Media of Computer Science

ETL Implementation with Pentaho for Sales Data Visualization: A Case Study of Lunabit Beauty Bar

I Gde Eka Dharsika — 2025-12-26

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.

Preprocessing Image for License Plate Detection: A Systematic Literature Review

Riyan Bagas Dwi Prasetyo — 2026-01-14

Rapid population growth contributes to an increase in the volume of vehicles, creating major challenges in their management. One potential solution is the application of deep learning-based artificial intelligence technology for automatic detection of vehicle license plates. This research uses a Systematic Literature Review (SLR) approach to evaluate the performance of various deep learning architectures in the detection process. Out of 125 articles identified, 20 articles were selected based on specific selection criteria. The analysis revealed that preprocessing techniques, such as HE, AHE, ECHE, CLAHE, and ECLACHE, have significant contributions in the processing of vehicle license plate datasets. These techniques were able to improve the visual quality of the images, thus supporting the detection process with an accuracy rate of more than 95%. This research also identified challenges, such as high computational requirements and large-scale data processing. Further research is recommended to apply preprocessing on standardized datasets to develop a reliable, efficient and sustainable detection system.

Implementation of Blockchain Technology for Securing Data Point Transactions in an IoT-Based Waste Sorting System

Naufal Raihan Elriza — 2025-12-27

An Internet of Things (IoT) based waste sorting device awards points to users who dispose of waste through it, as long as the user is registered in the system. However, despite these benefits, this system is vulnerable to various forms of cybercrime. One such challenge is the rise of data manipulation and cyberattacks such as sql injection and threats from internal parties (Insider Threats). This research aims to secure point data transactions in an Internet of Things (IoT) based waste sorting system integrated with blockchain technology to improve security in recording user point data. Tests were conducted to ensure that point data sent from IoT devices were successfully recorded on the blockchain network permanently and verified through transaction hashes in etherscan and to prevent sql Injection and Insider Threat attacks in attempts to illegally alter data. The results of the data transmission test to the blockchain network, which was carried out 30 times, showed that each transaction was successfully recorded and provided a transaction hash. In addition, the attack test, which was carried out 30 times, each attack resulted in a notification with the text “[PERINGATAN] Terjadi Percobaan Pengubahan Poin " in red. Using the blockchain network, both attacks failed to alter user points