JIE Scientific Journal on Research and Application of Industrial System

Development of an Artificial Neural Network Model for Predicting Speeding Behaviour: A Case Study from Indonesia

Sekar Sakti — 2026-04-20

Traffic accidents are the third leading cause of death in Indonesia, with speeding behavior being the predominant human factor responsible for most fatal outcomes. Early detection of drivers’ propensity to speed is therefore essential for effective prevention strategies. This study develops an Artificial Neural Network (ANN) model to predict the tendency of drivers to speed on intercity roads using a labeled questionnaire dataset comprising 14 input variables. The dataset was divided into training, validation, and testing subsets, where the validation set was used for hyperparameter tuning, while the testing set was used for final evaluation on unseen data. The model was trained using the Adam optimizer with a binary cross-entropy loss function. The optimal configuration consists of a single hidden layer with 12 neurons using ReLU activation, a Sigmoid output layer, 750 training epochs, and a learning rate of 0.03. The final model achieved an accuracy of 86.67% and a Cohen’s kappa value of 0.7339, which indicates strong predictive reliability. These findings demonstrate the model’s potential as a valuable tool for relevant stakeholders to identify high-risk drivers and design targeted interventions. As a result, the model can be used to proactively reduce speeding-related traffic accidents and improve road safety on intercity routes.

Developing A Web Based OEE Monitoring System for Pharmaceutical Industry

Hery Hamdi Azwir — 2026-04-20

PT. XYZ is a leading biopharmaceutical company in Indonesia that produces and sells health products. A critical aspect of its operations is calculating Overall Equipment Effectiveness (OEE) to ensure optimal production and minimize downtime. Currently, XYZ conducts OEE calculations manually, leading to significant challenges. Manual data collection and processing are time-consuming, taking up to a week to complete. This delay hinders timely decision-making and increases the risk of errors, including miscalculations and inaccuracies in data analysis. Such inefficiencies negatively impact production planning and resource utilization. To address this problem, this research proposes the development of a web-based application to automate the OEE calculation process. Using the Object-Oriented System Design (OOSD) approach and Object-Oriented Programming (OOP) methodology, the application streamlines OEE data input, automates the calculation of Availability, Performance, and Quality components, and presents results through interactive visualizations. By transitioning from a manual to an automated system, the new application significantly reduces the time required for OEE calculations, providing users with fast and accurate results to support better operational decisions.

Analisis Efektivitas Mesin Incinerator Reciprocating CRE-500 dengan Menggunakan Metode OEE dan RCA+

Putri Sulistya Ananda Syahril — 2026-04-20

PT. XYZ merupakan perusahaan yang bergerak di bidang pengelolaan limbah B3 dengan menggunakan mesin Incinerator Reciprocating CRE-500 sebagai fasilitas utamanya. Namun, mesin ini memiliki downtime tertinggi mencapai 9,6 jam, yang berdampak signifikan terhadap penurunan efektivitas operasional. Penelitian ini bertujuan untuk menghitung dan menganalisis nilai Overall Equipment Effectiveness (OEE) beserta komponennya, yaitu Availability, Performance, dan Quality Rate, sebagai tolok ukur produktivitas mesin. Selain itu, dilakukan identifikasi akar penyebab ketidakefektifan mesin melalui pendekatan Root Conflict Analysis (RCA+). Hasil perhitungan menunjukkan nilai OEE mesin Incinerator Reciprocating CRE-500 sebesar 59% pada bulan Desember 2024, angka ini masih berada di bawah standar world class OEE sebesar 85%. Analisis RCA+ berhasil mengidentifikasi enam kontradiksi utama yang menjadi penyebab rendahnya efektivitas mesin, di antaranya adalah ketidaksesuaian prosedur operasi, keterbatasan pada sistem pendinginan, serta frekuensi perawatan yang belum optimal. Temuan ini menjadi dasar penting bagi perusahaan dalam merumuskan strategi peningkatan efektivitas mesin dan efisiensi proses operasional secara menyeluruh.