Al Quran is a divine text which represents the purest and most authentic form of the classical Arabic language. To understand the meaning of each verse, a deep knowledge of Arabic linguistic is essential. Therefore, our scholars have made their efforts by engaging themselves in the works of explaining al Quran's words, interpreting its meanings into Arabic and other languages. Currently, more people are interested in knowing the content of al-Quran, especially for non-Muslim, after 9/11 tragedy. Thus, a flexible model that can represent Qur'anic concept is required for people to understand the content of the Quran. In this research, we propose a Multi-Relational Latent Morphology-Semantic Analysis Model (MORPHOSEM) based on a combination of Arabic Semantic and six multiple relations between words, which are synonym, antonym, hypernym, hyponym, homonym and meronym, to precisely extract Qur'anic concept. The existing literatures focus only on very limited relationships between words which could not extract the in-depth concept of Qur'anic without considering the importance Arabic Semantic. Therefore, the objectives of this research are: (1) to analyses and categorize Quranic words according to Arabic Semantic patterns, (2) to propose a new model for extracting Quranic concept using MORPHOSEM, (3) to investigate semantic relationships between Qur'anic words, and (4) to validate the proposed model with Arabic linguistic, and Qur'anic experts. This research will be conducted qualitatively through content analysis approach a new innovative technological technique. It is expected that the model will come out with a precise analysis for extracting Qur'anic concept. This will be very significant in enhancing the overall Quran's understanding among the society in Malaysia and Muslim's world for sustainable society.