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All Journal Coding: Jurnal Komputer dan Aplikasi Journal of Information Systems and Technology Research Internet of Things and Artificial Intelligence Journal
Putra, Donny Dwi
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Aplikasi Python untuk Deteksi Wajah pada Frame Menggunakan Algoritma Haar Cascade Classifier di OpenCV Silalahi, Dinah Makhroza; Putra, Donny Dwi; Sari, Dwi Prapita; Pramudya, Farhan Amar; Supiyandi, Supiyandi
Coding: Jurnal Komputer dan Aplikasi Vol 12, No 3 (2024): Edisi Desember 2024
Publisher : Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/coding.v12i3.88402

Abstract

Penelitian ini mengembangkan aplikasi berbasis Python untuk mendeteksi wajah dalam frame video secara real-time menggunakan pustaka OpenCV. Teknologi face detection memungkinkan sistem mengenali dan mendeteksi wajah manusia pada citra atau video, yang relevan untuk aplikasi di bidang keamanan dan interaksi manusia-komputer. Penelitian ini bertujuan merancang dan mengimplementasikan aplikasi yang mampu mendeteksi wajah dengan akurasi tinggi dan respons cepat. Metode yang digunakan melibatkan algoritma Haar Cascade Classifier, diterapkan dalam pengolahan frame video dari kamera secara berurutan. Hasil pengujian menunjukkan aplikasi memiliki kemampuan deteksi yang baik, bahkan dalam kondisi pencahayaan yang beragam dan posisi wajah yang tidak seragam. Dengan kecepatan deteksi yang memadai, aplikasi ini berpotensi diterapkan di berbagai bidang. Penelitian ini memberikan kontribusi signifikan terhadap pengembangan teknologi face detection yang lebih efektif dan efisien, dengan pemanfaatan algoritma Haar Cascade Classifier yang mampu mencapai tingkat akurasi rata-rata sebesar 92% dan kecepatan proses rata-rata 30 ms per frame dalam kondisi optimal.
Transformation of Binjai Police Presence Application: UI/UX Design with Design Thinking Method to Improve Efficiency and User Experience Algifahri, Muhammad Dzar; Putra, Donny Dwi; Zulfi, Tio Fahreza Zulfi; Lubis, Aidil Halim
Internet of Things and Artificial Intelligence Journal Vol. 4 No. 1 (2024): Volume 4 Issue 1, 2024 [February]
Publisher : Association for Scientific Computing, Electronics, and Engineering (ASCEE)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31763/iota.v4i1.690

Abstract

Attendance systems have become integral to attendance management and employee supervision in various organizations. Binjai Resort Police, as a law enforcement agency in the region, is now using an access control system for all its employees. The system is expected to be a new solution for attendance management in the agency, providing efficiency and accuracy in monitoring employee attendance. In today's digital era, attention to user interface (UI/UX) is essential in product development, especially mobile applications. The ultimate goal of this study is to create an attendance mobile application prototype that meets the company's needs. Design Thinking methodology was used to focus on problem-solving by prioritizing end-user needs. The design process consists of five steps: Empathize, Define, Ideate, Prototype and Testing, and Testing. The test results show that the design is already running well, following the needs, and has the potential for further development.
Web-Based Decision Support System for Superior Corn Seed Selection Using FMADM and AHP Algorithms Putra, Donny Dwi; Hasugian, Abdul Halim
Journal of Information Systems and Technology Research Vol. 4 No. 3 (2025): September 2025
Publisher : Ali Institute or Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/jistr.v4i3.1331

Abstract

Indonesia as an agricultural country still faces challenges in meeting national corn demand due to dependency on imports. One critical issue is the inaccurate selection of superior seeds that suit local conditions. This study aims to develop a web-based decision support system (DSS) for superior corn seed selection using the Fuzzy Multi-Attribute Decision Making (FMADM) algorithm combined with the Analytical Hierarchy Process (AHP) method.The research was conducted in Sei Tembo Village, Langkat Regency, with data obtained through observation, interviews with farmers, and literature review. The AHP method was applied to determine the weights of five criteria: water content, pest resistance, productivity, fruit size, and harvest time. Consistency testing produced a CR value of 0.028, indicating reliable weighting. The FMADM method was then used to rank 142 seed alternatives based on these weights.The results showed that the proposed system successfully ranked Srikandi Putih 1 (A32) as the best alternative with a score of 0.950, while Bima5 Bantimurung (A130) had the lowest score of 0.632. Productivity was identified as the dominant factor (weight = 0.484) in determining superior seeds.These findings demonstrate that the web-based DSS can improve accuracy and objectivity in seed selection, helping farmers reduce trial-and-error decisions. Practically, this system supports agricultural productivity improvement and contributes to strengthening national food security by reducing reliance on corn imports.
Co-Authors Abdul Halim Hasugian Aidil Halim Lubis Algifahri, Muhammad Dzar Pramudya, Farhan Amar Sari, Dwi Prapita Silalahi, Dinah Makhroza Supiyandi Supiyandi Zulfi, Tio Fahreza Zulfi