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All Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JURNAL MAHAJANA INFORMASI Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Brilliance: Research of Artificial Intelligence
M. Hamdani Santoso
Universitas Medan Area
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Library & Information Science Mathematics Other

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Journal : journal of informatics and telecommunication engineering

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Wayang Image Classification Using SVM Method and GLCM Feature Extraction Muhathir Muhathir; M Hamdani Santoso; Diah Ayu Larasati
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 4, No 2 (2021): EDISI JANUARY 2021
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v4i2.4524

Abstract

Wayang is a masterpiece of art that has been able to survive centuries of change and development as a reflection of life for the majority of society. Wayang has a high value because it does not only function as a "entertainment" spectacle, but also has many lessons and life values that can be learned from a wayang show. Puppet itself has various types and forms, and these forms have their own uniqueness, because of the many types of Puppet, many people do not know all the names and types of wayang. Therefore, in this research, we will discuss how to recognize wayang objects based on wayang images using the SVM and GLCM methods as feature extraction. The results showed that the classification of wayang using the SVM (Support Vector Machine) method and the GLCM (Gray Level Co-Occurrence Matrix) feature extraction can recognize wayang objects based on wayang images and classify them quite accurately and a maximum total accuracy of 83.2% is obtained.
Analysis Naïve Bayes In Classifying Fruit by Utilizing Hog Feature Extraction Muhathir Muhathir; Muhammad Hamdani Santoso; Rizki Muliono
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 4, No 1 (2020): ---> EDISI JULI
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (300.115 KB) | DOI: 10.31289/jite.v4i1.3860

Abstract

Indonesia has abundant natural resources, especially the results of its plantations. Lots of local fruit that can be used starting from the root to the skin of the fruit. Local fruit can be consumed as fresh fruit and can also be processed into drinks and food. This is reflected in the diversity of tropical fruits found in Indonesia. Fruits that are rich in benefits and can be used as medicines such as Apples, Avocados, Apricots, and Bananas. These fruits are often found around us. In Indonesia these fruits are produced and also exported abroad. However, the limited methods and technology used to classify this fruit are interesting things to discuss and become the main focus in this research. This study analyzed using the Naïve Bayes algorithm and feature extraction of HOG (Oriented Gradient Histogram) to obtain more effective classification results. The results showed that the collection of fruit using the Naïve Bayes method and HOG feature extraction had not yet obtained maximum classification results, only with an accuracy of 56.52%.Keywords – Apple, Avocado, Apricot, Banana, Naïve Bayes, HOG.
Co-Authors Diah Ayu Larasati Dimas Eka Wuri Dimas Eka Wuri Juanda Hakim Lubis Juanda Hakim Lubis Kori Isabella Hutabarat Muhathir, Muhathir Rizki Muliono