Article Per Year (5 Year)
p-Index From 2020 - 2025
0.408
P-Index
This Author published in this journals
All Journal J-SAKTI (Jurnal Sains Komputer dan Informatika) J-SAKTI (Jurnal Sains Komputer dan Informatika)
Syakir, Yusuf
Unknown Affiliation
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Energy

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Analisis Marketplace Shopee Untuk Memprediksi Penjualan dengan Algoritma Regresi Linier Syakir, Yusuf; Hermanto, Teguh Iman; Ramadhan, Yudhi Raymond
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.501

Abstract

Many methods can be used to predict sales, one of which is the processing of sales data using the method of data mining with a linear regression algorithm. The data in this study used is data on sales of the Ariqa Collection Boutique in the Shopee marketplace starting from May 2020 to April 2022. By using a linear regression algorithm, the Ariqa Collection Boutique can predict sales estimates based on total visitors and total orders. The data mining method used is SEMMA (Sample, Explore, Modify, Model, Assess). With the Rapidminer Studio 9.10 tools the test results Mean Square Error (MSE) value is 5.172.628.212.404, Root Mean Square Error (RMSE) is 2.274.341, and Mean Absolute Percentage Error (MAPE) is 4.34%. Based on the MAPE value obtained, the accuracy of the linear regression algorithm in predicting sales of Ariqa Collection Boutique in the Shopee marketplace provides high accuracy
Analisis Marketplace Shopee Untuk Memprediksi Penjualan dengan Algoritma Regresi Linier Syakir, Yusuf; Hermanto, Teguh Iman; Ramadhan, Yudhi Raymond
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 6, No 2 (2022): EDISI SEPTEMBER
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v6i2.501

Abstract

Many methods can be used to predict sales, one of which is the processing of sales data using the method of data mining with a linear regression algorithm. The data in this study used is data on sales of the Ariqa Collection Boutique in the Shopee marketplace starting from May 2020 to April 2022. By using a linear regression algorithm, the Ariqa Collection Boutique can predict sales estimates based on total visitors and total orders. The data mining method used is SEMMA (Sample, Explore, Modify, Model, Assess). With the Rapidminer Studio 9.10 tools the test results Mean Square Error (MSE) value is 5.172.628.212.404, Root Mean Square Error (RMSE) is 2.274.341, and Mean Absolute Percentage Error (MAPE) is 4.34%. Based on the MAPE value obtained, the accuracy of the linear regression algorithm in predicting sales of Ariqa Collection Boutique in the Shopee marketplace provides high accuracy
Co-Authors Hermanto, Teguh Iman Ramadhan, Yudhi Raymond