Management of Traditional Business into Modern: from Microsoft Excel to Deep Learning for prototyping classification Swiftlet’s nests - Hanna Arini Parhusip; Suryasatriya Trihandaru; Kristoko Dwi Hartomo; Karina Bianca Lewerissa; Linda Ariany Mahastanti; Djoko Hartanto (CV. Inara in Colaboration with www.stie-sampit.ac.id, 2024)
In this article, the transformation of traditional management of Swiftlet’s nests into modern business is proposed. Traditional business means that data management of Swiftlet’s nests is done manually, sorted by recording in Microsoft Excel. This is done by PT Waleta Asia Jaya, a company engaged in processing Swiftlet’s nests. This sorting is done because the number of feathers in the Swiftlet’s nests determines the price and cost of workers in processing feather cleaning. In addition, the shape of the Swiftlet’s nests needs attention. However, because it is complex, sorting is done simpler. Originally, Swiftlet’s nests were sorted into 50 categories. To facilitate sorting, deep learning is used with the SSD Mobile Net V2 algorithm as an algorithm to classify into 7 categories based on feather intensity. The device is still a prototype that shows an 85% accuracy rate but has been quite helpful in the process of purchasing Swiftlet’s nests before processing.