Text Mining Approach for Topic Modeling of Corpus Al Qur'an in Indonesian Translation

The Qur’an is the religious text for Muslims that is revealed to humanity as a guide to solve any problems in all aspects of life. Therefore Quranic text is widely translated in various countries around the world, including in Indonesia which predominantly by Muslim. Difficulties in understanding the Quranic text in Arabic as well as the limited research on the Indonesian translation Quran related to science and technology, have opened a broad challenge to contribute to this realm. This paper proposed topic modelling of corpus in Indonesian Translation Quran by generated four main topics that are firmly related to human life, such as 1) heaven (surga) and hell (neraka), 2) The world (dunia) and the hereafter (akhirat), 3) Science (ilmu), charity (amal), and jihad, 4) Day (siang), night (malam), life (hidup), and death (mati). Those four topics were related to the moderator variables associated with the revelation location of Quranic verses (Makki and Madani). Of all the modeling topics tested by word count, Makki's Surahs contributes above 50% compared to Madani's Surahs. So the study results can be a reinforcement from the science's point of view that Makki verses were indeed emphasizing the faith as the foundation of Islam. This can be seen from the frequencies numbers that indicate the words “hidup” (161), “neraka” (157), “surga” (105), “dunia” (127), “amal” which is closely related to the human faith during their life in the world was discussed more in Makki's verses than Madani's.