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All Journal Jurnal Buana Informatika Media of Computer Science
Ida Bagus Gede Sarasvananda
Program Studi Informatika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Udayana
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science

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Inspired GWO-based Multilevel Thresholding for Color Images Segmentation via M. Masi Entropy I Made Satria Bimantara; I Wayan Supriana; I Komang Arya Ganda Wiguna; Ida Bagus Gede Sarasvananda
Jurnal Buana Informatika Vol. 16 No. 2 (2025): Jurnal Buana Informatika, Volume 16, Nomor 02, Oktober 2025
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jbi.v16i2.12463

Abstract

Image segmentation is crucial in image processing and computer vision, with multilevel thresholding (ML-ISP) offering robust solutions for complex images. However, effectively applying ML-ISP to RGB color images remains a challenge due to computational complexity and the limitations of traditional optimization algorithms, such as the Grey Wolf Optimizer (GWO). This study proposes an Inspired Grey Wolf Optimizer (IGWO) to address these issues and enhance ML-ISP for RGB color images. The performance stability of IGWO is comprehensively evaluated using three distinct objective functions: the Otsu method, the Kapur Entropy, and the M. Masi Entropy. Qualitative and quantitative analyses using PSNR, SSIM, and UQI were conducted on benchmark images. Results consistently demonstrate that IGWO, particularly with M. Masi Entropy, achieves superior segmentation quality. This research incorporates GridSearch-based hyperparameter tuning. The findings highlight the effectiveness and robustness of the proposed IGWO approach for complex ML-ISP tasks on color images.
ETL Implementation with Pentaho for Sales Data Visualization: A Case Study of Lunabit Beauty Bar I Gde Eka Dharsika; Ni Kadek Ayu Sulistiawati; Ida Bagus Gede Sarasvananda
Media of Computer Science Vol. 2 No. 2 (2025): December 2025
Publisher : CV. Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mcs.v2i2.239

Abstract

The rapid growth of information technology has encouraged businesses to optimize their data management through data warehousing and visualization. This study presents the implementation of the Extract, Transform, Load (ETL) process using Pentaho Data Integration (PDI) for the development of a sales data visualization dashboard at Lunabit Beauty Bar. The ETL process was carried out on sales transaction data originally stored in CSV format and later structured into a MySQL-based data warehouse. The stages of ETL include data extraction, transformation involving cleaning, integration, and validation to ensure consistency, and loading into the warehouse for further analysis. The visualization dashboard displays several analytical perspectives, including sales trends over time, sales performance by treatment, customer contributions, and treatment ranking from highest to lowest. To evaluate system performance and usability, a User Acceptance Test (UAT) was conducted involving 16 respondents, including the owner and staff. The results showed a satisfaction rate of 94%, indicating that the system met the company's needs in providing valid, clear, and easy-to-understand information. This research demonstrates that the integration of ETL processes with data visualization tools can support business decision-making, particularly in monitoring sales performance and designing promotional strategies.
Co-Authors I Gde Eka Dharsika I Komang Arya Ganda Wiguna I Made Satria Bimantara I Wayan Supriana Ni Kadek Ayu Sulistiawati