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

Rolliawati, Dwi and Rozas, Indri Sudanawati and Khalid, Khalid and Rozas, Indri Sudanawati (2020) Text Mining Approach for Topic Modeling of Corpus Al Qur'an in Indonesian Translation. In: ICONQUHAS 2018, 2-4 October 2018, Bandung, Indonesia.

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Abstract

Qur’an is a religious text for Moslem 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 is predominantly inhabited by Moslem. Difficulties in understanding the Arabic Quranic text as well as still limited research on the Indonesian translated Quran in accordance to science and technology, have opened a broad challenge to contribute to this realm. This paper proposed topic modelling of corpus in Indonesian Translated Quran by generating four main topics that were closely/firmly related to human life: 1) heaven (surga) and hell (neraka), 2) World (dunia) and Afterlife (akhirat), 3) Science (ilmu), charity (amal) and jihad, 4) Day (siang), night (malam), life (hidup), and death (mati). The moderator variables for this research were defined as Makki and Madani, as terms referring to the revelation location of Quranic verses. In conclusion, the study results hopefully can be benefited as a convincing contribution from science's point of view that Makki’s verses are indeed emphasizing the faith as the foundation of Islam. This can be seen from number frequencies of the words “hidup” (161), “neraka” (157), “surga” (105), “dunia” (127), “amal” which are closely related to human faith in life were mentioned, discussed and elaborated more in Makki's verses than in Madani's.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: component; indonesian translation quran makki madani topic modeling corpus
Subjects: H Social Sciences > H Social Sciences (General)
Depositing User: EAI Editor IV
Date Deposited: 12 Jul 2021 12:49
Last Modified: 12 Jul 2021 12:49
URI: https://eprints.eudl.eu/id/eprint/4598

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