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All Journal Bulletin of Electrical Engineering and Informatics JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING
Saib Suwilo
Department Of Mathematics, Faculty Of Mathematics And Natural Sciences, Universitas Sumatera Utara
Computer Science & IT Electrical & Electronics Engineering Engineering

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Goal Programming Method in Optimizing Course Student Admission, Operational Costs and Profits Muhammad Khahfi Zuhanda; Saib Suwilo; Opim Salim Sitompul; Mardingsih Mardingsih
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 5, No 2 (2022): Issues January 2022
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v5i2.6072

Abstract

In today's business competition, educational institutions or courses require optimizing profits. However, this is not easy because, in its implementation, there are many priority objective functions that must be fulfilled. In this case, the course institution has different class programs, namely literacy, numeracy, and math olympiad programs, with various operational costs per program type and course fees per program type. This problem requires setting priorities because of the limited number of revenues, operating costs, and profit targets. In this paper, the researcher uses Winter's Exponential Smoothing forecasting model to determine the number of students, operating costs, and profits in the following year. Then the researcher analyzes the planning with the goal programming method to minimize the deviation of the multi-objective programming. This research shows that the number of student admissions who can meet market demand for January 2021 decreased by 5.41%, in February decreased by 3.20%, in March decreased by 1.29%, April remained constant, in May increased by 1.44%, June increased by 2.16%, July increased 2.82%, August increased 2.78%, September increased 3.47%, October increased 3.22%, November an increase of 3.33%, and for December an increase of 2.69%. The total operational cost that does not exceed the target limit is Rp. 30,475,0000 for one year. The total profit has reached the target to be achieved, which is Rp. 322,150,000 for one year.
Improved Benders decomposition approach to complete robust optimization in box-interval Hendra Cipta; Saib Suwilo; Sutarman Sutarman; Herman Mawengkang
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.4394

Abstract

Robust optimization is based on the assumption that uncertain data has a convex set as well as a finite set termed uncertainty. The discussion starts with determining the robust counterpart, which is accomplished by assuming the indeterminate data set is in the form of boxes, intervals, box-intervals, ellipses, or polyhedra. In this study, the robust counterpart is characterized by a box-interval uncertainty set. Robust counterpart formulation is also associated with master and subproblems. Robust Benders decomposition is applied to address problems with convex goals and quasiconvex constraints in robust optimization. For all data parameters, this method is used to determine the best resilient solution in the feasible region. A manual example of this problem's calculation is provided, and the process is continued using production and operations management–quantitative methods (POM-QM) software.
Co-Authors Heni Pujiastuti Herman Mawengkang Mardingsih Mardingsih Muhammad Khahfi Zuhanda Opim Salim Sitompul Sutarman Sutarman