The use of FMADM and SAW Methods in Decision-Making in Selecting the Chairman of the Study Program

The selection of Head of Study Program (Head of Study Program) in Higher Education is often still done subjectively through personal recommendations, without measurable assessment instruments and transparent evaluation reports. This study aims to design a decision support system based on Fuzzy Multiple Attribute Decision Making (FMADM) with the Simple Additive Weighting (SAW) method to improve the objectivity and accountability of the Head of Study Program selection process. The research data consists of 10 candidates for permanent lecturers in the Informatics Engineering Study Program at Kuantan Singingi Islamic University in 2025 with five assessment criteria: length of service (C1), functional position (C2), education (C3), performance (C4), and achievement (C5). The analysis process was carried out by converting the data into fuzzy numbers, normalizing according to attribute types, and calculating preference values ​​using the SAW method. The results showed that the top three candidates were Harianja, S.Pd., M.Kom and Elgamar, S.Kom., M.Kom with the highest V value of 2.75, followed by Febri Haswan, S.Kom., M.Kom with a value of 2.50. The main contribution of this research is to provide a Head of Study Program selection model that is consistent with other MADM methods (TOPSIS and VIKOR), in accordance with historical selection patterns, and is able to increase transparency, objectivity, and accountability through measurable evaluation reports that can be used as a basis for the SOP for selecting Heads of Study Programs.

Authors

Publication Details

Journal
INOVTEK Polbeng - Seri Informatika
Published
2025-09-16
DOI
https://doi.org/10.35314/b3ext947
Primary Topic
Management and Optimization Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The use of FMADM and SAW Methods in Decision-Making in Selecting the Chairman of the Study Program

Helpi Nopriandi, Jasri Jasri, Erlinda Erlinda, Elgamar Syam et al.
INOVTEK Polbeng - Seri Informatika
Management and Optimization Techniques
article

The use of FMADM and SAW Methods in Decision-Making in Selecting the Chairman of the Study Program

Helpi Nopriandi, Jasri Jasri, Erlinda Erlinda, Elgamar Syam, Sri Chairani, M Yusfahmi
article en

Abstract

The selection of Head of Study Program (Head of Study Program) in Higher Education is often still done subjectively through personal recommendations, without measurable assessment instruments and transparent evaluation reports. This study aims to design a decision support system based on Fuzzy Multiple Attribute Decision Making (FMADM) with the Simple Additive Weighting (SAW) method to improve the objectivity and accountability of the Head of Study Program selection process. The research data consists of 10 candidates for permanent lecturers in the Informatics Engineering Study Program at Kuantan Singingi Islamic University in 2025 with five assessment criteria: length of service (C1), functional position (C2), education (C3), performance (C4), and achievement (C5). The analysis process was carried out by converting the data into fuzzy numbers, normalizing according to attribute types, and calculating preference values ​​using the SAW method. The results showed that the top three candidates were Harianja, S.Pd., M.Kom and Elgamar, S.Kom., M.Kom with the highest V value of 2.75, followed by Febri Haswan, S.Kom., M.Kom with a value of 2.50. The main contribution of this research is to provide a Head of Study Program selection model that is consistent with other MADM methods (TOPSIS and VIKOR), in accordance with historical selection patterns, and is able to increase transparency, objectivity, and accountability through measurable evaluation reports that can be used as a basis for the SOP for selecting Heads of Study Programs.

INOVTEK Polbeng - Seri InformatikaVol. 10(3)
Openalex Percentile: Top 63%
Management and Optimization Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.