[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124269-id":3,"doc-seo-124269-113":31,"detail-sidebar-cat-0-id-113":93},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},124269,2336475104042,"Skyler","https://ap-avatar.wpscdn.com/avatar/22000c4c32af1715be0?x-image-process=image/resize,m_fixed,w_180,h_180&k=1786537525561427321",54,"Penelitian & Laporan","Pemanfaatan Algoritma Decision Tree Pada Machine Learning Dalam Penentuan Klasifikasi Kinerja Karyawan Pada CV Duta Media","Penilaian kinerja karyawan berperan penting dalam membantu pencapaian tujuan perusahaan, namun penilaian tradisional sering mengalami kendala berupa rendahnya akurasi dan objektivitas yang dapat memunculkan bias serta ketidakadilan. Penelitian ini mengusulkan sistem klasifikasi berbasis machine learning menggunakan algoritma Decision Tree dengan data kinerja karyawan. Model dibangun dan diuji melalui metode supervised learning untuk mengelompokkan kinerja berdasarkan produktivitas, keterampilan, disiplin, dan prestasi kerja. Hasil menunjukkan akurasi 80% serta mendukung pengambilan keputusan strategis, sekaligus membuka peluang peningkatan pada kasus kompleks.","Pemanfaatan Algoritma Decision Tree Pada Machine Learning Dalam Penentuan Klasifikasi Kinerja Karyawan Pada CV Duta Media  \nIenda Meiriska*1, Ade Sukma Wati2, Lailatur Rahmi3  \n1,2,3Jurusan Manajemen Informatika, Politeknik Negeri Sriwijaya, Palembang e-mail: *[1](1ienda meiriska@polsri.ac.id)[ienda meiriska@polsri.ac.id](1ienda meiriska@polsri.ac.id), [2](2adesukmawati22@gmail.com)[adesukmawati22@gmail.com](2adesukmawati22@gmail.com), [3](3lailatur.rahmi@polsri.ac.id)[lailatur.rahmi@polsri.ac.id](3lailatur.rahmi@polsri.ac.id)  \nAbstrak  \nPenilaian kinerja karyawan merupakan salah satu langkah penting dalam mendukung pencapaian tujuan perusahaan. Namun, penilaian kinerja sering kali menghadapi tantangan, seperti kurangnya akurasi dan objektivitas. Untuk mengatasi permasalahan tersebut, penelitian ini mengusulkan pemanfaatan model klasifikasi berbasis machine learning, dengan menggunakan algoritma Decision Tree. Model ini dirancang untuk mengklasifikasikan kinerjakaryawan berdasarkan empat aspek utama, yaitu produktivitas, keterampilan, disiplin, dan prestasi kerja. Metode yang digunakan dalampenelitian ini adalah supervised learning denganalgoritma Decision Tree, di mana data kinerja karyawan digunakan untuk membangun dan menguji model klasifikasi. Penelitian ini bertujuan untuk menciptakan sistem penilaian yang akurat, objektif, dan dapat diandalkan oleh manajemen perusahaan dalam mengevaluasi dan meningkatkan kinerja sumber daya manusia.Hasil penelitian menunjukkan bahwa model klasifikasi ini mampu mencapai tingkat akurasi sebesar 80%, yang menunjukkan kemampuan model dalam memprediksi kinerja karyawan secara keseluruhan. Meskipun akurasi yang dicapai cukup baik, hasil ini juga mengindikasikan adanya ruang untuk pengembangan lebih lanjut gunameningkatkan akurasi dan konsistensi prediksi, terutama pada kasus-kasus yang kompleks. Implementasi model ini memberikan manfaat signifikan dalam mendukung pengambilan keputusan strategis oleh manajemen perusahaan, sekaligus berkontribusi pada peningkatankualitas sumber daya manusia.  \nKata kunci—Machine Learning, Kinerja Karyawan, Decision Tree  \nAbstract  \nEmployee performance assessment is a critical step in achieving corporate objectives.  \nHowever, this process often faces challenges such as a lack of accuracy and objectivity. To address these issues, this study proposes utilizing a machine learning-based classification model using the Decision Tree algorithm. The model is designed to classify employee performance based on four key aspects: productivity, skills, discipline, and work achievements. The research employs a supervised learning method with the Decision Tree algorithm, using employee performance data to build and evaluate the classification model. The objective of this study is to create an accurate, objective, and reliable assessment system that management can use to evaluate and improve human resource performance. The results indicate that the classification model achievesan accuracy level of 80%, demonstrating the model's capability to predict employee performance comprehensively. While this accuracy is considered satisfactory, the findings also suggest room for further development to enhance prediction accuracy and consistency, particularly in complex cases. The implementation of this model offers significant benefits in supporting strategic decision-making by company management and contributes to improving the quality of human resources.  \nKeywords—Machine Learning, Employee performance,, Decision Tree  \n1. PENDAHULUAN  \nKinerja  \nserta  \npegawai mempunyai dampak besar terhadap produktivitas dan efisiensi operasional, menjadi dasar utama pengambilan keputusan terkait promosi, insentif dan  \npengembangan kompetensi. Namun metode penilaian kinerja tradisional yang umumnya mengandalkan observasi dari atasan atau bentuk standar seringkali menghadapi permasalahandalam hal objektivitas dan konsistensi. Keterbatasan tersebut dapat menimbulkan bias, tidakakuratan, bahkan ket","cbCaihbH8p85ZlFY","https://ap.wps.com/l/cbCaihbH8p85ZlFY","pdf",503170,5,1,10,"Indonesian","id",113,"# Pendahuluan\n## Latar belakang kinerja dan tantangan penilaian tradisional\n## Peran machine learning dan pembelajaran mesin\n## Alasan pemilihan algoritma Decision Tree","[{\"question\":\"Apa masalah utama pada penilaian kinerja karyawan yang dibahas dalam dokumen ini?\",\"answer\":\"Penilaian kinerja tradisional dinilai kurang akurat dan kurang objektif, sehingga berpotensi menimbulkan bias, ketidakakuratan, bahkan ketidakadilan yang memengaruhi motivasi dan kepuasan kerja.\"},{\"question\":\"Bagaimana model Decision Tree digunakan untuk menentukan klasifikasi kinerja karyawan?\",\"answer\":\"Model dibangun dengan supervised learning menggunakan data kinerja karyawan untuk membentuk dan menguji model klasifikasi berdasarkan atribut produktivitas, keterampilan, disiplin, dan prestasi kerja.\"},{\"question\":\"Seberapa baik performa model klasifikasi yang dihasilkan, dan apa implikasinya?\",\"answer\":\"Model mencapai akurasi 80% dalam memprediksi kinerja secara menyeluruh. Hasil ini juga menunjukkan masih ada ruang pengembangan untuk meningkatkan akurasi dan konsistensi pada kasus yang kompleks.\"}]","Pemanfaatan Algoritma Decision Tree Pada Machine Learning Dalam Penentuan Klasifikasi Kinerja Karyawan Pada CV Duta Media | PDF",1785821300,15,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":88,"head_meta":90,"extra_data":92,"updated_unix":29},"utilizing-decision-tree-algorithm-in-machine-learning-for-employee-performance-classification-at-cv-duta-media","",{"@graph":37,"@context":87},[38,55,70],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,49,52],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":48},"https://docshare.wps.com/id/document/","Document",2,{"item":50,"name":12,"@type":44,"position":51},"https://docshare.wps.com/id/document/penelitian-laporan/",3,{"item":53,"name":13,"@type":44,"position":54},"https://docshare.wps.com/id/document/utilizing-decision-tree-algorithm-in-machine-learning-for-employee-performance-classification-at-cv-duta-media/124269/",4,{"url":53,"name":13,"@type":56,"author":57,"headline":13,"publisher":59,"fileFormat":62,"inLanguage":24,"description":14,"dateModified":63,"datePublished":64,"encodingFormat":62,"isAccessibleForFree":65,"interactionStatistic":66},"DigitalDocument",{"name":9,"@type":58},"Person",{"url":42,"name":60,"@type":61},"DocShare","Organization","application/pdf","2026-08-15","2026-08-04",true,{"@type":67,"interactionType":68,"userInteractionCount":20},"InteractionCounter",{"@type":69},"ViewAction",{"@type":71,"mainEntity":72},"FAQPage",[73,79,83],{"name":74,"@type":75,"acceptedAnswer":76},"Apa masalah utama pada penilaian kinerja karyawan yang dibahas dalam dokumen ini?","Question",{"text":77,"@type":78},"Penilaian kinerja tradisional dinilai kurang akurat dan kurang objektif, sehingga berpotensi menimbulkan bias, ketidakakuratan, bahkan ketidakadilan yang memengaruhi motivasi dan kepuasan kerja.","Answer",{"name":80,"@type":75,"acceptedAnswer":81},"Bagaimana model Decision Tree digunakan untuk menentukan klasifikasi kinerja karyawan?",{"text":82,"@type":78},"Model dibangun dengan supervised learning menggunakan data kinerja karyawan untuk membentuk dan menguji model klasifikasi berdasarkan atribut produktivitas, keterampilan, disiplin, dan prestasi kerja.",{"name":84,"@type":75,"acceptedAnswer":85},"Seberapa baik performa model klasifikasi yang dihasilkan, dan apa implikasinya?",{"text":86,"@type":78},"Model mencapai akurasi 80% dalam memprediksi kinerja secara menyeluruh. Hasil ini juga menunjukkan masih ada ruang pengembangan untuk meningkatkan akurasi dan konsistensi pada kasus yang kompleks.","https://schema.org",{"og:url":53,"og:type":89,"og:title":13,"og:site_name":60,"og:description":14},"article",{"robots":91,"canonical":53},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":94},[95,100,104,108,112,116,118,122,126,130,134],{"id":96,"doc_module":4,"doc_module_name":47,"category_name":97,"show_sort_weight":98,"slug":99},55,"Agama & Spiritualitas",60,"religion-spirituality",{"id":101,"doc_module":4,"doc_module_name":47,"category_name":102,"show_sort_weight":98,"slug":103},48,"Cerita & Novel","story-novel",{"id":105,"doc_module":4,"doc_module_name":47,"category_name":106,"show_sort_weight":98,"slug":107},56,"Gaya Hidup","lifestyle",{"id":109,"doc_module":4,"doc_module_name":47,"category_name":110,"show_sort_weight":98,"slug":111},51,"Komik","comic",{"id":113,"doc_module":4,"doc_module_name":47,"category_name":114,"show_sort_weight":98,"slug":115},53,"Layanan Kesehatan","healthcare",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":98,"slug":117},"research-report",{"id":119,"doc_module":4,"doc_module_name":47,"category_name":120,"show_sort_weight":98,"slug":121},49,"Sastra","literature",{"id":123,"doc_module":4,"doc_module_name":47,"category_name":124,"show_sort_weight":98,"slug":125},52,"Teknologi","technology",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":128,"show_sort_weight":98,"slug":129},50,"Ujian","exam",{"id":131,"doc_module":4,"doc_module_name":47,"category_name":132,"show_sort_weight":98,"slug":133},57,"Umum","general",{"id":135,"doc_module":4,"doc_module_name":47,"category_name":136,"show_sort_weight":4,"slug":137},181,"Formulir","formulir"]