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All Journal Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer
Adi Setiyawan
Fakultas Ilmu Komputer, Universitas Brawijaya
Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Engineering

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Rancang Bangun Sistem Klasifikasi Padi Siap Dipanen dengan Parameter Warna Padi dan Warna Daun menggunakan Metode Random Forest Adi Setiyawan; Dahnial Syauqy; Sabriansyah Rizqika Akbar
Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer Vol 6 No 7 (2022): Juli 2022
Publisher : Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya

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Abstract

Indonesia is an agricultural country, where the agricultural sector has a very important role in improving the national economy. One type of food crop in Indonesia is rice, which currently Indonesian people still use rice as a staple food. The process for planting and caring for rice in Indonesia is currently still less effective and efficient, this has an impact on harvest and post-harvest yields including farmers will lose as much as 20.51% of rice when the harvest time is not right, rice that falls by 9, 52%, rice lost during drying time was 2.13% and the loss during milling was 2.19%. Currently, farmers are still routinely checking the rice fields to see if the rice is ready to be harvested, but farmers have problems checking the paddy fields because erratic weather factors can affect the growth of rice plants. Based on this problem, the authors developed a pre-existing tool using the TCS3200 color sensor to detect the value of leaf color and rice panicle color using the Random Forest method to see whether the rice classification results are ready to be harvested which will be displayed on the 16x2 LCD output and the sound on the buzzer. , so that farmers do not lose their crops due to loss and can get maximum yields. After testing 20 times by inserting the object into the hole on the tool that has been made, the system can detect RGB color values with a low percentage of error. From the results of testing the Random Forest method, the results of the test accuracy are 95% with an average computation time of 38.95ms.
Co-Authors Dahnial Syauqy Sabriansyah Rizqika Akbar