Klasifikasi Status Erupsi Gunung Berapi dengan menggunakan Analisa Template Matching dan Algoritma KNN. (Classification of Volcano Eruption Status Using Template Matching Analysis and the KNN Algorithm).

Arizona, Lintang Ragadanu (2023) Klasifikasi Status Erupsi Gunung Berapi dengan menggunakan Analisa Template Matching dan Algoritma KNN. (Classification of Volcano Eruption Status Using Template Matching Analysis and the KNN Algorithm). Undergraduate thesis, Universitas 17 Agustus 1945 Surabaya.

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	Text LOA_Mandita et al. _ KLASIFIKASI STATUS ERUPSI GUNUNG BERAPI DENGAN MENGGUNAKAN ANALISA TEMPLATE MATCHING DAN ALGORITMA KNN _ INSERT _ Information System and Emerging Technology Journal.pdf Download (108kB)

Abstract

One type of geological disaster that often occurs in Indonesia is a volcanic eruption. Because Indonesia has many active volcanoes with different eruption types and statuses, this country is considered the country with the most active volcanoes in the world. Although seismographs are used to record volcanic activity, the tool still cannot classify the type of earthquake and the status of volcanic eruptions. To overcome this, researchers propose the use of Machine Learning in classifying volcanic eruption status. Machine Learning is a branch of Artificial Intelligence (AI) that facilitates human performance. There are seven branches of AI, including machine learning, natural language processing, expert systems, vision, speech, planning, and robotics. In this study, Machine Learning methods were used in the form of Template Matching and K-Nearest Neighbor (KNN) to classify the type and status of volcanic eruptions. The test results are the accuracy of the confusion matrix, precision, recall, and f1-score where to find the best K in the KNN model it is divided into K=1, 3, 5, 7, 11. The best results obtained for K are at a data ratio of 90:10, namely K = 1 where the accuracy on big data (the majority) is 91% and accuracy on all data (overall data) is 87%. The test results are also in the form of how the KNN model predicts new data using KNN predict. Keywords : Volcanic eruptions, seismic classification, machine learning, template matching, KNN.

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