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All Journal Voteteknika (Vocational Teknik Elektronika dan Informatika) Elkom: Jurnal Elektronika dan Komputer INTECOMS: Journal of Information Technology and Computer Science Petir Energi & Kelistrikan Budimas : Jurnal Pengabdian Masyarakat Journal Zetroem Jurnal Difusi Applied Information Technology and Computer Science (AICOMS)
Wahyudi, Eka
Jurusan Teknik Informatika Politeknik Negeri Ketapang
Religion Humanities Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Social Sciences Other

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IoT and Machine Learning-Based Smart Watering Model for Water Optimization in Vegetable Gardens Novi Indah Pradasari; Eka Wahyudi; Darmanto; Ar-Razy Muhammad; Rizqia Lestika Atimi; Indra Pratiwi
ZETROEM Vol 8 No 2 (2026): ZETROEM
Publisher : Prodi Teknik Elektro Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/ztr.v8i2.7532

Abstract

Efficient water management has become increasingly important in modern agriculture due to growing increasing demand for finite water supplies and the necessity of promoting sustainable farming practices. Traditional time-based irrigation approaches often result in inefficient water use and limited adaptability to dynamic environmental conditions. This study presents the design and preliminary validation of an Internet of Things (IoT)- and Machine Learning (ML)-based smart irrigation framework at Technology Readiness Level (TRL) 3. The proposed framework integrates real-time sensor measurements, external weather information, and a Random Forest–based forecasting algorithm to determine crop water demand support adaptive irrigation scheduling. Experimental and simulation-based evaluations demonstrated that the Random Forest model achieved satisfactory predictive performance, with an RMSE of 0.19 L/m² and an MAE of 0.16 L/m². Furthermore, the proposed framework showed the potential to reduce irrigation water consumption by approximately 30% compared with conventional fixed-schedule irrigation while maintaining adequate water availability for crop growth. The integration of multi-source environmental data and predictive analytics enabled more accurate irrigation decisions, contributing to improved water-use efficiency and reduced irrigation-related operational costs. These findings highlight integrating connected sensing systems with machine learning techniques can facilitate evidence-based irrigation management while promoting long-term agricultural sustainability.
Prototyping IoT-Based Safety Telemetry System for Forest Firefighters Eka Wahyudi; Novi Indah Pradasari; Ar-Razy Muhammad; Darmanto; Dedy Hidayat Kusuma; Indra Pratiwi; Herman
ZETROEM Vol 8 No 2 (2026): ZETROEM
Publisher : Prodi Teknik Elektro Universitas PGRI Banyuwangi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36526/ztr.v8i2.7533

Abstract

Forest fires significantly impact the environment, carbon emissions, and public health. Ensuring the safety of forest firefighters remains a critical challenge, as they operate in high-risk environments with limited communication infrastructure. This study develops an Internet of Things (IoT)-based safety telemetry system utilizing LoRa communication to monitor firefighters’ physiological and environmental conditions in real time. The system is built on an ESP32 microcontroller integrated with sensors for body temperature, heart rate, ambient temperature and humidity, CO and CO₂ concentrations, as well as a GPS module for location tracking. Sensor data are transmitted via a LoRa SX1278 module to a Raspberry Pi–based gateway and subsequently forwarded to a cloud server for visualization and monitoring. System performance was evaluated in forested and residential environments over distances of up to 1 km. The results demonstrated an average data transmission success rate of 97% with a latency of 1.47 seconds, indicating reliable LoRa communication in areas with limited cellular network coverage. Furthermore, the sensors achieved measurement errors below 3%, while the system operated continuously for 12.5 hours with a power consumption of only 0.68 W, demonstrating high accuracy, reliability, and energy efficiency. The system also provides an early warning mechanism for hazardous conditions encountered by firefighters. User evaluations revealed an 89% satisfaction rate, particularly regarding the effectiveness of the early warning feature and overall system usability. These findings demonstrate that the proposed LoRa-based IoT telemetry system can effectively enhance firefighter safety through accurate, reliable, and energy-efficient real-time monitoring.
Pengembangan Sistem Monitoring Energi Solar Cell Berbasis IoT pada Perangkat Smart Farming Eka Wahyudi; Novi Indah Pradasari
Applied Information Technology and Computer Science (AICOMS) Vol 5 No 1 (2026): AICOMS
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/55tc1469

Abstract

This study develops and tests an Internet of Things (IoT)-based solar energy monitoring system for smart farming equipment, including automated irrigation systems, lighting, and CCTV. The system is implemented using voltage and current sensors, an ESP32 microcontroller, Wi-Fi connectivity, cloud storage, and a monitoring dashboard. A research and development approach utilizing a prototyping model was employed. System evaluation covered energy performance, sensor reading accuracy, and communication quality. Actual measurements over a 30-day period showed an average photovoltaic energy yield of 1,312.34 Wh/day and a load consumption of 686 Wh/day, with a minimum State of Charge (SOC) of 22.64%. Sensor accuracy testing yielded a power Mean Absolute Percentage Error (MAPE) of 0.86%, while IoT communication testing achieved a transmission success rate of 99.67% with an average latency of 1.00 second. The test results demonstrate that the system is capable of integrated energy monitoring and data communication for smart farming equipment.
Perancangan Sistem Panic Button Terintegrasi dengan Call Center 112 Kabupaten Ketapang Eka Wahyudi; Novi Indah Pradasari; Darmanto
Applied Information Technology and Computer Science (AICOMS) Vol 4 No 2 (2025)
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/zdh60p27

Abstract

Ensuring security and safety in residential areas requires an emergency reporting mechanism that is both rapid and user-friendly. This study designed and implemented a "Panic Button" system integrated with the Ketapang Regency 112 Call Center, utilizing ESP-NOW wireless communication and ESP8266-based devices. System development followed the Waterfall model, encompassing requirements analysis, design, implementation, testing, deployment, and maintenance. The system comprises a Panic Button device featuring three incident categories, a mobile application, a web-based monitoring dashboard, a database, and an API for reporting integration. Testing involved black-box testing across 81 test variables and User Acceptance Testing (UAT) using a dichotomous scale, involving one 112 Call Center operator and ten application users. The results demonstrated a 100% success rate for all 81 test variables, while the UAT yielded "Yes" responses for all 58 items (100%). These findings indicate that the system fulfills its intended functions and was highly well-received within the tested scenarios and among the participants.
Smart Medicine Box Berbasis IoT dengan Integrasi Firebase untuk Pengelolaan Jadwal Minum Obat Novi Indah Pradasari; Eka Wahyudi
Applied Information Technology and Computer Science (AICOMS) Vol 4 No 2 (2025)
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/b74d2769

Abstract

This study developed an Internet of Things (IoT)-based smart medicine box to assist in managing medication schedules through automated reminders and web-based schedule monitoring. The system was developed using the Waterfall model and integrates the NodeMCU ESP8266, RTC DS3231, TCRT5000 infrared sensor, buzzer, LED, Firebase Realtime Database, and a web interface. Testing was conducted using Black Box Testing on functions such as registration, login, schedule management, alarms, sensors, and long-term scheduling, alongside User Acceptance Testing (UAT). All scenarios—including registration, login, adding/deleting schedules, alarm activation, and long-term scheduling—performed as expected. The open/close detection test using the TCRT5000 sensor succeeded in 4 out of 5 trials (80%). UAT conducted by two testers yielded a score of 48 out of 50 (96%), indicating excellent acceptance of the system's functionality. These results demonstrate that the prototype successfully integrates cloud-based scheduling with physical reminders, although sensor detection reliability requires further improvement.
Rancang Bangun dan Uji Kinerja Smart Fertigation Berbasis IoT dengan Monitoring Kelembapan Tanah dan EC pada Budidaya Hortikultura Novi Indah Pradasari; Eka Wahyudi; Darmanto
Applied Information Technology and Computer Science (AICOMS) Vol 5 No 1 (2026): AICOMS
Publisher : Pengelola Jurnal Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58466/r4gran03

Abstract

This study aimed to design and evaluate the performance of an Internet of Things (IoT)-based smart fertigation system that utilizes soil moisture and electrical conductivity (EC) parameters to monitor and control water and nutrient delivery. The system was developed using an ESP32 microcontroller, soil moisture and EC sensors, pump/valve actuators, and an IoT dashboard for real-time monitoring of cultivation conditions. Testing involved system design, sensor calibration, IoT communication testing, control logic verification, and a 30-day *pakcoy* (bok choy) cultivation trial. Test results indicated that the soil moisture sensor achieved an RMSE of 1.21 percentage points, while the EC sensor recorded an RMSE of 0.042 mS/cm. IoT communication performance demonstrated a data transmission success rate of 99.17% with an average latency of 1.64 seconds. The implementation of smart fertigation reduced water consumption by 22.34% and nutrient usage by 24.10% compared to scheduled delivery methods. Additionally, water productivity increased by 44.02%. These results demonstrate that the IoT-based smart fertigation system effectively monitors and controls water and nutrient delivery, offering the potential to enhance resource use efficiency in horticultural cultivation.
Co-Authors Ar-Razy Muhammad Darmanto, Darmanto Herman Indra Pratiwi Indra Pratiwi Indra Pratiwi Kharisma Kharisma Kusuma, Dedy Hidayat Novi Indah Pradasari Refid Ruhibnur Rizqia Lestika Atimi Rizqia Lestika Atimi . Ruhibnur, Refid Rustiarni Rustiarni Sartika .