PERANCANGAN MODEL PRODUCT BUNDLING BERDASARKAN KARAKTERISTIK DEMOGRAFIS PELANGGAN PT X MENGGUNAKAN TEKNIK DATA MINING

• Main Author: Harja Putra, Dion
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/77834
• Institution: Institut Teknologi Bandung

PT X is a technology start-up company that operates in the education sector (edtech) by providing study abroad consultation services and foreign language classes. To increase customer purchase intention, PT X intends to initiate the implementation of a product bundling strategy. Product bundling is a strategy that combines multiple products or services as part of a single-priced package to increase the value offered to customers. Decisions in determining which products or services will be combined into one bundle must be based on a comprehensive model so that it can meet customer needs and on the other hand bring profits to the company. Therefore, this research intends to build a model that can decide recommendations for optimal product or service combinations to support the product bundling strategy initiated by PT X. The methodology used in this research was developed from the Cross Industry Standard Process for Data mining (CRISP-DM) framework by using k-modes clustering to group customers based on the similarity of specific demographic characteristics and association rule mining using the Apriori algorithm to find rules that indicate the existence of associations between pairs of products or services that should be grouped into one bundle for each customer group. The modeling in this research generates four customer groups along with recommendations for optimal product or service combinations for each group. In this research, an application prototype was also developed that was able to execute models in the form of a Graphical User Interface (GUI) using the Python programming language.