Extracting meaningful concept of Al-Quran using text mining approach: a case study on al-Baqarah chapter

This project portrays the process of Natural language processing (NLP) of text mining using analytic programming language to extract the term or concept in Al-Quran. Understanding the concept defined from the verses of Al-Quran will help users to learn Al-Quran in more faster. The current Al-Qur’an learning approach is using conventional method that needs help from an Islamic Scholar ‘ULAMA’ to facilitate user to understand the concept of verses in the Al-Qur’an in easy manner. Obviously, the scholar relies on his personal knowledge and familiarity of the Qur’an contents. However, there is a lack of computational tools to help the reader to capture and understand the concepts inside the verse of the Al-Qur’an. Therefore, using text mining approach, it can support the process of identifying the meaningful concept behind the verses (e.g., Prophets, Messengers and fasting). This project elaborate the details of the task in different perspective by looking at the problem statement, objectives, research methodology, expected outcomes and significance of the output. Essentially, the extracting and evaluation of text analysis approach has been done by using powerful analytic programming language called R. The benchmarking method has been used to validate the result of this project that based on similarity of concept produced from the NLP process with the concept determined by the existing Al-Quran textbook published from two different publishers. The NLP process that based on unigram technique has successful produced the meaningful concepts of Al-Baqarah chapter, which is has the similarity with the concepts determined by the Al-Quran textbooks.