Fresy Nugroho, Puspa Miladin Safitri A. Basid, Yunifa Miftachul Arif, Norizan Mat Diah, Firma Sahrul Bahtiar, Hani Nurhayati, Fachrul Kurniawan, Nurizal Dwi Priandani, Dodik Arwin Dermawan
This paper classifies the simulations of homogeneous synthetic images, heterogeneous synthetic hazy images, and original hazy images taken from CCTV (Close Circuit Television) of Mt. Kelud crater using the GLCM (Gray Level Co-Occurrence Matrix) method. The average feature values obtained using the GLCM (Gray Level Co-Occurrence Matrix) method are used to compare the similarity of gray feature values of the three and then classify thin, medium, and thick images. The results for classifying thin haze, medium haze, and thick haze on the homogeneous synthetic hazy image test data obtained an accuracy value of 50%, a precision value of 46%, and a sensitivity value of 65%. As for the classification of thin, medium, and thick fog on heterogeneous synthetic hazy images, test data obtained an accuracy value of 42%, a precision value of 32%, and a sensitivity value of 48%. © 2023 IEEE.
Universitas Islam Negeri Maulana Malik Ibrahim, Informatics Engineering, Faculty of Science and Technology, Malang, Indonesia; School of Computing Sciences, College of Computing, Informatics and Media, Universiti Teknologi Mara, Shah Alam, Malaysia; Library and Information Science, Universitas Islam Negeri Maulana Malik Ibrahim, Faculty of Science and Technology, Malang, Indonesia; Manajemen Informatika Program Vokasi, Universitas Negeri Surabaya, Surabaya, Indonesia
