Application of Convolutional Neural Network Using TensorFlow as a Learning Medium for Spice Classification

  • Muhammad Naufal Adi Saputro Universitas Sebelas Maret
  • Febri Liantoni Universitas Sebelas Maret
  • Dwi Maryono Universitas Sebelas Maret

Abstract

The purpose of this research are: (1) To determine the accuracy of the CNN method in the development of a website for classifying spices, (2) To assess the feasibility of the spice classification website as a learning medium, (3) To ascertain user responses to the spice classification website as a learning medium. The method employed in this research is research and development. This study utilizes the ADDIE development method, which comprises 5 stages: (1) Analysis, (2) Design, (3) Development, (4) Implementation, and (5) Evaluation. The research yielded a significantly high accuracy rate. This is demonstrated by the results showing an accuracy of 96%, precision of 97%, and recall of 96%. Moreover, the research found the developed website to be feasible. This is supported by the evaluation using the Learning Object Review Instrument (LORI), resulting in a score of 88% from media experts and a score of 90% from subject matter experts. Additionally, user response was positive. This is evidenced by testing the learning media on 10th-grade culinary students from SMK N 4 Surakarta, which yielded a score of 76% using the System Usability Scale (SUS), indicating a favorable usability assessment. In conclusion, the spice classification website, as a learning medium, can be employed as a suitable educational tool.

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Published
2024-07-01
How to Cite
Saputro, M., Liantoni, F., & Maryono, D. (2024). Application of Convolutional Neural Network Using TensorFlow as a Learning Medium for Spice Classification. Ultimatics : Jurnal Teknik Informatika, 16(1), 8-15. https://doi.org/https://doi.org/10.31937/ti.v16i1.3304