Publication:
Comparative Study of Machine Learning Approach on Malay Translated Hadith Text Classification based on Sanad

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dc.ConferencecodeUniv Tun Hussein Onn Malaysia, Fac Mech & Mfg Engn
dc.ConferencedateJUL 22-23, 2017
dc.ConferencelocationLangkawi, MALAYSIA
dc.Conferencename8th International Conference on Mechanical and Manufacturing Engineering (ICME)
dc.contributor.authorRahifah, Sen_US
dc.contributor.authorNajib, Men_US
dc.contributor.authorAbd Rahman, Nen_US
dc.contributor.authorIsmail, NKen_US
dc.contributor.authorAlias, Nen_US
dc.contributor.authorNor, ZMen_US
dc.contributor.authorAlias, MNen_US
dc.date.accessioned2024-05-29T02:49:37Z
dc.date.available2024-05-29T02:49:37Z
dc.date.issued2017
dc.description.abstractSanad is one of important part used to determine the authentication of hadith. However, very little research work has been found on classification of Malay translated Hadith based on sanad. There are some researches done using machine learning approach on hadith classification based on sanad but using different objective with different language. This research is to see how Machine Learning techniques are used to classify Malay translated Hadith document based on sanad. In this paper, SVM, NB and k-NN are used to identify and evaluate the performance of Malay translated hadith based on sanad. The performances are evaluated based on standard performance metrics used in text classification which is accuracy and response time. The results show that SVM has the highest accuracy and k-NN has the best response time (time taken in process for classification data) compare to other classifier. In future, we plan to extend this paper with the analysis on interclass similarity and also test on larger dataset.
dc.identifier.doi10.1051/matecconf/201713500066
dc.identifier.issn2261-236X
dc.identifier.scopusWOS:000461100400063
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/10886
dc.identifier.volume135
dc.languageEnglish
dc.language.isoen_USen_US
dc.publisherE D P SCIENCESen_US
dc.sourceWeb Of Science (ISI)
dc.sourcetitle8TH INTERNATIONAL CONFERENCE ON MECHANICAL AND MANUFACTURING ENGINEERING 2017 (ICME'17)
dc.titleComparative Study of Machine Learning Approach on Malay Translated Hadith Text Classification based on Sanaden_US
dspace.entity.typePublication

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