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All Journal Jurnal Informatika dan Teknik Elektro Terapan Jurnal Edik Informatika : Penelitian Bidang Komputer Sains dan Pendidikan Informatika Sistemasi: Jurnal Sistem Informasi Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer International Journal of Artificial Intelligence Research RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JITK (Jurnal Ilmu Pengetahuan dan Komputer) JOURNAL OF APPLIED INFORMATICS AND COMPUTING JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) METIK JURNAL Jurnal Informasi dan Teknologi Vocatech : Vocational Education and Technology Journal Jurnal Sosial Humaniora Sigli Jurnal Computer Science and Information Technology (CoSciTech) Jurnal Pendidikan dan Teknologi Indonesia International Journal of Engineering, Science and Information Technology Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) TECHSI - Jurnal Teknik Informatika Journal of Information Technology (JINTECH) Jurnal Teknologi Terapan and Sains 4.0 Journal of Computer Engineering, Electronics and Information Technology Journal Of Artificial Intelligence And Software Engineering Jurnal Informatika: Jurnal Pengembangan IT Jurnal Komputer dan Teknologi (JUKOMTEK) Jurnal Malikussaleh Mengabdi Jurnal Ragam Pengabdian Teewan Journal Solutions Proceeding of The International Conference on Electrical Engineering and Informatics Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS) Jurnal Pengabdian Masyarakat Teknologi Informasi (PERANTI)
Muhammad Fikry
Teknik Informatika Universitas Malikussaleh
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Journal : journal of applied informatics and computing

 1 
Development of an IoT-Based Smart Greenhouse with Fuzzy Logic for Chrysanthemum Cultivation Khairina, Jikti; Nurdin, Nurdin; Fikry , Muhammad
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10313

Abstract

Conventional cultivation of Chrysanthemum plants in greenhouses faces serious challenges such as inefficiency, response delays, and errors in temperature and humidity settings due to manual management. These conditions result in unsuitable growing environments that can reduce the quality and quantity of harvests. To overcome these problems, this study developed a smart greenhouse system based on the Internet of Things (IoT) and cloud computing with the application of fuzzy logic. The system is designed to automatically monitor and control temperature, humidity, and light intensity using NodeMCU ESP32, DHT22 and BH1750 sensors, as well as relay-based actuators and mini air conditioners. Environmental data is sent to the cloud and processed using the Sugeno fuzzy method to produce adaptive and precise control decisions. Test results show that the system can maintain stable and optimal environmental conditions with an average temperature control difference of 30.341% and an actuator efficiency of 9.34% against microcontroller commands. This system provides a modern solution to the limitations of traditional methods, and supports smart agriculture in tropical climates such as Lhokseumawe.
Integrated Emergency Communication System for Disaster Areas Using Long Range Mahadika Luqman; Muhammad Fikry; Yesy Afrillia
Journal of Applied Informatics and Computing Vol. 10 No. 3 (2026): June 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i3.12753

Abstract

Natural disasters disrupt communication infrastructure, hindering emergency response coordination. This study designs and evaluates an integrated emergency communication system combining LoRa for transmission, GPS for geolocation, and BLE for alternative interface. The system comprises a Field Device with a 9-state finite-state machine, a Beacon Network forming a linear multi-hop relay chain with heartbeat-based node failure detection, and a Headquarter Device connected to the Blynk platform for monitoring and notifications. A custom binary protocol with 8 message types uses packed structures. All performance was evaluated in urban area, except maximum communication direct range in urban area and rural area. PDR achieves 100% up to 1,000 m Line-of-Sight with an average end-to-end latency of 1.02 s. A single beacon relay extends communication range to 2000 m compared to maximum direct communication range, 1288 m in rural area and 1044 m in urban campus area. Outdoor GPS accuracy measures 0.945 m, while indoor accuracy 28.68 m due to building attenuation. The system successfully detected motion >5 m with 100% sensitivity within 5 s. Usability testing average completion times of 14.84 s via physical interface and 23.85 s via mobile application. BLE range reaches 16 m outdoors and 11 m indoors. Operational durations were 4.32 h for the Field Device, 9.18 h for the Beacon Network, and 8.03 h for the Headquarter Device, falling short of the 12-hour target, necessitating aggressive GPS duty cycling and Wi Fi sleep modes. This study evaluates three critical factors for emergency response: network determinism, payload efficiency, and power autonomy.
Comparative Analysis of CNN and YOLO for Aromatic Leaf Detection on Android-Based Deep Learning Applications Yuli Safrina; Muhammad Fikry; Mukhlis Abd Muthalib
Journal of Applied Informatics and Computing Vol. 10 No. 3 (2026): June 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i3.13015

Abstract

Commonly used aromatic leaves in Indonesian cuisine include bay leaves (Syzygium polyanthum), pandan leaves (Pandanus amaryllifolius), lime leaves (Citrus hystrix), curry leaves (Murraya koenigii), and turmeric leaves (Curcuma longa). Their similar shapes, colors, and textures often make manual identification difficult. Therefore, deep learning technology can be utilized to automatically identify and detect aromatic leaf types through digital images. This study aims to analyze the performance of a Convolutional Neural Network (CNN) using the EfficientNet-B0 architecture and the YOLOv11 model with the AdamW optimizer in detecting and classifying aromatic leaves. The system is implemented using a Python Flask framework for the web based backend and Flutter for the mobile application interface on Android devices. The dataset used in this study consists of 671 digital images obtained through direct image collection and supporting datasets. The dataset is categorized into five classes: bay leaf, pandan leaf, lime leaf, curry leaf, and turmeric leaf. Furthermore, the dataset is divided into training data (89%), validation data (7%), and testing data (4%). The results show that the YOLOv11 model outperforms the CNN (EfficientNet-B0) model. YOLOv11 achieved a precision of 73.36%, recall of 84.35%, mAP50 of 83.93%, and mAP50-95 of 71.38%. Meanwhile, EfficientNet-B0 achieved a best validation accuracy of 81.40% and a test accuracy of 62.07%. Based on experimental results, YOLOv11 demonstrates higher detection confidence and more consistent performance compared to EfficientNet-B0. In addition, YOLOv11 is more suitable for mobile deployment due to its real-time object detection capability with faster inference speed, while the system is supported by a Flask based backend and a Flutter mobile application interface.
Real-Time Heart Rate Pattern Analysis During Computer-Based Work Activities Muhammad Fatiha Assyfa; Muhammad Fikry; Zara Yunizar
Journal of Applied Informatics and Computing Vol. 10 No. 4 (2026): August 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i4.13148

Abstract

The development of Internet of Things (IoT) technology provides opportunities for real-time health monitoring systems, including stress detection based on users’ physiological conditions. This study aims to develop an IoT-based heart rate monitoring and stress detection system using a Pulse Sensor and ESP8266 microcontroller. The system is designed to read heart rate signals in real-time and transmit the data to a computer through serial USB communication for further processing using the Python programming language. The data processing stages include signal preprocessing, Beats Per Minute (BPM) calculation, sliding window processing, and kurtosis analysis as an indicator of user stress levels. The processed data are visualized through a Streamlit-based monitoring dashboard in the form of time-series graphs, gauge meters, and real-time user condition status. The study involved 20 Informatics Engineering students performing computer-based work activities within a certain duration. The results show that the system is capable of performing real-time heart rate monitoring and stress analysis effectively. The kurtosis values indicate changes in heart rate signal distribution patterns that can be used as indicators of normal and stress conditions. The developed system is expected to provide a simple, affordable, and extensible health monitoring solution.
Co-Authors Aldo januansyah. H Amalia, Iklasni Ananda, Silvia Angela, Angela Annisa Annisa Annisa Helmina Aprian Gigin Prasetia Ar Razi Ar Razi Asrianda Asrianda Aynun, Nur Ayunda Putri Azzahra Iskandar, Farah Budi Bahreisy Bustami Bustami Bustami Chrisnata Manihuruk Cut Ita Erliana Dahlan Abdullah David Fadlianda Dessayani Putri Dimas Pratama, Dimas Dyah Ika Rinawati Ella Suzanna Erwanda, Ade Putra Eva Darnila Fadlisyah Fadlisyah Fadlisyah Fadlisyah Fadlisyah Faiz Syukri Arta Faiz Fajar Rivaldi Chan Fajriana, Fajriana Faradilla, Cut Meutia Hadi Iskandar Hafiz Al Kautsar Aidilof Hafizh Al Kautsar Aidilof Hafizh Al Kautsar Aidilof Hamdhana, Defry Hasan Tahir Helmi Naluri Herman Fithra Hidayatsyah Hidayatsyah Hizamrul jaen Hutagalung, Yorio Arwandi Wisdom Ibnu Khaldun Ida Wahyuni Ima Pratiwi Imam Rosadi Irfan Sahputra Iskandar, Fahra Azzahra Ismail Ismail Jikti Khairina Khaidar, Al Khairina, Jikti Kurnia Amanda, Destiara Kurniawati Kurniawati Lidya Rosnita Lutfi, Raihansyah Luthvy Ilhamdi M Ishlah Buana Angkasa M. Rafli Al Thoriq Mustafa Mahadika Luqman Maharani, Silfa Maksal Mina Mardiansyah, M Rizki Maulana, OK Muhammad Majid Mhd Firza Ryzaaldy Muchlis Abdul Muthalib Muhammad Al Imran Muhammad Dastur Muhammad Fatiha Assyfa Muhammad Fikry Muhammad Iqbal Muhammad Iqbal Muhammad Sapriadi Muhammad Yani, Muhammad Muhammad Zikri Mukhlis Mukhlis Mukti Qamal Muqarrabin, Khalis Al Nanda Nan Arif H Nazwa Aulia NELI SUSANTI, NELI Nunsina Nura Usrina Nurdin Nurdin nuryana nuryana, nuryana Rahma, Mutiara Raihansyah, Khananda Rifkial Iqwal Rini Meiyanti Risawandi, Risawandi Rizal S.Si., M.IT, Rizal Rizki Suwanda Romi Asmara Rozzi Kesuma Dinata Safwandi Safwandi Said Fadlan Anshari Salahuddin Salahuddin Saputra, Ferdy Sari, Cut Jora Sayed Fachrurrazi Sembiring, Vivi Dista Br Silfa Maharani Br Padang Subhan Hartanto Subhan Hartanto Sudirman Sudirman Sujacka Retno Sukma Rizki Tarigan, Anggun Kinanti Taufiq Taufiq Taufiqurrahman Taufiqurrahman Tejas Shinde Teuku Nabil Muhammad Dhuha Umar Khalil Utomo, Muhammad Fikri Wahdana, Aldi Wirda Syahrifa Yani, Muhamamd Yesy Afrillia Yesy Afrillia Yuli Safrina Yulinazira, Ulfa Yusriyana, Yusriyana Yusrizal Hasbi Zahratul Fitri Zara Yunizar Zara Yunizar zulfhazli zulfhazli