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All Journal Jurnal PkM MIFTEK Journal of Intelligent Systems Technology and Informatics
Muhammad Nadhief Rahmat Firdaus
Institut Teknologi Garut
Humanities Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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Implementasi Sistem Panic Button Terintegrasi Aplikasi Kawal Desa Dan Sirene Untuk Peningkatan Keamanan Desa Pangauban Dini Destiani Siti Fatimah; Kamila Lutfi Zakiah; Muhammad Nadhief Rahmat Firdaus; Ihsan Yafi Pirmansyah; Moch. Rifal Azril; Wilyandi Fajri; Kamilaeni; Fadilah Nur Fatimah; Destian Muhammad Lutfi; M. Fikri Akmaludin; Dzikra Ilham Ilahi; Meitha Amanda; Muhammad Fakhri Asy-syauqi; Ghiffari; Rafly Achmad Fauzan; Ray Faizi Muhammad Sumarno; Inayatul Ikrimah; Muhammad Naufal Abdul Tsany; Ipan Munigar Rohman; Muhamad Farhan
Jurnal PkM MIFTEK Vol 7 No 1 (2026): Jurnal PkM Miftek
Publisher : Institut Teknologi Garut

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33364/miftek/v.7-1.3142

Abstract

The village of Pangauban in Cisurupan Subdistrict, Garut Regency, has experienced rapid progress. However, this village does not yet have an adequate integrated security system. This condition has resulted in ineffective communication between village officials and residents when dealing with emergency situations, causing a slow response to reports of important incidents. Therefore, technology-based innovations are urgently needed to facilitate coordination and accelerate response times, thereby enhancing the sense of security for the entire village community. Through the Thematic Community Service Program (KKN), we implemented a Panic Button/Emergency feature on the existing Kawal Desa application. This feature is designed to make it easier for residents to report important incidents, enabling village officials to respond quickly and efficiently. The methods used are quantitative and workshops. The stages of the activity include observation, socialization, and system implementation. The siren hardware is installed in the village office and then configured wirelessly with the Kawal Desa application. After that, socialization and training are provided to RT, RW, and residents on how to use the system, both manually and through the application.
Fake News Detection in Indonesian Language Using IndoBERT with LIME-Based Keyword Interpretation Rifki Ramdani; Muhammad Nadhief Rahmat Firdaus
Journal of Intelligent Systems Technology and Informatics Vol 2 No 2 (2026): JISTICS, July 2026
Publisher : Aliansi Peneliti Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64878/jistics.v2i2.198

Abstract

Fake news dissemination in the digital era has become a serious issue, particularly in political and public information domains. This study proposes an Indonesian fake news detection system that uses the IndoBERT transformer model, combined with LIME (Local Interpretable Model-Agnostic Explanations), for keyword-based interpretation. The primary objective of this study is not only to achieve high classification performance but also to enhance model transparency by identifying the most influential words contributing to prediction results. This study follows the SEMMA (Sample, Explore, Modify, Model, Assess) methodology, starting with dataset collection, exploratory data analysis, text preprocessing, model fine-tuning, and evaluation, and concluding with interpretability analysis using LIME. The dataset consists of 31,310 Indonesian political news articles categorized into hoax and factual classes. IndoBERT is fine-tuned using the Hugging Face framework with optimized hyperparameters and class weighting to address class imbalance. Experimental results show that the proposed model achieves an accuracy of 99.78%, precision of 99.81%, recall of 99.52%, and F1-score of 99.66%, demonstrating strong performance in distinguishing hoax and factual news. Furthermore, LIME-based analysis provides interpretable insights by highlighting keywords that influence model predictions, thereby improving transparency and user trust. Words associated with conspiracy and unverified claims contribute strongly to the hoax class, while terms related to official institutions and statistical information support factual classification. The results indicate that integrating IndoBERT with LIME not only improves classification performance but also enhances explainability in Indonesian fake news detection systems.
Co-Authors Destian Muhammad Lutfi Dini Destiani Siti Fatimah Dzikra Ilham Ilahi Fadilah Nur Fatimah Ghiffari Ihsan Yafi Pirmansyah Inayatul Ikrimah Ipan Munigar Rohman Kamila Lutfi Zakiah Kamilaeni M. Fikri Akmaludin Meitha Amanda Moch. Rifal Azril Muhamad Farhan Muhammad Fakhri Asy-syauqi Muhammad Naufal Abdul Tsany Rafly Achmad Fauzan Ray Faizi Muhammad Sumarno Rifki Ramdani Wilyandi Fajri