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All Journal Jurnal Komputer, Informasi dan Teknologi
Putra, Erwin Dwik
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Computer Science & IT Electrical & Electronics Engineering

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Journal : Jurnal Komputer, Informasi dan Teknologi

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Classification Of Besurek Batik Fabrics Using Gray Level Co-Occurrence Matrix (GLCM) Features Extraction Ma’ruf, M. Taufik; Putra, Erwin Dwik; Reswan, Yuza; Juhardi, Ujang
Jurnal Komputer, Informasi dan Teknologi Vol. 3 No. 2 (2023): Desember
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v3i2.1211

Abstract

Besurek Batik is a characteristic of Bengkulu province, Besurek motifs are Rafflesia, Calligraphy, Paku Niches, Moon, Kuau Bird, and Jasmine. Besurek batik has high complexity in its manufacture and has many different types of motifs, therefore the identification of Besurek cloth in Bengkulu Province makes it easier to classify batik motifs and can also be an effort to preserve the culture of Bengkulu province. A feature extraction and method are used to classify Besurek type images of Bengkulu province using feature extraction Gray Level Co-Occurrence Matrix (GLCM) where glcm is used for feature extraction analysis, then classified using the K-Nearest Neighbor Algorithm (KNN). Based on the results of the analysis obtained from the Besurek motif, namely with an accuracy value of 0.93333, a recall of 0.93333 and a precision value of 0.94444 with an average value of 0.938856 at an angle of 1350.
Human Object Counter Tracking Using Connected Component Labelling On Digital Image Processing Lestari, Fitri; Putra, Erwin Dwik; Sonita, Anisya; Darnita, Yulia
Jurnal Komputer, Informasi dan Teknologi Vol. 3 No. 2 (2023): Desember
Publisher : Penerbit Jurnal Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53697/jkomitek.v3i2.1218

Abstract

Object tracking is usually used to determine the position of objects and environmental conditions around these objects. Objects that require supervision in order to run properly require a system to monitor the object. Every movement of the object will be known directly through the camera image. So in this study a system was created to detect and track objects. Implementing an object detection system based on image processing using the connected component labeling method. Then displaying the detection results on the divided image frame. Moving object detection and tracking The algorithm used to detect and track moving objects is connected component labeling. Based on the analysis of the workings of the connected component labeling algorithm for detecting and tracking moving objects using video, it can be concluded that the connected component labeling algorithm has succeeded in tracking and labeling each object based on the position and number of objects, even though they look erratic, in human movement.
Co-Authors Darnita, Yulia Fitri Lestari, Fitri Juhardi, Ujang Ma’ruf, M. Taufik Sonita, Anisya Yuza Reswan