PREDIKSI PENJUALAN KENDARAAN MOTOR TERLARIS PADA PT. HASJRAT ABADI YAMAHA CABANG GORONTALO OUTLET 3S TELAGA DENGAN MENGGUNAKAN ALGORITMA NEURAL NETWORK
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Institusion
Universitas Muhammadiyah Gorontalo
Author
Mantida, Kadir
Subject
QA75 Electronic computers. Computer science
Datestamp
2024-03-05 02:48:14
Abstract :
This research was conducted at PT. Hasjrat Abadi Yamaha Gorontalo Branch Outlet 3S Telaga. This research aims to provide a solution in dealing with the research. Neural network algorithm modeling was carried out using Excel. After the data has been processed and tested into Rapidminer to get the best results based on the research stages. This data will be divided into data that will be used for training and testing in artificial neural networks with a total of 180 records with 3 motor units. Based on the test results on the Rapidminer, the smallest value obtained on the NMAX motorbike was 0.135, on the Aerox motorbike the smallest value was 0.153, while on the Mio motorbike the smallest value was 0.164, so it can be seen that the results obtained from comparing the three types of motors obtained the smallest value on Nmax motorbike with the smallest RMSE value of 0.135 and after testing using calculations in Microsoft Excel it can be seen that the prediction results are from 2018-2022 and the data error range is the result of denormalized data with a value ranging from -3.374 to 0.06.
This research was conducted at PT. Hasjrat Abadi Yamaha Gorontalo Branch Outlet 3S Telaga. This research aims to provide a solution in dealing with the research. Neural network algorithm modeling was carried out using Excel. After the data has been processed and tested into Rapidminer to get the best results based on the research stages. This data will be divided into data that will be used for training and testing in artificial neural networks with a total of 180 records with 3 motor units. Based on the test results on the Rapidminer, the smallest value obtained on the NMAX motorbike was 0.135, on the Aerox motorbike the smallest value was 0.153, while on the Mio motorbike the smallest value was 0.164, so it can be seen that the results obtained from comparing the three types of motors obtained the smallest value on Nmax motorbike with the smallest RMSE value of 0.135 and after testing using calculations in Microsoft Excel it can be seen that the prediction results are from 2018-2022 and the data error range is the result of denormalized data with a value ranging from -3.374 to 0.06.
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