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All Journal INOVTEK Polbeng - Seri Informatika Jurnal Informatika Universitas Pamulang Journal of Information Systems and Informatics Joined Journal (Journal of Informatics Education Jurnal Sistem Informasi dan Sistem Komputer LogicLink: Journal of Artificial Intelligence and Multimedia in Informatics Julia Jurnal
Rahmawan Bagus Trianto
Universitas An Nuur
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering Other

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PREDIKSI TINGKAT KELULUSAN MAHASISWA S1 UNIVERSITAS AN NUUR DENGAN METODE  DECISION TREE C4.5 Umar Haji Mussa’id; Agus Susilo Nugroho; Rahmawan Bagus Trianto
Julia: Jurnal Ilmu Komputer An Nuur Vol 4 No 1 (2024): Julia Jurnal
Publisher : LPPM Universitas An Nuur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35720/julia.v4i1.18

Abstract

One of the private universities in Purwodadi is An Nuur Purwodadi University. Many students have graduated from An Nuur Purwodadi University, but there are some students who did not graduate on time. This poses a problem and raises a significant question as to why these students did not graduate on time. A decision tree is a suitable data mining method for this research because it has the advantage of identifying and summarizing patterns in the data. The Decision Tree algorithm has an accuracy of 96.25%. The recall values for each class are 97.37% for the "Late" class and 95.00% for the "On-Time" class. Meanwhile, the precision values for each class are 94.87% for the "Late" class and 97.44% for the "On-Time" class 
ANALYSIS OF SENTIMENT ON TEACHER MARKETPLACE ISSUES USING THE LEXICON AND K-NEAREST NEIGHBOR ALGORITHMS Addien Anaba; Rahmawan Bagus Trianto; Eko Supriyadi
Julia: Jurnal Ilmu Komputer An Nuur Vol 4 No 1 (2024): Julia Jurnal
Publisher : LPPM Universitas An Nuur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35720/julia.v4i1.19

Abstract

The advancement of social media makes it easier for users to express opinions. Twitter has become one of the media that is loved by internet users, users can freely express their thoughts or opinions, apart from that they can also express everything that is being experienced. The busy issue of the Teacher Marketplace initiated by the Minister of Education, Nadiem Makarim, has invited many comments from internet users. Twitter users' tendencies in posting content can be determined by analyzing sentiment. In this research, the Lexicon and K-Nearest Neighbor (KNN) methods are proposed to analyze sentiment towards the education minister's discourse on Twitter social media on the topic of Teacher Marketplace Issue Sentiment by classifying it into positive, neutral and negative. The results of this research show that the accuracy value obtained was 91.70%, precision 90.51%, recall 71.95%. By carrying out this sentiment analysis, it is hoped that the problems contained in the Marketplace Guru topic controversy can be identified, used as input and consideration for further research.
Optimized K-Means Clustering for Web Server Anomaly Detection Using Elbow Method and Security-Rule Enhancements Trianto, Rahmawan Bagus; Muin, Muhammad Abdul; Vikasari, Cahya
Journal of Information System and Informatics Vol 7 No 4 (2025): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v7i4.1391

Abstract

Anomaly detection in web server environments is essential for identifying early indicators of cyberattacks that arise from abnormal request behaviors. Traditional signature-based mechanisms often fail to detect emerging or obfuscated threats, requiring more adaptive analytical approaches. This study proposes an optimized anomaly detection model using K-Means clustering enhanced with engineered security-rule features and the Elbow Method. Two datasets were used: a small dataset of 3,399 log entries from one VPS and a large dataset of 223,554 entries collected from three VPS nodes, all sourced from local production servers of the Department of Computer and Business, Politeknik Negeri Cilacap. The preprocessing pipeline includes timestamp normalization, removal of non-informative static resources, numerical feature scaling, and TF-IDF encoding of URL paths. Domain-driven security features entropy scores, encoded-payload indicators, abnormal status-code ratios, and request-rate deviations were integrated to improve anomaly separability. Experiments across five model configurations show that combining larger datasets with rule-based features significantly enhances clustering performance, achieving a Silhouette Score of 0.9136 and a Davies–Bouldin Index of 0.4712. The results validate the effectiveness of incorporating security-rule engineering with unsupervised learning to support early-warning threat detection in web server environments.
Sistem Informasi Peminjaman Alat Praktikum Laboratorium Multimedia Berbasis Website dengan Framework Laravel Kukuh Muhammad; Rahmawan Bagus Trianto; Dwi Novia Prasetyanti
Joined Journal (Journal of Informatics Education) Vol 7 No 2 (2024): Volume 7 Nomor 2 (2024)
Publisher : Universitas Ivet

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31331/joined.v7i2.3560

Abstract

Sistem Informasi Peminjaman Alat Praktikum merupakan aplikasi berbasis web yang dirancang untuk mengelola proses peminjaman alat praktikum bagi mahasiswa atau pengguna di laboratorium multimedia. Laboratorium Multimedia memiliki tanggung jawab menyediakan fasilitas peminjaman alat praktikum untuk mendukung kegiatan belajar mengajar. Diperlukan sistem untuk mempermudah dan mengefisienkan proses peminjaman alat, dengan memanfaatkan teknologi komputer. Oleh karena itu, penelitian ini bertujuan untuk menerapkan Sistem Informasi Peminjaman Alat Praktikum Berbasis Web dengan bahasa pemrograman web pada Laboratorium Multimedia menggunakan framework Laravel. Dalam pengembangan sistem ini, metode Waterfall digunakan sebagai pendekatan pembangunan. Untuk menguji kelayakan sistem, dilakukan evaluasi menggunakan metode System Usability Scale (SUS). Hasil pengujian dengan menyebarkan 30 kuisioner dengan metode SUS menggunakan skala linkert menunjukkan nilai kelayakan sebesar 85,5%, yang menempatkannya dalam kategori Excellent menurut standar usability, menunjukkan bahwa sistem ini berhasil memenuhi kriteria kemudahan penggunaan dan kepuasan pengguna.
Co-Authors Achmad Rizki Ramadhani Addien Anaba Agus Susilo Nugroho Agus Susilo Nugroho Andri Triyono andri triyono Andri Triyono Arum, Dhika Malita Puspita Cahya Vikasari, Cahya Dhika Malita Dwi Novia Prasetyanti Eko Supriyadi Fida Maisa Hana Imam Prayogo Pujiono Kukuh Muhammad Muhammad Abdul Muin Muhammad Akbar Mustofa Supriyadi, Eko Supriyadi Triyono, Andri Umar Haji Mussa’id