Diana Juni Triani, NPM 2007100006 (2023) ANALYSIS OF PUBLIC PURCHASE INTEREST IN YAMAHA MOTORCYCLES USING THE K-NEAREST NEIGHBOR METHOD. Tugas_ Akhir (Artikel) Sinkron : Jurnal dan Penelitian Teknik Informatika, 8 (3). pp. 1238-1254. ISSN 2541-2019 (e-ISSN) / 2541-044X (p-ISSN)
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Abstract
This data mining will carry out a classification of people who are interested and not interested in buying Yamaha motorcycles. In the data mining process, a method is needed that can provide goals to the data mining process. That's because there are many data mining methods that can be used. In this study the method that will be used by the author is the K-Nearest Neighbor (kNN) method. This method will be used to classify people's buying interest in Yamaha motorbikes. This research was conducted because there are some people who say that Yamaha motorbikes are not good, use of wasteful fuel. Therefore this research was conducted to prove this statement. So a research was made about people's buying interest in Yamaha motorbikes. Classification results obtained from 100 community data. From the classification process that has been carried out, the results show that 41 community data (41% representation) are interested in buying Yamaha motorcycles and 59 community data (59% representation) are not interested in buying Yamaha motorbikes. The results obtained state that there are still many people who are interested in Yamaha motorbikes. But it can be used as a reference that people are interested in motorbikes that have a good appearance, use economical fuel and are affordable. These results were obtained from the community's answers in the questionnaire, they were interested in motorbikes that use little fuel, have good designs and are affordable. Keywords: Classification, Confusion Matrix, Data Mining, K-Nearest Neighbor (kNN), Motorcycle.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Classification, Confusion Matrix, Data Mining, K-Nearest Neighbor (kNN), Motorcycle. |
| Subjects: | T Technology > T Technology (General) T Technology > TL Motor vehicles. Aeronautics. Astronautics |
| Divisions: | Fakultas Sains Dan Teknologi > Informatika Komputer |
| Depositing User: | Unnamed user with email repository@ulb.ac.id |
| Date Deposited: | 17 Nov 2023 03:16 |
| Last Modified: | 17 Nov 2023 03:16 |
| URI: | http://repository.ulb.ac.id/id/eprint/504 |
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