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All Journal Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) International Journal of Computer and Information System (IJCIS)
Ys, Herawati
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering

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Swarm Intelligence Framework using Hybrid ACO–PSO for Lecture Scheduling in Higher Education Hidayat, Rahmad; Sri Lestari, Ninik; Sukirno, Sukirno; Rosmalina, Rosmalina; YS, Herawati; Ramady, Givy Devira; Suhana, Asep; Willa Permatasari, Raden; Sukandi, Ganjar Kurniawan; Afiyah, Salamatul; Aca, Rukman; Subawi, Handoko
International Journal of Computer and Information System (IJCIS) Vol 6, No 3 (2025): IJCIS : Vol 6 - Issue 3 - 2025
Publisher : Institut Teknologi Bisnis AAS Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29040/ijcis.v6i3.252

Abstract

Complex combinatorial optimization problems that must meet various hard constraints and soft constraints occur in lecture scheduling. A feasible and high-quality schedule in limited computing time is often difficult to produce using conventional methods. In this study, a hybrid optimization model is proposed that combines Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO), the aim of which is to improve solution quality and convergence speed. In this model, ACO builds solutions based on pheromone intensity and heuristic information, while PSO is used to dynamically adjust ACO parameters through learning from individual and global search experiences. The model is implemented using MATLAB R2023b and tested on real data involving 10 courses, 4 classrooms, and 6 time slots per day. The ACO+PSO approach is significantly able to reduce the penalty value. This approach reflects better fulfillment of constraints and is the result of experiments obtained. Compared to pure ACO, the hybrid method shows more consistent and stable performance in various trials. Visualization of parameter convergence also strengthens the effectiveness of this hybrid approach in finding the optimal parameter configuration. This research contributes to the development of an intelligent lecture scheduling system that is adaptive and aligned with institutional policies.
Particle Swarm Optimization for Interference Mitigation of Wireless Body Area Network: A Systematic Review Hidayat, Rahmad; Lestari, Ninik Sri; Sujana, Ahmad; Mahardika, Andrew Ghea; YS, Herawati; Ramady, Givy Devira
Jurnal Ilmiah Teknik Elektro Komputer dan Informatika Vol. 9 No. 4 (2023): December
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26555/jiteki.v9i4.27171

Abstract

Wireless body area networks (WBAN) has now become an important technology in supporting services in the health sector and several other fields. Various surveys and research have been carried out massively on the use of swarm intelligent (SI) algorithms in various fields in the last ten years, but the use of SI in wireless body area networks (WBAN) in the last five years has not seen any significant progress. The aim of this research is to clarify and convince as well as to propose a answer to this problem, we have identified opportunities and topic trends using the particle swarm optimization (PSO) procedure as one of the swarm intelligence for optimizing wireless body area network interference mitigation performance. In this research, we analyzes primary studies collected using predefined exploration strings on online databases with the help of Publish or Perish and by the preferred reporting items for systematic reviews and meta-analysis (PRISMA) way. Articles were carefully selected for further analysis. It was found that very few researchers included optimization methods for swarm intelligence, especially PSO, in mitigating wireless body area network interference, whether for intra, inter, or cross-WBAN interference. This paper contributes to identifying the gap in using PSO for WBAN interference and also offers opportunities for using PSO both standalone and hybrid with other methods to further research on mitigating WBAN interference.
Co-Authors Aca, Rukman Givy Devira Ramady Lestari, Ninik Sri Mahardika, Andrew Ghea ROSMALINA ROSMALINA, ROSMALINA Salamatul Afiyah Sri Lestari, Ninik Subawi, Handoko Suhana, Asep Sujana, Ahmad Sukandi, Ganjar Kurniawan Sukirno Sukirno Willa Permatasari, Raden