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All Journal JurTI (JURNAL TEKNOLOGI INFORMASI) J-Icon : Jurnal Komputer dan Informatika
Joko Sutrisno
Universitas Budi Luhur
Computer Science & IT

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IMPELEMENTASI ALGORITMA PROFILE MATCHING DALAM PEMBERIAN BONUS AKHIR TAHUN KARYAWAN Fakhrul Arifqi; Joko Sutrisno
(JurTI) Jurnal Teknologi Informasi Vol 4, No 1 (2020): JUNI 2020
Publisher : Universitas Asahan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (605.379 KB) | DOI: 10.36294/jurti.v4i1.1287

Abstract

Abstract - To support the performance and motivate the spirit of employees in the work then it is necessary to reward a certain amount of money as a form of appreciation to the employees of the year-end bonus recipients. As for the problems that occur during this there is a subjective assessment of the next side assessment to a person employee so that the employee whose target scale is achieved does not get the final bonus. In this research using the Profile Matching method in resolving the problem, the Profile Matching method is implemented into a decision support system. So the results of this research is an application that can provide output in the form of each employee's alignment so that decision-makers can consider and make decisions about who the employees are selected to get the year-end bonus.Keywords - Assessment, Profile Matching, Employees, Decisions. Abstract - Untuk menunjang kinerja dan memotivasi semangat karyawan dalam bekerja maka diperlukan sebuah penghargaan berupa nominal uang dengan jumlah tertentu sebagai bentuk apresiasi kepada karyawan penerima bonus akhir tahun. Adapun permasalahan yang terjadi selama ini adanya penilaian yang bersifat subyektif yaitu penilaian berpihak sebelah kepada seseorang karyawan sehingga karyawan yang target penjualanya tercapai tidak mendapatkan bonus akhir. Pada penelitian ini menggunakan metode Profile Matching didalam menyelesaikan permasalahan  tersebut, metode Profile Matching diimplementasikan kedalam sebuah sistem pendukung keputusan. Sehingga hasil penelitian ini adalah sebuah aplikasi yang mampu memberikan keluaran berupa perangkingan masing-masing karyawan sehingga pihak pengambil keputusan dapat mempertimbangkan dan mengambil keputusan mengenai siapa karyawan yang terpilih untuk mendapatkan bonus akhir tahun. Kata kunci - Penilaian, Profile Matching, Karyawan, Keputusan.
KLASTERISASI DATA HASIL STUDI PELACAKAN TENTANG KARIR DAN PEKERJAAN LULUSAN PERGURUAN TINGGI MENGGUNAKAN ALGORITMA K-MEANS Joko Sutrisno; Arief Wibowo; Bayu Satria Pratama
J-Icon : Jurnal Komputer dan Informatika Vol 11 No 2 (2023): Oktober 2023
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v11i2.12031

Abstract

Higher education has a responsibility to produce quality graduates. One indicator of the quality of graduates is the status of getting a job, the condition of the suitability of the field of work with the educational program pursued, and the waiting period to get the job. What is being done to find out these conditions is to conduct a tracer study for graduates. This study analyzes data from a college graduate tracking study about careers and jobs using a data mining clustering algorithm, namely K-Means. The results showed that the analysis of the tracking study data formed several graduate clusters with an evaluation value of the Davies-Bouldin Index (DBI) reaching 0.287 in the first trial and 0.291 in the second trial. The clusters formed consist of groups of graduates with status still needing to be working or currently working. The profile of graduates from each cluster can be identified in the form of a relatively short waiting period of less than six months to get a first job or a relatively slow waiting period of more than one year. Another cluster specification that is formed is about the profile of graduates with the level of compatibility between the education attained and the field of work carried out. The results of this study serve as feedback for study program managers to measure the quality of graduates and the improvements in the educational process that need to be made.
Co-Authors Arief Wibowo Bayu Satria Pratama Fakhrul Arifqi