Management of Traditional Business into Modern: from Microsoft Excel to Deep Learning for prototyping classification Swiftlet’s nests

Authors

  • Hanna Arini Parhusip Fakultas Sains dan Matematika, Universitas Kristen Satya Wacana , Jl.Diponegoro 52-60, 50711, Salatiga, Jawa Tengah, Indonesia
  • Suryasatriya Trihandaru Fakultas Sains dan Matematika, Universitas Kristen Satya Wacana , Jl.Diponegoro 52-60, 50711, Salatiga, Jawa Tengah, Indonesia https://orcid.org/0000-0002-7147-1673
  • Kristoko Dwi Hartomo Fakultas Sains dan Matematika, Universitas Kristen Satya Wacana , Jl.Diponegoro 52-60, 50711, Salatiga, Jawa Tengah, Indonesia https://orcid.org/0000-0003-0237-851X
  • Karina Bianca Lewerissa Fakultas Sains dan Matematika, Universitas Kristen Satya Wacana , Jl.Diponegoro 52-60, 50711, Salatiga, Jawa Tengah, Indonesia https://orcid.org/0009-0006-4545-6804
  • Linda Ariany Mahastanti Fakultas Sains dan Matematika, Universitas Kristen Satya Wacana , Jl.Diponegoro 52-60, 50711, Salatiga, Jawa Tengah, Indonesia https://orcid.org/0000-0002-2827-9192
  • Djoko Hartanto PT Waleta Asia Jaya, Dukuh Canden RT 07 RW 03 Kutowinangun, Sidorejo Lor, Tingkir, 50742, Salatiga, Jawa Tengah, Indonesia

DOI:

https://doi.org/10.51601/ijcs.v4i2.268

Abstract

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.

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Published

2024-05-25

How to Cite

Arini Parhusip, H., Trihandaru, S., Hartomo, K. D., Bianca Lewerissa, K., Ariany Mahastanti, L. ., & Hartanto, D. . (2024). Management of Traditional Business into Modern: from Microsoft Excel to Deep Learning for prototyping classification Swiftlet’s nests. International Journal Of Community Service, 4(2), 123–132. https://doi.org/10.51601/ijcs.v4i2.268

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