Mayang Sari, NPM 2007100027 (2023) ANALYSIS OF THE NEURAL NETWORK METHOD TO DETERMINE INTEREST IN BUYING PERTAMAX FUE. Tugas_ Akhir (Artikel) Sinkron : Jurnal dan Penelitian Teknik Informatika, 8 (2). pp. 1031-1039. ISSN 2541-2019 (e-ISSN) / 2541-044X (p-ISSN)
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Abstract
Fuel is one of the needs that is used by the community as a material to be used on motorcycles or cars. Fuel has become an important need for society, because when there is no fuel, a motorbike or car that is owned by someone cannot be used. Each vehicle has its own fuel, for motorbikes the fuel is pertalite, Pertamax, Pertamax Turbo and for cars the fuel is diesel and dexlite. For the fuel used in motorbikes, there are some people who are interested in Pertalite fuel and there are not many people who are interested in Pertamax fuel. So researchers will make a study of public interest in Pertamax fuel. This research will be made using the neural network method by classifying community data in data mining. This study aims to see the public's interest in purchasing Pertamax fuel. The research process was carried out with the initial stages of collecting and selecting data to be used, then preprocessing, then designing the neural network method and finally the testing process to obtain classification results using the neural network method. The results obtained from data classification using the neural network method state that there are 23 people who are interested in Pertamax fuel and 18 people who are not interested in Pertamax fuel. It turns out that many people are interested in Pertamax fuel. Keywords: Classification, Confusion Matrix, Fuel, Neural Network, Roc Analysis.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Classification, Confusion Matrix, Fuel, Neural Network, Roc Analysis. |
| 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: | 02 Feb 2024 04:31 |
| Last Modified: | 02 Feb 2024 04:31 |
| URI: | http://repository.ulb.ac.id/id/eprint/573 |
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