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All Journal Dinamik Building of Informatics, Technology and Science Jurnal Media Computer Science
Nuari, Reflan
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Computer Science & IT

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Penerapan Sistem Pendukung Keputusan Pemilihan Cleaning Servis Terbaik Menggunakan Kombinasi Metode Pembobotan Entropy dan COPRAS Nuari, Reflan; Setiawansyah, Setiawansyah; Mesran, Mesran
Building of Informatics, Technology and Science (BITS) Vol 6 No 2 (2024): September 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v6i2.5796

Abstract

The main problem in choosing the best cleaning service is often a challenge because it involves a variety of complex and subjective criteria. Cleaning service performance assessments are not only based on factors such as speed and efficiency in work, but also include other aspects such as cleanliness of work results, interpersonal skills, and the ability to comply with safety procedures. The purpose of this research is to implement a system that is able to evaluate and select cleaning service providers objectively and effectively. The Entropy method to measure and assign weights to relevant criteria in the assessment of cleaning service providers, based on the information contribution of each criterion. The COPRAS method to assess and compare various alternative cleaning service providers based on the weight of predetermined criteria, so as to identify the service provider that best meets the desired needs and standards. Based on the results of the ranking that has been carried out by applying the entropy and COPRAS weighting methods, Hadi Santoso occupies the top position with a perfect score of 100, showing that he is the best cleaning service employee among other candidates. Dewi Lestari is ranked second with a score of 96.07, which also shows a very good performance but slightly below Hadi. Meanwhile, Haryani occupies third place with a score of 92.46. Even though it is in last place, this score still reflects a fairly satisfactory performance. This difference in scores indicates a variation in the performance aspects assessed, so that it can be used as a basis for decision-making for awards or service quality improvement.
Perbandingan Metode Maut, Smart dan Waspas dalam Sistem Pendukung Keputusan menentukan Karyawan Terbaik pada Sisilia Boutique Juliansyah, Muh Rifki; Nuari, Reflan
Dinamik Vol 31 No 1 (2026)
Publisher : Universitas Stikubank

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35315/dinamik.v31i1.10339

Abstract

This study compares the effectiveness of MAUT (Multi-Attribute Utility Theory), SMART (Simple Multi-Attribute Rating Technique), and WASPAS (Weighted Aggregated Sum Product Assessment) methods in a decision support system for determining the best employees at Sisilia Boutique. The quality of human resources is crucial in the retail business, but performance evaluation is often influenced by subjectivity. To address this, a multi-criteria-based decision support system is needed. MAUT translates preferences into a numerical scale, SMART calculates the average value of attributes based on weights, while WASPAS combines weighted summation (WSM) and weighted multiplication (WPM) for more balanced results. Employee performance data from Sisilia Boutique in June 2025, including attendance, store layout, customer service, and discipline, were used as the research object. The comparison results show consistency in the highest (K3) and lowest (K7) ratings across the three methods, with differences in the middle ratings. WASPAS offers a more balanced distribution of final scores, making it a comprehensive alternative for performance evaluation.
Decision Support System for Selecting Market-Ready Buffalo Using the SAW Method: A Case Study of Livestock Farms in Tulang Bawang Regency Dermawan, Ryan; Nuari, Reflan
Jurnal Media Computer Science Vol 5 No 2 (2026): April
Publisher : LPPJPHKI Universitas Dehasen Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37676/jmcs.v5i2.11157

Abstract

Tulang Bawang Regency has significant potential for buffalo farming, but the process of determining marketable buffalo is still carried out conventionally based on the farmers' experience. This approach has the potential to lead to less objective decisions because it does not consider all criteria in a structured manner. This study aims to develop a decision support system using the Simple Additive Weighting (SAW) method to assist in the more systematic selection of marketable buffalo. The criteria used include weight, age, health condition, height, and price, weighted based on their level of importance. The research data consisted of ten alternative buffaloes obtained from farms in Tulang Bawang Regency. Process analysis was carried out through decision matrix normalization and preference value calculations to produce a final ranking. The results show that the SAW method is able to provide the best alternative recommendations based on the highest preference values, thus helping farmers make more objective, measurable, and transparent decisions compared to conventional methods
Co-Authors Dermawan, Ryan Juliansyah, Muh Rifki Mesran, Mesran Setiawansyah Setiawansyah