Analisis Pola Pembelian Melalui Ponsel Menggunakan Algoritma Apriori dan Fp–Growth Pada Millenium Ponsel

Abstract

The purpose of this research is to understand the main factors that influence consumer decisions in purchasing the device. By exploring information about consumer preferences, needs, and behavior, this study seeks to identify purchasing trends and understand how aspects such as mobile phone features, price, and brand influence consumer choices. The main objective of this study is to provide in- depth insights to technology industry players so that they can develop more effective and relevant marketing and product strategies to meet dynamic market needs. To achieve this goal, this study uses the Apriori and FP-Growth methods, which are data mining algorithms that are effective in finding associations and patterns in transaction data. The Apriori method focuses on identifying the frequency of occurrence of itemsets and forming association rules based on support and confidence values, while FP- Growth uses a tree approach to store and extract frequently occurring patterns more efficiently. Both methods allow for in-depth analysis of mobile phone purchase data, so that complex patterns can be revealed more accurately and quickly. The results of this study indicate that there is a very clear mobile phone purchasing pattern among consumers, with confidence values reaching 90% for some association rules. For example, consumers who purchase phones with AMOLED displays tend to also choose large battery capacities from certain brands. These patterns indicate strong and consistent preferences across consumer groups, providing manufacturers with opportunities to target specific market segments with tailored product offerings. These findings not only provide valuable insights into consumer behavior but also help companies optimize their marketing strategies and increase their competitiveness in the technology industry.