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All Journal ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Teknik Informatika UNIKA Santo Thomas JUKI : Jurnal Komputer dan Informatika MEANS (Media Informasi Analisa dan Sistem) JPM: JURNAL PENGABDIAN MASYARAKAT Jurnal Teknik Informatika Unika Santo Thomas (JTIUST) Journal of Artificial Intelligence and Engineering Applications (JAIEA) Geosfera: Jurnal Penelitian Geografi Majalah Ilmiah METHODA TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Jurnal Widya Climago Jurnal Pengabdian Masyarakat Nauli Journal of Computation Physics and Earth Science
Marzuki, Sinambela
Badan Meteorologi, Klimatologi dan Geofisika
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Astronomy Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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Peningkatan Literasi Kebencanaan untuk Optimalisasi Informasi Peringatan Dini Bencana Geo-Hidrometeorologi Munawar, Munawar; Haryanto, Yosafat Donni; Abigael, Febby Debora; Muftareza, Arfany Dimas; Muthahhari, Ilham; Mardiyansyah, Adji; Sinambela, Marzuki
JPM: Jurnal Pengabdian Masyarakat Vol. 6 No. 3 (2026): January 2026
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/jpm.v6i3.2629

Abstract

Tangerang City is one of the regions in Banten Province that is vulnerable to geo-hydrometeorological disasters and has a relatively large population with rapid urban growth, which can increase the risk of such disasters. Therefore, information, understanding, and actions regarding geo-hydrometeorological disasters are required. Environmental damage and land use change, such as deforestation, urbanization, river sedimentation, and land function conversion, are significant issues. This activity aims to enhance disaster literacy based on Meteorology, Climatology, Geophysics, and Instrumentation (MKGI) in Tangerang City, scheduled for Monday, July 21, 2025, at SMA Al-Husna, Tangerang City, with a total of 67 participants. Through interactive methods that include material presentation, question and answer sessions, quizzes, and questionnaire filling, participants are provided with a comprehensive understanding of geo-hydrometeorological disasters, mitigation strategies, and the utilization of technology in early warning systems. One of the innovations of this activity is the development of a weather forecast information product based on Telegram bot for the area of Tanah Tinggi Village, which provides weather forecast information automatically using open data from BMKG. Evaluation results show that participants had a good understanding of the socialization material, especially in the topics of information dissemination and geohydrometeorological disasters. The questionnaire index score reached 87.60%, falling into the category of "Strongly Agree". The developed Telegram product successfully presents real-time weather information every 3 hours in a structured and easily accessible manner. This activity proves that a literacy approach based on MKGI and technology can have a positive impact in raising awareness and improving preparedness against geo-hydrometeorological disaster risks.
Using AI in Telegram Bots for Earthquake Information Delivery and Analysis Justicea, Ayu Adi; Agustin, Rala Kurniawan; Suko , Suko; Harahap, Darwin; Sinambela, Marzuki
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 5 No 1 (2025): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol5No1.pp110-115

Abstract

Indonesia is located in the Pacific Ring of Fire, making it vulnerable to earthquake activity. Earthquake events often require fast and accurate information delivery to reduce the impact of disasters. However, conventional systems often face obstacles such as information delays and lack of real-time impact analysis. Advances in artificial intelligence (AI) and machine learning (ML) provide opportunities to overcome these problems. AI is able to process seismic data efficiently, detect earthquake patterns, and predict their impact. By utilizing Telegram bots as a medium, earthquake information can be delivered quickly through real-time notifications, which are easily accessible to the public. The development of AI-based Telegram bots aims to provide earthquake information automatically, including location, magnitude, and potential impact, as well as analyze historical data to predict seismic activity trends. This solution is expected to increase public awareness and response in dealing with earthquake disasters.
Perhitungan Radiasi Matahari dari Data Cuaca Satelit di Batam Menggunakan Regresi Linier, Hutan Acak, dan Pohon Keputusan Simanjuntak, Prayoga Pandapotan; Marzuki Sinambela
Journal of Computation Physics and Earth Science (JoCPES) Vol 5 No 2 (2025): Journal of Computation Physics and Earth Science
Publisher : Yayasan Kita Menulis - JoCPES

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63581/JoCPES.v5i2.13

Abstract

This study addresses the necessity of evaluating solar radiation as a renewable energy source in tropical regions, specifically focusing on the challenges of estimation in Batam. The objective is to model daily solar radiation levels using satellite-derived weather data to overcome the lack of surface observation stations. Daily meteorological variables, including air temperature, relative humidity, rainfall, surface pressure, and wind speed, were sourced from the NASA POWER platform for the period January 1, 2020, to July 2, 2025. To ensure robust model generalization and prevent data leakage, the dataset was partitioned chronologically, utilizing data from 2020–2024 for training and the year 2025 for independent testing. Three computational models Linear Regression (LR), Random Forest (RF), and Decision Tree (DT) were applied to the processed data. The evaluation results indicate that the Random Forest model achieved the highest relative performance among the tested algorithms, recording a Mean Squared Error (MSE) of 19.61, a Mean Absolute Error (MAE) of 3.42, and a coefficient of determination R² of 0.20. In comparison, the Linear Regression model produced an R² of 0.19, while the Decision Tree showed significantly lower predictive accuracy. Despite being the most viable model, an R² of 0.20 reveals that the current predictors explain only 20% of the variance in solar radiation, highlighting the inherent complexity of tropical atmospheric dynamics. These findings suggest that while machine learning offers a promising framework for energy planning in Batam, further research incorporating additional explanatory features, such as cloud cover or aerosol indices, is required to improve model reliability.
Co-Authors Abigael, Febby Debora Adi, Suko Prayitno Adithya, Andri Ramadhan Agustin, Rala Kurniawan Agustina, Idri Albertus Tua Simanullang Alexander F.T Parera Ari Mutanto, Ari Bertalina Sihotang Darwis Robinson Manalu Dumayanti, Imelda Sri Dwiyanto . Emerson Limbong Eva Darnila Eva Darnila eva darnila, eva darnila FAUZAN, RAIHAN AHMAD Febria Anita, Febria Hadi, Ahmad Fauzi Faishal Harahap, Darwin Hartoyo, Puji Haryanto, Yosafat Donni Indra Kelana Jaya Jamaluddin Jamaluddin Jamaluddin, Jamaluddin Janner Simarmata Justicea, Ayu Adi Larosa, FGN Larosa Mardiyansyah, Adji Margono Mira Hestina Ginting Muftareza, Arfany Dimas Munawar Munawar Muthahhari, Ilham Naibaho, Jimmy F. Niken Woro Palupi Nur Hidayat Patra Mesiari Tarigan Purwantiningsih, Purwantiningsih Rachmawardani, Agustina Rahayu, Teguh RB. Yanuar Harry W Riama, Nelly Florida Ritonga, Anggiat P Rumahorbo, Benget RUSANTO, BENYAMIN HERYANTO Samuel Van Basten Halomoan Manurung Saragih, Naikson F. Setiawan, Elyas Silalahi, Veraci Simanjuntak, Prayoga Pandapotan Simanullang, Harlen Sinaga, Winton Sudarisman, Maman SUHARINI, YUSTINA SRI Suko , Suko Sunardi Sunardi Sunardi, Sunardi Supandi, Achmad Surianto Sitepu Teguh Rahayu Teguh Rahayu TONNI LIMBONG Trihadi, Edward Widada Sulistya Wisnu Wardono Yohanna, Margaretha Yosvin Apriando Yudha, I Putu Putra Wira Sarwa