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All Journal Asian Journal of Applied Education Komputasi : Jurnal Ilmiah Ilmu Komputer dan Matematika
Rajainal Saragih
Politeknik Bisnis Indonesia
Computer Science & IT Control & Systems Engineering Education Mathematics Other

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Weighted Goal Programming Model for Course Scheduling Optimization: A Case Study at Computer Science Study Program Yessy Hans Aprilia Manurung; Juli Antasari Br Sinaga; Yoel Octobe Purba; Rajainal Saragih
Asian Journal of Applied Education (AJAE) Vol. 5 No. 3 (2026): July 2026
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ajae.v5i3.16754

Abstract

Course scheduling is a complex combinatorial optimization problem frequently constrained by limited physical resources and time availability. This study formulates a mathematical model to optimize the Even Semester course schedule at the Computer Science Study Program, HKBP Nommensen Pematangsiantar University, which operates under critical infrastructure constraints: five regular classrooms and one computer laboratory. The Weighted Goal Programming (WGP) method with a binary Mixed Integer Linear Programming (MILP) approach was implemented using Python software. The model integrates hard constraints to guarantee a conflict-free schedule for both rooms and lecturers, and accommodates soft constraints through hierarchical priority weighting. Priority goals include optimizing laboratory allocation for practicum courses, equalizing lecturers' teaching workloads to prevent burnout, and minimizing late-evening class sessions. Computational results confirm that the model achieved convergence to a Global Optimal Solution with an objective function value of 19. The WGP model successfully eliminated all scheduling conflicts (zero conflict) and compressed the physical facility requirement from 13 rooms in the manual schedule to only five regular classrooms and one computer laboratory. Furthermore, the proportion of evening classes was significantly reduced, resulting in a more efficient, equitable, and operationally applicable course schedule.
Application of CPM and PERT Methods in Residential Construction Project Scheduling: A Case Study Rajainal Saragih; Hengki Mangiring Parulian Simarmata; July Antasari Br Sinaga; Gayus Simarmata; Andi Manalu
Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Vol. 23 No. 2 (2026): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Program Studi Ilmu Komputer, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/komputasi.v23i2.101

Abstract

This study aims to analyze and optimize the scheduling of a residential construction project using the CPM, crashing techniques, and the PERT. A quantitative approach is employed by utilizing data obtained from observations and interviews conducted on a housing construction project in Bandar District, Simalungun Regency. CPM analysis is used to identify the critical path and determine the project duration, while crashing techniques are applied to obtain acceleration alternatives by considering additional costs. Furthermore, the PERT method is used to analyze uncertainty in project duration and to calculate the probability of project completion. The results show that the project duration under normal conditions is 59 days, with the critical path identified as A–B–D–E–G–H–J–O–P. After applying crashing, the project duration is reduced to 55 days with an additional cost of IDR 212,500. The PERT analysis indicates that the expected project duration is 44 days, with a completion probability of approximately 99% for a target duration of 49 days. These findings demonstrate that the combination of CPM, crashing, and PERT methods is effective in improving time and cost efficiency, while also providing a more reliable basis for decision-making under conditions of uncertainty.
Co-Authors Andi Manalu Gayus Simarmata Hengki Mangiring Parulian Simarmata Juli Antasari Br Sinaga July Antasari Br Sinaga Yessy Hans Aprilia Manurung Yoel Octobe Purba