Boosting Stemmer Performance Using Cache Method

Abstract

Stemming is the process of returning the word to the base word by disappearing the append. This is important to support better information re-meeting. Some research in stemming algorithms includes nazief &adriani algorithms, confix stripping, enhanced confix stripping, arifin and porter algorithms. The stemming algorithm for Bahasa Indonesia is divided into two, namely those that use a dictionary and do not use a dictionary. Some studies have shown that stemmers that use dictionary have high accuracy but low process speed, while stemmers that do not use dictionary have low accuracy but higher process speed. In this study, two methods were used: the stemmer method using cache and stemmer without cache to see the comparison of process speed from stemmers that use dictionary. The test data for this study is text data obtained from the corpus site. Process analysis is completed by calculating each speed, memory usage and cpu of each method, then each method is compared. Results from tests from test data showed that the cache method improved stemmer performance.