The Quran is a Muslim holy book that consists of 6236 ayat or verses which divides into 144 surahs or chapters. In each chapter, there are many entities scattered in each verse. For a person, finding a particular entity will be difficult without a classification process, Resulting in difficulties in understanding the Quran. A system can be modeled to extract the information on entities in the Quran to solve this problem. Therefore, we want to offer a method to identify and classify entities using Entity recognition. The system will use the SVM techniques where the system will be given various entities from the Quran as an input to be able to identify correct entities. We are using the dataset obtained from website tanzil.net consists of 19.473 tokens and 720 entities. The classification scenario using a linear kernel with unigram produces the highest f-measure value of 0.75.