The Implementation of the CNN Method on Smart Image Recognition and Identification of Heritage (SIRIH) of Sundanese Traditional Tools
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Abstract
Sundanese is a regional language in West Java. Young people rarely use local languages, so they need to be preserved by using technology. Image processing technology can help the process of strengthening the Sundanese language and culture. Researchers developed Sundanese traditional tools because their existence is not only related to Sundanese language and terms, but also related to philosophy and local wisdom values. This application is called Smart Image Recognition and Identification of Heritage (SIRIH). The development of this android-based innovative application is based on image recognition technology with the CNN method. Based on the test results, the classification accuracy of pre-trained CNN is 98%, and val accuracy at 86%. Accuracy test results on the application show good and maximum results (90%-100%) if the item is in sufficient light, both indoors and outdoors, while dim light will reduce accuracy to around 60%-70%. Blurred images also affect accuracy by up to 50%.
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