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All Journal Building of Informatics, Technology and Science Jurnal ABDINUS : Jurnal Pengabdian Nusantara Jurnal Teknik Informatika (JUTIF) Journal Social Science And Technology For Community Service Jurnal Pendidikan dan Teknologi Indonesia Bulletin of Computer Science Research JUSTIN (Jurnal Sistem dan Teknologi Informasi) Jurnal Telematics and Information Technology (TELEFORTECH) Paradigma Jurnal Ilmiah Computer Science CHAIN: Journal of Computer Technology, Computer Engineering and Informatics
Priandika, Adhie Thyo
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Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media

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Journal : Paradigma

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Implementation of the Standard Deviation Multi-Objective Optimization by Ratio Analysis Method in Warehouse Staff Recruitment Selection Putra, Farhan Nopransyah; Priandika, Adhie Thyo
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.v27i2.8373

Abstract

The warehouse staff selection process has a crucial role in ensuring optimal operational efficiency and logistics management. A selection approach that considers aspects of technical skills, work experience, and compatibility with the organization's culture is essential in ensuring the efficiency and effectiveness of logistics management. The labor selection process, including in the context of warehouse staff recruitment, often faces challenges due to subjectivity in decision-making. The implementation of the SD-MOORA method is the main goal in this study in the process of accepting warehouse staff to improve the objectivity and accuracy of candidate selection, the results of this study are expected to contribute to improving the efficiency of the labor selection process and support data-based decision-making in human resource management. The data used in this study consists of 8 candidates and 6 criteria in the selection of warehouse staff admission. The final outcome of optimizing the SD-MOORA method for ranking warehouse staff admissions shows that GT secured the top rank with a value of 0.3827, indicating it is the most suitable candidate according to the selection criteria. AN followed in second place with a score of 0.3752, and BD placed third with a score of 0.3579. This study significantly contributes to advancing the development of decision support systems for warehouse staff selection by applying the SD-MOORA method. By objectively considering the weighting of criteria using standard deviations, this approach enhances both the accuracy and transparency of candidate rankings.
Combination of Logarithmic Least Square Weighting and MAUT Method for Best Employee Selection in Retail Companies Saputra, Aditya; Priandika, Adhie Thyo
Paradigma - Jurnal Komputer dan Informatika Vol. 27 No. 1 (2025): March 2025 Period
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/mf9wad40

Abstract

Selecting the best employees plays a crucial role in enhancing the performance of retail companies. Given that each employee has unique roles, responsibilities, and working conditions, creating a truly fair and consistent assessment standard can be challenging. Additionally, subjective factors such as personal bias or preferences of the assessor can influence the evaluation outcome. The integration of LLSW and the MAUT method in employee selection offers a systematic approach that combines precise weighting with multi-criteria utility analysis. This combination aims to improve the accuracy, objectivity, and transparency of the decision-making process. By utilizing both methods, retail companies can establish a more effective, transparent, and data-driven selection system, ensuring that the best employees are chosen based on rational and fair evaluations. The results of the employee selection process using LLSW and MAUT showed that Employee RS ranked first with the highest score of 0.7485, indicating the strongest qualifications compared to the other candidates. Employee LK and Employee ML ranked second and third with scores of 0.6035 and 0.572, respectively, demonstrating solid performance. These selection outcomes can assist companies in recruiting the most suitable workforce for their operational needs and vision, ultimately leading to improved productivity and service quality in the long run. The main contribution of this research is capable of improving accuracy and fairness in employee performance evaluation. This approach reduces the subjectivity that often occurs in conventional assessment processes in the retail sector, as well as providing a basis for transparent and measurable decision-making.
Co-Authors Adi Sucipto, Adi Aditya Saputra Agus Wantoro Ahdan, Syaiful An’ars, M. Ghufroni Ari Sulistiyawati Aryani, Venty A’yun, M Qurrota Dedi Darwis Edison, Arif Rahman Fitratullah, M. Gunawan, Rakhmat Dedi Hayatunnisa, Destaria Koeswara, Wawan Lutfy, Azza’zunda Choibar Ningsih, Ristia Octaviansyah, A. Ferico Permata, Permata Prabowo, Fransiskus Wahyu Sandy Putra, Farhan Nopransyah Putri, Jeni Sagita Rifaldo, Setiawan Rohmat Indra Borman Rosella, Rosella Safira, Wilga Salsabila Indriyani Sari, Kevinda Setyani, Tria Simamora, Parningotan Tien Yulianti Very Hendra Saputra Wahyuni, Dita Septia Yuri Rahmanto Yusran, Muhamad