PENERAPAN ORANGE DATA MINING UNTUK PEMBELAJARAN SISTEM MANUFAKTUR DISKRIT PADA KASUS KLASIFIKASI DAN KLASTERISASI GAMBAR HEWAN BERBASIS MACHINE LEARNING
DOI:
https://doi.org/10.36761/hexagon.v6i2.5144Keywords:
Industry 4.0, Orange Data Mining, Machine Learning, Classification, Clustering, CRISP-DMAbstract
Politeknik ATI Makassar has introduced technologies such as Artificial Intelligence, Internet of Things, and Big Data Analytics in the Discrete Manufacturing Systems course. This research focuses on the application of Data Science using the Orange Data Mining application for the classification and clustering of animals. The adopted experimental method involves controlling variables by following the CRISP-DM methodology. Evaluation results indicate that the logistic regression model is the best, with an AUC accuracy of 1 and a precision of 0.962. Clustering resulted in two clusters: C1 for cats and C2 for cows, with a silhouette score of 0.145. This research demonstrates the effectiveness of the Orange Data Mining application in teaching discrete manufacturing systems based on machine learning.
References
AJDA. (2017, April 3). (University of Ljubljana) Retrieved from https://orangedatamining.com/blog/image-analytics-clustering/
Alwi, M. N. (2024, Juni 19). (Dicoding) Retrieved from https://dicoding.com/blog/crisp-dm-tahapan-studi-kasus-kelebihan-dan-kekurangan/
Feby , D. (2022, Desember 6). (DQLab) Retrieved from https://dqlab.id/kenali-tools-data-science-terbaik-untuk-data-mining
Hozairi, Anwari, & Alim, S. (2021). Implementasi Orange Data Mining untuk Klasifikasi Kelulusan Mahasiswa Dengan Model k-Nearest Neighbor, Decision Tree serta Naive Bayes. Jurnal Ilmiah NERO, 6(2), 133-144.
Mujiyono, Simarmata, M. K., Mustofa, Agus, M., Heriyanto, L., Siregar, M. T., & Lutfi. (2021). TRANSFORMASI INDUSTRI 4.0 MANUFAKTUR DISKRIT. Jakarta Selatan: Pusat Pengembangan Pendidikan Vokasi Industri Badan Pengembangan Sumber Daya Manusia Industri Kementerian Perindustrian Republik Indonesia.
Nantasenamat, C. (2020, Juli 28). Retrieved from https://towardsdatascience.com/the-data-science-process-a19eb7ebc41b
Pusdiklat Kominfo. (2024, juli 15-19). (Digitalent) Retrieved from https://digitalent.kominfo.go.id/pelatihan/8856
Wiguna, R. R., & Rifai, A. I. (2021). Analisis Text Clustering Masyarakat Di Twitter Mengenai Omnibus Law Menggunakan Orange Data Mining. Journal of Information Systems and Informatics, 3(1), 1-12. Retrieved from http://journal-isi.org/index.php/isi
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