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All Journal Buletin Poltanesa Bulletin of Computer Science Research Bulletin of Information Technology (BIT) Jurnal Riset Inossa : Media Hasil Riset Pemerintahan, Ekonomi dan Sumber Daya Alam BEduManageRs Journal : Borneo Educational Management and Research Journal
Salmon
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Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Strategi Manajemen Pendidikan Berbasis Machine Learning untuk Prediksi Prestasi Siswa Pratiwi, Heny; Sa'ad, Muhammad Ibnu; Salmon
BEduManagers Journal : Borneo Educational Management and Research Journal Vol. 6 No. 1 (2025): BEduManagers Journal : Borneo Educational Management and Research Journal
Publisher : Manajemen Pendidikan Program Doktor

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/bedu.v6i1.5016

Abstract

Prediksi prestasi akademik siswa berbasis data menjadi keperluan strategis dalam manajemen pendidikan modern. Studi ini mengkaji efektivitas dua model Machine Learning—Support Vector Machine (SVM) dan Random Forest—dalam memprediksi capaian akademik peserta didik SMA Negeri menggunakan data sintetis yang menyerupai data riil sekolah. Dataset dikembangkan dari tiga variabel utama: nilai semester, tingkat kehadiran, dan latar belakang sosial ekonomi. Model diuji menggunakan validasi silang lima lipat dan dievaluasi melalui metrik akurasi, presisi, recall, serta F1-score. Hasil menunjukkan bahwa Random Forest lebih stabil dan unggul secara akurasi dibandingkan SVM dalam konteks data multidimensi non-linier. Studi ini menunjukkan potensi integrasi sistem prediktif ke dalam praktik manajerial sekolah untuk mendukung pengambilan keputusan berbasis data yang lebih akurat dan preventif terhadap kegagalan akademik.
Rancang Bangun Aplikasi Edukasi Interaktif Pengenalan Pahlawan Indonesia Menggunakan Algoritma Fisher-Yates Nadhif Nandana Kartomo; Salmon; Rizky Zakariyya Rasyad
Bulletin of Computer Science Research Vol. 5 No. 4 (2025): June 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bulletincsr.v5i4.672

Abstract

This research was conducted to develop an interactive media application for introducing the names of Indonesian national heroes. If successful, this research is expected to provide users with an easier way to learn and recognize Indonesian national heroes. The study was carried out at SMP 21 Samarinda. The data collection methods used were observation, in which direct observations were conducted at SMP 21 Samarinda, and interviews, involving direct question-and-answer sessions related to the objectives of the research. The system development tools used in this study were Adobe Flash CS6 and Adobe Photoshop CS6. The final result of this research is an interactive media application for introducing the names of Indonesian national heroes, implementing the Fisher-Yates shuffle algorithm to make the learning experience more engaging and easier to understand for users.
Pengembangan Aplikasi Pendataan Keluar-Masuk STNK pada Sistem Kredit PT Indeks Media Finance Arfyanti, Ita; Salmon; Rajiansyah
Poltanesa Vol 23 No 1 (2022): Juni 2022
Publisher : P3KM Politeknik Pertanian Negeri Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51967/tanesa.v23i1.1211

Abstract

Dalam proses pengajuan pembiayaan kredit motor dan mobil bekas, kelengkapan surat-surat dalam hal ini STNK menjadi salah satu syarat yang harus dipenuhi. Jika STNK sudah tidak berlaku maka PT Indeks Media Finance melakukan pengurusan melalui biro jasa. Penelitian ini berfokus pada membangun sebuah aplikasi pendataan keluar masuk STNK. Metode Pengembangan sistem yang digunakan penelitian yaitu metode System Development Life Cycle (SDLC) atau yang lebih dikenal siklus hidup pengembangan sistem mulai dari tahapan analisis, desain sampai implementasi dan pengujian. Harapan sistem yang dibangun tidak hanya dapat mendata keluar-masuk STNK tetapi juga dalam hal pembuatan laporan untuk pimpinan.
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.
Pengembangan Platform LMS Asli Cerdas dalam Upaya Meningkatkan Literasi Digital Anak Usia Sekolah di Kota Samarinda sebagai Mitra Ibu Kota Nusantara (IKN): Innovation of the Asli Cerdas LMS Platform in Enhancing Digital Literacy Among School-Age Children in Samarinda Sa'ad, Muhammad Ibnu; Nursobah; Pajar Pahrudin; Pitrasacha Adytia; Hanifah Ekawati; Salmon
Jurnal Riset Inossa : Media Hasil Riset Pemerintahan, Ekonomi dan Sumber Daya Alam Vol. 7 No. 1 (2025): Juni
Publisher : Badan Perencanaan Pembangunan Daerah, Penelitian dan Pengembangan Kota Samarinda

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54902/jri.v7i1.171

Abstract

Digital literacy is a fundamental competency in preparing the younger generation to face the challenges of the digital transformation era. Samarinda City, as a strategic partner of the National Capital (IKN), plays an important role in preparing adaptive and tech-literate human resources. This study aims to develop a Learning Management System (LMS) platform called Asli Cerdas to enhance digital literacy among elementary and middle school students. The method used is descriptive-exploratory, involving 675 respondents from 10 districts in Samarinda. Instruments such as digital literacy questionnaires and field observations were used to collect both quantitative and qualitative data. The results showed that students had an average digital literacy index of 3.60, with the lowest score in the aspect of digital safety. Teachers showed better scores but still require technical training to maximize technology use. The Asli Cerdas platform was developed with features including local content, self-assessment tools, and offline access. Pilot testing of the platform showed a 24% improvement in students' understanding of digital literacy. This study recommends the adoption of locally based LMS platforms supported by regional policies to strengthen the digital learning ecosystem in areas that serve as partners to IKN
Co-Authors H, Mini Hanifah Ekawati Ita Arfyanti Muhammad Ibnu Saad Saad Nadhif Nandana Kartomo Nursobah Pahrudin, Pajar Pitrasacha Adytia Pratiwi, Heny Rajiansyah Rizky Zakariyya Rasyad SA'AD, MUHAMMAD IBNU Siti Lailiyah, Siti