KLASIFIKASI KUALITAS INDEX UDARA DUNIA DENGAN METODE ARTIFICIAL NEURAL NETWORK DAN SUPPORT VECTOR MACHINE KERNEL RBF
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Abstract
Air pollution has become a significant problem worldwide, and air quality must be addressed to prevent physiological disorders and respiratory-related deaths. This study examines how two machine learning algorithms, Artificial Neural Network (ANN) and Support Vector Machine (SVM), function to provide insights into machine learning algorithms for addressing air pollution worldwide. The results show that ANN achieved perfect accuracy, while Support Vector Machine (SVM) with RBF kernel attained 0.99 accuracy. The main objective of this research is to predict the air quality index worldwide.
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[1] D. Fang, B. Chen, K. Hubacek, R. Ni, L. Chen et al,“Clean air for some: Unintended spillover effects of regional air pollution policies,” Science Advances, vol. 5, no. 4, pp. 4707–4731, 2019.
[2] D. A. Glencross, T. R. Ho, N. Camiña, C. M. Hawrylowicz and P. E. Pfeffer, “Air pollution and its effects on the immune system,” Free Radical Biology and Medicine, vol. 151, pp. 56–68, 2020.
[3] A.Y. Sun B.R. Scanlon How can big data and machine learning benefit environment and water management: a survey of methods, applications, and future directions, Environ. Res. Lett. 14 (7) (Jul. 2019), 073001
[4] M. Bagheri, A. Akbari, S.A. Mirbagheri, Advanced control of membrane fouling in filtration systems using artificial intelligence and machine learning techniques: a critical review, Process Saf. Environ. Prot. 123 (Mar. 2019) 229–252
[5] F. Hassanpour, S. Sharifazari, K. Ahmadaali, S. Mohammadi, Z. Sheikhalipour, Development of the FCM-SVR hybrid model for estimating the suspended sediment load, KSCE J. Civ. Eng. 23 (6) (Jun. 2019) 2514–2523
[6] X. Li, L. Jin, and H. Kan, ‘‘Air pollution: A global problem needs local fixes,’’ Nature, vol. 570, no. 7762, pp. 437–439, Jun. 2019.
[7] Y. Ding and Y. Xue, ‘‘A deep learning approach to writer identification using inertial sensor data of air-handwriting,’’ IEICE Trans. Inf. Syst., vol. E102-D, no. 10, pp. 2059–2063, 2019
[8] M. Jia, A. Komeily, Y. Wang, and R. S. Srinivasan, ‘‘Adopting Internet of Things for the development of smart buildings: A review of enabling technologies and applications,’’ Automat. Construct., vol. 101, pp. 111–126, May 2019.
[9] L. A. Demidova, "Two‐stage hybrid data classifiers based on svm and knn algorithms," symmetry, vol. 13, no. 4, p. 32, 2021.
[10] M. Nurkholifah, Jasmarizal, Y. Umar, and Rahmaddeni, “ANALISA PERFORMA ALGORITMA MACHINE LEARNING DALAM PREDIKSI PENYAKIT LIVER,” Jurnal Indonesia: Manajemen Informatika dan Komunikasi, vol. 4, no. 1, pp. 164–172, Jan. 2023.
[11] N. Yolanda Paramitha et al., “Klasifikasi Penyakit Stroke Menggunakan Metode Naïve Bayes,” 2023.
[12] A. Putri, C. Syaficha Hardiana, E. Novfuja, F. Try Puspa Siregar, Y Fatma, and R.Wahyuni, “Comparison of K-NN, Naive Bayes and SVM Algorithms for Final-Year Student Graduation Prediction KomparasiAlgoritma K-NN, Naive Bayes dan SVM untuk Prediksi KelulusanMahasiswa Tingkat Akhir,” Institut Riset dan Publikasi Indonesia (IRPI) MALCOM Indonesian Journal of Machine Learning and Computer Science Journal Homepage, vol. 3, no. 1, pp. 20–26, 2023.
[13] D. Septhya, K. Rahayu, S. Rabbani, V. Fitria, Y. Irawan, and R. Hayami, “MALCOM: Indonesian Journal of Machine Learning and Computer Science Implementation of Decision Tree Algorithm and Support Vector Machine for Lung Cancer Classification Implementasi Algoritma Decision Tree dan Support Vector Machine untuk Klasifikasi Penyakit Kanker Paru,” vol. 3, pp. 15–19, 2023.
[14] S. S. T. E. A. R., A. N. Ade Silvia Handayani1, “KLASIFIKASI KUALITAS UDARA DENGAN METODE SUPPORT VECTORMACHINE,” JIRE (Jurnal Informatika & Rekayasa Elektronika), 2020.
[15] R. abibah br Lumbantobing, “Prediksi Harga Cryptocurrency Menggunakan Algoritma Support Vector Machine,” 2023.
[16] J. I. Matematika and S. Adi, “MATHunesa Tahun 2022 KOMPARASI METODE SUPPORT VECTOR MACHINE (SVM), K-NEAREST NEIGHBORS (KNN), DAN RANDOM FOREST (RF) UNTUK PREDIKSI PENYAKIT GAGAL JANTUNG Atik Wintarti”.
[17] A. M. Siregar and H. H. H, “Implementasi Algoritma Neural Network untuk Mendukung Keputusan di Desa Tamanmekar,” Petir, vol. 13, no. 1, pp. 21–32, 2020, doi: 10.33322 petir v13i1.768.
[18] Purba Daru Kusuma, “Machine Learning Teori, Program, Dan Studi Kasus”, ISBN 9786230210839, 6230210835, 2020.
[19] Irkham Widhi Saputro, Bety Wulan Sari, “Uji Performa Algoritma Naive Bayes untuk Prediksi Masa Studi Mahasiswa”, Citec Journal, Vol. 6, No. 1 ISSN: 2460-4259, Universitas AMIKOM Yogyakarta, 2019.
[20] Charles R Harris, K. Jarrod Millman, Stefan J. van der Walt, dll “Array programing with Numpy”, ISSN 14764687, 2020.