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Journal : Jurnal Teknik Informatika C.I.T. Medicom

Study Tentang Model Fuzzy Goal Programming Pada Pendekatan Masalah Perencanaan Produksi Desi Vinsensia; Yulia Utami; Mian Sari Simanjuntak; Arya Riski Tarigan
Jurnal Teknik Informatika C.I.T Medicom Vol 13 No 2 (2021): September: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol13.2021.149.pp75-81

Abstract

The production planning system can provide satisfaction to the manufacture with the desire target and also with the available raw materials. In achieving the target of goals also face a situation of uncertainty (fuzzy). The aims of this study is proposed the model of fuzzy goal programming approach to optimize production planning system. In this model obtaining maximizing profit and revenue with consider minimize costs of labor cost, raw materials cost, time machine production, and also inventory cost. The numerical example is illustrate that the fuzzy goal programming model can optimize optimize production and profit according desired of decision maker.
PERAMALAN JUMLAH MAHASISWA BARU DENGAN PENDEKATAN REGRESI LINIER Yulia Utami; Desi Vinsensia; Aura Nissa; Sulastri Sulastri
Jurnal Teknik Informatika C.I.T Medicom Vol 14 No 1 (2022): March: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol14.2022.231.pp10-15

Abstract

Forecasting models are the result of developments in the field of science and technology that provide convenience in predicting future events. This paper aims to develop a linear regression model to predict the number of new students in the next year. The data to be used in this study is the total of students majoring in informatics engineering and information management during the last 5 years. Based on result obtained the number of student for department of Informatics Engineering is 198 people with a MAPE (Mean Absolute Percentage Error) score of 16.5%, and for the new students department of Informatic Management is 8 people with a MAPE score of 16.1%.
A Improve refinement approach iterative method for solution linear equition of sparse matrices Desi Vinsensia; Yulia Utami; Fathia Siregar; Muhammad Arifin
Jurnal Teknik Informatika C.I.T Medicom Vol 15 No 6 (2024): January : Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/cit.Vol15.2024.721.pp306-313

Abstract

In this paper, systems of linear equations on sparse matrices investigated through modified improve method using Gauss-Seidel and successive overrelaxation (SOR) approach. Taking into adapted convergence rate on the Improve refinement Gauss-seidel outperformed the prior two Gauss-Seidel methods in terms of rate of convergence and number of iterations required to solve the problem by applying a modified version of the Gauss-Seidel approach. to observe the effectiveness of this method, the numerical example is given. The main findings in this study, that Gauss seidel improvement refinement gives optimum spectral radius and convergence rate. Similarly, the SOR improved refinement method gives. Considering their performance, using parameters such as time to converge, number of iterations required to converge and spectral radius level of accuracy. However, SOR works with relaxation values so that it greatly affects the convergence rate and spectral radius results if given greater than 1.