📅 02 January 2024
DOI: 10.61132/jupiter.v2i1.37
Analisis Sistem Pendukung Keputusan Menggunakan Algoritma AHP Dan Topsis Untuk Menentukan Mahasiswa Lulusan Terbaik
Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika
Asosiasi Riset Ilmu Teknik Indonesia (ARITEKIN)
📄 Abstract
This research examines the application of the Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods in determining the best graduate students in the Ners Professional Study Program at Muhammadiyah University of East Kalimantan. The third step of the AHP method involves converting the values in the pairwise comparison matrix to decimal form, which is then normalized to calculate the priority weight of each criterion and sub-criteria. Next, checking the logic of the criteria and designing AHP-TOPSIS for ranking were carried out. The analysis showed that AHP resulted in 5 ranking changes with a percentage change of 4.4%, while TOPSIS resulted in 3 ranking changes with a percentage change of 3.9%. From these results, the AHP-TOPSIS method proved to have an accuracy of 83.00%. This article also presents a comparison between AHP, TOPSIS, and AHP-TOPSIS methods, where the best student selected is Dinda Ayu Framaisella. This research provides practical guidance for decision makers in solving multi-criteria problems and contributes to the selection of the best graduate students with a comprehensive and accurate approach.
🔖 Keywords
#AHP; TOPSIS
ℹ️ Informasi Publikasi
Tanggal Publikasi
02 January 2024
Volume / Nomor / Tahun
Volume 2, Nomor 1, Tahun 2024
📝 HOW TO CITE
Mukminatul Munawaroh; Hamada Zein; Fajri Harits Muzaki; Febri Ananda Chairi; Lidya Sari; Bobi Zinaidin Zidan; Muhammad Aditya Pratama; Novia Hidayati Ramadhani; Reyka Luna Karalo; Ririn Wahyuni, "Analisis Sistem Pendukung Keputusan Menggunakan Algoritma AHP Dan Topsis Untuk Menentukan Mahasiswa Lulusan Terbaik," Jupiter: Publikasi Ilmu Keteknikan Industri, Teknik Elektro dan Informatika, vol. 2, no. 1, Jan. 2024.
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