cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Mesran
Contact Email
mesran.skom.mkom@gmail.com
Phone
+6282370070808
Journal Mail Official
mesran.skom.mkom@gmail.com
Editorial Address
Jl. Besar Namorambe, P. Mansion, No 14, Kab. Deli Serdang, Sumatera Utara, 20356
Location
Kab. deli serdang,
Sumatera utara
INDONESIA
Journal of Decision Support System Research
Published by ADA Research Center
ISSN : -     EISSN : 3026006X     DOI : -
Core Subject : Science,
Computer Science & IT
Journal of Decision Support System Research journal publishes manuscripts within the fields of: 1. Natural Language Processing Pattern Classification, 2. Speech recognition and synthesis, 3. Robotic Intelligence, 4. Big Data, 5. Informatics Techniques, 6. Image and Speech Signal Processing, 7. Data Mining 8. Decision Support System, 9. Experts System, and 10. Cryptography
Arjuna Subject : Ilmu Komputer (semua kategori) - Kecerdasan Buatan
Articles 5 Documents
 1 
Search results for , issue "Vol. 2 No. 2 (2025): January 2025" : 5 Documents clear
Sistem Pendukung Keputusan Penerimaan KIP Menggunakan Metode Multi-Objective Optimization by Ratio Analysis (MOORA) Eka Gustina Bancin; Ebenezer Bangun; Muhammad Syahrizal; Hetty Rohayani
Journal of Decision Support System Research Vol. 2 No. 2 (2025): January 2025
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/dss.v2i2.93

Abstract

The Indonesia Smart Card for Higher Education (KIP Kuliah) is a government-funded scholarship program designed for students with strong academic potential but limited economic resources, as regulated in Minister of Education and Culture Regulation No. 12 of 2015 on the Indonesia Smart Program. Universitas Budi Darma Medan is one of the universities entrusted to accept and select prospective scholarship recipients. However, the large number of applicants requires a decision support system (DSS) to make the selection process more objective, efficient, and accurate. This study applies the Multi-Objective Optimization by Ratio Analysis (MOORA) method to determine KIP recipients. The MOORA method was chosen for its simplicity, flexibility, and effectiveness in weighting and ranking alternatives based on several predetermined criteria, namely number of achievement certificates, parents’ income, interview test scores, written test scores, and home ownership. Data from seven applicants were analyzed using weights established by the university. The results show that MOORA successfully generated a clear and measurable ranking, with alternative A5, Fredy Fau, obtaining the highest score of 0.1725 and ranked first as the best candidate for KIP assistance. Therefore, the application of the MOORA method within a DSS proves effective in assisting universities to carry out the selection process objectively and transparently.
Decision Support System for Determining the Best Coffee Shop Using the Multi Attribute Utility Theory (MAUT) Method with Rank Order Centroid (ROC) Weighting Ermis Claudia Malau, Risa; Mesran
Journal of Decision Support System Research Vol. 2 No. 2 (2025): January 2025
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/dss.v2i2.94

Abstract

This study discusses the development of a decision support system (DSS) to determine the best coffee shop using the Multi Attribute Utility Theory (MAUT) method and Rank Order Centroid (ROC) weighting. The background of this research is based on the rapid growth of the coffee shop business, which has led to intense competition, requiring business owners to have appropriate strategies and decision-making in choosing a strategic location, adequate facilities, and competitive pricing. The MAUT method is applied because it can accommodate various attributes and criteria that influence decision-making, while ROC is utilized to assign objective weights to each criterion. This study involved five alternative coffee shops, and five evaluation criteria. The results of the calculations show that Coffee Lab achieved the highest final utility value of 0.718, thus being ranked as the best coffee shop, followed by Coffeenatics with 0.395 in second place, Dominico with 0.233 in third place, Kallia with 0.188 in fourth place, and Kopi Tuya with 0.054 in the last position. These findings demonstrate that the application of the MAUT method with ROC weighting can provide objective, systematic, and accurate recommendations in determining the best alternative based on the established criteria. Therefore, this research is expected to serve as a reference for the application of DSS in the coffee shop business sector as well as in other areas that require multi-criteria decision-making.
Decision Support System for Recipients of Cash Social Assistance using the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) Method Alfarisi Pasaribu, Ahmad; Saputra, Imam; Karim, Abdul
Journal of Decision Support System Research Vol. 2 No. 2 (2025): January 2025
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/dss.v2i2.95

Abstract

Cash Social Assistance (BST) is assistance in the form of money provided to poor, disadvantaged, and/or vulnerable families affected by the Corona Virus Disease 2019 (COVID-19) outbreak. The amount of Cash Social Assistance is IDR 600,000/family/month. This Cash Social Assistance is a social safety net program of the Ministry of Social Affairs intended for poor and vulnerable families affected by Covid-19. This program is a special assignment assistance from the President. Social assistance for areas outside Jabodetabek is provided in the form of money, while for the Jabodetabek area it is provided in the form of basic necessities. The provision of BST assistance does not include recipients of the Family Hope Program (PKH), Staple Food Cards, and Pre-Employment Cards. To obtain the Cash Social Assistance (BST) funds, the government has set several criteria for which families can be determined and are entitled to receive the Cash Social Assistance (BST). These criteria will later help government agencies in determining which residents can be selected to receive the Poor Family Assistance Fund. Therefore, a government agency must have a Decision Support System for Cash Social Assistance (BST) recommendations using the Multi Objective Optimization on the Basis of Ratio Analysis (MOORA) method, with the existence of a decision support system for determining Cash Social Assistance (BST) it is expected to run well, be on target, and be received by the entitled people. Thus, decision makers can compare the performance between the old system and the decision support system for determining BST funds using the Multi Objective Optimization On The Basis Of Ratio Analysis (MOORA) method without having to re-request data on families who will be given Cash Social Assistance (BST) funds.
Sistem Pendukung Keputusan Rekomendasi Pemilihan Calon Ketua BEM dengan Menggunakan Metode MOORA Halomoan Hasibuan, Haposan; Laia, Sarpita; Mesran
Journal of Decision Support System Research Vol. 2 No. 2 (2025): January 2025
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/dss.v2i2.96

Abstract

The Student Executive Board (BEM) is an official student organization that holds a strategic role as a forum for aspirations, advocacy, coordination, and the development of student potential in higher education institutions. The election of BEM chairman candidates at Universitas Budi Darma was previously conducted manually, making it less efficient and lacking systematic evaluation criteria. Therefore, this study aims to design a decision support system (DSS) for selecting BEM chairman candidates using the Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) method. The MOORA method was chosen because it is capable of optimizing various conflicting criteria simultaneously. This study involved seven alternative candidates and seven criteria, namely leadership training (LDK), student activity, vision and mission, semester GPA (IPS), non-academic achievements, academic achievements, and semester level, with weights determined using the Rank Order Centroid (ROC) method. The collected data were then processed through normalization, weighting, and MOORA optimization calculations to determine candidate rankings. The results showed that out of the seven candidates, the best alternative was obtained by candidate A3 named Debby with a score of 0.4108. The implementation of this system proved to provide objective, fast, and accurate recommendations in determining the most suitable BEM chairman candidate. Thus, the MOORA method can serve as an effective solution to improve the quality of the BEM election process and support the enhancement of student organizational performance at Universitas Budi Darma.
Sistem Pendukung Keputusan Seleksi Dosen Non Komputer Terbaik Menggunakan Metode Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) Harry Pollin Sitorus; Khairuddin
Journal of Decision Support System Research Vol. 2 No. 2 (2025): January 2025
Publisher : ADA Research Center

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64366/dss.v2i2.97

Abstract

The teaching profession holds a strategic role in advancing knowledge and fostering student development. Budi Darma University, as one of the higher education institutions, strives to provide recognition to the best non-computer lecturers, evaluated through measurable criteria such as competence, research output, achievements, educational background, and disciplinary records. However, the similarity of qualifications among lecturers often creates challenges in conducting fair and accurate selection. Therefore, this study applies a Decision Support System (DSS) using the Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) method to assist decision-making in selecting the best non-computer lecturer. The research involved seven lecturers as alternatives and six assessment criteria, with weights determined using the Rank Order Centroid (ROC) method. The process included defining alternatives, weighting criteria, normalizing the decision matrix, and calculating MOORA optimization values. The results show that alternative A1, namely Suginam, obtained the highest optimization score of 0.6211, and was therefore designated as the best non-computer lecturer. These findings highlight that the MOORA method can provide objective, transparent, and systematic selection results in decision-making processes. Furthermore, this study demonstrates the flexibility of the MOORA method to be adapted to various selection needs in academic settings, particularly in improving lecturer quality and motivation through performance-based recognition.

Page 1 of 1 | Total Record : 5

 1 

Filter by Year

2025 2025


Reset
Filter By Issues
All Issue Vol. 2 No. 3 (2025): May 2025 Vol. 2 No. 2 (2025): January 2025 Vol. 2 No. 1 (2024): September 2024 Vol. 1 No. 3 (2024): May 2024 Vol. 1 No. 2 (2024): January 2024 Vol. 1 No. 1 (2023): September 2023