ANALISIS KEBUTUHAN WAKTU ALGORITMA INSERTION SORT, MERGE SORT, DAN QUICK SORT DENGAN KOMPLEKSITAS WAKTU - albar Pratama; Anita Desiani; Irmeilyana Irmeilyana (Annual Research Seminar (ARS), 2017)
Sorting is a crucial problem in data processing or database. Data  processing will be more simple if the data has been sorted. Sorting problem requires special  techniques to make the process of sorting faster. The techniques are named as sorting algorithms. The reliability of an algorithm can be measured by its time complexities. The time complexity T(n) is the number of operations performed in an algorithm for N data input. One of time complexities is Big-O or worst case. The Worst case (Big-O) is a time complexities for the worst condition of an algorithm.   This study will analyze the time complexity of the algorithms Insertion Sort, Merge Sort and Insertion Sort based on their Big-O (worst case). Each algorithm will be calculated its complexity time in two ways. The first is calculated based on their steps in sorting process and the second is calculated based on their coding and running program using C++. The time complexity of Merge Sort is O(n log n) and time complexity of Quick Sort and Insertion Sort is O(n2), it means the time complexity of Merge Sort is less and faster for large N data input than Quick Sort and Insertion Sort. Otherwise Insertion Sort is faster for small N data input than Merge Sort and Quick Sort. Quick sort needs much time to sort data not only for small N data input but also for large N data input. It means Quick Sort doesn’t work well in worst case.