{"title":"层次分析法与简单多属性评分法相结合的最佳讲师选择","authors":"Deni Mahdiana, Nidya Kusumawardhany","doi":"10.1109/ICoSTA48221.2020.1570615695","DOIUrl":null,"url":null,"abstract":"This study aims to develop a model of decision support systems (DSS) for the selection of the best lecturer at the Faculty of Information Technology of Universitas Budi Luhur using a combination of Analytical Hierarchy Process (AHP) and Simple Multi-Attribute Rating Technique (SMART) methods. In this study, 12 (twelve) criteria were used to select the best lecturers: Educational level, Academic functional position, Lecturer Certification, Lecturer Semester Performance Index, Number of Respondents, Average Number of Meetings, Number of Research, Number of community service, Number of Publications, Number of Grants, Discipline submit final exam scores and Faculty Discipline.The results of the calculation of the consistency ratio (CR) for the best lecturer selection criteria obtained CR values = 0.06. The calculation results are not more than 0.1 or 10 percent, so the comparison of the best lecturer selection criteria is consistent and does not require revision of the assessment. Quality Testing of DSS application software for the best lecturer selection was tested based on 4 (four) McCall method variables, namely Functionality, Reliability, Usability, and Efficiency. The overall test results show that the quality of the application of the decision support system for the selection of the best lecturers has a \"Good\" criterion of 78.20 percent.","PeriodicalId":375166,"journal":{"name":"2020 International Conference on Smart Technology and Applications (ICoSTA)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"The Combination of Analytical Hierarchy Process and Simple Multi-Attribute Rating Technique for The Selection of The Best Lecturer\",\"authors\":\"Deni Mahdiana, Nidya Kusumawardhany\",\"doi\":\"10.1109/ICoSTA48221.2020.1570615695\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study aims to develop a model of decision support systems (DSS) for the selection of the best lecturer at the Faculty of Information Technology of Universitas Budi Luhur using a combination of Analytical Hierarchy Process (AHP) and Simple Multi-Attribute Rating Technique (SMART) methods. In this study, 12 (twelve) criteria were used to select the best lecturers: Educational level, Academic functional position, Lecturer Certification, Lecturer Semester Performance Index, Number of Respondents, Average Number of Meetings, Number of Research, Number of community service, Number of Publications, Number of Grants, Discipline submit final exam scores and Faculty Discipline.The results of the calculation of the consistency ratio (CR) for the best lecturer selection criteria obtained CR values = 0.06. The calculation results are not more than 0.1 or 10 percent, so the comparison of the best lecturer selection criteria is consistent and does not require revision of the assessment. Quality Testing of DSS application software for the best lecturer selection was tested based on 4 (four) McCall method variables, namely Functionality, Reliability, Usability, and Efficiency. The overall test results show that the quality of the application of the decision support system for the selection of the best lecturers has a \\\"Good\\\" criterion of 78.20 percent.\",\"PeriodicalId\":375166,\"journal\":{\"name\":\"2020 International Conference on Smart Technology and Applications (ICoSTA)\",\"volume\":\"59 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Smart Technology and Applications (ICoSTA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICoSTA48221.2020.1570615695\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Smart Technology and Applications (ICoSTA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICoSTA48221.2020.1570615695","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Combination of Analytical Hierarchy Process and Simple Multi-Attribute Rating Technique for The Selection of The Best Lecturer
This study aims to develop a model of decision support systems (DSS) for the selection of the best lecturer at the Faculty of Information Technology of Universitas Budi Luhur using a combination of Analytical Hierarchy Process (AHP) and Simple Multi-Attribute Rating Technique (SMART) methods. In this study, 12 (twelve) criteria were used to select the best lecturers: Educational level, Academic functional position, Lecturer Certification, Lecturer Semester Performance Index, Number of Respondents, Average Number of Meetings, Number of Research, Number of community service, Number of Publications, Number of Grants, Discipline submit final exam scores and Faculty Discipline.The results of the calculation of the consistency ratio (CR) for the best lecturer selection criteria obtained CR values = 0.06. The calculation results are not more than 0.1 or 10 percent, so the comparison of the best lecturer selection criteria is consistent and does not require revision of the assessment. Quality Testing of DSS application software for the best lecturer selection was tested based on 4 (four) McCall method variables, namely Functionality, Reliability, Usability, and Efficiency. The overall test results show that the quality of the application of the decision support system for the selection of the best lecturers has a "Good" criterion of 78.20 percent.