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All Journal JITCoS : Journal of Information Technology and Computer System Prosiding Seminar Nasional Ilmu Komputer, Sosial Sains, Teknik Dan Multi-disiplin Ilmu
Salsabila Nasution
Universitas Islam Negeri Sumatera Utara
Religion Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering

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Computer-Based Data Visualization Analysis for Simplifying Complex Information Salsabila Nasution; Fatwa Aulia; Saprina Putri Utama Ritonga; Anggi Jelita Sitepu; Supiyandi Supiyandi
Prosiding Seminar Nasional Ilmu Komputer, Sosial Sains, Teknik dan Multi-Disiplin Ilmu Vol. 1 (2025)
Publisher : Raskha Media Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64803/ikosstemi.v1.43

Abstract

This study aims to analyze global temperature data by employing computer visualization as a tool to simplify complex information. The dataset was obtained from Kaggle, specifically the Global Land Temperatures by City dataset, which contains monthly average temperature data from various cities worldwide. The methods applied include data preprocessing, descriptive statistical analysis, and data visualization using the Python programming language with the Pandas, Matplotlib, and Seaborn libraries. The visualization results reveal an upward trend in the global average temperature from 1900 to 2020, with an increase of approximately 1°C, indicating the occurrence of global warming. Computer visualization has proven to be effective in helping researchers and policymakers better understand temperature change patterns compared to numerical table-based analysis. Therefore, this study emphasizes that the application of computer visualization is an efficient solution for presenting and analyzing large-scale data, making it more interpretable.
Parking Route Modeling Using the A* Algorithm for Density Reduction at the Faculty of Science and Technology, State Islamic University of North Sumatra Asro Hayati Berutu; Salsabila Nasution; Suci Rahmadani
JITCoS : Journal of Information Technology and Computer System Vol. 1 No. 2 (2025): Journal of Information Technology and Computer System
Publisher : CV. Multimedia Teknologi Kreatif

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65230/jitcos.v1i2.46

Abstract

The increasing number of vehicles on university campuses has led to significant congestion, particularly around parking areas. This study aims to design an intelligent parking route model using the Density-Aware A* algorithm to minimize vehicle congestion within the Faculty of Science and Technology (FST) at UIN North Sumatra. The proposed approach represents the internal campus network as a weighted graph, where each edge integrates both spatial distance and a density penalty that reflects the occupancy-to-capacity ratio of each parking area. The algorithm was implemented and simulated using Python and the NetworkX library within Google Colab. The results show that the system accurately identifies the optimal parking route based on vehicle type and real-time occupancy data. For motorcycles, the optimal path is A > B > F with a total cost of 23.06, while for cars, the most efficient path is A > B > H with a total cost of 18.21. The findings indicate that incorporating density-based cost adjustments effectively balances travel efficiency and vehicle distribution, contributing to overall congestion reduction in the FST–FKM corridor. Future research should focus on integrating live sensor data and adaptive feedback mechanisms to support large-scale deployment across diverse campus environments.
Co-Authors Anggi Jelita Sitepu Asro Hayati Berutu Fatwa Aulia Saprina Putri Utama Ritonga Suci Rahmadani Supiyandi Supiyandi