Open AccessPerformance Analysis of Hashing Methods on the Employment of App
Author(s) -
Anton Yudhana,
Abdul Fadlil,
Eko Prianto
Publication year - 2018
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v8i5.pp3512-3522
Subject(s) - computer science , linear hashing , hash table , hash function , quotient , dynamic perfect hashing , universal hashing , process (computing) , value (mathematics) , double hashing , data mining , mathematics , computer security , operating system , machine learning , pure mathematics
The administrative process carried out continuously produces large data. So the search process takes a long time. The search process by hashing methods can save time faster. Hashing is methods that directly access data in a table by making references to the key that hashing becomes the address in the table. The performance analysis of the hashing method is done by the number of 18 digit character values. The process of analysis is done on applications that have been implemented in the application. The algorithm of hashing method analyzed is progressive overflow (PO) and linear quotient (LQ). The main purpose of performance analysis of hashing method is to know how gig the performance of each method. The results analyzed showed the average value of collision with 15 keys in the analysis of 53.3% yield the same value, while 46.7% showed the linear quotient has better performance.