KLASIFIKASI PENGOLAHAN DATA KOMPOSISI SAMPAH DENGAN MENGGUNAKAN METODE NAIVE BAYES
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Institusion
Institut Teknologi Perusahaan Listrik Negara
Author
Siahaan, Narti
Luqman, Luqman
Karmila, Sely
Luqman, Luqman
Karmila, Sely
Subject
Teknik Informatika
Datestamp
2023-06-22 04:51:52
Abstract :
Waste has always been a problem in big cities in Indonesia. The volume of waste is increasing but the Final Disposal Site (TPA) is limited, of course, it becomes a problem if it is not handled carefully. So at this time the use of waste management can be used as an alternative as a primary energy source for power plants. Information technology has a very important role in the effort to achieve the target of New and Renewable Energy (EBT) that has been set by the government, especially processing the data generated during the energy supply chain process so that an efficient and optimal WTE model will be obtained in achieving the EBT target. In this case, the authors take advantage of working with supervisors and the Waste to Energy Lab of the PLN Institute of Technology to be able to make this happen by converting waste into New and Renewable Energy (EBT). The author obtained data on the composition of municipal waste throughout Indonesia and then clusified the data using the Naïve Bayes method. Classification using the method of generating a model of the Naïve Bayes algorithm using 300 datasets of waste types. After Determining the Classification Model with the Naïve Bayes Method, the Model Testing was carried out using the Confusion Matrix Method using 240 datasets as Testing data, so the level of accuracy of the Classification Model in this study was 97.50%.
Waste has always been a problem in big cities in Indonesia. The volume of waste is increasing but the Final Disposal Site (TPA) is limited, of course, it becomes a problem if it is not handled carefully. So at this time the use of waste management can be used as an alternative as a primary energy source for power plants. Information technology has a very important role in the effort to achieve the target of New and Renewable Energy (EBT) that has been set by the government, especially processing the data generated during the energy supply chain process so that an efficient and optimal WTE model will be obtained in achieving the EBT target. In this case, the authors take advantage of working with supervisors and the Waste to Energy Lab of the PLN Institute of Technology to be able to make this happen by converting waste into New and Renewable Energy (EBT). The author obtained data on the composition of municipal waste throughout Indonesia and then clusified the data using the Naïve Bayes method. Classification using the method of generating a model of the Naïve Bayes algorithm using 300 datasets of waste types. After Determining the Classification Model with the Naïve Bayes Method, the Model Testing was carried out using the Confusion Matrix Method using 240 datasets as Testing data, so the level of accuracy of the Classification Model in this study was 97.50%.
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