Implementasi Algoritma Convolutional Neural Network Dan Linear Regresi Untuk Memprediksi Kebakaran Hutan

Authors

  • Fajar Sodik Yogyakarta AMIKOM University
  • Ahmad Sanusi Mashuri Yogyakarta AMIKOM University
  • Syaiful Huda Universitas Amikom
  • Kusrini Kusrini Universitas Amikom
  • Khusnawi Khusnawi Universitas Amikom

DOI:

https://doi.org/10.31154/cogito.v9i1.401.28-37

Keywords:

Kebakaran Hutan, Convolutional Neural Network, Linear Regresi

Abstract

Kebakaran hutan dan lahan merupakan salah satu masalah lingkungan dalam hal ekonomis dan ekologis yang merugikan. Jumlah hotspot kebakaran hutan dia Provinsi Jawa Timur telah meningkat secara dramatis menyebabkan kabut asap yang berbahaya. Penelitian ini bertujuan untuk mengklasifikasi kebakaran hutan dan lahan di Kabupaten Kediri Jawa Timur. Model klasifikasi kebakaran hutan menggunakan algoritma Convolutional Neural Network dan Linier Regresi. Atribut yang digunakan untuk klasifikasi terdiri dari suhu dan api. Klasifikasi suhu menghasilkan nilai Mean Precentage Absolute Error pada algoritma regresi Linear sebesar 3% dan akurasi 90% pada algoritma Convolutional Neural Network. Dengan demikian, dapat disimpulkan bahwa model klasifikasi menggunakan Convolutional Neural Network dan Linier Regresi memiliki potensi untuk digunakan secara efektif sehingga dapat membantu pihak berwenang dalam mencegaha kebakaran hutan dan lahan.

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Published

2023-06-30

How to Cite

Sodik, F., Mashuri, A. S., Huda, S. ., Kusrini, K., & Khusnawi, K. (2023). Implementasi Algoritma Convolutional Neural Network Dan Linear Regresi Untuk Memprediksi Kebakaran Hutan. CogITo Smart Journal, 9(1), 28–37. https://doi.org/10.31154/cogito.v9i1.401.28-37

Issue

Vol. 9 No. 1 (2023): Cogito Smart Journal

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Articles

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