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All Journal Dinamik Techno.Com: Jurnal Teknologi Informasi JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Teknoinfo KOMPUTIKA - Jurnal Sistem Komputer Jurnal Tekno Kompak Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Teknologi dan Sistem Informasi J-Intech (Journal of Information and Technology) Paradigma Journal of Engineering and Information Technology for Community Service Jurnal Ilmiah Computer Science CHAIN: Journal of Computer Technology, Computer Engineering and Informatics
Ulum, Faruk
Universitas Terknokrat Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Education Electrical & Electronics Engineering Engineering Environmental Science Library & Information Science Mathematics Social Sciences Other

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Evaluasi Management Requests dan Incidents Mutu Layanan Jaringan Wifi Menggunakan COBIT 2019 Jaganatha, Jaganatha; Ulum, Faruk
Dinamik Vol 31 No 1 (2026)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v31i1.10409

Abstract

This study compares two service management models to evaluate the governance of the Wi-Fi network in Dusun Gita Nagari Baru. The main objective is to measure user satisfaction and service quality following the implementation of the COBIT 2019 framework, particularly the DSS02 domain (Manage Service Requests and Incidents). The research employed a mixed methods approach, using historical-comparative document analysis and Likert scale questionnaires distributed to 21 active users. The data were analysed through gap analysis, capability level mapping, and descriptive statistical analysis to identify performance differences between two periods. The results indicate that most indicators in the COBIT 2019 capability model are at Level 4 (Predictable), one indicator reaches Level 5 (Optimising), and another indicator is at Level 3. Indicators directly related to the DSS02 domain, such as ease of reporting, response speed, schedule accuracy, and repair time, demonstrate the most significant improvements. These findings support the hypothesis that implementing COBIT 2019-based governance for DSS02 can enhance user satisfaction and the quality of Wi-Fi network services in rural areas. This study also provides practical recommendations for the sustainable management of digital infrastructure in areas with limited access.
Modification of Additive Ratio Assessment Method through Distance-Based Weighting Approach for Optimizing Assessment Accuracy Rakhmat Dedi Gunawan; Muhammad Waqas Arshad; Agung Deni Wahyudi; Ryan Randy Suryono; Tri Widodo; Faruk Ulum
Paradigma - Jurnal Komputer dan Informatika Vol. 27 No. 2 (2025): September 2025 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/p.v27i2.8810

Abstract

The Additive Ratio Assessment (ARAS) method is one of the approaches in multi-criteria decision making (MCDM) used to determine the best alternative based on a number of predetermined criteria. The drawback of this method is its heavy reliance on the accuracy of the criterion weighting determination; non-objective weights can lead to biased results. This study aims to improve the accuracy of ranking in multicriteria decision-making through the modification of the ARAS method with a distance-based weighting approach called ARAS-D. The ARAS method, known for its simplicity in calculation, was modified to be more responsive to the distribution of alternative data on each criterion. This distance-based weighting approach objectively determines the weight of the criteria based on variations in data performance, thereby reducing subjectivity in the weighting process. A case study was conducted on the selection of a new store location with six main criteria: rental cost, building area, accessibility, consumer traffic, parking availability, and infrastructure. The results of the evaluation show that the ARAS-D method is able to produce more precise ratings than the standard approach. Store locations with the highest utility value are recommended as the best choice, proving the effectiveness of the method in supporting strategic decisions. The results of the New Store Location 5 alternative rating obtained the highest score with a value of 0.9083, indicating that this location is the most optimal choice overall. This is followed by New Store Location 3 with a value of 0.8617 and New Store Location 1 with a value of 0.8415, which also shows excellent performance against the criteria that have been set. This research contributes to the development of more adaptive and data-based decision-making methods.
Integration of Data Assessment Method Weighting and Proximity Indexed Value for Best Employee Selection in Decision Support Systems Setiawansyah Setiawansyah; Dyah Ayu Megawaty; Faruk Ulum; Agung Deni Wahyudi; Fadila Shely Amalia
CHAIN: Journal of Computer Technology, Computer Engineering, and Informatics Vol. 4 No. 4 (2026): Volume 4 Number 4 October 2026 (Issue in Progress)
Publisher : PT. Tech Cart Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58602/chain.v4i4.378

Abstract

The selection of the best employee is a multi-criteria decision-making problem because employee performance is evaluated using several criteria with different levels of importance. Subjective criterion weighting may not fully represent the characteristics of the assessment data and can influence the resulting decision. This study proposes the integration of Data Assessment Method (DAM) Weighting and Proximity Indexed Value (PIV) within a Decision Support System for best employee selection. DAM Weighting is employed to determine objective criterion weights based on the information contained in the assessment data, while PIV is used to evaluate the relative proximity of each employee alternative to the reference condition. The results show that the criterion weights are relatively balanced, with R1 obtaining the highest weight of 0.1494 and R4 the lowest weight of 0.1381. The PIV calculation produces different proximity values among the nine employee alternatives, with Alt-08 obtaining the lowest value of -2.2864, followed by Alt-09 at -1.8580 and Alt-06 at -1.7148. Based on the resulting ranking, Alt-08 is identified as the best employee. These findings indicate that the integration of DAM Weighting and PIV can provide an objective, quantitative, and data-oriented mechanism for supporting best employee selection in a Decision Support System.
Co-Authors Aditia Yudhistira Ahmad Ichsan Amarudin Amarudin Ari Sulistiyawati Bentar Priyopradono Budi Hijriyanto Dedi Triyanto Dyah Ayu Megawaty Erliyan Redy Susanto Fadila Shely Amalia Feri Fariyanto Gunawan, Rakhmat Dedi Irawan, Made Jaganatha, Jaganatha Junhai Wang Jupriyadi, Jupriyadi Megawaty, Dyah Ayu Muhammad Hari Wibowo Muhammad Jasmin Jasmin Muhammad Najib Muhammad Waqas Arshad Muhtad Fadly Neneng, N Oktavia Rahmawati Parjito Parjito Permata Permata Pratiwi, Tia Nanda Rinaldi Muchtar Riska Aryanti Rohima Julyana Ryan Randy Suryono Setiawansyah Setiawansyah Slamet Riadi suaidah suaidah Sumanto Sumanto Susanto, Erliyan Redy Temi Ardiansah Tri Widodo Wahyudi, Agung Deni Wang, Junhai Yuri Rahmanto Zaenal Abidin Zahara Yunita