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Sahat Sonang
Politeknik Bisnis Indonesia
Computer Science & IT

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SISTEM PENDUKUNG KEPUTUSAN PENENTUAN PELANGGAN TERBAIK MENGGUNAKAN METODE WEIGHTED PRODUCT Victor Marudut Mulia Siregar; Sahat Sonang; Erikson Damanik
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 4 No 2 (2021)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v4i2.392

Abstract

This study aims to overcome the problem of selecting the best customer at Pematangsiantar Subur Graphic Printing. For the smooth running of the printing business, Subur Graphics maintains good relations with consumers by giving rewards to the best customers. In determining the best customer for graphic fertile printing, it is still done manually. To help overcome the problem of selecting the best customer, a decision support system is designed. Web-based decision support system built using the Weighted Product method. This decision support system uses criteria consisting of total shopping, payment method, length of subscription, payment status and total visits. The result of this research is a web-based decision support system with an output consisting of recommendations for the three best customers, namely the first best alternative Pd_Pphn with a vector value of V 0.085, the second best alternative GPIB Maranatha with a vector value of V 0.080, and the third best alternative SPTI_Ib_Mrni with a vector value of V 0.077. With a decision support system for determining the best customer using the weighted product method, Subur Graphic Printing can easily select the best customer.
PREDIKSI PRESTASI MAHASISWA DENGAN MENGGUNAKAN ALGORITMA BACKPROPAGATION Sahat Sonang; Arifin Tua Purba; Sarida Sirait
Jurnal Tekinkom (Teknik Informasi dan Komputer) Vol 5 No 1 (2022)
Publisher : Politeknik Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37600/tekinkom.v5i1.512

Abstract

This study aims to overcome the problems in predicting student achievement at the Polytechnic Business Indonesia Pematangsiantar. To predict student achievement is done by applying Backpropagation algorithm and implement it into Matlab software. Backpropagation algorithm is one of the methods on artificial neural networks that is quite reliable in solving problems including prediction. In this study conducted on the object of students semester One with a lot of data samples 26 samples. The data sample is divided into two parts, 70% of the data is used as training data and 30% of the data is used as testing data. This study uses ten architectural models, namely 9-2-1, 9-3-1, 9-4-1, 9-5-1, 9-6-1, 9-7-1, 9-8-1, 9-9-1, 9-10-1, 9-11-1. Of the ten Backpropagation network architecture models implemented in predicting student achievement in Matlab software obtained the best output is 9-2-1 pattern with epoch 8149, time duration for 17 seconds, and MSE (error rate) value of 2.80 e-05 for training and MSE (error rate) of 0.1248 with accuracy of 87.5% for testing. The best architecture obtained is expected to be used as a picture by the academic Polytechnic Business Indonesia (PBI) in predicting student achievement.
Co-Authors Arifin Tua Purba Erikson Damanik Sarida Sirait Victor Marudut Mulia Siregar