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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Bulletin of Electrical Engineering and Informatics SMATIKA Jurnal Ilmiah FIFO AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat Rancang Bangun BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Teknoinfo ComTech: Computer, Mathematics and Engineering Applications Building of Informatics, Technology and Science TIN: TERAPAN INFORMATIKA NUSANTARA Abdi Kami : Jurnal Pengabdian Kepada Masyarakat IJPD (International Journal Of Public Devotion) Jurnal Teknologi dan Sistem Informasi Journal Social Science And Technology For Community Service Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) COMMENT: Journal of Community Empowerment Journal of Engineering and Information Technology for Community Service Jurnal Ilmiah Edutic : Pendidikan dan Informatika Journal of Computing and Informatics Research Journal of Informatics, Electrical and Electronics Engineering Bulletin of Informatics and Data Science ABDI KAMI: Jurnal Pengabdian Kepada Masyarakat
Ahmad Ari Aldino
Universitas Teknokrat Indonesia
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Journal : Bulletin of Informatics and Data Science

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Combination of Grey Relational Analysis (GRA) and Simplified Pivot Pairwise Relative Criteria Importance Assessment (PIPRECIA-S) in Determining the Best Staff Setiawansyah, Setiawansyah; Sintaro, Sanriomi; Saputra, Very Hendra; Aldino, Ahmad Ari
Bulletin of Informatics and Data Science Vol 2, No 2 (2023): November 2023
Publisher : PDSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61944/bids.v2i2.67

Abstract

Problems in selecting the best staff often involve complex challenges such as difficulty finding candidates with good performance. The problems faced in the selection of the best are only based on the assessment of discipline and productivity of performance carried out by the staff, so the assessment process does not use aspects of criteria that are considered important in selecting the best staff.  This study aims to determine the best staff based on predetermined criteria and in determining the selection of the best staff using the Gray Relational Analysis (GRA) decision model while in determining the weight of criteria using the Simplified Pivot Pairwise Relative Criteria Importance Assessment (PIPRECIA-S) model so that the weight of the resulting criteria is not based on assumptions from decision makers. The results of the best staff assessment ranking using the Gray Relational Analysis method and the Simplified Pivot Pairwise Relative Criteria Importance Assessment weighting method obtained the results, namely for Rank 1 obtained by Denis Irawan with a final Gray Relational Analysis value of 0.243014. The results of data processing in the TRITAM Model test for the best staff selection application were adjusted to the conclusion of the overall results of the TRITAM Model criteria for technology acceptance, the results were good at 82.56%.
Combination of MEREC and WASPAS Methods for Performance Assessment in the Decision Support System for Member Admission for the Metaverse Team Putra, Ade Dwi; Rahmanto, Yuri; Darwis, Dedi; Aldino, Ahmad Ari; Setiawansyah, Setiawansyah
Bulletin of Informatics and Data Science Vol 3, No 1 (2024): May 2024
Publisher : PDSI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61944/bids.v3i1.100

Abstract

The selection of the right team members is critical to the success of complex and multidisciplinary Metaverse projects, the previous method used in this selection employed criteria weights based on individual evaluator assessments.. This study proposes the application of a combination of MEREC (method based on the removal effects of criteria) and WASPAS (weighted aggregated sum product assessment) methods to build a DSS in the selection of Metaverse team members. The MEREC method is used to determine the weight of relevant criteria, such as technical skills, communication, innovation, problem-solving, team collaboration, and experience. Meanwhile, the WASPAS method is used to rank candidates based on evaluation scores calculated using a combination of the Weighted Sum Model (WSM) and the Weighted Product Model (WPM). The results showed that the candidate with the highest score was Member Candidate 5 with a score of 0.9806, followed by Member Candidate 11 with a score of 0.944 and Member Candidate 9 with a score of 0.9433. This research proves that the combination of MEREC and WASPAS methods can be used effectively to select team members who have the best quality and are in accordance with the needs of Metaverse projects. A major contribution of this research is the development of a more objective and structured method for the selection of team members in technology projects that require multidisciplinary expertise
Co-Authors Abraham Julius Achmad Yudi Wahyudin Aditia Yudhistira Akmal Junaidi Andi Nurkholis Anggarini, Defia Riski Ari Sulistiyawati Arif Munandar Asmiati Asmiati Budiono, Andiswar Muhamad Deby Sintia Amelia Dedi Darwis Dhira Atika Emi Suryati Febryansyah, Rido Fera Lestari Gibtha Fitri Laxmi Heni Sulistiani Ika Septiana Ika Septiana Intan Hamzah Isnain, Auliya Rahman Larasati Ahluwalia Lathifah Lathifah Lestari, Fera Lulud Oktaviani Marchamah Ulfa, Marchamah Megawaty, Dyah Ayu Muhammad Alfathaan Nabila Arra Putri Neneng Neneng ningtyas, Kurnia rimadhanti Olvi Lorensky Yeztiani Palupiningsih, Pritasari Pasaribu, A. Ferico Octaviansyah Putra, Ade Dwi Qadhli Jafar Adrian Rido Febryansyah Riyama Ambarwati Ryan Randy Suryono Sanriomi Sintaro Saputra, Alvin Setiawansyah Setiawansyah Sitna Hajar Hadad Styawati Styawati suaidah suaidah SUAIDAH SUAIDAH, SUAIDAH Surahman, Ade Very Hendra Very Hendra Saputra Very Hendra Saputra yasin, ikbal Yuni Tri Lestari, Yuni Tri Yuri Rahmanto