Comparison of Simple Additive Weighting Method and Weighted Performance Indicator Method for Lecturer Performance Assessment

Full Text (PDF, 305KB), PP.1-11

Views: 0 Downloads: 0


Terttiaavini 1,2,* Yusuf Hartono 3 Ermatita 4 Dian Palupi Rini 4

1. Sriwijaya University, Faculty of Engineering Doctoral Program, 30128, Palembang, Indonesia

2. Indo Global Mandiri University, Faculty of Computer Science, Palembang 30129 Indonesia

3. Sriwijaya University, Faculty of Mathematic Science, Palembang, 30128, Indonesia

4. Universitas Sriwijaya, Faculty of Computer Science, Palembang, 30128, Indonesia

* Corresponding author.


Received: 15 Jun. 2022 / Revised: 20 Jul. 2022 / Accepted: 24 Aug. 2022 / Published: 8 Apr. 2023

Index Terms

Comparison method, Simple Additive Weighting Method, Weighted Performance Indicator Method, Lecturer Performance Assesment, Respondents Opinion.


The development of methods for assessing lecturers' performance is needed to motivate lecturers to achieve institutional targets. Currently, lecturers are required to be able to adapt to the rapid development of technology. Lecturer performance assessment must be done periodically. Competence is measured as a basis for planning resource development activities. The method that is often used for assessing lecturer performance is the Simple Additive Weighting (SAW) method. However, the SAW method has drawbacks, namely 1) the process of determining criteria is only carried out by the leadership (subjective); 2) The SAW method can only be applied to multi-criteria data ; 3) Data ranking problems. Based on this deficiency, a new method was built, namely, the Weighted Performance Indicator (WPI) method using respondents’ opinion to determine the criteria. This study aims to compare the performance of the two methods. Testing criteria using SPPS application dan WPI method, while testing methods utilized the SAW method and the WPI method. The results of the criterion test show the Percentage of Similarity of data validity = 96.7 % witht the minimum percentage limit (MPL) = 40%. While the results of the SAW method and WPI method testing resulted in the highest score in the 13th alternative, namely SAW score (v13) = 793.76 and WP score (WP13) = 0.928, and the lowest value in the 30th alternative, SAW score (v30) = 18.60 and WP score (WP30) = 0.140. the ranking positions in these two methods show similarities. However, for other alternatives, the rating value can be different. 
The WPI method is a scientific development in the field of decision support systems that can be applied to other performance assessments, such other human resources, system performance assesment etc. 
The results of this study prove that the WPI method can be used as a performance assessment method with different characteristics from the SAW method.

Cite This Paper

Terttiaavini, Yusuf Hartono, Ermatita, Dian Palupi Rini, "Comparison of Simple Additive Weighting Method and Weighted Performance Indicator Method for Lecturer Performance Assessment", International Journal of Modern Education and Computer Science(IJMECS), Vol.15, No.2, pp. 1-11, 2023. DOI:10.5815/ijmecs.2023.02.01


[1]Terttiaavini T, Rita wirya saputra. Pengembangan Sistem Informasi Kinerja Dosen Berbasis Web Dalam Upaya Meningkatkan Kompetensi Dosen Di Univ. Indo Global Mandiri. J Inform Glob Vol 2013;4:42–53.

[2]Terttiaavini T, Zamzam F, Ramadhan M, Saputra TS. Knowledge Mangement System sebagai Dasar Pengembangan Sistem Informasi Kinerja Dosen 2020;11:1–6.

[3]Presiden Republik Indonesia. Peraturan Republik Indonesia Nomor 37 Tahun 2009 Tentang Dosen. 2009.

[4]Khan W, Rahaman MM. Measuring the performance of e-primary school systems in Bangladesh. Int J Mod Educ Comput Sci 2020;12:35–41.

[5]Lucky EO-I, Yusoff NBM. A Conceptual Framework On Teaching Qualifications, Characteristics, Competence And Lecturer Performance For Higher Education Institutions in Nigeria. Malaysian Online J Educ 2020;4:1–16.

[6]Sinaga A, Maulana D. Implementation of Weighted Product Method for Evaluating Performance of Technicians. Mod Educ Comput Sci 2022;4:30–42.

[7]Zhang X, Liu Y. Evaluating the undergraduate course based on a fuzzy ahp-fis model. Int J Mod Educ Comput Sci 2020;12:55–66.

[8]Majumder M. Multi Criteria Decision Making. Int. J. Res. Appl. Sci. Eng. Technol., vol. 49.98, 2015, p. 35–47.

[9]Taufiq R, Septarini RS, Hambali A, Yulianti Y. Analysis and Design of Decision Support System for Employee Performance Appraisal with Simple Additive Weighting (SAW) Method. OpenjournalUnpamAcId 2020;5:275–80.

[10]Subagyo HD, Ariani A, Qoriani HF, Widodo G. Decision Supporting System Employee Performance Appraisal Narotama University with Simple Additive Weighting Method (SAW). Int Conf Green Technol 2017;8:273–7.

[11]Terttiaavini, Zamzam F, Ramadhan M, Saputra TS. Design a Decision Support System to Evaluate The Performance of Indonesian Lecturers by Developing a Simple Additive Weighting Method. Test Eng Manag 2019;28:36–41.

[12]Aziz TFA, Sulistiyono S, Harsiti H, Setyawan A, Suhendar A, Munandar TA. Group decision support system for employee performance evaluation using combined simple additive weighting and Borda. IOP Conf Ser Mater Sci Eng 2020;830.

[13]Daniawan B. Evaluation of Lecturer Teaching Performance Using AHP and SAW Methods. Bit-Tech 2018;1:30–9.

[14]Karami A, Bennett LS, He X. Mining Public opinion about economic issues: Twitter and the U.S. Presidential election. ArXiv 2018;9.

[15]Malonda R. Opini Publik Terhadap Pencitraan Politik dalam Meningkatkan Tingkat Elektabilitas Politik Pada Pemilu Presiden Tahun 2019 di Kabupaten Mihanasa. J Polit 2019;8:1–15.

[16]Juariyah J, Wijayanti N. Opini Mahasiswa Dalam Pemilu Presiden 2019 (Studi Kasus Aktifis Bem Fisip Tentang #2019Gantipresiden Pada Lima (5) Perguruan Tinggi Di Kabupaten Jember). Mediakom 2020;4:43–57.

[17]Hinderks A, Schrepp M, Domínguez Mayo FJ, Escalona MJ, Thomaschewski J. Developing a UX KPI based on the user experience questionnaire. Comput Stand Interfaces 2019;65:38–44.

[18]Nastišin IĽ. Research on the most important KPIs in social media that should be tracked. J Glob Sci 2017:1–6.

[19]Boulianne S. Mini-publics and Public Opinion: Two Survey-Based Experiments. Polit Stud 2018;66:119–36.

[20]Zhou X. Hierarchical Item Response Models for Analyzing Public Opinion. Polit Anal 2019;27:481–502.

[21]Terttiaavini, Hartono Y, Ermatita, Rini DP. Building a Weighted Performance Indicator Concept utilized The Respondent ’ s Opinion Approach. 2021 3rd Int. Conf. Electron. Represent. Algorithm. 3rd ed., IEEE; 2021, p. 137–42.

[22]Terttiaavini, Ermatita. Sistem Penilaian Kinerja Dosen menggunakan Decision Maker Respondent Opinion Model. J Inform Glob 2022;13:1–6.

[23]Nurmalini, Rahim R. Study Approach of Simple Additive Weighting For Decision Support System. IJSRST 2017;3.

[24]Kaliszewski I, Podkopaev D. Simple Additive Weighting – a metamodel for Multiple Criteria Decision Analysis methods. Expert Syst Appl 2016:1–7.

[25]Afshari A, Mojahed M, Yusuff RM. Simple Additive Weighting approach to Personnel Selection problem. Int J Innov Manag Technol 2010;1:511–5.

[26]Irvanizam I, Rusdiana S, Amrusi A, Arifah P, Usman T. An application of fuzzy multiple-attribute decision making model based onsimple additive weighting with triangular fuzzy numbers to distribute the decenthomes for impoverished families An application of fuzzy multiple-attribute decision making model based. SEMIRATA- Int. Conf. Sci. Technol. 2018, 2018.

[27]Aldamak A, Zolfaghari S. Review of efficiency ranking methods in data envelopment analysis. Meas J Int Meas Confed 2017;106:161–72.

[28]Ghozali I. Aplikasi Analisis Multivariate Dengan Program IBM SPSS 25. 2018.

[29]Ercan I, Yazici B, Sigirli D, Ediz B, Kan I. Examining cronbach alpha, theta, omega reliability coefficients according to the sample size. J Mod Appl Stat Methods 2007;6:291–303.

[30]Adler S, Campion M, Colquitt A, Grubb A, Murphy K, Ollander-Krane R, et al. Getting rid of performance ratings: Genius or folly? A debate. Ind Organ Psychol 2016;9:219–52.