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All Journal Jurnal Teknologi Terpadu Journal of Artificial Intelligence and Engineering Applications (JAIEA)
John Bush Henrydunan
Universitas Negeri Medan
Automotive Engineering Computer Science & IT Control & Systems Engineering Engineering

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Sistem Informasi Kalkulator Kesehatan dan Kebugaran Tubuh Berbasis Web Rizky Wahyudi; John Bush Henrydunan; Muhammad Alfin; Debi Yandra Niska
Jurnal Teknologi Terpadu Vol 11 No 2 (2025): Desember, 2025
Publisher : LPPM STT Terpadu Nurul Fikri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54914/jtt.v11i2.1678

Abstract

Health and fitness play a crucial role in improving the quality of life. This study aims to develop a web-based health calculator system capable of automatically, in real time, calculating health indicators such as ideal body weight, Body Mass Index (BMI), basic and daily calorie needs, and body fat levels. This system was built using the Waterfall method with HTML, CSS, PHP, and JavaScript technologies. To assess accuracy, testing was conducted on five user datasets by comparing the system's calculations with manual calculations using standard formulas. The difference between the two was calculated as the average relative deviation for each indicator: 0.13% (BMI), 0.84% (ideal body weight), 0.27% (basic calories), 0.27% (daily calories), and 0.73% (body fat levels). Since all deviations were <1%, the system's overall accuracy was estimated to exceed 99%. The test results can be further visualized graphically to clarify the comparison of values. The system also demonstrated ease of use and responsive performance. In conclusion, this system can be used as an accurate and practical educational tool to support self-monitoring of health.
Smart Safety Room: ESP32 Decision Tree-Based Multi-Hazard Detection System Jogi Purba; Dedy Kiswanto; John Bush Henrydunan; Revidamurti Dly
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.1947

Abstract

Physical space security and safety remain fundamental challenges in various sectors, ranging from residential buildings to critical server rooms. Conventional security systems often rely on single sensors or passive alarms that cannot respond comprehensively to multiple simultaneous threats. This research proposes a Smart Safety Room, an ESP32-based integrated multi-sensor security system that combines gas sensors (MQ-2), fire sensors (flame sensors), PIR sensors, and visual-audio output components including OLED displays, RGB LEDs, and buzzers. The system implements a decision tree algorithm with hierarchical priorities to classify room conditions into three categories: SAFE, ALERT, and DANGER based on a combination of sensor data. Testing was conducted through four main scenarios: normal conditions, fire detection, intrusion detection, and dual threat conditions. The results show that the system achieved an overall accuracy of 96.5% with detailed performance of 96% for the fire sensor, 94% for the gas sensor, and 98% for the PIR sensor. The average response time was under 300 milliseconds for all types of detection, meeting the real-time system requirements. The decision tree showed excellent classification performance with an F1-score ranging from 95-97% for all categories. The web-based real-time monitoring dashboard successfully displayed sensor status with auto-refresh every 1 second and a data loss rate of only 0.8% during continuous operation.
Co-Authors Dedy Kiswanto Jogi Purba Muhammad Alfin Niska, Debi Yandra Revidamurti Dly Rizky Wahyudi