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All Journal Jurnal Informasi Sains dan Teknologi (ISAINTEK) Journal of Embedded Systems, Security and Intelligent Systems
Utami Kusuma Dewi
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Computer Science & IT Other

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Desain, Implementasi Dan Evaluasi Sistem Informasi Penggajian Di Universitas Berbasis Web Villy Satria Praditha; Ario Harry Prayogo; Anranur Uwaisy Marchiningrum; Feddy Dea Reskyadita; Nurjayanti Nurjayanti; Utami Kusuma Dewi; Ryan Lingga Wicaksono
Jurnal Informasi, Sains dan Teknologi Vol. 7 No. 1 (2024): Juni: Jurnal Informasi Sains dan Teknologi
Publisher : Politeknik Negeri FakFak

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/isaintek.v7i1.183

Abstract

The university's payroll process includes information about various employees, including lecturers and administrative employees with varying details such as personal data, position and salary information. This research is focused on rebuilding the payroll application due to several shortcomings or challenges associated with the existing application. This research presents a detailed investigation into the design, implementation, and evaluation of a payroll application tailored for the university environment. This research covers main aspects such as use case analysis, relational database schema, application display and testing. Use case analysis begins with identifying and understanding the various scenarios and requirements specific to a university payroll system. Through thorough exploration of user roles, system functionality. Relational database schemas are designed to efficiently store and manage complex payroll data, ensuring accurate and efficient processing. Compatibility testing plays an important role in ensuring the integration of payroll applications with existing systems. This research performs black-box testing to test application functionality and application compatibility testing with various hardware configurations, operating systems, and web browsers to ensure optimal performance and accessibility. The results of this research contribute to the advancement of payroll management and provide guidance for the development of deep payroll applications in universities.
A Comparative Study of Decision Tree and Gradient Boosting Tree Algorithms for Predicting College Enrollment Decisions of High School Students Aras, Rezty Amalia; Utami Kusuma Dewi; Yabes Dwi Nugroho
Journal of Embedded Systems, Security and Intelligent Systems Vol 7 No 1 (2026): March 2026
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jessi.v7i1.2601

Abstract

The declining interest of high school students in pursuing higher education has become a major concern in Indonesia's education sector. This study aims to develop a data-driven predictive model to assist schools in identifying students’ decisions regarding further education. The study compares two popular classification algorithms, Decision Tree and Gradient Boosted Tree, using a dataset of 300 high school students comprising 10 attributes such as school accreditation, parental income, interest level, and residential status. The research method involves data preprocessing, model training, and performance evaluation using a confusion matrix to measure accuracy, precision, and recall. The results show that the Decision Tree algorithm achieved an accuracy of 76.67%, with a precision of 78.57% and a recall of 73.33% for the "college" class. Meanwhile, the Gradient Boosted Tree produced an accuracy of 73.33%, with a strength in recall for the "not attending college" class at 80%, but was less optimal in detecting students who pursued higher education. It can be concluded that the Decision Tree outperforms in terms of accuracy and interpretability, making it more suitable for use in school environments as a decision-support tool for early intervention, scholarship programs, and career counseling.
Co-Authors Anranur Uwaisy Marchiningrum Aras, Rezty Amalia Ario Harry Prayogo Feddy Dea Reskyadita Nurjayanti Nurjayanti Ryan Lingga Wicaksono Villy Satria Praditha Yabes Dwi Nugroho