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All Journal JUSIFO : Jurnal Sistem Informasi Jurnal Pendidikan Informatika dan Sains Indonesian Journal of Data and Science Jurnal Riset Sistem Informasi dan Teknologi Informasi (JURSISTEKNI) Jurnal Teknik Informatika (JUTIF) Jurnal Pengabdian Kepada Masyarakat Abdi Nusa Jurnal Pengabdian Kepada Masyarakat Abdi Putra Jurnal Algoritma The Indonesian Journal of Computer Science
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Universitas Nusa Putra
Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Mathematics Physics Public Health Other

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Journal : Indonesian Journal of Data and Science

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Classification of Employee Attendance Categories Using the Gradient Boosted Trees Algorithm Safitri, Mutia; Saepudin, Sudin; Irawan, Carti; Mupaat
Indonesian Journal of Data and Science Vol. 6 No. 3 (2025): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v6i3.301

Abstract

Employee attendance is a crucial factor in human resource management as it affects productivity and operational efficiency. However, the recording and analysis of employee attendance often encounter challenges, particularly in terms of the accuracy and effectiveness of the systems used. This study aims to develop an employee attendance classification model using the Gradient Boosted Trees algorithm to improve the accuracy of grouping attendance categories such as Present, Permission, Sick, Leave, and Absent into attendance level categories: High, Medium, and Low. The research method includes collecting employee attendance data throughout the year 2024. The model evaluation is carried out using metrics such as accuracy, precision, recall, and the confusion matrix. The results indicate that the developed model achieves an accuracy of 100.00%, with a mean precision of 100.00% and a mean recall of 100.00%.
Application Of K-Means Clustering Algorithm to Identify the Best-Selling Digital Printing Services Fatahali Ramadhan, Ana; Saepudin, Sudin; Irawan, Carti; Mupaat
Indonesian Journal of Data and Science Vol. 6 No. 3 (2025): Indonesian Journal of Data and Science
Publisher : yocto brain

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56705/ijodas.v6i3.316

Abstract

The digital printing industry in Indonesia is experiencing rapid growth thanks to the increasing demand from companies for printing services such as banners, stickers, brochures, and business cards. CV. Copy Paste is one of the companies operating in the digital printing industry that fulfills various printing orders every month. However, the company has difficulty identifying the most popular printing services, which makes it difficult to develop a targeted promotional strategy. In view of this problem, the aim of this study is to group digital printing services according to their popularity using the K-Means Clustering method. This study uses a quantitative approach, collecting sales data from the last 12 months, covering 160 types of services. The steps taken include preliminary data processing, namely attribute selection, data cleaning, and data transformation so that it can be effectively processed using the K-Means algorithm, implemented in the Python programming language. The test results show that digital printing services can be divided into three clusters: 115 less popular services (C1), 31 fairly popular services (C2), and 14 very popular services (C3). The results of this study provide information that can be used as a basis for strategic decisions regarding promotion and service management. In this way, the K-Means Clustering algorithm has proven effective in helping companies group products in a more objective and measurable way based on historical data.  
Co-Authors Aan Setiawati adang badru jaman,anggun fergina, adang badru jaman,anggun fergina Adhitia Erfina Alex Andini Wangsa Putri Andrean, Okta Teza Anita Rahayu Arif Rakhman Suharso Arny Lattu Carti Irawan Deudeu Sri Rahayu Dinata, Fajar Sukarsa Edwinanto Fahmi Fauzi Fatahali Ramadhan, Ana Feri Fahmi Al Gadri Gina Syabani Yuda Indri Febriani Irawan, Carti Jelita Asian Marina Artiyasa Mega Putri Utami Muchlis Ali Muhamad Natsir Muhammad Ikrar Dharda Muharrik Muslih, Muhamad Neng Sri Intan Septiani Nunik Destria Arianti Rohmat Rohmat Saepudin, Sudin Safitri, Mutia Sagita Widya Sri Lestari Taufik Rido Tegar Alif Putra Tubagus Dzikril