{"title":"A TOPSIS AND ELECTRE COMPARISON ANALYSIS ON WEB-BASED SOFTWARE","authors":"Rivensin Rivensin, Deny Jollyta","doi":"10.21107/KURSOR.V11I1.253","DOIUrl":null,"url":null,"abstract":"Methods in the Decision Support System (DSS) have their own techniques in solving organizational problems. Determining the appropriate DSS method with the problem is a common difficulty experienced by organizations. The performance of a DSS method can be measured in various ways. This research aims to determine the performance of the two DSS methods, specifically Technique for Others Preference by Similarity to Ideal Solution (TOPSIS) and Election at Choix Traduisant La Realite (ELECTRE) which are applied to the best lecturer selection system. The research was carried out on software designed using efficiency as one of the International Organization for Standardization (ISO) 9126. The performance of both methods tested on validity and sensitivity testing. The results showed that the TOPSIS performance was better in terms of efficiency and sensitivity. TOPSIS execution time is 0.0085 seconds faster and has a greater sensitivity value of 2.18% compared to ELECTRE. Validity result gave the best results reaching 100% to ELECTRE. That means, the ELECTRE calculation can be trusted because it has a perfect level of accuracy.","PeriodicalId":52605,"journal":{"name":"Jurnal Ilmiah Kursor Menuju Solusi Teknologi Informasi","volume":"35 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Ilmiah Kursor Menuju Solusi Teknologi Informasi","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21107/KURSOR.V11I1.253","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Methods in the Decision Support System (DSS) have their own techniques in solving organizational problems. Determining the appropriate DSS method with the problem is a common difficulty experienced by organizations. The performance of a DSS method can be measured in various ways. This research aims to determine the performance of the two DSS methods, specifically Technique for Others Preference by Similarity to Ideal Solution (TOPSIS) and Election at Choix Traduisant La Realite (ELECTRE) which are applied to the best lecturer selection system. The research was carried out on software designed using efficiency as one of the International Organization for Standardization (ISO) 9126. The performance of both methods tested on validity and sensitivity testing. The results showed that the TOPSIS performance was better in terms of efficiency and sensitivity. TOPSIS execution time is 0.0085 seconds faster and has a greater sensitivity value of 2.18% compared to ELECTRE. Validity result gave the best results reaching 100% to ELECTRE. That means, the ELECTRE calculation can be trusted because it has a perfect level of accuracy.
决策支持系统(DSS)中的方法在解决组织问题方面有自己的技术。针对问题确定合适的决策支持系统方法是组织经常遇到的困难。决策支持系统的性能可以用不同的方法来衡量。本研究旨在确定两种DSS方法的性能,特别是应用于最佳讲师选择系统的他人偏好相似技术(TOPSIS)和选择Traduisant La Realite (ELECTRE)。本研究以国际标准化组织(ISO) 9126标准之一的效率为基础,进行软件设计。对两种方法进行了效度和灵敏度测试。结果表明,TOPSIS在效率和灵敏度方面都有较好的表现。与ELECTRE相比,TOPSIS的执行时间快0.0085秒,灵敏度值更高,为2.18%。效度结果表明,该方法的效度达到100%。这意味着,ELECTRE的计算是可信的,因为它具有完美的准确性。