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The Analisis Perbandingan Algoritma Floyd-Warshall dan A Star (A*) dalam Penentuan Lintasan Terpendek Ahmad Fadillah
JATISI (Jurnal Teknik Informatika dan Sistem Informasi) Vol 9 No 4 (2022): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v9i4.2663

Abstract

Makassar City is one of the cities in Indonesia as well as the capital city of South Sulawesi (Sulsel) Province. Based on data from the Directorate General of Population and Civil Registration (Dukcapil) and the Ministry of Home Affairs (Kemendagri), the total population of South Sulawesi will reach 9.19 million as of June 2021. Of this number, 8.26 million people (89.87%) are Muslim. Determining the trajectory of Islamic studies at the Makassar City Mosque, it takes the shortest path to the location of the mosque that conducts Islamic studies so that people can easily find out the distance, trajectory, and travel time to find the shortest path. The Floyd-Warshall algorithm is used to solve the shortest path problem. This algorithm compares all possible paths in the graph for each edge of all vertices. The A Star algorithm is a computer algorithm that is widely used in path finding and graph traversal, the process of efficiently plotting a transverse path between points, called nodes. The results showed that the comparison between the two algorithms based on the starting point and destination point in the search for distance, trajectory and travel time had different values ​​and each algorithm had a different trajectory search process. Based on the results of black box testing on the system declared valid or as expected. The system testing on the Admin User Acceptance Test (UAT) is 86,85% and the general public UAT test results are 83,46%.
ANALISIS VISUAL DAN KLASTERISASI MULTIDOMAIN MENGGUNAKAN PYTON: KEUANGAN, GIZI, DAN POLITIK Abu Bakar Riziq; Ahmad Fadillah; Fahmi Firmansyah; Gumilang Ali Prayogi; Defri Sulaeman; Intan Kumalasari
Journal of Research and Publication Innovation Vol 3 No 3 (2025): JULY
Publisher : Journal of Research and Publication Innovation

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

Abstract

This study applies data visualization and machine learning techniques to explore patterns across three distinct domains: corporate financial reports, food nutritional content (amino acids), and vote distribution in regional elections. Using Python and libraries such as pandas, scikit-learn, matplotlib, and seaborn, this study utilizes the KMeans algorithm, Principal Component Analysis (PCA), and linear regression. The results are evaluated using the Silhouette Score to assess cluster quality. This study demonstrates that an exploratory approach with Python is effective in uncovering insights from cross-domain data and supporting data-driven decision-making.