Sales Trend Analysis With Machine Learning Linear Regression Algorithm Method
DOI:
10.33395/sinkron.v8i3.13809Keywords:
Analysis, Trend, Linear Regression, RapidminerAbstract
The development of online business in Indonesia is now very rapid, with the process being done by ordering goods through resellers or distributors using one of the social media. Item purchases are made based on product information, prices, discounts and inventory quantities using a decision model. In the sales process, Toko Serbu Aek Batu usually releases several different items to be offered to the market at different prices, but not all items are in high demand. Multiple linear regression is an analysis that describes the relationship between dependent variables and factors that affect more than one independent variable. The purpose of this study is to analyze sales trends using a linear regression method using rapidminer. The results of this study are prediction calculations using manual calculations with rapidminer the same results, predicting the price desired by buyers using a linear regression algorithm with the original price is not much different and rapidminer is very accurate to be used in predicting sales trends at the price desired by customers, so that sellers can pay more attention to things that are very influential in the sales process.
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References
Adiguno, S., Syahra, Y., & Yetri, M. (2022). Prediksi Peningkatan Omset Penjualan Menggunakan Metode Regresi Linier Berganda. Jurnal Sistem Informasi Triguna Dharma (JURSI TGD), 1(4), 275. https://doi.org/10.53513/jursi.v1i4.5331
Andrianto, R., & Irawan, F. (2023). Implementasi Metode Regresi Linear Berganda Pada Sistem Prediksi Jumlah Tonase Kelapa Sawit di PT . Paluta Inti Sawit. Jurnal Pendidikan Tambusai, 7(1), 2926–2934.
Ariska, A. M., Irawati, N., & Muhazir, A. (2022). Penerapan Elektronik Customer Relationship Management (E-CRM) Dalam Penjualan Roti Berbasis Web. Jurnal Media Informatika Budidarma, 6(2), 1090. https://doi.org/10.30865/mib.v6i2.4002
Fabriani, S., & Juanita, S. (2020). Implementasi Electronic Relationship Management ( E- Crm ) Pada Beauty Karlina Salon Untuk Meningkatkan. Idealis, 3(1), 381–385.
Hartati, E., Indriyani, R., & Trianingsih, I. (2020). Analisis Kepuasan Pengguna Website SMK Negeri 2 Palembang Menggunakan Regresi Linear Berganda. MATRIK : Jurnal Manajemen, Teknik Informatika Dan Rekayasa Komputer, 20(1), 47–58. https://doi.org/10.30812/matrik.v20i1.736
Mardiatmoko, G. (2020). Pentingnya Uji Asumsi Klasik Pada Analisis Regresi Linier Berganda (Studi Kasus Penyusunan Persamaan Allometrik Kenari Muda [Canarium Indicum L.]. BAREKENG: Jurnal Ilmu Matematika Dan Terapan, 14(3), 333–342.
Purwadi, P., Ramadhan, P. S., & Safitri, N. (2019). Penerapan Data Mining Untuk Mengestimasi Laju Pertumbuhan Penduduk Menggunakan Metode Regresi Linier Berganda Pada BPS Deli Serdang. Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika Dan Komputer), 18(1), 55–61. https://doi.org/10.53513/jis.v18i1.104
Puteri, K., & Silvanie, A. (2020). Machine Learning untuk Model Prediksi Harga Sembako. Jurnal Nasional Informatika, 1(2), 82–94.
Siregar, A. Z. (2021). Implementasi Metode Regresi Linier Berganda Dalam Estimasi Tingkat Pendaftaran Mahasiswa Baru. Kesatria : Jurnal Penerapan Sistem Informasi (Komputer Dan Manajemen), 2(3), 133–137. https://tunasbangsa.ac.id/pkm/index.php/kesatria/article/view/73
Triyanto, E., Sismoro, H., & Laksito, A. D. (2019). Implementasi Algoritma Regresi Linear Berganda Untuk Memprediksi Produksi Padi Di Kabupaten Bantul. Rabit : Jurnal Teknologi Dan Sistem Informasi Univrab, 4(2), 66–75. https://doi.org/10.36341/rabit.v4i2.666
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