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Fajrul Islami
Universitas Putra Indonesia YPTK Padang
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Journal : journal of computer scine and information technology

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Simple Additive Weighting (SAW) Method to Provide Recommendations for Selection of Graphic Processing Unit (GPU) Adrul Hutama; Fajrul Islami; Dodi Guswandi
Journal of Computer Scine and Information Technology Volume 9 Issue 2 (2023): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jcsitech.v9i2.71

Abstract

CV. Venes Jaya is a company that operates in the field of technological equipment such as computer hardware, monitors, recording equipment, communications equipment, networks, and many more. With the complete range of products sold and reliable teams, this company still has problems in providing recommendations for GPU selection to customers. This process is still carried out manually, namely by providing recommendations according to the funds owned by the customer. If there is more than one alternative that suits the funds owned by the customer, employees will have difficulty choosing them. Such a manual process is likely to be wrong or mistaken. Therefore, there is a need for innovation that can help and make it easier for employees to provide recommendations for GPU selection to customers, namely by implementing a Decision Support System (SPK) that uses the Simple Additive Weighting (SAW) method built with the VB programming language, and a MySQL database. in determining GPU recommendations that will be given to customers. This system is expected to help CV. Venes Jaya in providing GPU recommendations quickly, precisely and accurately. The results obtained from this research are that Alternative 5, namely the Gigabyte RTX 3080 Ti Gaming OC, was selected as the best alternative with a total value of 1. These results are the results obtained from the Decision Support System created by the author, where these results will be used as recommendations to customers in choosing Graphics . Processing Unit (GPU). This system can help CV. Venes Jaya in providing GPU recommendations to customers quickly, precisely and accurately
Customer Relationship Management Increasing Curtain Sales with Importance Performance Analysis and Customer Satisfaction Index Methods Andrian, Reski; Islami, Fajrul; Arlis, Syafri
Journal of Computer Scine and Information Technology Volume 11 Issue 1 (2025): JCSITech
Publisher : Universitas Putra Indonesia YPTK Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35134/jcsitech.v11i1.132

Abstract

The increasingly rapid advancement of technology has an indirect impact on humans. Computers are one of the results of technological advances that can help humans improve the quality and quantity of work. By using computers as one of the tools in presenting data information, especially data processing supported by PHP and MySQL applications, it can support the speed of data processing as efficiently as possible. This study uses the Importance Performance Analysis (IPA) Method and the Customer Satisfaction Index (CSI) Method. The IPA method is a method used to map the relationship between interests and performance of each attribute to meet consumer satisfaction by providing a Likert scale. While the CSI method is a method used to determine the level of consumer satisfaction as a whole by looking at the level of satisfaction of product and service attributes. Based on the combination of the IPA and CSI methods carried out directly in the field using interview techniques, as well as by studying books related to the problems discussed, it is expected that the new system that will be implemented can improve the quality of information so that it can be useful for the relevant agencies. The results of this study are based on the consumer satisfaction index of 82.24% , so that by applying these two methods, it can find consumer satisfaction in increasing curtain sales.
Co-Authors Adrul Hutama Agung Ramadhanu Andre Gunawan Andrian, Reski Arsyah, Ulya Ilhami Devita, Retno Dodi Guswandi emil nafan Gushelmi Hadi Syahputra Putra Irfan Rizki Nur Lusman, Akbar Pratiwi, Mutiana Putra, Ondra Eka Rianti, Eva Sarjon Defit Sumijan Sumijan Sumijan Syafri Arlis Tahmid, Riskian Vivik Shofiah Raudatussalamah