Article Per Year (5 Year)
p-Index From 2021 - 2026
5.955
P-Index
This Author published in this journals
All Journal Kreano, Jurnal Matematika Kreatif-Inovatif Journal The Winners Jurnal Teknologi Informasi dan Ilmu Komputer Journal of Information Systems Engineering and Business Intelligence Jurnal Pembelajaran Matematika Journal of Information Technology and Computer Science Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Sistem Informasi, Teknologi Informasi, dan Edukasi Sistem Informasi (JUST-SI)
Uun Hariyanti, Uun
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Mathematics Social Sciences

Published : 50 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : journal of information technology and computer science

 1 
Naive Bayes with SMOTE for Predicting the Competitiveness of Vocational School Graduates on Imbalanced Data (Case Study: SMK Negeri 3 Malang) Arsy Kurnia Fitri; Wijoyo, Satrio Hadi; Hariyanti, Uun
Journal of Information Technology and Computer Science Vol. 11 No. 1: April 2026
Publisher : Faculty of Computer Science (FILKOM) Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jitecs.111870

Abstract

Vocational high schools (SMK) aim to produce work-ready graduates. However, the open unemployment rate (TPT) for SMK graduates remains high at 9.01%, indicating a significant competency gap. This study designs a model to predict graduates workforce competitiveness using the Naive Bayes algorithm combined with the Synthetic Minority Over-sampling Technique (SMOTE). SMOTE is employed to address the class imbalance between capable and incapable graduates. The study follows the Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology, utilizing academic scores and tracer study datasets. Evaluation results demonstrate that applying SMOTE with a 70:30 train-test split successfully increased model accuracy to 97%. Notably, the model effectively detects the minority class with a Recall of 90%. Furthermore, cross-validation yielded an average accuracy of 97.66%, demonstrating stable performance. Finally, the model was implemented as a web-based dashboard to serve as an early warning system for schools.
Co-Authors Abdilah, Yan Amal Abrar Erlangga, Alif Muhammad Adiastuti, Lintang Eka Aditya Rachmadi, Aditya Admaja Dwi Herlambang, Admaja Dwi Adzkia, Muhammad Hilmi Afranita, Yanuarin Salwa Agung Wicaksono, Satrio Aisyah, Kindi Alghiffari, Farrell Arrazi Andi Reza Perdanakusuma, Andi Reza Arsy Kurnia Fitri Aswin Suharsono, Aswin Attalea Yessa, Achmad Firdaus Baehaqi Choirinnisa, Fadila Dewi, Fikriya Rachma Diyu Nugroho, Gavino Barca Erlangga, Alif Muhammad Abrar Faizatul Amalia, Faizatul Farisi, Hariz Fitri, Arsy Kurnia Fitria, Illa Hibadurrahman, Mohammad Hafidz Husodo, Safira Luthfiana Hutapea, Wilson Hamonangan Ariyanto Hwang, Wu-Yuin Istyadi, Jenita Jayadi, Delisya Junaidi Junaidi Kartika Sari, Adinda Firda Khalid Rahman, Khalid Laksmana, Kumara Sahasika Muslimah Az-Zahra, Hanifah Nabhan, Muhammad Nadhif Nabila, Failashofi Novita, Salma Nugroho, Alief Nurkhamid, Nurkhamid Nurtantyana, Rio Permatasari, Desifa Prastinanda, Fadhilah Alya Pratama, Edwin Samodra Pratama, Yoga Aditya Prima Zulvarina, Prima Purba, Vera Margaretha Purnawirawan, Okta Puspita, Amelia Dhea Retno Indah Rokhmawati, Retno Indah Riswan Septriayadi Sianturi Safie, Laquisha Dinara Sakilah, Irba Satrio Hadi Wijoyo Simanjuntak, Theresia Surya Sabatini siwabessy, Christian Adrianus Taufani, Qhonitha Adilla Tri Afirianto, Tri Triutami, Tabita Wahyu Wahyudi, Valentina Priesty Wibisono Sukmo Wardhono, Wibisono Sukmo Wicaksono, Tegar Setyo Wijayanto, Dimas Reza Winarno, Adimasta Raffindani Yanuar, Athallarifky Yulis Tyaningsih, Ratna Yusi Tyroni Mursityo Zanah, Yulia Husnathul Zega, Luther Risman Luosaro