Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
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This Author published in this journals
All Journal KOLONI Journal of Electrical Engineering and Informatics
Ainun Jariyah
Politeknik Negeri Ujung Pandang
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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Pemanfaatan Looker Studio untuk Visualisasi Kinerja Program Studi D4 Teknik Multimedia dan Jaringan Ainun Jariyah; Irmawati Irmawati; Tantri Indrabulan; Muhammad Ilyas Syarif; Riesa Krisna Astuti Sakir
KOLONI Vol. 1 No. 4 (2022): DESEMBER 2022
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/koloni.v1i4.510

Abstract

The Internal Quality Audit (IQA) process provides information related to performance of Study Program, this performance is represented by twelve criteria based on IQA instrument. The problem is Study Program team describes every condition of the twelve performance achievements in narrative and graphical form using Microsoft Excel and presented to audit team, this’s less effective because Study Program team's explanation cannot be accessed either online or in real time. Alternative solution is the creation of dashboard become right solution to visualize data related to Study Program performance by online so that it is easily accessible to interested parties. The method used is identifying dashboard needs, starting making and presenting dashboard, as well as testing and evaluating. The result is dashboard using Looker Studio which is presented in web view using Google Site to visualize Study Program performance which is illustrated through four criteria, namely lecturers, students, research, and community service whose function is to answer several IQA question instruments related to these criteria. The conclusion is the dashboard successfully answers IQA questions regarding parameters of Study Program performance for 4 criteria, and also presentation of the dashboard on Google Site makes monitoring performance data for each criterion easier to analyze. Keywords: dashboard, google site, looker studio, online, visualization  
Real-Time Vehicle Stopping Duration Detection and Calculation System in Drop-Off Areas Based on CCTV Cameras Using YOLOv8 Ainun Jariyah; Nurul Khaerani Hamzidah; Syahrir Syahrir
Journal of Electrical Engineering and Informatics Vol. 3 No. 2 (2026): Journal of Electrical Engineering and Informatics
Publisher : Fakultas Teknik Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/jeeni.v3i2.12492

Abstract

Objective: Campus drop-off areas often experience congestion due to vehicles stopping beyond the permitted duration without effective monitoring. This research aims to develop a real-time system for detecting and calculating vehicle stopping duration in campus drop-off areas using CCTV cameras and the YOLOv8 deep learning model. Method: This research applies a research and development (R&D) approach with a case study at the drop-off area of the Electrical Engineering Building, Campus 2, Ujung Pandang State Polytechnic (PNUP). The dataset, managed through Roboflow, comprises 803 images of cars and motorcycles (640×640 pixels), split into 78% training, 20% validation, and 2% test data. Model training and testing were conducted in Google Colab, while Visual Studio Code served as the main code editor. Results: The YOLOv8 model at epoch 42 of 50 achieved precision 90.8%, recall 98.5%, mAP50 94.5%, and mAP50-95 73.3%. The system successfully detects vehicles in real-time, recognizes drop-off boundaries, calculates stopping duration, and delivers voice notifications via speaker along with violation reports to a website dashboard and Telegram Bot. Novelty: This research integrates YOLOv8 object detection with polygon-based boundary recognition, automatic duration calculation, voice alerts, and dual monitoring through a website dashboard and Telegram Bot. The integration offers an automated solution for managing campus drop-off areas, reducing congestion and improving traffic efficiency.
Co-Authors Indrabulan, Tantri Irmawati Irmawati Muhammad Ilyas Syarif Nurul Khaerani Hamzidah Riesa Krisna Astuti Sakir Syahrir Syahrir