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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) MATICS : Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Information Systems Engineering and Business Intelligence Format : Jurnal Imiah Teknik Informatika Sistemasi: Jurnal Sistem Informasi JOIV : International Journal on Informatics Visualization Tech-E Abdimas Dewantara JURNAL INSTEK (Informatika Sains dan Teknologi) Jurnal Pemberdayaan: Publikasi Hasil Pengabdian Kepada Masyarakat Jurnal Tekno Kompak Jurnal TIKOMSIN (Teknologi Informasi dan Komunikasi Sinar Nusantara) Jurnal Abdimas Serawai Abdi-Dharma Jurnal Sistem Informasi dan Bisnis Cerdas JSITIK: Jurnal Sistem Informasi dan Teknologi Informasi Komputer Jurnal Sains, Nalar, dan Aplikasi Teknologi Informasi JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Daniawan, Benny
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Religion Agriculture, Biological Sciences & Forestry Arts Humanities 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 Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Nursing Public Health Social Sciences Other

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Enhancing Employee Motivation: A TOPSIS-Based Decision Support System for Incentive Allocation through Performance Evaluation Sutyawati, Yuke Subaikah; Daniawan, Benny
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 16, No 1 (2024): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v16i1.23921

Abstract

Information technology is developing rapidly and has a significant role in various aspects, one of which is making decisions to evaluate employee performance. Employee performance assessment is an important activity and is often carried out by companies to determine employee performance in a certain period. A company's progress is greatly influenced by the good and bad of the system that is running. The decision support system can improve and influence the assessment of existing performance in the company. If the decision support system is inadequate, it can lead to errors in decision-making. This research was conducted at PT. App Inti provides enthusiasm and motivation to employees, and the company performs performance assessments every six months, which will influence the adjustment of employee salary increases. However, the current assessment process still uses simple methods and often experiences difficulties assessing performance, making the assessments less effective. Because errors and inaccuracies often occur during assessments, to make it easier for companies to make decisions and help solve these problems, a decision support system was designed using the TOPSIS method. The TOPSIS is a multi-attribute decision-making method often used to complete practical decisions. Then, the results can be considered and help the company determine a decision based on the alternatives and criteria that the company has decided. Then, the results of this research can help companies determine which employees are more visible during the assessment. Then, the TOPSIS ranking results are used to adjust salary increases that have been selected by the company, thereby helping companies make decisions more quickly.Keywords: Performance Appraisal, Decision Support System, TOPSIS
Talent Development Center Recommendation System Using Content-Based Filtering Putri, Maysha Permata; Daniawan, Benny
MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) Vol 18, No 1 (2026): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v18i1.32816

Abstract

The development of digital technology has led to increased gadget usage among children, often resulting in a decline in interest in productive physical and social activities. The Indonesian Child Protection Commission reported that over 71.3% of school-age children using gadgets daily. This condition highlights the need for efforts to redirect children's attention toward more beneficial activities, one of which is talent development. Early talent development is crucial for supporting personal potential and future career paths. However, limited information often becomes an obstacle in choosing the right place for talent development that suits an individual's needs and interests. This study aims to design a system that can provide talent development center recommendations for seekers. By implementing the Content-Based Filtering (CBF) method, the system matches user preferences—such as interests, skills, and preferred types of activities expressed in keywords—with the descriptions of available talent development center. Weighting is carried out using the Term Frequency–Inverse Document Frequency (TF-IDF) algorithm to enhance the relevance of the recommendations by calculating the similarity level between talent development center descriptions based on keyword weights. This approach allows the system to provide more personalized recommendations without relying on other users' data. The testing conducted in this study, using 7 sample talent development places, resulted in 5 recommendations with the top recommendation being Chic’s Musik, which had the highest TF-IDF value of 1.9029.Index Terms— Content-Based Filtering, Recommendation System, TF-IDF, Talent Development
Co-Authors Aditiya Hermawan Akbar, Junaidi Amin Suyitno Andri Wijaya Arijanto, Rudy Ceng Giap, Yo Culadi, Rafael Daniel Damayanti, Lily Danny Manongga Darmawan, Ivander Dethan, Jacob Febryadi Nithanel Dram Renaldi Dyah Safitri, Ramona edy Edy Edy Fennita, Fennita Fenriana, Indah Hariyanto, Susanto Haryani Haryani Irwan Sembiring Joko Siswanto JUNAEDI Juniar, Diana Krismiyati Kusnadi, Michael Putra Lasut, Desiyanna Lou Wenson, Hebert Lunardi, Lidya Masyshe Miechael, Miechael Nathaniel, Joese Noviany, Caroline Pipit Rusmandani, Pipit Putri, Maysha Permata Ramadika, Irvan Rahul Ramona Safitri, Ramona Riki Rino Rino Rino Sutarto Wijono Sutyawati, Yuke Subaikah Suwitno Suwitno Suwitno, Suwitno Theopillus J. H. Wellem Wijaya, Ardie Willy Wijaya, Willy Wydiastuty Kusuma, Lianny Yakub, Handoyo Yusuf Kurnia, Yusuf