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All Journal Dinamik Seminar Nasional Aplikasi Teknologi Informasi (SNATI) Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Algoritma Telematika : Jurnal Informatika dan Teknologi Informasi Format : Jurnal Imiah Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JIKO (Jurnal Informatika dan Komputer) Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control CogITo Smart Journal JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jiko (Jurnal Informatika dan komputer) JISKa (Jurnal Informatika Sunan Kalijaga) JAMINFOKOM Decode: Jurnal Pendidikan Teknologi Informasi Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Jurnal Algoritma
Rusydi Umar
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Library & Information Science Public Health Other

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PERANCANGAN KLASIFIKASI PASIEN STROKE DENGAN METODE K-NEAREST NEIGHBOR Rahmat Ardila Dwi Yulianto; Imam Riadi; Rusydi Umar
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 8 No 2 (2023): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v8i2.3454

Abstract

Stroke is a disease characterized by impaired brain function caused by a lack of oxygen supply and blood flow to the brain, affecting several brain functions that make sufferers experience difficulty in carrying out activities. the classification of stroke patients found is still in the form of medical records that have not been integrated so it takes longer time to detect. The K-NN algorithm is part of a machine learning algorithm that can be used to classify one of the cases, namely the classification of stroke patients. K-NN is used as a class determining algorithm to enter new data that is input according to the format. Based on the results obtained, this study leads to system design using the Unified Model Language (UML) and system user interface design.
Security Analysis of Web-based Academic Information System using OWASP Framework Rusydi Umar; Imam Riadi; Elfatiha, Muhammad Ihya Aulia
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 9, No. 4, November 2024
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v9i4.2015

Abstract

The Academic Information System plays a crucial role in efficiently managing student, faculty, and campus administration data. However, system security needs to be a primary concern as it is vulnerable to cyber attacks. This research aims to analyze the security of the Academic Information System at the Muhammadiyah Business Institute Bekasi. The research method used is a comprehensive security analysis based on the OWASP framework. The study includes identifying potential vulnerabilities, penetration testing, and system improvement recommendations. Testing is conducted through simulated attacks based on the OWASP-released security risk list (OWASP Top Ten Most Critical Web Application Security Risks). The analysis results indicate that the system is vulnerable to Broken Authentication due to weak passwords, Sensitive Data Exposure due to URLs pointing to direct directories, and Security Misconfiguration due to open protocols. Furthermore, in CVSS scoring, Broken Authentication scored 4.8 (Medium), Sensitive Data Exposure and Security Misconfiguration scored 5.3 (Medium), Cross-Site Scripting scored 2.0 (Low) and Using Component with Known Vulnerabilities scored 2.0 (Low), while SQL Injection, XXE, Broken Access Control, Insecure Deserialization, and Insufficient Logging and Monitoring scored 0.0 (No Vulnerability). Recommendations for future system improvements include regularly updating the system to prevent new security vulnerabilities, better server configurations, and routine system monitoring to promptly anticipate suspicious activities.
Prediksi Kelulusan Tepat Waktu Berdasarkan Riwayat Akademik Menggunakan Metode Naïve Bayes Imam Riadi; Rusydi Umar; Rio Anggara
Decode: Jurnal Pendidikan Teknologi Informasi Vol. 4 No. 1: MARET 2024
Publisher : Program Studi Pendidikan Teknologi Infromasi UMK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51454/decode.v4i1.308

Abstract

Kelulusan tepat waktu mahasiswa memiliki dampak besar dalam dunia pendidikan. Namun, tidak semua mahasiswa, mampu mencapai prestasi tersebut. Oleh karena itu, diperlukan penelitian yang mendalam dalam menganalisis data kelulusan sebagai upaya mendukung mahasiswa agar berhasil menyelesaikan studi mereka tepat waktu. Penelitian data kelulusan bisa dilakukan menggunakan tehnik klasifikasi data mining. Klasifikasi merupakan salah satu pengolahan dalam data mining dilakukan dengan cara mengelompokkan dengan metode tertentu. Penelitian ini membangun aplikasi dengan implementasi metode naive bayes dengan mempertimbangkan parameter menghasilkan klasifikasi mahasiswa lulus tidak tepat waktu dan lulus tepat waktu. Tahapan pada penelitian seperti load data, cleaning data, selection data, transformation data, data training, data testing, dan hasil prediksi. Tahapan pengujian akurasi penelitian menggunakan metode confusion matrix mendapat akurasi 72% dengan total penerapan data sejumlah 291 dengan detail 273 data training dan 18 data testing. Hasil akurasi menunjukkan bahwa sistem prediksi kelulusan dapat digunakan FTI UAD sebagai salah satu acuan dan pertimbangan fakultas mengambil langkah-langkah kelulusan mahasiswa.
Virtual Reality for Traffic Safety Education in Elementary Schools Vera Yuli Erviana; Wijaya, Oktomi; Dwi Sulisworo; Rusydi Umar
Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Vol. 8 No. 2 (2025): February 2025
Publisher : Fakultas Kesehatan Masyarakat, Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/mppki.v8i2.6598

Abstract

Introduction: Traffic safety education needs to be taught to children at an early age. Traffic safety training for children in a real-world environment has several challenges and difficulties. Letting children practice in the real traffic environment will expose them to potential hazards. The purpose of this study was to develop media promotion for traffic safety education using a virtual reality (VR) for elementary school students. Methods: This research design used the 4-D model (define, design, develop, and disseminate). Data were collected qualitatively by conducting FGDs and interviews, while quantitative data were collected by distributing questionnaires. Results: The traffic safety VR media tested 4 scenarios, namely: driving equipment, traffic lights, how to cross the road, and walking etiquette. The validity test results show that VR traffic safety is feasible to be used as learning media for elementary school students. Students and teachers responded positively to this media. The advantage of this media is that it is fun and interactive for children. Conclusion: Media promotion for traffic safety education using virtual reality can be applied in a wider scope in other elementary schools. Future research can develop more complex scenarios such as cycling, crossing railroad, and many more. The use of virtual reality (VR) in traffic safety training provides an immersive and interactive learning experience, which is more engaging compared to traditional methods.
Analysis of the Saintekmu Website Quality on User Satisfaction Using the Modified System Usability Scale and Webqual 4.0 Method Fitrah, Fitrah Juliansyah; Abdul Fadlil; Rusydi Umar
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 6 (2023): December 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i6.5116

Abstract

Today, websites are a major means of finding or providing information. The Saintekmu website was created to offer top-notch service to students. One way to ensure that the website's services are appropriate and that information technology is being used to its fullest potential is to evaluate the level of service provided and improve its quality. This study aims to compare the results of two methods - the System Usability Scale (SUS) and Webqual - used to determine the quality and expectations of website users. The study distributed questionnaires online using Google Forms and had a sample size of 20 students. The data collected was analyzed using the SPSS program. The results of the SUS method indicated that the website acceptability range was in the marginal category, with a score of 69.9 and a classification rating of OK. The Webqual method yielded an R square of 0.948, indicating that the website's usability, quality, and interaction variables had a significant effect on user satisfaction. All WebQual 4.0 dimensions had a positive and significant effect on user satisfaction, both partially and simultaneously. This study provides Muhammadiyah Saintek University with reference material to evaluate its website in the future.
Anomaly Detection in Cloud Device-Based Information Technology Infrastructure Using Isolation Forest Algorithm ., Andi Zulherry; Imam Riadi; Rusydi Umar
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 9 No. 2 (2026): Issues January 2026
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Cloud device-based information technology infrastructure generates large volumes of operational data that are dynamic and heterogeneous, increasing the complexity of monitoring and anomaly detection processes. Conventional rule-based approaches and supervised learning methods are often less effective due to limited labeled data and their inability to detect newly emerging anomaly patterns. Therefore, this study aims to apply and evaluate the Isolation Forest algorithm as an anomaly detection method for cloud device-based information technology infrastructure. The research data consist of system and network performance metrics, including CPU usage, memory utilization, disk activity, and network traffic collected from a cloud environment. The research stages include data preprocessing, normalization, and feature selection to improve data quality and model performance. The Isolation Forest algorithm is implemented using an unsupervised learning approach, where anomalies are identified based on the algorithm’s ability to isolate data points that exhibit characteristics deviating from the majority of normal data. Model performance is evaluated using a confusion matrix with accuracy, precision, recall, and F1-score metrics, while parameter optimization is conducted using the grid search method to obtain the best configuration. The results indicate that the Isolation Forest algorithm is able to detect anomalies effectively, achieving high accuracy and a good balance between precision and recall. The model with optimal parameters demonstrates improved performance by reducing detection errors compared to the baseline configuration. Thus, the Isolation Forest algorithm can serve as a reliable and scalable solution to support monitoring activities and enhance the reliability of cloud infrastructure.
Co-Authors ., Andi Zulherry Abdul Fadlil Abdullah Hanif Abdullah Hanif Achmad Dito Achmad Noerkhaerin Putra Anthon Yudhana Anton Yudhana Arief Budiman Arief Setyo Nugroho Dewi Astria Faroek Dewi Soyusiawaty Elfatiha, Muhammad Ihya Aulia Erviana, Vera Yuli Fadhilah Dhinur Aini Fadlillah Mukti Ayudewi Fitrah, Fitrah Juliansyah Gema Kharismajati Imam Riadi Kgs Muhammad Rizky Alditra Utama Muhammad Noor Fadillah Mustafa Mustafa Oktomi Wijaya Peryanto, Ari Rahmat Ardila Dwi Yulianto Rauhulloh Ayatulloh Khomeini Noor Bintang Rio Anggara Rochmat Mantofani Sarjimin Sarjimin Sri Rahayu Astari sunardi sunardi Tri Lestari