Aplikasi untuk Deteksi dan Klasifikasi Motif Kain Tenun Timor Tengah Selatan berbasis ANFIS pada Platform Mobile di Provinsi NTT Application for Detection and Classification of South Central Timor Woven Fabric Motifs Based on ANFIS on a Mobile Platform in NTT Province
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2293-2311
Digital Object Identifier:
10.58578/masaliq.v5i5.7052
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Authors:Okthen Orlanda Naitboho1*, Ni Ketut Kertiasih2, Agus Aan Jiwa Permana3
Copyright :Authors retain copyright and grant the journal right of first publication.
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Abstract
The woven fabric from South Central Timor (TTS), East Nusa Tenggara Province, holds significant cultural and symbolic value; however, the influx of similar-patterned fabrics from outside the region presents challenges in authenticity identification, particularly among the general public and younger generations. This study aims to develop a mobile application based on the Adaptive Neuro-Fuzzy Inference System (ANFIS) to detect and classify motifs of TTS woven fabric. Texture feature extraction was conducted using the Gray Level Co-occurrence Matrix (GLCM) method, applying six key parameters: contrast, dissimilarity, homogeneity, energy, correlation, and ASM. The ANFIS model was trained for two types of classification: fabric authenticity (authentic vs. non-authentic), achieving an average accuracy of 87.50%, and regional motif classification (Amanatun, Amanuban, and Mollo), with an accuracy of 78.00%. The application was developed using a prototyping method and integrated with the classification system via FastAPI services. Black-box testing confirmed that all application features functioned as designed, while usability testing using the Usability Metric for User Experience (UMUX) yielded a score of 87.92, indicating a high level of user comfort and ease of use. The study concludes that the ANFIS-based mobile application is effective as a supporting tool in preserving TTS woven fabric through the application of intelligent technology.
Keywords: Mobile Application; TTS Woven Fabric; ANFIS; GLCM Texture Extraction; Image Classification
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