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All Journal The Indonesian Journal of Computer Science Jurnal Testing dan Implementasi Sistem Informasi
Auliani, Sephia Nazwa
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Computer Science & IT Electrical & Electronics Engineering Engineering

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Audit Tata Kelola Universitas Islam Negara Sultan Syarif Kasim Riau Repository System Menggunakan COBIT 2019 Alisya, Tita; Handayani, Hani; Auliani, Sephia Nazwa; Khairani, Luthfia; Megawati, Megawati
Jurnal Testing dan Implementasi Sistem Informasi Vol. 2 No. 1 (2024): Jurnal Testing dan Implementasi Sistem Informasi
Publisher : Lembaga Riset dan Inovasi Almatani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55583/jtisi.v2i1.754

Abstract

Teknologi Informasi telah menjadi pendorong utama keberhasilan organisasi di berbagai sektor, termasuk dunia Pendidikan. Universitas, sebagai lembaga pendidikan tinggi, semakin mengandalkan TI untuk mendukung operasional dan pengelolaan informasi akademis. Perpustakaan Universitas Islam Negeri Sultan Syarif Kasim Riau mendukukng fungsi operasional, pengelolaan di perpustakaan. Proses audit pada Perpustakaan dilakukan untuk mengetahui sejauh mana kinerja IT, sumber daya manusia serta capability level di perpustakaan. Penelitian ini menggunakan Framework COBIT 2019 dalam melakukan auidit. Didapatkan hasil pada 4 domain proses yaitu APO09, APO11, BAI04 dan BAI06. APO09 dan BAI04 berada pada level 2 dengan kategori largely achieved, sedangkan APO11 dan BAI06 berada pada level 5 dengan kategori  fully achieved.
Implementation of Density-Based Spatial Clustering of Applications with Noise and Fuzzy C – Means for Clustering Car Sales Auliani, Sephia Nazwa; Mustakim; Novita, Rice; Afdal, M
The Indonesian Journal of Computer Science Vol. 13 No. 4 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i4.4135

Abstract

This study compares the performance of two clustering algorithms, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Fuzzy C-Means (FCM), in clustering car sales data at PT. XYZ. The dataset, comprising sales transactions from 2020 to 2023, includes information about vehicles, customers, and transactions. Preprocessing methods such as data transformation and normalization were applied to prepare the data. The results indicate that DBSCAN produces clusters with better validity, measured using the Silhouette Score, compared to FCM. Specifically, DBSCAN achieves the highest Silhouette Score of 0.7874 in cluster 2, while FCM reaches a maximum score of 0.3666 in cluster 3. Thus, DBSCAN proves to be more optimal for clustering car sales data at PT. XYZ, highlighting its superior performance in terms of cluster validity.
Co-Authors Alisya, Tita Hani Handayani, Hani Khairani, Luthfia M. Afdal Megawati - Mustakim Rice Novita