Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal Abdi Jurnal Publikasi OKTAL : Jurnal Ilmu Komputer dan Sains
Muhammad Gifary Nezar
Unknown Affiliation
Astronomy Chemistry Computer Science & IT Electrical & Electronics Engineering Social Sciences Other

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

Found 2 Documents
Search

 1 
OPTIMALISASI PERSONAL BRANDING SISWA MELALUI PEMBUATAN WEBSITE CV DI ERA DIGITAL Dimas Aqil Setyawan; Julio Rohmatulloh Hardiansyah; Marisa Firdha; Muhammad Gifary Nezar; Pinhan Fatoni; Ratu Ayu Fatimah; Razky Zaihan Daulay; Robi Ramadhan; Salsabilla Pixy Anjelita; Siti Halimatul Aliyah; Muhammad Azis Sularso
Abdi Jurnal Publikasi Vol. 4 No. 3 (2026): Januari
Publisher : Abdi Jurnal Publikasi

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The rapid development of digital technology requires students to possess adaptive skills, particularly in building effective personal branding. Personal branding plays an important role in enhancing students’ competitiveness in both academic and professional environments. This report discusses the optimization of students’ personal branding through the development of a Curriculum Vitae (CV) website as a professional, informative, and easily accessible digital medium. The methods used include observation, design, and implementation of a CV website by utilizing simple web technologies tailored to students’ needs. The results indicate that the CV website helps students present their personal identity, competencies, experiences, and portfolios in a structured and attractive manner. Furthermore, the use of a CV website increases students’ self-confidence and readiness to face further education opportunities and job selection processes. Therefore, the development of a CV website can be considered an effective solution for optimizing students’ personal branding in the digital era.
Rekomendasi Fashion Menggunakan Content-Based Filtering dengan Integrasi Fitur Visual Dan Tekstual Gunawan Wibisono; Fiyado Yudha Witama; Muhammad Gifary Nezar; Perani Rosyani
OKTAL : Jurnal Ilmu Komputer dan Sains Vol 4 No 12 (2025): OKTAL : Jurnal Ilmu Komputer Dan Sains
Publisher : CV. Multi Kreasi Media

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The growth of fashion e-commerce leads to information overload for users. Traditional collaborative filtering-based recommendation systems often face cold-start problems. This study aims to develop a content-based fashion recommendation system that integrates visual and textual features without relying on user historical data. The proposed hybrid approach combines visual feature extraction using Convolutional Neural Network (VGG16) and textual feature extraction using Term Frequency-Inverse Document Frequency (TF-IDF). The Fashion Product Images dataset was modified from 44,400 to 5,000 samples through stratified sampling for computational efficiency. Experimental results show that the hybrid system with 60% visual and 40% textual weights achieved the best performance: Precision@5 of 78%, Recall@5 of 65%, and Accuracy@5 of 88%. The system's response time of 0.82 seconds meets real-time application criteria. Dataset reduction only decreased accuracy by 0.4% from the full dataset, but reduced training time by 82% and memory usage by 75%. This research proves that multimodal integration in content-based systems can produce relevant, personalized, and computationally efficient fashion recommendations.
Co-Authors Dimas Aqil Setyawan Fiyado Yudha Witama Gunawan Wibisono Julio Rohmatulloh Hardiansyah Marisa Firdha Muhammad Azis Sularso Perani Rosyani Pinhan Fatoni Ratu Ayu Fatimah Razky Zaihan Daulay Robi Ramadhan Salsabilla Pixy Anjelita Siti Halimatul Aliyah