Analyzing Malay Stemmer Performance Towards Fuzzy Logic Ranking Function on Malay Text Corpus

Abstract

In a way to make the result of Information Retrieval (IR) more accurate, a stemmer is needed to differentiate the words in searching useful information. This research aims to analyze both processing speed and accuracy of the Malay Language Stemmer such as Fatimah Stemmer and UniSZA Stemmer. This research will also compare the performance of Fuzzy Logic Ranking Function using the both stemmer. Evaluation of Recall and Precision using the relevant judgement list by the expert. The results presented UniSZA Stemmer clearly dominated the Fatimah Stemmer processing speed performance with faster times recorded in each set of the experiment, however, in term of accuracy, unfortunately Fatimah Stemmer has clearly dominated the UniSZA stemming accuracy performance with having much more correct stemmed words for each set of the experiment. The results also showed that Fuzzy Logic Ranking with Fatimah Stemmer has outperformed Fuzzy Logic Ranking with UniSZA Stemmer and English Porter Stemmer on 5 out of 8 Topic Set of query results on the Mean Average Precision measure. Fuzzy Logic Ranking with Fatimah Stemmer also gets the best result on the Precision at Rank 10, Mean Average Precision and the percentage of no relevant document in the top ten retrieved measures, on the topic that has most queries which is topic ‘Umum’ that has a total of 11 queries.