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All Journal Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Agrokreatif Jurnal Ilmiah Pengabdian kepada Masyarakat CIRCUIT: Jurnal Ilmiah Pendidikan Teknik Elektro Techne : Jurnal Ilmiah Elektroteknika Journal of Computer System and Informatics (JoSYC) Jurnal Darma Agung Jurnal Pengabdian kepada Masyarakat Kapas: Kumpulan Artikel Pengabdian Masyarakat SENAPAS E-Amal: Jurnal Pengabdian Kepada Masyarakat KOPEMAS Ulil Albab
Irwan Novianto
Universitas Nahdlatul Ulama Yogyakarta
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Public Health Social Sciences Other

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Journal : Journal of Computer System and Informatics (JoSYC)

 1 
Integrasi IoT pada Lahan Tanaman Wakaf Sebagai Media Monitoring dan Alerting pada Tumbuh Kembang Bibit Pohon Mahoni Hernawan, Septian Rico; Novianto, Irwan; Rina, Fadmi
Journal of Computer System and Informatics (JoSYC) Vol 6 No 1 (2024): November 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v6i1.5972

Abstract

Environmental damage in Indonesia is concerning, with the massive loss of green spaces in recent years. Consequently, there has been a drastic decline in air quality, contributing to the rise of diseases such as stroke, heart conditions, lung diseases, and even birth defects. The implementation of environment-based waqf activities, with waqf items in the form of trees, offers a practical solution that is accessible to the public. However, this effort has not yet been widely adopted or well-facilitated. The growth of tree seedlings is influenced by several factors, such as air temperature, soil pH, humidity, and carbon particles. A method for monitoring and alerting users is needed to ensure optimal plant growth. An IoT system is integrated for the plants in the waqf areas. Sensor data will be displayed on a screen, with an alerting function that sends alarms through a speaker. Mahogany seedlings were selected for testing due to their rapid growth. Integrating IoT devices for monitoring and alerting effectively increased the height of mahogany seedlings. Based on a two-month test on 10 seedlings across two different areas, a difference of 2.4 cm per two months, or 14.4 cm per year, was observed between IoT-integrated and non-IoT areas.
Analisis Ketidakseimbangan Tegangan Baterai dengan Pendekatan Random Forest, K Nearest Neighbors untuk Prediksi Balancing Charger Novianto, Irwan; Hernawan, Septian Rico
Journal of Computer System and Informatics (JoSYC) Vol 6 No 4 (2025): August 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josyc.v6i4.8116

Abstract

Inter-cell voltage imbalance degrades efficiency, accelerates aging, and increases failure risk in electrochemical energy storage systems. This study models and predicts balancing-charger conditions using two machine-learning algorithms Random Forest (RF) and K-Nearest Neighbors (KNN) across packs of 4, 8, 10, and 15 cells with five dataset scales (1,000; 5,000; 10,000; 15,000; and 20,000 samples). Voltage data were obtained through simulation and laboratory measurements on lithium-ion cells within 3.2–4.2 V, then normalized and split into training and testing sets. Performance was evaluated using accuracy, confusion matrices, and feature-importance analysis. Results show RF achieves 0.98 accuracy for 4-cell packs and remains high at 0.93 for 15-cell packs, whereas KNN attains only 0.94 and 0.37 on the same configurations. RF exhibits predictions concentrated along the confusion-matrix diagonal with well-distributed feature weights, indicating robustness to increasing dimensionality. The contributions are threefold: (1) an evaluation framework for comparing classifiers in multi-cell scenarios; (2) empirical evidence of RF’s scalability for detecting balancing conditions from single-voltage inputs; and (3) practical implications for BMS operation more accurate balancing decisions, prioritization of problematic cells, reduced futile equalization cycles, and potential energy savings together with extended service life. These findings recommend RF as a core algorithm for machine-learning-based balancing chargers, particularly for real-world deployment on power-constrained edge devices.
Co-Authors Abdulloh Badruzzaman Adelia Octora Pristi Sahida Adelia Octora Pristisahida Aditya Wahyu Pratama Ahmad Syaifudin Ahmad Syaifudin Akhmad Fakhurrozi Amanda Amanda Amanda Putri Aulia Amanda Putri Aulia Amelia Cahya Ramadhani Amirudin Husnul Hidayat Anugrah K Pamosoaji Ardiansyah, Rio Aris Kusumo Diantoro Bambang Suhartanto Bayu Megaprastio Bledug Kusuma Bledug Kusuma P Bledug Kusuma Prasaja Diantoro, Aris Kusumo Dito Aji Nugroho Diyon Saputro Djoko Budiyanto Setyohadi Duana Siska Mawardi Erica Herlinawati Fadmi Rina Fajri Rahmad Dani Hendrik Hendrik Hermanu Triwidodo I Nyoman Apraz Ramatryana Ilham Unggara Joang Ipmawati Kelana, Fajar Sidik Abdullah Laksana, Feri Febria Lilis Kurniasari Malik Khidir Mauladi Pratama Ma’arif, Ahmad Fahruddin Miftahul Hudha Millaty, Marosimy Millaty, Marosimy Mochamad Syamsiro Muhamad Adhitya Saputra Muhamad Nasruddin Manaf Muhammad Ikhsanudin Muhammad Ikhsanudin, Muhammad Nafiatul Umami Nur Azmi Ainur Bashir Oyas Wahyunggoro Pristi Sahida, Adelia Octora Rani Agustina Wulandari Restiadi Bayu Taruno Rico Setiono Bayu Saputra Rifqi Syarif Nasrulloh Rio Ardiansyah Rio Ardiansyah Risanuri Hidayat Roza Yusfiandayani Septian Rico Hernawan Ulif Simproni Zakiah Wulandari Zulfatun Ruscitasari Zulfatun Ruscitasari Zulkhairi Zulkhairi Sofyan