Knowledge Engineering and Data Science


Adaptive Neuro-Fuzzy Inference System for Waste Prediction

Haviluddin, Haviluddin (Unknown)
Pakpahan, Herman Santoso (Unknown)
Puspitasari, Novianti (Unknown)
Putra, Gubtha Mahendra (Unknown)
Hasnida, Rima Yustika (Unknown)
Alfred, Rayner (Unknown)



Article Info

Publish Date
30 Dec 2022

Abstract

The volume of landfills that are increasingly piled up and not handled properly will have a negative impact, such as a decrease in public health. Therefore, predicting the volume of landfills with a high degree of accuracy is needed as a reference for government agencies and the community in making future policies. This study aims to analyze the accuracy of the Adaptive Neuro-Fuzzy Inference System (ANFIS) method. The prediction results' accuracy level is measured by the value of the Mean Absolute Percentage Error (MAPE). The final results of this study were obtained from the best MAPE test results. The best predictive results for the ANFIS method were obtained by MAPE of 3.36% with a data ratio of 6:1 in the North Samarinda District. The study results show that the ANFIS algorithm can be used as an alternative forecasting method.

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Journal Info

Abbrev

publication:keds

Publisher

Subject

Computer Science & IT Engineering

Description

The journal welcomes experimental and theoretical findings on data science and knowledge engineering along with their applications to real-life ...