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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) 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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DAMPAK PENGGUNAAN MBANGKING PADA DIGITAL NATIVE MENGGUNAKAN METODE TECHNOLOGY ACCEPTANCE MODEL (TAM) maksal mina; Muhammad Fikry
Jurnal Komputer dan Teknologi Vol 5 No 2 (2026): JUKOMTEK JULI 2026
Publisher : Yayasan Pendidikan Cahaya Budaya Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64626/jukomtek.v5i2.568

Abstract

The rapid development of information technology has accelerated the transformation of banking services into digital-based systems, one of which is mobile banking (Mbanking). This service enables users to conduct financial transactions efficiently without physical interaction with bank offices. This study aims to analyze the effect of perceived usefulness, perceived ease of use, and perceived risk on the intention to use Mbanking among digital native generations using the Technology Acceptance Model (TAM) approach. This research employs a quantitative method with data collected through a Likert-scale questionnaire. The population consists of Generation Z and Millennials in Banda Aceh who use Mbanking services, with a total sample of 70 respondents selected using purposive sampling techniques. Data analysis was conducted using multiple linear regression with the assistance of SmartPLS software. The results indicate that perceived usefulness and perceived ease of use have a positive and significant effect on the intention to use Mbanking. In addition, perceived risk also shows a significant influence, indicating that security and trust are crucial factors in adopting digital banking services. Simultaneously, all independent variables significantly affect the intention to use Mbanking. These findings suggest that improving service benefits, ease of use, and system security can enhance users’ interest and sustained use of Mbanking, particularly among digital native groups.
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.
Internet of Things Based Detection System for Pencak Silat PSHT Basic Technique Movements Using the Support Vector Machine Method Ayunda Putri; Zara Yunizar; Muhammad Fikri; Fadlisyah; Hafiz Al Kautsar Aidilof
Jurnal Ragam Pengabdian Vol. 3 No. 2 (2026): Mei-Agustus, Sustainable Development Goals (SDGs): Multidisciplinary Perspectiv
Publisher : Lembaga Teewan Journal Solutions

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62710/j3rq4t73

Abstract

The utilization of technology in sports has become a crucial need to enhance modern coaching efficiency. In pencak silat, particularly within Persaudaraan Setia Hati Terate (PSHT), accurate mastery of basic techniques is essential. However, when students practice independently without supervision, they often struggle to ensure correct hand movements, lowering training quality and increasing injury risks. As a solution, this study develops a real-time, Internet of Things (IoT)-based hand movement monitoring system using Inertial Measurement Unit (IMU) sensors. The sensor data is processed via a Machine Learning approach utilizing a 7-SVM Pipeline architecture. The Support Vector Machine (SVM) algorithm is applied to Model 0 (Movement Classifier) for movement classification, and Models 1–6 (Correctness Classifier) to evaluate quality into "Correct" or "Incorrect". The model is tested using the Leave-One-Subject-Out (LOSO) Cross-Validation method. Results show that Model 0 recognizes movement types with a 63.3% accuracy on unseen subjects. Meanwhile, the correctness models yield varying results; the highest achievement reaches 100% for the Left Jab, whereas the lowest is 55% for the Right Combination due to subjects' biomechanical variations. The results are displayed on a website dashboard as an objective companion tool for independent training while supporting digitalization in preserving pencak silat culture.  
APLIKASI TEKNOLOGI INTERNET OF THING PADA ROBOT PENDETEKSI KEBOCORAN GAS AMONIA (NH3) Jikti Khairina; Nurdin Nurdin; Muhammad Fikry
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 11, No 1 (2026)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v11i1.7457

Abstract

Amonia adalah senyawa kimia dengan rumus NH3 Senyawa ini didapati berupa gas dengan bau tajam yang sangat khas, inilah yang disebut dengan bau amonia. Amonia memiliki sumbangan penting bagi keberadaan nutrisi di bumi, tetapi amonia sendiri adalah senyawa yang dapat merusak kesehatan. Jika terjadi kontak dengan gas amonia berkonsentrasi tinggi dapat menyebabkan kerusakan pada paru-paru bahkan sampai kematian. Amonia digolongkan sebagai bahan beracun jika terhirup langsung, pengangkutan amonia yang berjumlah lebih besar dari 3.500 galon (13,248 L) harus disertai dengan surat izin. Amonia umumnya bersifat basa (pKb=4.75), tetapi dapat juga bersifat sebagai asam yang amat lemah (pKa=9.25), amonia dapat terbentuk secara alami maupun sintetis. Amonia yang berada di alam merupakan hasil dekomposisi bahan organik. Di industri banyak yang menggunakan amonia sebagai salah satu bahan baku, contohnya seperti dalam penggunaan campuran bahan baku pembuatan pupuk. Gas amonia terkadang beresiko terjadi kebocoran pada pipa gas, jika terjadi kebocoran pada pipa maka dibutuhkan teknisi yang harus segera dikirimkan ke lokasi untuk mencari sumber kebocoran atau titik kebocoran pada pipa. Hal itu membuat teknisi membutuhkan tabung oksigen dan hal ini beresiko sangat tinggi dikarenakan daya tahan tabung oksigen hanya bertahan selama ±15 menit. Maka dibuatkanlah robot untuk dikirimkan ke lokasi yang berfungsi agar mengetahui informasi tentang lokasi kebocoran pipa gas dan informasi kadar gas langsung dapat diketahui melalui Android. Dalam kasus ini, rancang bangun robot menggunakan sensor MQ135. Oleh karena itu dibuatkanlah robot pendeteksi kebocoran gas dan mengetahui kadar dari gas amonia agar mempermudah teknisi dalam menemukan lokasi dan kadar gas amonia.
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 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 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