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All Journal JURNAL SISTEM INFORMASI BISNIS Jurnal Informatika Upgris JURNAL MEDIA INFORMATIKA BUDIDARMA ILKOM Jurnal Ilmiah The IJICS (International Journal of Informatics and Computer Science) JSAI (Journal Scientific and Applied Informatics) Jambura Journal of Electrical and Electronics Engineering Jurnal Teknologi Informasi Indonesia
Olha Musa
Universitas Ichsan Gorontalo Utara
Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering

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Sistem Informasi Layanan Pengaduan Perjudian Berbasis Web Musa, Olha; Ali, Satriadi D; Utiarahman, Siti Andini
Jurnal Informatika UPGRIS Vol 8, No 2: Desember 2022
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v8i2.14066

Abstract

Permasalahan yang ada adalah dengan kondisi yang ada di lapangan sulitnya masyarakat dalam melakukan pengaduan ke polres dengan perjalanan jarak jauh dan biaya transportasi. Tujuan dari Penelitian ini Merancang Sistem Informasi Layanan Pengaduan Perjudian Berbasis Web Pada Polres Bone Bolango.Penelitian ini menggunakan metode waterfall sumber data yang digunakan adalah data-data primer dan sekunder dengan metode pengumpulan data melalui observasi dan interview. Pengujian yang digunakan adalah whitebox dan blackbox. Hasil pengujian whitebox pada salah satu proses dalam sistem ini yaitu pada modul pendataan pengaduan dengan perolehan hasil yang seimbang yaitu Cyclomatic Complexity (CC) = 4, maka sistem ini dinyatakan dapat berjalan dengan baik. Sedangkan hasil pengujian blackbox dengan beberapa sampel pengujian menghasilkan sistem dapat berjalan sesuai dengan yang diharapkan dan efisien.Hasil kesimpulan bahwa Sistem Informasi Layanan Pengaduan Perjudian Berbasis Web Pada Polres Bone Bolango dapat memudahkan masyarakat untuk menyampaikan pengaduan perjudian serta memudahkan masyarakat untuk mendapatkan informasi penanganan pengaduan masyarakat.
SMART APPLICATION OF CLASS XI MATHEMATICS FORMULAS BASED ON ANDROID Musa, Olha; Ali, Satriadi D; Badaruddin, Muliati
Jambura Journal of Electrical and Electronics Engineering Vol 7, No 1 (2025): Januari - Juni 2025
Publisher : Electrical Engineering Department Faculty of Engineering State University of Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjeee.v7i1.28480

Abstract

Mastering mathematical formulas is often a challenge for high school students, especially grade XI students who cover complex topics such as algebra, trigonometry, calculus, and matrices. To help students understand and apply these formulas, an Android-based application was designed that provides interactive, easily accessible, and efficient learning facilities. Technological advances allow tasks to be completed more easily and in a shorter time, but increasingly sophisticated AI can still make mistakes in language translation, for example in chatgpt, the author's concern is that if there is an error in making mathematical formulas in completing the grade XI assignment, it will mislead students if they do not pay close attention and lack knowledge in completing the assignment. This study uses a descriptive method, which aims to describe or analyze the results without making broader generalizations. Application development follows the Prototype method, a widely used software development approach that allows for continuous interaction between developers and users, ensuring a clear understanding of system requirements and functionality. The results of the study include software testing using whitebox testing, which focuses on the internal structure and implementation of the application code. At this stage, the tester has complete knowledge of the system architecture and code. In addition, black-box testing is used for functional testing, where the behavior of a system is assessed by analyzing inputs and outputs. In black-box testing, the application is run, and data is entered to verify whether the output matches the expected results. This combination of testing methods ensures the robustness and functionality of the application in supporting 11th grade students with mathematical formulas.
Analysis of a Hybrid DNN–BiLSTM Framework for Longitudinal Prediction of Lung Disease Recurrence Using Clinical Data Olha Musa; Zainudin Sidik; Ifriandi Labolo; Muliati Badaruddin; Abdul Malik I. Buna
ILKOM Jurnal Ilmiah Vol 18, No 2 (2026)
Publisher : Prodi Teknik Informatika FIK Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/ilkom.v18i2.3222.404-419

Abstract

Predicting lung disease recurrence from longitudinal clinical data remains challenging because irregular temporal patterns and heterogeneous patient characteristics reduce the effectiveness of conventional deep learning models. This study analyzes a hybrid Deep Neural Network (DNN)–Bidirectional Long Short-Term Memory (BiLSTM) framework for the longitudinal prediction of lung disease recurrence using clinical data collected between 2021 and 2024 from a referral hospital in Gorontalo. The dataset includes demographic information, laboratory examination results, clinical diagnoses, and longitudinal medical records. Lung disease recurrence is defined as the reappearance or worsening of the disease during longitudinal clinical follow-up after the initial diagnosis or treatment. The proposed framework combines DNN to learn complex nonlinear relationships among multivariate clinical features and BiLSTM to capture temporal dependencies across sequential patient observations. Model performance was evaluated using Accuracy, Precision, Recall, F1-score, and Root Mean Square Error (RMSE), and compared with standalone DNN and BiLSTM models. Experimental results demonstrate that the proposed hybrid framework consistently outperformed the individual models, achieving an improvement of approximately 7–10% across the evaluation metrics while providing more stable longitudinal prediction performance. Furthermore, multivariate analysis identified dominant clinical variables associated with lung disease recurrence, improving the interpretability of prediction results for clinical decision-making. These findings indicate that the proposed framework provides an effective computational approach for longitudinal clinical prediction and supports the development of intelligent clinical decision support systems for recurrence risk assessment
Co-Authors Abdul Malik Buna Abdul Malik I. Buna Adam, Novita Alang Alang Alang, Alang Ali, Satriadi D Badaruddin, Muliati Fitriyanti Suleman Ifriandi Labolo Jorry Karim Linda Rahmawati Dunda Moh Rizal Pakaya Muliati Badaruddin Pusaka, Semerdanta Rahmawati Syahrir Abdussamad Utiarahman, Siti Andini Yulanda Yunus Zainudin Sidik