Aziz, Faruq
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Penerapan Konsep Finite State Automata Dalam Proses Pendaftaran Kelas Kursus Bahasa Inggris Pada Tempat Kursus Aziz, Faruq; Said, Fadillah; Sudrajat, Adjat
MATICS Vol 12, No 2 (2020): MATICS
Publisher : Department of Informatics Engineering

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/mat.v12i2.9330


Research on website-based test applications for digital course registration in order to make it easier for course institutions to determine classes that are consistent and effective and efficient. This research provides alternative solutions for course institutions for class selection or course program that is suitable for users who will study at the place of the course which is cost-effective and time-consuming too. In this study a course registration application is designed by integrating a website and database to retrieve data after the user has tested. It is intended that users who want to learn English can receive a choice of classes or programs in accordance with their abilities and initial knowledge. This minimizing test instructor errors in determining class and program choices that will be obtained by the user. In this study using the Finite State Automata (FSA) method to discuss the NFA type FSA model can be implemented in the registration process to the user (member) where the course is expected as needed and can better understand how the process of class or program selection is effective and right on target
Segmentation of Mango Fruit Image Using Fuzzy C-Means Marlinda, Linda; Fatchan, Muhamad; Widiyawati , Widiyawati; Aziz, Faruq; Indrarti, Wahyu
Sinkron : jurnal dan penelitian teknik informatika Vol. 5 No. 2 (2021): Article Research Volume 5 Number 2, April 2021
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v5i2.10933


Mango contains about 20 vitamins and minerals such as iron, copper, potassium, phosphorus, zinc, and calcium. The freshness of the ripe mango will taste sweet. The level of ripeness of the mango fruit can be seen from the texture of the skin and skin color. Ripe mangoes have a bright, fragrant color and a smooth skin texture. The problem found in mango segmentation is that the image of the mango fruit is influenced by several factors, such as noise and environmental objects. In measuring the maturity of mangoes traditionally, it can be seen from image analysis based on skin color. The mango peel segmentation process is needed so that the classification or pattern recognition process can be carried out better. The segmented mango image will read the feature extraction value of an object that has been separated from the background. The procedure on the image that has been analyzed will analyze the pattern recognition process. In this process, the segmented image is divided into several parts according to the desired object acquisition. Clustering is a technique for segmenting images by grouping data according to class and partitioning the data into mango datasets. This study uses the Fuzzy C Means method to produce optimal results in determining the clustering-based image segmentation. The final result of Fuzzy C-based mango segmentation processing means that the available feature extraction value or equal to the maximum number of iterations (MaxIter) is 31 iterations, error (x) = 0.00000001, and the image computation testing time is 2444.913636