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Journal : JURNAL MEDIA INFORMATIKA BUDIDARMA

Penerapan Data Mining Untuk Pengelompokan Terhadap Kualitas Kinerja Karyawan Dengan Menggunakan Algoritma K-Medoids Clustering Karim, Abdul; Esabella, Shinta; Kusmanto, Kusmanto; Hidayatullah, Muhammad; Suryadi, Sudi
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 8, No 2 (2024): April 2024
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v8i2.7445

Abstract

HR management is recognized as a global issue and an integral part of competitiveness in the arena of globalization. The organizational structure is the placement of tasks from the very top to the placement of very basic tasks. Assessing the quality of employee performance is one of the work evaluation sessions that can provide the best for industry and citizens. In position placement, if someone does not suit the position they have, it will cause problems such as the company's operational processes not running well. Performance appraisal of employees aims to see the performance results that have been carried out or given by employees when occupying a position. Problems related to performance appraisal are important problems that must be resolved immediately. Data mining is a data processing process in the past, where data in data mining is a collection of data that has been collected over a certain period of time. Information data mining is a series of processes for exploring added value in the form of data produced by extracting and identifying patterns in an information base. Clustering is a part of data mining that aims to group based on the formation of new clusters. The K-Medoids algorithm is a partitional clustering procedure that minimizes the distance between labeled points. The K-Medoids algorithm is a classic Clustering partition technique that groups data sets of ni objects into k groups known a priori. From the results of research conducted using the K-Medoids method, 3 clusters were obtained. Where in cluster 1 there are 4 employees, in cluster 2 there are 3 employees and in cluster 3 there are 3 employees.
Co-Authors A. Rahman Abdul Karim Abdul Karim Adlillah, Rihan Adrianus Inu Natalisanto Agus Muljanto, Muhammad Ahmad Ahmad Hasibuan, Thohar Ahmad Jaya Ahmad Zarkasi Aisyah, Della Aldes Lesbani Alhamda Rahman, Ghathfaan Ali Topan, Paris Amirin Kusmiran Ananda, Rizki Qori Andriani, Titi Ansar Suherman, Ansar Anugrah, Rifki Apriana Apriana Ardila, Bella Ariendika, Rama Ariyanto, Nova Aryanto, Nova Aslamiah Aslamiah Astuti, Karunita Ika Aswasulasikin As’ad Najib, Muhammad Aulia, Masyitah Aulia, Nindi B, Ihsan Bobbi Kurniawan Nasution, Muhammad Darmawan , Indra Darmawan, Indra Diani Ayu Pratiwi Diansari, Rani Eka Dimas Utomo Djatnika, Riki Dona Arsinta Etiana, Eka Fahmi Syuhada Falani, Achmad Zakki Fardinah, Fardinah Farhan Fathonah, Sharida Ratri Fauzia Dwi Kayanti Fernando Saputra Filanti, Wa Ode Safnano Giatma Dwijuna Ahadi Gunawan Hananda Putra, Muhammad Fauzan Hayati, Hikmah Hijrah, Muh. Husni Husni Ibrahim, Doni Septu Marsa Iga Mawarni Jaelani, Irsan Jaya Jaya , Ahmad Jaya, Ahmad Juniardi Akhir Putra Kartini Kartini Khairil Khairun Nisa Kholis Nurhanafi Kusmanto Kusmanto Liaten Lukluil, Lukluil Marini, Fika Maulida, Rahmi Maulidyawati , Desi Maulidyawati, Desi Misin, Misin Muhammad Faisal Mahdie Nadila Cantika Ramdani Nathaniela, Amanda Noor Mirad Sari Noviadi, Aditya Nugroho, Setyadi Nuraidha, Amalia C Nuraviat, Sitti Pebrian, Reza Presda, Ignasius Putri Indah Sayakti Rahayu, Putri Indi Rahmi Muthia Raihan, Muhammad Rakhmatullah, Aditya Noviadi Rani, Syahrul Rifandi, Muhammad Rifqi, Raoul Risfidian Mohadi Rukayah Saranty, Saranty Shalsabila Miracle, Annisaa Shinta Esabella Sofya, Nora Dery Suhardin Sultan Wachid , Muhammad Suryadi, Sudi Susi Rose Ardian, Anggeli Susilawati, Tri Syariful Alam Syawaliyah, Syawaliyah Topan, Paris Ali Ulfah, Syarifatul Umar Umar Violet, Violet Wahyudin Wahyudin Wathan, Arizalul* Wibiyan, Sahrul Windiarti Dwi Purnaningrum Yuliadi Yuliadi Zahira, Salsabila Zainudin Hassan