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All Journal Scientica: Jurnal Ilmiah Sains dan Teknologi
Nanang Mahrozi
Universitas Islam Negeri Maulana Malik Ibrahim, Malang, Indonesia
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Social Sciences Other

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ANALISIS PERBANDINGAN KECEPATAN ALGORITMA SELECTION SORT DAN BUBBLE SORT Nanang Mahrozi; Muhammad Faisal
Scientica: Jurnal Ilmiah Sains dan Teknologi Vol. 1 No. 2 (2023): Scientica: Jurnal Ilmiah Sains dan Teknologi
Publisher : Komunitas Menulis dan Meneliti (Kolibi)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.572349/scientica.v1i2.209

Abstract

Algorithms play a crucial role in software development and programming. Many programming paradigms have been developed to understand the basic concepts of algorithms, both general and specific. Data processing is essential in the sorting algorithm, especially in the context of selection sort and bubble sort. Both algorithms are designed to sort data with integer types. Each type of algorithm has different levels of effectiveness. The effectiveness of an algorithm can be measured based on the time and memory space needed to execute it. An efficient algorithm is one that optimizes the use of time and space minimally. The fewer resources needed to run an algorithm, the more effective it is considered. It is important to note that the time and space required by an algorithm are influenced by the amount of data processed and the type of algorithm applied, which is the main focus of this article, with an emphasis on the time complexity of various types of algorithms. The algorithms described in this study are implemented using the Python programming language in the Google Colab environment. Referring to the logic of the data sorting process using algorithms such as Selection Sort and Bubble Sort, it can be concluded that the selection sort algorithm has a speed advantage over bubble sort, as evidenced by testing with 100-100,000 data where selection sort is consistently faster.
Co-Authors Muhammad Faisal