QUDSY, MUHAMMAD FATHURAHMAN AL (2023) ANALISA PERBANDINGAN METODE LINEAR REGRESSION DAN SVR DALAM PREDIKSI DATA TIME SERIES PENJUALAN MAINAN DI PT. XYZ. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
Sales prediction is a strategy to see existing sales opportunities, which are expected to increase a company's revenue. One business that has attracted quite a lot of public interest is the sale of educational toys. This research will focus on applying the Linear Regression algorithm and the Support Vector Regression (SVR) algorithm in predicting the sales of educational toys. The dataset obtained is educational toy sales report data from 2018-2022, which comes from the company PT. XYZ. Then do some pre-processing methods, so that the dataset is ready for use. Furthermore, the dataset will be implemented into the Linear Regression algorithm and the SVR algorithm. The evaluation of the model will use the root mean square error (RMSE) test parameters and the coefficient of determination (R 2 ), to compare the results of the test values between the two algorithms which is better to use in this study. Based on the results of the experimental scenarios, it shows that the Linear Regression algorithm on the composition of 70% training data and 30% test data is better than the SVR algorithm in this study, by obtaining test results on test data with an R 2 value of 0.704668 and an RMSE value of 107202872.369211. Keywords: Educational toys, Prediction, Linear Regression, Support Vector Regression Prediksi penjualan merupakan salah satu strategi untuk melihat peluang penjualan yang ada, yang diharapkan dapat meningkatkan pendapatan suatu perusahaan. Salah satu bisnis yang cukup banyak menarik minat masyarakat adalah penjualan mainan edukatif. Pada penelitian ini akan berfokus dalam menerapkan algoritma Linear Regression dan algoritma Support Vector Regression (SVR) dalam memprediksi hasil penjualan mainan edukatif. Dataset yang didapatkan merupakan data laporan penjualan mainan edukatif dari tahun 2018-2022, yang berasal dari perusahaan PT. XYZ. Lalu dilakukan beberapa metode Pre-processing, agar dataset siap untuk digunakan. Selanjutnya dataset akan diimplementasikan kedalam algoritma Linear Regression dan algoritma SVR. Evaluasi model akan menggunakan parameter uji root mean square error (RMSE) dan nilai koefisien determinasi (R2 ), untuk dibandingkan hasil nilai pengujiannya antara kedua algoritma mana yang lebih baik untuk digunakan pada penelitian ini. Berdasarkan hasil skenario eksperimen yang dilakukan menunjukkan bahwa algoritma Linear Regression pada komposisi data latih 70% dan data uji 30% lebih baik dibandingkan algoritma SVR pada penelitian ini, dengan mendapatkan hasil pengujian pada data uji dengan nilai R 2 sebesar 0.704668 dan nilai RMSE sebesar 107202872.369211. Kata Kunci: Mainan edukatif, Prediksi, Linear Regression, Support Vector Regression
| Item Type: | Thesis (S1) |
|---|---|
| Call Number CD: | FIK/INFO. 23 123 |
| Call Number: | SIK/15/23/065 |
| NIM/NIDN Creators: | 41519010173 |
| Uncontrolled Keywords: | Mainan edukatif, Prediksi, Linear Regression, Support Vector Regression |
| Subjects: | 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum 000 Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 000. Computer Science, Information and General Works/Ilmu Komputer, Informasi, dan Karya Umum > 004 Data Processing, Computer Science/Pemrosesan Data, Ilmu Komputer, Teknik Informatika |
| Divisions: | Fakultas Ilmu Komputer > Informatika |
| Depositing User: | Sekar Mutiara |
| Date Deposited: | 06 Oct 2023 02:59 |
| Last Modified: | 06 Oct 2023 02:59 |
| URI: | http://repository.mercubuana.ac.id/id/eprint/81206 |
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