Kusdaryanto, Ardo
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Implementation of an Information System for Classroom Reservation at Esa Unggul University Siti Rodiyah; Sinulingga, Samuel Mahesa; Putra, Farrel Reyhan; Aryasatya, Muhammad Fathi; Kusdaryanto, Ardo; Sulistiyono, Rovy; Irawan, Bambang
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 8 No. 2 (2025): Jurnal Teknologi dan Open Source, December 2025
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v8i2.4633

Abstract

The manual management of room reservations at Esa Unggul University has long faced various administrative challenges, including irregular scheduling, delays in the approval process, and limited access to real-time room availability information. These issues reduce the overall efficiency of academic and administrative services. To address these problems, this study aims to design and implement a web-based information system that facilitates a more structured, transparent, and efficient room reservation process.The system was developed using the CodeIgniter 4 framework for the backend, while Bootstrap 5 and custom CSS were utilized for the frontend interface. MySQL served as the database management system, and application security features were enhanced with session-based authentication, input validation, data encryption, CSRF protection, Honeypot, and CloudFlare integration. Testing was conducted using the gray box method to evaluate both code reliability and system functionality from the user’s perspective.The results indicate that the application effectively handles room reservation requests, minimizes scheduling conflicts, and supports administrative staff in centrally monitoring room usage. This research contributes significantly to the digital transformation of campus administration and may serve as a reference for developing similar systems in other higher education institutions.
The The Use of the K-Means Algorithm in Analyzing E-Commerce Consumer Segmentation: A Case Study of the Online Retail Dataset (UK) Kusdaryanto, Ardo; Wijanarko, Christoporus Dimas; Widyantara Usat, Paskalis Dwi; Prabowo , Ary
JURNAL TEKNOLOGI DAN OPEN SOURCE Vol. 8 No. 2 (2025): Jurnal Teknologi dan Open Source, December 2025
Publisher : Universitas Islam Kuantan Singingi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36378/jtos.v8i2.4798

Abstract

This study aims to analyze consumer segmentation on e-commerce platforms by employing the K-Means algorithm as the primary clustering method. Using the Online Retail (UK) dataset, which contains comprehensive transaction records from a UK-based online retail company, the research focuses on identifying behavioral patterns among consumers. Several key variables, including purchase frequency, total transaction value, and recency or visit time, are processed to create meaningful clusters that represent different types of consumer behavior. The K-Means algorithm is applied through a series of preprocessing steps, such as data cleaning, feature selection, and normalization to ensure accurate clustering results. Once the clusters are formed, each consumer group is analyzed to determine its characteristics, purchasing tendencies, and potential value to the business. The segmentation results provide valuable insights for businesses in developing targeted marketing strategies and personalized service offerings. By understanding the unique preferences and behaviors within each cluster, companies can optimize promotional efforts, improve customer retention, and enhance overall user experience. The findings indicate that data-driven segmentation using the K-Means algorithm is a highly effective approach for gaining deeper, actionable insights into consumer behavior, thereby supporting more strategic decision-making in the e-commerce environment.