Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH)
Dina Suci Islamiyati
Universitas Pamulang, Tangerang
Computer Science & IT Decision Sciences, Operations Research & Management

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Penerapan Algoritma Knuth-Morris-Pratt dalam Mendeteksi Tingkat Kemiripan Judul Skripsi Berbasis Web Dina Suci Islamiyati; Ahmad Fikri
Journal of Information System Research (JOSH) Vol 3 No 2 (2022): Januari 2022
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (504.711 KB) | DOI: 10.47065/josh.v3i2.1168

Abstract

In terms of finding the problem topic for thesis titles, students often have difficulty in determining thesis titles, in addition, there may be similarities between students. Manually checking the title requires more effort, for it takes a system to detect the level of similarity in the thesis title. To design and build a thesis title-level detection system using the Knuth-Morris-Pratt algorithm. To find out the percentage of similarities in the title, the Knuth-Morris-Pratt algorithm at the time of matching the string is Enter query of the word to be searched, matching the word arrangement pattern used as an example at the beginning of the text. From left to right, this algorithm will match character per character pattern with characters in the corresponding text, the algorithm then shifts the wording pattern until the word arrangement pattern used as an example is at the end of the text. Based on the analysis, design and implementation of the similarity level detection system of two or more thesis titles using the Knuth Morris Pratt algorithm it can be concluded that: The detection system has been successfully created using the Knuth Morris Pratt algorithm (KMP). It has been obtained the results of analysis by the process of string matching between strings with patterns where the system postulates the results of analysis in the form of the number of word similarities and percentages
Co-Authors Ahmad Fikri