Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal Jurnal Informatika dan Teknik Elektro Terapan Madani: Multidisciplinary Scientific Journal
Nasution, Mansalwa Utama
Unknown Affiliation
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Education Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Physics Public Health Social Sciences Other

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Interaksi Berbasis Gestur: Inovasi dalam Pengalaman Pengguna di Lingkungan Virtual Gading, Rafli Arya; Akbar, Mukhamad Rizky; Nasution, Mansalwa Utama
Madani: Jurnal Ilmiah Multidisiplin Vol 3, No 4 (2025): May
Publisher : Penerbit Yayasan Daarul Huda Kruengmane

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.15420673

Abstract

This study discusses the evolution of human-computer interaction (HCI), which continues to advance alongside technological developments, particularly through innovations in gesture-based interaction. The research aims to explore the effectiveness of gestures in enhancing user experience in virtual environments, such as augmented reality (AR) and virtual reality (VR). The methodology employed is thematic analysis of relevant literature to identify innovation patterns and concept developments. Research findings indicate that: (1) gesture-based interaction improves user speed and accuracy in task completion; (2) the use of gestures creates a more immersive and intuitive experience; and (3) this technology enhances user engagement with digital systems, strengthening non-verbal communication. This research contributes significantly to the development of interface design and applications across various sectors, including education, entertainment, and healthcare.
TINJAUAN METODE PENGOLAHAN CITRA DIGITAL UNTUK DETEKSI OBJEK OTOMATIS Nasution, Mansalwa Utama; Lailan Sofinah Harahap; Fajar Syakbani
Jurnal Informatika dan Teknik Elektro Terapan Vol. 13 No. 3 (2025)
Publisher : Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jitet.v13i3.7135

Abstract

Deteksi objek otomatis merupakan bagian penting dalam pengolahan citra digital yang banyak diaplikasikan dalam bidang keamanan, medis, hingga kendaraan otonom. Penelitian ini bertujuan untuk meninjau dan membandingkan beberapa metode deteksi objek berbasis pengolahan citra digital dengan pendekatan klasik dan deep learning menggunakan Python. Metode klasik yang digunakan adalah Canny Edge Detection dan Template Matching, sedangkan pendekatan modern mencakup YOLOv5. Hasil eksperimen menunjukkan bahwa metode berbasis deep learning memberikan akurasi dan kecepatan deteksi yang lebih baik dibandingkan metode klasik. Evaluasi dilakukan berdasarkan metrik presisi, recall, dan Intersection over Union (IoU).
Co-Authors Akbar, Mukhamad Rizky Fajar Syakbani Gading, Rafli Arya Lailan Sofinah Harahap