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Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi)
Published by Lembaga Komunitas Informasi Teknologi Aceh
ISSN : -     EISSN : 25801643     DOI : https://doi.org/10.35870/jtik
Core Subject : Science, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi), e-ISSN: 2580-1643 is a free and open-access journal published by the Research Division, KITA Institute, Indonesia. JTIK Journal provides media to publish scientific articles from scholars and experts around the world related to Hardware Products, Software Products, IT Security, Mobile, Storage, Networking, and Review An application service. All published article URLs will have a digital object identifier (DOI).
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 722 Documents
 69   70   71   72   73 
Identification of Flower Type Images Using KNN Algorithm with HSV Color Extraction and GLCM Texture Poerwandono, Edhy; Taufik, M. Endang
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 3 (2025): JULI-SEPTEMBER 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i3.3826

Abstract

Due to the variety of types of flowers that exist and having and tracking each variety, making plant lovers and cultivators difficult to distinguish in determining the type of flower, it takes a very long time to find out the type of flower if you only rely on the five senses. With the application of the K-Nearest Neighbor algorithm and feature extraction of color and texture, it is very helpful in image processing to identify flowers more easily and shorten the time, with the greatest accuracy of 71% using the K-7 value, the flower was successfully carried out.
Prediksi Motif Batik dengan Menggunakan Metode Gabor Filter Convolution Neural Network Bili, Yudisman Ferdian; Tundo; Sutisna, Nandang; Putri, Atsilah Daini; Yuliantoro, Dita Tri; Nurmayanti, Laily
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 9 No 3 (2025): JULI-SEPTEMBER 2025
Publisher : Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v9i3.3798

Abstract

This research aims to develop a batik motif classification system by utilizing Convolutional Neural Network (CNN) and Gabor Filter, in order to increase accuracy in texture feature extraction. The batik dataset used goes through a preprocessing stage, which includes normalization and data augmentation. During training, the model was tested with 10,000 iterations, using the Adam optimizer and the Categorical Cross-Entropy loss function, and evaluated via a confusion matrix. Test results show accuracy reaching 87%, with a precision and recall value of 90% each, and an F1-score of 89%. This method has proven effective for classifying batik motifs and has the potential to be applied in the fields of education, textile industry and cultural preservation.

Page 73 of 73 | Total Record : 722

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