| Autor: |
Julia, Rinanda Arinta, Larasati, Aisyah, Darmawan, Vertic Eridani Budi, Chen, Yuh-Wen |
| Předmět: |
|
| Zdroj: |
AIP Conference Proceedings; 3/26/2024, Vol. 2927 Issue 1, p1-6, 6p |
| Abstrakt: |
This study aims to formulate a product bundling strategy for IndiHome products using the Apriori Algorithm, one of the association rule algorithms in data mining techniques. This study used 62,504 sales transaction data for IndiHome products at Telkom Jakarta Timur in 2021 to be processed through data mining techniques with the association method. The association method generates association rules based on the relationship between item. The evaluation of the results of this algorithm is based on the value of support, confidence level, and lift ratio. The results of this study reveal that the Apriori algorithm can form association rules that are applied in sales strategies to optimize products. Based on the result, this study finds that the association rules formed can be implemented into a product bundling strategy in terms of product mix strategy and sales channel strategy. Furthermore, this product bundle also shows the effectiveness of each channel location, so this application can be used to justify a marketing strategy that should be implemented. In addition, the sales force channel is one of the most effective and strategic selections that can offer attractive product package programs at competitive prices that can increase customer purchasing power. Thus, the company can increase product sales, especially achieve daily and monthly targets and optimize potential returns. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
|
