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p-Index From 2021 - 2026
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All Journal International Journal of Computer Technology and Science Journal of Engineering, Electrical and Informatics
Elviwani Elviwani
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Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Implementation of Social Media Network Block Access Using Fortinet Case Study at PT Estrada Rasiban Rasiban; Tri Wahyudi; Elviwani Elviwani; Aditya Bagas Pramudhi
International Journal of Computer Technology and Science Vol. 1 No. 1 (2024): International Journal of Computer Technology and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijcts.v1i1.296

Abstract

Computers in one of the network companies at PT. Estrada uses the Fortinet operating system. The final result expected through this implementation is to comprehensively see the capabilities of the firewall on Fortinet in overcoming the problem of blocking social media applications and streaming platforms during working hours. Blocking the application in question is the ability to filter web processes such as Facebook, Instagram, YouTube, etc. In the tests carried out, web filtering was able to block applications on social media and streaming platforms, which proves that the performance of web filtering is quite good. In analyzing web filtering performance, use the office hour rule tool by carrying out the rule schedule in the Fortinet network and displaying all the information in detail. The final result obtained in the network application filtering simulation process using Fortinet is that every network sent cannot be entered (blocked) on both social media applications and streaming platforms.
Optimization of Real-Time Student Face Recognition Attendance Using the YOLO v10 Algorithm Mesra Betty Yel; Elviwani Elviwani; Nandang Sutisna; Ziyad Fernanda Syams
International Journal of Computer Technology and Science Vol. 2 No. 4 (2025): International Journal of Computer Technology and Science
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijcts.v2i4.328

Abstract

This research is motivated by the problems in manual attendance systems at schools, which remain vulnerable to fraud, time-consuming, and inefficient. The expected solution is to develop an automated attendance system based on face recognition that can operate in realtime with high accuracy. The research object is vocational high school students, with the applied method implementing the YOLO v10 algorithm for face detection, followed by the face_recognition library for identification. The instruments used include an Imou CCTV camera as the input device, a mid-range laptop as the hardware platform, and Python with SQLite as the software environment for data processing and attendance storage. The results show that the developed system achieved an average face detection accuracy of 96% under normal lighting and 91% under low lighting, with an average processing speed of 27 FPS. The implementation of an anti-duplication feature also ensured data validity by allowing each student to be recorded only once per day. In conclusion, the use of YOLO v10 in face-based attendance proved to be effective, efficient, and capable of reducing fraud. The implication of this study is that the system can be applied in both Islamic boarding schools and general schools as a modernization of attendance systems, with a recommendation for further development through web-based application and cloud database integration.
Application of TF-IDF and Xgboost Methods for Public Sentiment Analysis Towards Ozzaskin Skincare Brand on Social Media Mesra Betty Yel; Elviwani Elviwani; Nova Dahliyanti; Ahmad Syahran Zidane
Journal of Engineering, Electrical and Informatics Vol. 5 No. 1 (2025): Journal of Engineering, Electrical and Informatics
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jeei.v5i1.3676

Abstract

Ozzaskin is a local skincare brand founded by Ustadzah Oki Setiana Dewi that targets Muslim women and focuses on reducing dark spots and acne scars. Over time, this domestic brand has attracted considerable public attention on social media—particularly among mothers—garnering both praise for its product efficacy and criticism regarding price and texture. This study aims to analyze public sentiment toward the Ozzaskin brand by performing web scraping on Instagram and TikTok data, employing TF-IDF for textual feature extraction and XGBoost as the classification algorithm. The findings are expected to provide a comprehensive overview of consumer perceptions of Ozzaskin and to assist the marketing team and product developers in formulating communication strategies and improving product formulas that more effectively address user needs. The novelty of this research lies in the comprehensive application of the TF-IDF + XGBoost framework for brand-related sentiment analysis on Indonesian-language social media.
Co-Authors Aditya Bagas Pramudhi Ahmad Syahran Zidane Betty Yel, Mesra Nandang Sutisna Nova Dahliyanti Rasiban Rasiban Tri Wahyudi Ziyad Fernanda Syams