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All Journal Pythagoras: Jurnal Matematika dan Pendidikan Matematika Jurnal Pendidikan Matematika dan IPA Journal of Education and Learning (EduLearn) Auladuna AKSIOMA: Jurnal Program Studi Pendidikan Matematika SIGMA: Jurnal Pendidikan Matematika Math Didactic: Jurnal Pendidikan Matematika MaPan : Jurnal Matematika dan Pembelajaran JRPM (Jurnal Review Pembelajaran Matematika) Pi: Mathematics Education Journal Numeracy : Jurnal Ilmiah Pendidikan Matematika Beta: Jurnal Tadris Matematika Teorema: Teori dan Riset Matematika Jurnal Basicedu Al-Khwarizmi: Jurnal Pendidikan Matematika dan Ilmu Pengetahuan Alam Building of Informatics, Technology and Science J-PiMat : Jurnal Pendidikan Matematika PHI: Jurnal Pendidikan Matematika Proximal: Jurnal Penelitian Matematika dan Pendidikan Matematika Jurnal PEKA (Pendidikan Matematika) Rainstek : Jurnal Terapan Sains dan Teknologi Kognitif: Jurnal Riset HOTS Pendidikan Matematika Bulletin of Information Technology (BIT) Pedagogy : Jurnal Pendidikan Matematika Jurnal Basicedu Pi: Mathematics Education Journal Indonesian Journal of Multidisciplinary and Educational Researcher JRAMathEdu (Journal of Research and Advances in Mathematics Education) Profesi Pendidikan Dasar Madrasah Ibtidaiyah Education Journal Jurnal Pendidikan Progresif
Siti Lailiyah, Siti
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Agriculture, Biological Sciences & Forestry Humanities Chemistry Computer Science & IT Education Languange, Linguistic, Communication & Media Library & Information Science Mathematics Physics Social Sciences Other

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Journal : Bulletin of Information Technology (BIT)

 1 
Clustering Academic Data of Junior High School Students to Identify Learning Groups Using The DBSCAN Algorithm at SMP Muhammadiyah 5 Samarinda H, Mini; Lailiyah, Siti; Salmon
Bulletin of Information Technology (BIT) Vol 6 No 4 (2025): Desember 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v7i1.2293

Abstract

The formation of study groups at the junior high school level plays an important role in improving the quality of learning and promoting equality in student learning outcomes. However, the process of grouping students is still largely carried out manually based on teachers’ intuition, subjective observations, or attendance data, which may lead to mismatches in students’ abilities and hinder the optimal achievement of learning objectives within the school environment. This study aims to identify study groups based on students’ academic data at SMP Muhammadiyah 5 Samarinda. The data used include scores in science (exact) and non-science (non-exact) subjects, exam results, assignment scores, attendance records, and parents’ educational backgrounds. The research stages consist of data cleaning, feature engineering, standardization, the application of the DBSCAN algorithm, and evaluation using the Silhouette Score. The analysis results reveal three main clusters: cluster 0 with 89 students (medium achievement), cluster 1 with 50 students (high achievement), and cluster 2 with 5 students (low achievement). In addition, 14 students (8.9%) were identified as noise. The Silhouette Score value of 0.217 indicates that the cluster separation quality is relatively weak; however, DBSCAN successfully detected outliers that may not be identified by other algorithms. These findings suggest that, although the cluster quality is not yet optimal, the applied algorithm remains useful for exploring students’ learning patterns and can serve as a basis for more targeted learning interventions.
Application of The Naïve Bayes Algorithm for Employee Performance Prediction Based on SIMPEG at TVRI East Kalimantan Station Hanani, Ishmah; Lailiyah, Siti; Yulindawati
Bulletin of Information Technology (BIT) Vol 6 No 4 (2025): Desember 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bit.v7i1.2294

Abstract

Employee performance evaluation is a crucial aspect of public organizational management, including at the public broadcasting institution TVRI East Kalimantan Station. To date, attendance indicators obtained from the Employee Management Information System (SIMPEG) have often been used as the primary benchmark, as the data are objectively and structurally available. However, a single attendance-based approach risks overlooking more substantive aspects of work achievement. Therefore, this study integrates attendance data with the Employee Performance Targets (SKP) to construct a more representative performance label. The method employed is a classification approach using the Naïve Bayes (GaussianNB) algorithm. The research dataset consists of attendance records (normal attendance, leave, official duty, study assignment, early departure, absence, and total working days) and quantized SKP scores. Performance labels were generated using a composite score (0.30 × attendance percentage + 0.70 × normalized SKP), which was then categorized into three classes: Excellent, Good, and Needs Improvement. The model was trained using SIMPEG and SKP data that had undergone preprocessing, data partitioning, and class balancing. Experimental results show that the model achieved an accuracy of 0.83, with a precision of 0.86, recall of 0.84, and F1-score of 0.83 on the test data. These results indicate that the model can consistently recognize employee performance patterns across all categories. Practically, this study offers a simple, efficient, and easily implementable predictive framework to support more objective processes of coaching, monitoring, and reward allocation within TVRI East Kalimantan Station.
Co-Authors A Saepul Hamdani, A Saepul Abidah, Mafruhatul Adjeng Alifiahaqsya, Retno Afianah, Vina Nur Afifah, Eka Nur Afifah, Kiki Rizkiatul Ahmad Lubab, Ahmad Amanda Sita Aning Wida Yanti Asmiyah, Siti Auliyah, Arifah Himmatul Azizah, Syafrinnissa Bahasa Indonesia, Bahasa Indonesia Dina, Anni Mujahidad Ekawati, Hanifah Endah Retnowati ERMAN ERMAN Faridah, Nadia Risya Fatah, Muhammad Firman Fitria Anis Kurlillah H, Mini Hanani, Ishmah Heri Kiswanto Hidayah, Nadiyah Lailatul Indayati, Tatik Irmanila, Elmita Ismawa, Yayuk Kharisma, Nur Izzatul Kusaeri Kusaeri Kusaeri Lestari, Nurul Dwi Lisanul Uswah Sadieda Marhumah Marhumah Mariani, Dewi Nabilah, Nafisyah Alfiyanti Naryaningsih, Putri Dwi Nuryaningsih, Putri Dwi Oktiana, Puja Erwinda Rahmayanti, Jesica Dwi Ramadani, Titania Galuh Rey S, Shizukana Desurya Reza Andrea Rosidatul Ilma, Rosidatul Salim, M Salmon Salsabila Sari, Dewi Asri Fatma Sari, Firda Mareta Sa’adah, Aliyatus Setiaputri, Alvina Nanda Setyawati, Maunah Sulthoniyah, Imroatus Sutini Sutini, Sutini Syamsuddin Mallala Taufik Taufik Untsa, Ashfiyatul Wadud, Ahmad Jauharul Yulaikha, Siti Yulidar, Riska Yulindawati Yuni Arrifadah, Yuni Yunita Yunita Zahroh, Alfiatuz