Evaluasi Kepuasan Pengguna Sistem Informasi Akademik Dengan Metode End-User Computing Satisfaction (EUCS) Di AMIK Universal

Abstract

In the field of management information systems, data processing efficiency is a critical factor in supporting timely and accurate decision-making. One of the fundamental techniques in data processing is sorting, which organizes data in a specific order to facilitate searching, reporting, and analysis. This study compares the performance of three sorting algorithms—Bubble Sort, Merge Sort, and Quick Sort—in the context of management information system data processing. The research employs a qualitative approach by analyzing the time complexity and space complexity of each algorithm using mathematical analysis and simulation with sample datasets. The results show that Quick Sort has the best average-case performance with O(n log n) time complexity, making it suitable for large-scale data processing in management information systems. Merge Sort offers consistent performance regardless of initial data conditions with O(n log n) time complexity, while Bubble Sort has the highest time complexity of O(n²), making it less efficient for large datasets. The analysis concludes that algorithm selection significantly impacts the performance of management information systems in processing academic, financial, and administrative data.