In the agriculture industry, determining the ripeness level of fruits is a very important aspect. This is related to maintaining the quality of the production, and during the distribution process. Currently, human sensory tests are still commonly used to evaluate food products with inconsistent results. This study developed a system to discriminate the durian ripeness level using gas sensors and neural network based on the character of the fruit aroma. This system succeeded in distinguishing the ripeness of durian including unripe, ripe and overripe with performance evaluation values above 91%.

Original languageEnglish
Pages (from-to)677-684
Number of pages8
JournalProcedia Computer Science
Publication statusPublished - 2021
Event6th Information Systems International Conference, ISICO 2021 - Virtual, Online, Italy
Duration: 7 Aug 20218 Aug 2021


  • Agriculture
  • Durian ripeness level
  • Food
  • Gas sensors
  • Neural network


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