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All Journal JMPM: Jurnal Matematika dan Pendidikan Matematika Building of Informatics, Technology and Science Journal of Students‘ Research in Computer Science (JSRCS) Journal of Fundamental Mathematics and Applications (JFMA) Hortatori : Jurnal Pendidikan Bahasa dan Sastra Indonesia International Journal of Information Technology and Computer Science Applications (IJITCSA) Journal of Computer Science Contributions (Jucosco)
Ramdhania, Khairunnisa Fadhilla
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Engineering Languange, Linguistic, Communication & Media Mathematics

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Journal : Journal of Students‘ Research in Computer Science (JSRCS)

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Algoritma Levenshtein Distance sebagai Solusi Efisiensi Pencarian pada Training Registration System Akbar, Iqbal Faris; Mugiarso; Ramdhania, Khairunnisa Fadhilla; Rasim
Journal of Students‘ Research in Computer Science Vol. 5 No. 2 (2024): November 2024
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/mzr20n84

Abstract

The training registration process at Company XYZ faced several challenges, including the use of physical documents, slow file submission, non-standardized document numbering, and inefficient file storage. This research aimed to develop a web-based application called "Training Registration System" using the Waterfall software development method to address these issues, as well as implementing the Levenshtein Distance algorithm in the search feature to enhance training search efficiency. The results showed that the application successfully improved the efficiency and accuracy of the training registration and search process by eliminating the need for physical file submission, accelerating the workflow, and reducing the potential for errors. The implementation of the Levenshtein Distance algorithm also proved effective in improving the efficiency of training searches based on training names, even in cases of typos, such as the strings "Trainning" and "Training" which had a similarity score of 87.5% based on similarity weight calculations.
Analisis Clustering K-Means untuk Pemetaan Tingkat Pengangguran Terbuka di Provinsi-Provinsi Indonesia Tahun 2013-2023 Ramadhan, Alif Izzuddin; Ramdhania, Khairunnisa Fadhilla; atika, prima dina
Journal of Students‘ Research in Computer Science Vol. 5 No. 2 (2024): November 2024
Publisher : Program Studi Informatika Fakultas Ilmu Komputer Universitas Bhayangkara Jakarta Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31599/wbpydb62

Abstract

This study analyzes unemployment rates in Indonesian provinces using data from the Central Statistics Agency (BPS) for the period 2013-2023 and the K-Means clustering algorithm. The aim is to group regions based on the Open Unemployment Rate (TPT). Two main clusters were produced: one with a high unemployment rate (cluster 0) and one with a low unemployment rate (cluster 1). Cluster 0 consists of 12 provinces, while cluster 1 consists of 22 provinces. The model evaluation shows a Davies-Bouldin Index score of 0.7041, indicating good clustering quality. The clustering results are visualized in the form of a map for easy interpretation. This research is expected to help policymakers design more effective policies in reducing unemployment in Indonesia, provide deep insights into regional differences in terms of unemployment, and support targeted decision-making.
Co-Authors Aida Fitriyani, Aida Akbar, Iqbal Faris Al Bari, Naufal Al Fajriy, Muhamad Fadilah Hadi, Muhamad Habib Abfsan Maulana Hasan, Febri Zulfatian Hasnandi, Azhar Heikal, Muhammad Alvien Hidayat, Dian Fitrianto Juhanda Khalida, Rakhmi Kuning, Layung Lestari, Nur’aini Puji Mahardika, Fauzan Naufaldy Mugiarso Novarizal, Safarin Pratama, Aldira Ryan Pribadi, Janwar Irwansah Prima Dina Atika Rafika Sari Ramadhan, Alif Izzuddin Rasim Ratna Salkiawati Ratna Sari Saputra, Rues Rizki SITI SETIAWATI Subakti, Rizky Tb Ai Munandar, Tb Ai