IJARCCE ISSN (Online) 2278-1021 ISSN (Print) 2319-5940 International Journal of Advanced Research in Computer and Communication Engineering Vol. 9, Issue 11, November 2020 DOI 10.17148/IJARCCE.2020.91111 Copyright to IJARCCE IJARCCE 63 This work is licensed under a Creative Commons Attribution 4.0 International License Selection of the best lecturers using the Simple Additive Weighting method Achmad Noeman 1 , Wowon Priatna 2 , Abrar Hiswara 3 Department of Informatics, Faculty of Computer Science, Universitas Bhayangkara Jakarta Raya Jalan Raya Perjuangan Bekasi Utara, West Java, Indonesia 1,2,3 Abstract: In the process of determining the best lecturer by students, there are several criteria, including in terms of explaining the material, teaching methods, which make it easier for students to follow their courses. To assist in the selection process for someone to become the best lecturer for students, a decision support system is needed using Fuzzy Multiple Addictive Decision Making (FMADM). This study uses the SAW (Simple Addictive Weighted) method based on predetermined criteria. The SAW method can determine the selection of the best lecturer based on predetermined criteria for students, as well as looking for the weight value of each attribute to get the best lecturer. Keywords: Fuzzy Multiple Addictive Decision Making, SAW Method, Decision Support System, criteria for the best lecturers I. INTRODUCTION lecturers who are liked by students are a must in creating a comfortable and smooth learning process in the classroom that makes students enthusiastic about participating in the lecture process so that the learning process is more effective. Lecturers are professional educators and scientists with the main task of transforming and developing knowledge[1]. Bhayangkara Jakarta Raya University is a higher education institution that seeks to improve the quality of the learning process so that it can produce graduates who have competencies in their fields. Based on the Law of Republic of Indonesia No. 14 of 2005 concerning Teachers and Lecturers, that lecturers are entitled to promotions and awards according to with his academic performance[2]. With the appreciation of lecturers it can increase motivation which will have an impact on the development of academic management in universities. Lecturers who have achievements will be proud of their universities. So it is necessary to choose the best lecturer. In selecting the best lecturers at Bhayangkara Jakarta Raya University, there are several factors that become performance assessments, namely the teaching and learning process, questionnaires, student guidance, research and community service[3]. In selecting the best lecturer, computer tools are needed to obtain a decision support system[4] carried out by the decision maker[5]. This study uses the Simple Additive Weighting (SAW) method. The SAW method is used to determine weights and criteria. II. RESEARCH METHODOLOGY A. Analysis Data The basic concept of the SAW method is to find the weighted sum of the performance ratings for each alternative on all attributes. The SAW method requires a decision matrix normalization process (X) to a scale that can be compared with all available alternative ratings. The SAW method requires a decision matrix normalization process (X) to a scale that can be compared with all available alternative ratings. Fuzzy Multiple Addictive Decision Making (FMADM) is a method used to find optimal alternatives from a number of alternatives with certain criteria[6]. The essence of FMADM is to determine the weight value for each attribute, then proceed with a ranking process that will select the criteria.