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All Journal Bulletin of Electrical Engineering and Informatics Jurnal TIMES JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JTIK (Jurnal Teknik Informatika Kaputama) International Journal of Engineering, Science and Information Technology Yayasan Cita Cendikiawan Al Khwarizmi Prioritas : Jurnal Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat (Jubdimas)
Erianto Ongko
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PELATIHAN PENERAPAN SISTEM PENDUKUNG KEPUTUSAN PENENTUAN JUMLAH PEMBERIAN PAKAN IKAN DI DESA MARIENDAL II Zuhanda, Muhammad Khahfi; Hartono, Hartono; Rahman, Sayuti; Sembiring, Arnes; Syah, Rahmad; Ramdan, Dadan; Aritonang, Mendarissan; Rahmadhani, Citra; Suswati, Suswati; Satria, Habib; Ongko, Erianto
JUBDIMAS ( Jurnal Pengabdian Masyarakat) Vol 5 No 1 (2026): Artikel Pengabdian Maret 2026
Publisher : Yayasan Cita Cendikiawan Al Kharizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/jubdimas.v5i1.403

Abstract

This community service activity aims to improve the efficiency of fish feeding management through the implementation of a Decision Support System (DSS) using the Simple Additive Weighting (SAW) method in Mariendal II Village. The main problem faced by fish farmers is the manual feeding process based on estimation, leading to inefficiency and suboptimal fish growth. The method used in this activity is a participatory approach consisting of socialization, training, technology implementation, and evaluation. The developed system considers several criteria, including fish biomass, age, population, water quality, feeding time, and feed type. The results show that participants experienced significant improvements in knowledge and skills in using the DSS. The system successfully provided optimal feeding recommendations and was integrated with an automatic feeder, resulting in more consistent and efficient feeding practices. This activity also increased farmers’ awareness of technology adoption in aquaculture. Overall, the implementation of DSS contributes to reducing feed waste, improving productivity, and supporting sustainable fish farming practices.
Metaheuristic nurse scheduling with hospital clustering using flower pollination algorithm Zuhanda, Muhammad Khahfi; Hartono, Hartono; Rahman, Sayuti; Gio, Prana Ugiana; Ongko, Erianto
Bulletin of Electrical Engineering and Informatics Vol 15, No 3: June 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i3.11243

Abstract

Effective nurse scheduling is essential to ensure balanced workloads, reduce fatigue, and maintain healthcare service quality. However, the nurse scheduling problem (NSP) is complex due to constraints related to nurse skills, task requirements, and legal working-hour limits. This study proposes an integrated framework combining a mathematical optimization model with metaheuristic algorithms to generate optimal daily nurse activity schedules. Genetic algorithm (GA) and simulated annealing (SA) are employed to produce near-optimal solutions for nurse populations ranging from 3 to 50 individuals, considering skill-level compatibility, workload balance, and maximum working hours. Experimental results using real scheduling data from 30 nurses across three skill levels demonstrate that all generated schedules satisfy the imposed constraints, with no nurse exceeding the 12hour daily working limit. Comparative analysis shows that GA achieves lower scheduling costs for larger nurse populations, while SA consistently requires significantly shorter computation times, making it suitable for time-sensitive applications. In addition, the flower pollination algorithm (FPA) is used to cluster 3,155 hospitals based on bed capacity, service variety, and workforce size, supporting data-driven workforce distribution analysis. The proposed framework integrates operational scheduling optimization with hospital-level clustering, providing practical decision support for healthcare workforce planning.
Co-Authors Aritonang, Mendarissan Asmah Indrawati Dadan Ramdan Gio, Prana Ugiana Habib Satria Hartono Hartono Hartono Hartono Lili Suryati Muhammad Khahfi Zuhanda Muhammad Zen, Muhammad Rachmat Aulia, Rachmat Rahmad Syah, Rahmad Rahmadhani, Citra Rahman, Sayuti Retna Astuti Kuswardani Sembiring, Arnes Sukiman Sukiman Suswati suswati suswati Zuhanda, Muhammad Khahfi