Siana Halim
Petra Christian University

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Predicting the Readiness of Indonesia Manufacturing Companies toward Industry 4.0: A Machine Learning Approach Sean Yonathan Tanjung; Kresnayana Yahya; Siana Halim
Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Vol. 23 No. 1 (2021): June 2021
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jti.23.1.1-10

Abstract

This research discusses Indonesia's readiness to implement industry 4.0. We classified the Indonesia manufacturing companies' readiness, which is listed in the Indonesia Stock Exchange, in industry 4.0 based on the 2018 annual reports. We considered 38 variables from those reports and reduced them using principal component analysis into 11 variables. Using clustering analysis on the reduced dataset, we found three clusters representing the readiness level in implementing industry 4.0.  Finally, we used the decision tree for analysing the classification rules. As the finding of this study, Total book value of the machine is the variable that defined the readiness of a company in industry 4.0. The bigger those values are, the more ready a company to compete in industry 4.0. The other measures, i.e., Total cost of revenue by total revenue; Direct labor cost; Total revenue/Total employee and Transportation cost/Total revenue, will define the readiness of a manufacturing company to transform into industry 4.0. or not ready to transform into industry 4.0.
Integrating Real-Time IoT Based Monitoring and Dashboard Design for Closed-House Hen Farming Andreas Handojo; Edyq Setijarso; Siana Halim; Tanti Octavia
Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Vol. 27 No. 2 (2025): December 2025
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jti.27.2.237-248

Abstract

This paper presents a comprehensive solution that integrates IoT-based hardware systems with a real-time dashboard specifically designed for closed-house poultry farming, focusing on laying hens. Since laying hens are homeothermic animals, they are sensitive to temperature and humidity. Therefore, it is essential to monitor and control these environmental factors, along with ventilation, in real time. We describe a smart monitoring system that combines sensors, microcontrollers, and Android-based dashboards to provide actionable insights into poultry health and egg production performance. This system tracks various parameters, including temperature, humidity, equipment status, and key production indicators such as Hen Day Production (HDP), Hen House Production (HHP), and Feed Conversion Ratio (FCR). Evaluations conducted with local poultry farmers have shown improved awareness, usability, and the potential for increased operational efficiency. Despite some limitations, the dashboard provides a clear overview and helps inform decisions aimed at enhancing conditions and boosting egg production. This tool enables breeders to monitor and improve the performance of their laying hens and manage feeding strategies effectively. Additionally, it can assist in controlling and enhancing the closed-house environments and ventilation systems. The system's performance and usability were evaluated through User Acceptance Testing (UAT) and production Key Performance Indicators (KPIs), confirming its potential to enhance operational efficiency.