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All Journal Bulletin of Computer Science Research KLIK: Kajian Ilmiah Informatika dan Komputer EXPLORER
Waqas Arshad, Muhammad
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Computer Science & IT

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Combination of CRITIC Weighting Method and Multi-Atributive Ideal-Real Comparative Analysis in Staff Admissions Waqas Arshad, Muhammad; Mesran; Setiawansyah, Setiawansyah; Suryono, Ryan Randy; Rahmanto, Yuri
Explorer Vol 4 No 2 (2024): July 2024
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/explorer.v4i2.1428

Abstract

Staff recruitment is a critical process in human resource management where organizations select and place individuals who fit the needs and goals of the company. This process involves identifying position needs, job postings, screening applicants, interviewing, skills evaluation, and making a final decision to determine the most suitable employee. The integration of CRITIC and MAIRCA allows the staff selection process to be more objective and systematic. CRITIC helps in assessing the importance of each criterion by considering its relevance, thus ensuring that the evaluation is not based on just one dimension. On the other hand, MAIRCA provides a comprehensive framework by comparing each candidate against the desired ideal standards and their actual achievements in relevant attributes. The combination of these two methods not only strengthens accuracy in staff selection, but also ensures that decisions are made in accordance with the organization's strategic goals to achieve optimal performance and effectiveness. The ranking results obtained the results of rank 1 with a value of 0.0824 obtained by Alternative G, rank 2 with a value of 0.0798 obtained by Alternative B, and rank 3 with a value of 0.0778 obtained by Alternative C.
Implementation of Entropy and Additive Ratio Assessment Methods in Determining the Best Warehouse Location Waqas Arshad, Muhammad; Setiawansyah; Mesran
Bulletin of Computer Science Research Vol. 4 No. 4 (2024): June 2024
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v4i4.360

Abstract

The main problems in determining warehouse location include high operational costs, inadequate accessibility and infrastructure, and strict and complex local regulations. In addition, environmental risks and natural disasters, as well as economic fluctuations and market dynamics also add to the challenge of choosing an optimal location. The purpose of this study is to apply the Entropy and ARAS methods in evaluating the potential of optimal warehouse locations, thereby providing clear and structured guidance for decision-makers in choosing the optimal warehouse location to meet the company's operational and strategic needs. The implementation of the entropy and ARAS methods in determining the best warehouse location involves a systematic approach in evaluating several criteria that are important for optimal decision-making. The Entropy method helps in objectively assessing the importance of each criterion by quantifying the uncertainty or variation present in the data. The ARAS method complements this by allowing comparative analysis of alternative warehouse locations based on their performance against ideal criteria, taking into account both quantitative and qualitative aspects. Thus, both methods provide a solid framework for selecting warehouse locations that not only meet logistics requirements efficiently but are also in line with strategic business objectives, ensuring a well-informed decision-making process in supply chain management and logistics. The results of the ranking of the best warehouse location selection using the entropy and ARAS methods show AB Location as the first rank with a value of 0.9781, DD Location as the second place with a value of 0.8362, and IP Location as the third place with a value of 0.8143.
Optimization of Alternative Assessment with Modified MOORA Method: Case Study of Contract Employee Selection Waqas Arshad, Muhammad; Sintaro, Sanriomi; Rahmanto, Yuri; Wantoro, Agus; Setiawansyah
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 4 No. 6 (2024): Juni 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v4i6.1891

Abstract

Multi-Objective Optimization by Ratio Analysis (MOORA) is a multi-criteria decision-making method used to evaluate and select the best alternative based on multiple objectives or criteria. One of the main disadvantages of the MOORA method is subjectivity in the determination of the weight of criteria. In this method, the decision maker must determine the relative weight of each criterion used to evaluate alternatives. Subjectivity in the weighting of criteria can also lead to inconsistencies between different decision makers or experts, resulting decisions can be less transparent and less acceptable to all parties involved, reducing confidence in the validity and accuracy of the results. Optimization of alternative assessment with modified MOORA method is to develop alternative assessment methods that are more accurate and objective by integrating standard deviation into the MOORA method. This study aims to overcome the weaknesses of conventional MOORA methods in dealing with data variation and assessment subjectivity by introducing a more data-driven mechanism of calculating the weight of criteria. Through testing and comparing performance between modified MOORA methods and conventional methods, this study aims to demonstrate improved accuracy, consistency, and reliability in alternative assessment results. In addition, this research is expected to provide practical implementation guidance for the application of the modified MOORA method in the Decision Support System (DSS), so as to improve the efficiency and quality of decision making in various sectors. The ranking results showed that the results of rank 1 were obtained by Employee 6 with a final score of 0.3375, rank 2 was obtained by Employee 3 with a final score of 0.2904, and rank 3 was obtained by Employee 7 with a final score of 0.2756. The results of the comparison test of the original rank with SD-MOORA showed a correlation value of 1, so it can be concluded that there is a very strong and positive relationship between the original rating and the SD-MOORA rating. This shows that the rating produced by SD-MOORA is very consistent with the original ranking, thus giving validity to the effectiveness of SD-MOORA in replicating the original rating results more objectively and efficiently. The results of the SD-MOORA modification showed significant improvements in the accuracy and objectivity of decision making.
Combination of Weighted Product Method and Entropy Weighting in the Best Warehouse Employee Recommendation Waqas Arshad, Muhammad; Darwis, Dedi; Sulistiani, Heni; Suryono, Ryan Randy; Rahmanto, Yuri; Megawaty, Dyah Ayu; Setiawansyah
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 5 No. 1 (2024): Agustus 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v5i1.2095

Abstract

The best warehouse employees are individuals who show exceptional dedication and precision in carrying out their duties. Not only do they ensure that every process, from receipt to delivery, is carried out with high accuracy, but they are also proactive in finding ways to improve operational efficiency. The main problem lies in the proper assessment of employees' technical skills and soft skills, such as rigor, time management ability, and teamwork. Additionally, the selection process can be complicated when it comes to balancing previous work experience and adaptability to new technologies. Without effective assessment methods, the risk of selecting the wrong employee can negatively impact the overall productivity and operational efficiency of the warehouse. The purpose of the study, which combines entropy weighting method with the WP method is an approach that can increase objectivity and accuracy in multi-criteria decision-making. In this combination, the Entropy method is used first to objectively determine the weight of the criteria based on the degree of variation or information contained in the data of each criterion. The weights generated by the Entropy method reflect the importance of criteria based on how much information is provided, assuming that criteria with more variety have more information. Once the weights are determined, the Weighted Product method is used to evaluate and rank alternatives. Based on the results of the recommendation for the selection of the best warehouse employee Hadi occupies the top position in the selection of the best warehouse employee with a score of 0.07194. His position was followed by Putri who got a score of 0.07082, showing a performance that was also very good and only slightly below Hadi. Budi is ranked third with a score of 0.06621, while Deni is ranked fourth and Kiki is fifth with a score of 0.06544 and 0.06524, respectively. The score obtained by each employee shows a relatively small difference, reflecting the fierce competition and high quality of performance among the employees
Co-Authors Agus Wantoro Dedi Darwis Heni Sulistiani Megawaty, Dyah Ayu Mesran, Mesran Ryan Randy Suryono Sanriomi Sintaro Setiawansyah Setiawansyah Yuri Rahmanto