Exploring Meaningful Concepts of Al-Baqarah Chapter Using Text Mining Approach

• Main Authors: Ta'a, Azman, Sudin, Shahrizal
• Format: Conference or Workshop Item
• Language: English
• Published: 2018
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://repo.uum.edu.my/25224/1/KMICE%202018%20194%20199.pdf; http://repo.uum.edu.my/25224/; http://www.kmice.cms.net.my/ProcKMICe/KMICe2018/toc.html
• Institution: Universiti Utara Malaysia

This paper portrays the process of Natural language processing (NLP) to explore the meaningful concept in Al-Baqarah chapter of Al-Quran. Understanding the concept defined from the verses of Al-Quran will help users to learn Al-Quran content. Traditionally, the learner needs help from an Islamic Scholar to determine and understand the concept of Al-Quran verses. However, current tools lack to help user to extract and explore the meaningful concepts of the Al-Qur’an verses. This paper elaborates the using of text mining approach for identifying the meaningful concept such as prophets, messengers and fasting. Essentially, the analysis of meaningful concepts in Al-Baqarah chapter was performed using text mining approach in R Programming. The benchmarking approach has been used to validate the meaningful concepts produced from the analysis. The validation method compared the similarity of meaningful concept with the existing Al-Quran Malay translation text. The results have shown the similarity of meaningful concepts produced from text mining analysis with the existing Al-Quran textbooks.