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All Journal Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Ilmu Komputer Aceh
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Universitas Almuslim
Computer Science & IT Decision Sciences, Operations Research & Management Education Engineering Library & Information Science Mechanical Engineering

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Model Pengenalan Wajah Menggunakan Algoritma k-Nearest Neighbors Rifa Hayatul Nisa; Iqbal; Imam Muslem
Jurnal Ilmu Komputer Aceh Vol 3 No 2 (2026): Jurnal Ilmu Komputer Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim

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Abstract

This study explores the development of a face recognition model using the K-Nearest Neighbors (KNN) algorithm as a classification method in biometric systems. The dataset consists of 1,000 grayscale facial images sized 128x128 pixels, collected from 10 individuals with 100 images each. Feature extraction was conducted using the Histogram of Oriented Gradients (HOG) technique to capture distinctive facial characteristics. The experimental results show that the optimal k value is 4, producing a validation accuracy of 75.37%. Further testing achieved an accuracy of 81.37% with an average F1-score of 0.81, demonstrating reliable recognition performance. Live recognition tests confirmed that the system can still identify faces under real-world conditions, such as varied orientations and partial occlusions. These results indicate that KNN is an effective and efficient algorithm for small to medium-scale face recognition tasks, offering fast training time and practical applicability for biometric identification systems.
Klasifikasi Varietas Biji Kopi Arabika Gayo Berbasis Deteksi Objek Menggunakan Algoritma Yolov5 Randa Mah Bengi; Iqbal; Riyadhul Fajri
Jurnal Ilmu Komputer Aceh Vol 3 No 2 (2026): Jurnal Ilmu Komputer Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim

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Abstract

Gayo Arabica coffee is one of Indonesia’s leading agricultural commodities with high economic value, especially in the export market. However, the process of classifying coffee bean varieties is still mostly performed manually, which can lead to misidentification and inconsistency in quality control. This study aims to develop an automatic classification system for Gayo Arabica coffee bean varieties using a deep learning approach based on the You Only Look Once version 5 (YOLOv5) model. The dataset consisted of 1,500 images of three main varieties: Tim-tim (Gayo 1), Bor-bor (Gayo 2), and Ateng Super (Gayo 3), with 500 images per class. The images were collected through direct observation and documentation in Aceh Tengah and labeled using LabelImg. The model was trained using the Python programming language with the Ultralytics YOLOv5 library based on PyTorch. Model performance was evaluated using precision, recall, and mean Average Precision (mAP) metrics, as well as a confusion matrix. The final model achieved an accuracy of 96% with an mAP50–95 value of 0.99, indicating that the YOLOv5-based system can effectively and consistently classify coffee bean varieties in real-time. The results of this study are expected to assist farmers and coffee industry stakeholders in improving the efficiency and accuracy of post-harvest quality control
Rancang Bangun Sistem Informasi Rental Mobil Terintegrasi Whatsapp API Gateway Muhammad Akhyar; Iskandar Zulkarnaini; Iqbal
Jurnal Ilmu Komputer Aceh Vol 3 No 2 (2026): Jurnal Ilmu Komputer Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim

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Abstract

This study aims to design and implement a web-based car rental information system integrated with a WhatsApp API Gateway to improve operational efficiency and customer communication. The background of this research is the use of manual systems in rental services, which often leads to delays, data recording errors, and ineffective information delivery. The development method used is the Waterfall model, consisting of requirement analysis, system design, implementation, and testing stages. The system is developed using PHP as the programming language and MySQL as the database management system. System functionality is evaluated using Black Box Testing to ensure that all features operate according to user requirements. The results show that the system successfully automates key processes such as user registration, vehicle booking, transaction management, and notification delivery. Furthermore, the integration with WhatsApp API Gateway enables automatic message delivery with a success rate of 100% and a response time of less than 10 seconds. The implementation of this system significantly improves service efficiency, reduces human error, and enhances the quality of communication between service providers and customers.
Implementasi Radio Frequency Identification Sebagai Sistem Keamanan Sepada Motor Berbasis Arduino Riyadhul Fajri; Iqbal; Farizal
Sisfo: Jurnal Ilmiah Sistem Informasi Vol. 9 No. 1 (2025): Sisfo: Jurnal Ilmiah Sistem Informasi, Mei 2025
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/sisfo.v9i1.22134

Abstract

Perkembangan teknologi dan kebutuhan manusia yang makin meningkat merupakan dua hal yang saling mempengaruhi satu sama lain. Masyarakat luas menggunakan kendaraan sepeda motor untuk memudahkan menjangkau ke berbagai tempat. Sistem keamanan kendaraan bermotor konvensional sendiri yang masih sangat lemah. Sebagai contoh hanya dengan kunci T pencuri dapat dengan mudah membobol kunci kendaraan bermotor. Namun, maraknya pencurian yang terjadi khususnya pada sepeda motor membuat banyak orang berusaha untuk lebih meningkatkan sistem keamanan sepeda motor baik menggunakan alat-alat pengaman dari sistem lama ke sistem baru, untuk mengurangi hal-hal yang tidak kita inginkan kunci kontak sepeda motor diganti dengan sebuah sistem pengaman yang mana Pada masa sekarang ini dikenal suatu sistem Radio Frequency Identification (RFID) yang memanfaatkan gelombang radio untuk melakukan proses identifikasi. Kendaraan ini tidak lagi menggunakan kunci kontak biasa tapi menggunakan sebuah kartu tag ID sebagai kartu identitas atau pengenal ketika hendak menghidupkan atau mematikan mesin sepeda motor. Kinerja kartu ini juga didukung oleh Mikrocontroller Arduino Nano dan Relay. Dalam perancangan alat ini, kami menghubungkan kabel-kabel yang ada pada kotak pengaman (Alat Perancangan yang terdiri dari hardware Arduino Nano, RFID reader, LCD dan Relay) dengan input dan output saklar yang ada pada sepeda motor sehingga pada saat perakitan atau percobaan yang dilakukan dengan tiga tahap (scan) untuk menghidupkan dan mematikan mesin sepeda motor. Scan pertama, untuk memposisi ON kan kelistrikan sepeda motor. Scan kedua, untuk menghidupkan mesin sepeda motor. Scan ketiga, untuk mematikan mesin sepeda motor.
Co-Authors Farizal Iskandar Zulkarnaini Muhammad Akhyar Muslem R, Imam Randa Mah Bengi Rifa Hayatul Nisa Riyadhul Fajri