Kersen fruit, native to Southern Mexico and often found in Indonesia, has health benefits that attract people. It is round with a diameter of 1-1.5 cm, yellowish green in color when young, and turns red when ripe. Determining the maturity level of kersen, which has been done manually, is essential for people to consume good quality fruit. This study aims to simplify the identification of Kersen fruit maturity through image processing using the Support Vector Machine (SVM) method with a parameter value of C-25. The test results show that this method achieves the best accuracy level of 72% in identifying the ripeness of kersen fruit, so it can be an effective solution in making it easier for people to determine the level of fruit ripeness.
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