Online Measuring Feature for Batik Size Prediction using Mobile Device: A Potential Application for a Novelty Technology

Abstract

The garment industry, particularly the batik sector, has experienced significant growth in Indonesia, coinciding with a rise in the number of online consumers who purchase batik products through e-Marketplaces. The observed upward trend in growth has seemingly presented certain obstacles, particularly in relation to product alignment and product information dissemination. Typically, batik entrepreneurs originate from micro, small, and medium enterprises (MSMEs) that have not adhered to global norms. Consequently, the sizes of batik products offered for sale sometimes exhibit inconsistencies. The issue of size discrepancies poses challenges for online consumers seeking to purchase batik products through e-commerce platforms. An effective approach to address this issue involves employing a smartphone camera to anticipate body proportions, specifically the length and width of those engaged in online shopping. Subsequently, by the utilization of machine learning techniques, the optimal batik size can be determined. The UKURIN feature was created as a response to a specific requirement. However, it is essential to establish a methodology for investigating the elements that impact the intention to use this feature. This will enable developers to prioritize their feature development strategies more effectively. A total of 179 participants completed an online questionnaire, and subsequent analysis was conducted utilizing the Extended Technology Acceptance Model framework. The findings indicate that Perceived Usefulness emerged as the most influential factor. Consequently, when designing and developing the novelty feature of UKURIN, it is imperative for designers and application developers to prioritize the benefits aspect.