Algoritma Pemograman : Kunci Efisiensi Dalam Pengelolaan Data Besar

Abstract

This research aims to explain the key role of programming algorithms in improving the efficiency of big data processing. This abstract will discuss the methods used in the research, the results obtained, and the implications of the findings. This research uses an analytical and experimental approach to study various types of programming algorithms used in big data processing. Data collection methods involve literature review and experiments with representative datasets. The results show that selecting the right programming algorithm can significantly improve the efficiency of big data processing. Efficient sorting algorithms, such as merge sort and quick sort, can sort data with a time complexity of O(n log n). In addition, machine learning algorithms have also proven effective in analyzing and making decisions based on big data. The implications of these findings are that the use of the right programming algorithms can optimize big data processing in various fields, such as business, education, and research. By implementing efficient programming algorithms, organizations can save time, resources, and improve decision-making quality.