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All Journal Jurnal Ilmiah Informatika dan Ilmu Komputer Jurnal Ilmiah Computer Science Journal of Information Technology, Software Engineering and Computer Science
Sriyasa, I Wayan
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering

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Sistem Pendukung Keputusan Penentuan Kinerja Sales Terbaik Menggunakan Kombinasi Grey Relational Analysis dan Pembobotan Rank Sum Citra, Puspa; Sriyasa, I Wayan; Santoso, Heri Bambang
Jurnal Ilmiah Computer Science Vol. 2 No. 2 (2024): Volume 2 Number 2 January 2024
Publisher : PT. SNN MEDIA TECH PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jics.v2i2.26

Abstract

The best sales performance is one of the key elements in the business world that not only reflects the ability of individuals or sales teams to achieve sales targets, but also becomes a key pillar in the growth and success of the company. The problem in choosing the best sales performance is that there is no decision support system model in choosing the best sales performance. The purpose of this study is to determine the best sales performance by applying the GRA method and rank sum weighting in the assessment of existing sales performance, so that the results of the sales performance appraisal will be a recommendation for companies in determining the best sales performance. The ranking results showed the highest value of 0.1309 obtained by sales Hadi for rank 1, the next highest value of 0.0941 obtained by sales Arini for rank 2, the next highest value of 0.0777 obtained by sales Cindy for rank 3.
Kombinasi Metode Rank Sum dan Grey Relational Analysis dalam Pemilihan Pelanggan Terbaik Sriyasa, I Wayan
Journal of Information Technology, Software Engineering and Computer Science (ITSECS) Vol. 2 No. 4 (2024): Volume 2 Number 4 October 2024
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/itsecs.v2i4.162

Abstract

Selecting the best customers is an important process in marketing and customer relationship management (CRM) strategies that aim to identify the customers who contribute the most to the success of the business. The main problem in selecting the best customer lies in the difficulty in objectively assessing and comparing customer performance, given the diversity of characteristics of each customer. The combination of rank sum and GRA methods is an approach that combines two powerful techniques in multi-attribute decision-making to evaluate and select the best alternatives. This approach aims to overcome the limitations of each method when used separately, and take advantage of the advantages of both methods in producing more objective and accurate decisions. The results of the alternative ranking show that Customer C is ranked first with a value of 0.2, followed by Customer A (0.1865) and Customer G (0.1864). Meanwhile, customers with the lowest GHG values, such as Customer H (0.0167), are in last position because their performance is furthest from ideal conditions. These results help visualize the ranking order based on the performance of each alternative, making it easier to make decisions in choosing the best customers. This research contributes to generating objective and transparent decisions, as well as helping companies identify potential customers based on criteria such as loyalty, revenue contribution, or long-term potential.
Sistem Pendukung Keputusan Pemilihan E-Commerce Menggunakan Pembobotan Entropy dan COPRAS Citra, Puspa; Santoso, Heri Bambang; Sriyasa, I Wayan
Jurnal Ilmiah Informatika dan Ilmu Komputer (JIMA-ILKOM) Vol. 3 No. 1 (2024): Volume 3 Number 1 March 2024
Publisher : PT. SNN MEDIA TECH PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/jima-ilkom.v3i1.25

Abstract

The choice of e-commerce platform is crucial for businesses that want to expand their reach and increase sales online. By choosing the right e-commerce platform, businesses can optimize their online operations, increase customer satisfaction, and achieve sustainable growth in an increasingly competitive digital marketplace. This study aims to select e-commerce using a combination of entropy weighting methods and COPRAS in producing alternative assessments and ratings of existing e-commerce, so that it becomes a recommendation for the public in choosing an e-commerce as a transaction platform. The ranking results in the final e-commerce score are rank 1 obtained for Shoope e-commerce with a value of 100%, rank 2 obtained for Tokopedia e-commerce with a value of 95.93%, rank 3 obtained for Lazada e-commerce with a value of 80.93%, and rank 4 obtained for Blibli e-commerce with a value of 58.07%. The recommendation results for selecting an E-Commerce platform using a combination of Entropy and COPRAS weighting methods provide the highest recommendation to the Shoope E-Commerce platform with the highest value of 100%.
Co-Authors Citra, Puspa Santoso, Heri Bambang