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All Journal Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) JOIV : International Journal on Informatics Visualization Indonesian Journal for Social Responsibility Abdi Psikonomi Almufi Jurnal Pengabdian kepada Masyarakat Journal of Informatics and Communication Technology (JICT) Teknologika Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) Journal of Informatics and Communication Technology (JICT)
Vivi Monita
Telkom University
Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Social Sciences Other

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Comparative Analysis of Daily and Weekly Heavy Rain Prediction Using LSTM and Cloud Data Monita, Vivi; Sevirda Raniprima; Nanang Cahyadi
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 10 No. 4 (2024): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v10i4.30374

Abstract

Indonesia's distinct geographic and climatic features make forecasting the weather there tricky. Due to its location at the equator and between two enormous oceans, the nation endures erratic weather patterns. Despite technical developments, the Meteorology, Climatology, and Geophysics Agency (BMKG) require assistance with precise forecasting. This research seeks to increase prediction accuracy using the Long Short-Term Memory (LSTM) algorithm, a deep learning technique appropriate for time series data processing. The research focuses on cloud data sets to improve the prediction of heavy rain. The potential of LSTM in weather forecasting has been demonstrated in earlier research, focusing on identifying rain at particular intervals. This research compares daily and weekly heavy rain prediction models using Python.  Results reveal that the weekly model outperforms the daily model, achieving 85% accuracy compared to 80%. These findings highlight the effectiveness of LSTM in addressing the limitations of existing methods, offering a foundation for more reliable weather forecasting tailored to Indonesia’s conditions.
Sosialisasi Pemahaman dan Penerapan Prototipe Solar Cell di Sekolah Menengah Kejuruan Voctech 1 Tangerang Monita, Vivi; Faradina, Cut; Syafana, Fathiyah
Indonesian Journal for Social Responsibility Vol. 8 No. 01 (2026): June 2026
Publisher : LPkM Universitas Bakrie

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36782/ijsr.v8i01.521

Abstract

Solar energy is an abundant and environmentally friendly renewable energy source; therefore, its utilization through solar cell technology is highly relevant in addressing energy challenges in the Industrial Era 4.0. However, many Vocational High School (SMK) students still lack a deep understanding of the working principles and applications of this technology. The activity of socializing and implementing solar cell prototypes at SMK Voctech 1 Tangerang aims to enhance students' understanding of the concept, benefits, and operation of solar cells, as well as provide direct practical experience in installing and operating simple solar power systems. This activity involves delivering theoretical material on solar energy, types of solar cells, and implementing a 360 WP solar cell prototype that can be used to charge electronic devices, serving as a simulation of alternative energy sources. The results of the activity showed that students were able to conceptually and technically understand solar cell technology and were able to install and operate the prototype well. Thus, this activity is expected to be the first step in fostering students' awareness and skills in utilizing renewable energy independently and sustainably.
Smart Monitoring Anak Usia Dini: Pemantauan Kembang Tumbuh dan Status Gizi Berbasis Aplikasi Android di TKIT Al-Munar Fu’adah, R Yunendah Nur; Monita, Vivi; Rahmaniar, Thalita Dewi
Almufi Jurnal Pengabdian Kepada Masyarakat Vol 5 No 2: Desember (2025)
Publisher : Yayasan Almubarak Fil Ilmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63821/ajpkm.v5i2.583

Abstract

Permasalahan gizi dan keterlambatan kembang tumbuh anak usia dini masih menjadi tantangan dalam upaya peningkatan kualitas kesehatan anak di Indonesia. Salah satu kendala yang dihadapi adalah belum optimalnya pemantauan pertumbuhan anak secara rutin serta keterlibatan orang tua dalam pencatatan perkembangan anak. Kegiatan pengabdian kepada masyarakat ini bertujuan mengimplementasikan konsep smart monitoring anak usia dini melalui pemanfaatan aplikasi Android untuk pemantauan kembang tumbuh dan status gizi anak di TKIT Al-Munar, Kota Bandung. Metode pelaksanaan kegiatan meliputi pengumpulan data awal melalui observasi dan wawancara, studi literatur dan penyusunan materi, sosialisasi dan pelatihan penggunaan aplikasi kepada guru dan orang tua, implementasi aplikasi dalam pemantauan rutin, serta evaluasi kegiatan melalui kuesioner dan diskusi. Aplikasi Android yang digunakan dilengkapi dengan fitur pencatatan data pertumbuhan dan perhitungan status gizi berdasarkan indikator antropometri sesuai standar World Health Organization (WHO), sehingga memungkinkan pemantauan pertumbuhan anak secara mandiri dan berkelanjutan. Peran mitra difokuskan pada pendampingan orang tua dan integrasi penggunaan aplikasi dalam aktivitas pemantauan di lingkungan sekolah. Hasil kegiatan pengabdian kepada masyarakat menunjukkan peningkatan pemahaman dan partisipasi guru serta orang tua dalam pemantauan kembang tumbuh dan status gizi anak. Implementasi aplikasi ini mempermudah pencatatan dan pelaporan data pertumbuhan anak, serta berpotensi mendukung upaya pencegahan dini masalah gizi pada anak usia dini.
Co-Authors Anggiratih, Endang Faradina, Cut Fu’adah, R Yunendah Nur Hanan Lutfianto, Naufal Indrarini Dyah Irawati Musiafa, Zayid Nanang Cahyadi Niswah, Nailah Khairun Putri Rahmawati Rahmadi Rahmadi Rahmah, Githa Desyana Nur Rahmaniar, Thalita Dewi Reza Ramadani Firman Rizka Rachmawati ROHMAT TULLOH RR. Erna Sadiarti Budiningtyas Seshariana Rahma Melati Sevierda Raniprima Sevirda Raniprima Sherfina Salsabila Syafana, Fathiyah Wendanto, Wisnu Wisnu Wendanto Yudiansyah Yudiansyah