Sukemi, Sukemi (2019) Identification using the K-Means Clustering and Gray Level Co-occurance Matrix (GLCM) At Maturity Fruit Oil Head. IEEE xplore, - (193427). pp. 1-4. ISSN 978-1-7281-2207-6
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Abstract
This study discusses the identification of its palm fruit camp picture image using K-Means Clustering and identification GLCM. Process fruits traditionally experienced constrained due to human nature that has flaws that the desired results are not effective. Advances in computer technology have come into the world in terms of the farm before harvest and post-harvest. This Dimolished how to recognize the fruit so that it correspond to real conditions. Condition of oil palm fruit is determined by the level of maturity in terms of color, texture and shape of the oil palm fruit. Identification which did classify in the category of mature and not mature. Determination of identification with the K-means clustering method that uses the difference in euclidean distance and GLCM feature extraction as a reference. For the results of the present study is equal to 90% of the 50 test data.
| Item Type: | Article |
|---|---|
| Subjects: | Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation. |
| Divisions: | 09-Faculty of Computer Science > 56201-Computer Systems (S1) |
| Depositing User: | Dr. Sukemi Sukemi |
| Date Deposited: | 18 Jan 2022 05:59 |
| Last Modified: | 18 Jan 2022 05:59 |
| URI: | http://repository.unsri.ac.id/id/eprint/60624 |
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