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

Marcellio Aurel Christian; Eka Dyar Wahyuni; Mohammad Al Hafidz

doi:10.70340/jirsi.v5i3.385

Authors

Marcellio Aurel Christian Universitas Pembangunan Nasional "Veteran" Jawa Timur
Eka Dyar Wahyuni Universitas Pembangunan Nasional “Veteran” Jawa Timur
Mohammad Al Hafidz Universitas Pembangunan Nasional “Veteran” Jawa Timur

DOI:

https://doi.org/10.70340/jirsi.v5i3.385

Keywords:

BERTopic, topic modeling, Free Nutritious Meal Program, social media X, text mining

Abstract

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.

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