at Alesha Motor Speed Workshop is still conducted manually, making it inefficient and prone to data errors. This study aims to design and develop a web-based workshop management information system to improve operational effectiveness and service quality. The method used is Rapid Application Development (RAD), which consists of the following stages: requirement planning, RAD design workshop, and implementation. Data collection was conducted through observation and interviews; the system was then designed using UML and implemented using the Laravel framework. System testing was performed using Black Box Testing and User Acceptance Testing (UAT). The results of the Black Box Testing indicated that all system features functioned in accordance with the specified requirements. Meanwhile, the UAT results yielded a score of 89.7%, indicating that the system falls into the “very good” category and is acceptable to users. The developed system is capable of managing data in an integrated manner, supporting service processes and real-time reporting. Thus, this system can improve operational efficiency and the quality of workshop services.

Pengaruh Faktor-Faktor UTAUT2 terhadap Niat Penggunaan Aplikasi Strava

2026-05-05T16:47:55+07:00

The rapid development of digital technology has led to an increased use of fitness applications such as Strava to support people’s physical activities. This study analyzes the factors influencing the intention to use the Strava application using the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) approach. A quantitative method was employed, with data collected through a Google Form questionnaire distributed to 442 active Strava users in Indonesia selected using purposive sampling. The data were analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM) with the assistance of SmartPLS 4.0. The results indicate that Performance Expectancy, Effort Expectancy, Social Influence, Hedonic Motivation, and Perceived Privacy Protection have a positive and significant effect on Behavioral Intention, with Performance Expectancy emerging as the most dominant factor. This suggests that the perceived benefits in supporting physical activities and achieving fitness goals are the primary drivers of Strava usage, while the other variables also contribute to shaping users’ intention to use the application. Therefore, the UTAUT2 model is proven to be relevant in explaining user acceptance of the Strava application.

Penentuan Destinasi Wisata melalui Penggunaan Fitur Tag Lokasi pada Konten TikTok dengan Pendekatan UTAUT2

2026-05-05T16:47:28+07:00

The development of TikTok as a social media platform has changed the way users search for tourism destination information and has begun to replace traditional search engines. One of the most frequently used features is the location tag in TikTok content, which enables fast and integrated access to information, although concerns regarding accuracy and trustworthiness still exist. This study aims to analyze the factors influencing the use of the location tag feature among Generation Z and Millennials using an extended UTAUT2 model with perceived trust. Data from 425 respondents were analyzed using PLS-SEM with SmartPLS 4. The results show that performance expectancy, effort expectancy, social influence, habit, and perceived trust significantly influence behavioral intention, while facilitating conditions and hedonic motivation do not significantly influence behavioral intention or actual behavior. In addition, behavioral intention and habit significantly influence actual behavior. These findings indicate that usage is driven by perceived usefulness, ease of use, habit, and trust, highlighting the importance of improving information quality.

Rancang Bangun Website Rekam Medis Terpadu untuk Praktik Mandiri Bidan Tingkat Kecamatan Menggunakan Metode Rapid Application Development

2026-05-05T09:49:04+07:00

This study aims to design and develop an Integrated Medical Records Website for midwives in private practice in Semampir District to support the digital management of health services. The developed system is expected to assist midwives in managing practice data, patient data, medical record documentation, and monitoring visit reports in an integrated manner. The system was developed using the Rapid Application Development (RAD) method through two iterations covering system design through to the implementation stage. System testing was conducted using Black Box Testing to ensure system functionality, as well as User Acceptance Testing (UAT) to measure user acceptance levels. The results of Black Box Testing showed that all system features functioned in accordance with functional requirements. Additionally, the UAT results indicated a user acceptance rate of 86.59%, leading to the conclusion that the system is user-friendly, supports service delivery processes, and aligns with the needs of independent midwifery practices.