Klasifikasi Keluhan Masyarakat Terhadap Sepeda Motor Listrik Dengan Menerapkan Algoritma Text Mining Dan Tf-Idf

Jupri Sinaga

Abstract


Electric motorbikes are motorbikes that are driven by a dynamo and accumulator so they do not cause emissions. This is different from conventional motorbikes (carburetor and injection) which still use gasoline for propulsion and cause very high pollution. With the existence of social media, it is now easier for people to express their complaints via social media. The problems experienced by the public in using electric motorbikes are that people tend to be wary of the battery running out and have difficulty setting charging patterns, then have difficulty finding the nearest fast charging/battery swapping battery charging station if a low battery occurs. This is the cause of reduced public interest in electric motorbikes. Therefore, classification by applying the Text Mining and TF-IDF algorithms aims to group problems that are currently occurring in the use of electric motorbikes. After processing using the Text Mining and TF-IDF algorithms, the 20 sample data produced more dominant battery complaint data with a weight value of 67.004.

Keywords


Classification; Electric Motorcycle; Text Mining; TF-IDF

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DOI: https://doi.org/10.30865/komik.v7i1.8059

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This work is licensed under a Creative Commons Attribution 4.0 International License.