SEGMENTASI PELANGGAN AGEN AMI MS GLOW PETERONGAN MENGGUNAKAN ALGORITMA K-MODES BERBASIS PYTHON

YAQIN, MOCHAMMAD AINUL (2022) SEGMENTASI PELANGGAN AGEN AMI MS GLOW PETERONGAN MENGGUNAKAN ALGORITMA K-MODES BERBASIS PYTHON. Other thesis, Universitas Pesantren Tinggi Darul 'Ulum.

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Abstract

Ms Glow is a local skincare brand that won the MURI record as a cosmetic company with the most sales network in Indonesia in 2021. One of Ms Glow's official agents in Jombang, that grows rapidly, is Agent Ami Ms Glow Peterongan. However, there are two problems faced by management, namely the inaccuracy of product stock and the drop of content interaction on social media. These problems can be solved if management can identify the characteristics of its customers. Therefore, in this study, customer segmentation of Agent Ami Ms Glow Peterongan was carried out by using the K-Modes Algorithm method. This algorithm can be used to handle categorical attribute data. This is in accordance with the processed research data which has a categorical attribute type. The results of this study are that the customers of Agent Ami Ms Glow Peterongan are divided into 3 segments which are dominated by the first segment, with customer characteristics: aged 26-35 years; not using KB and not pregnant; oily skin type; no acne outside the menstrual cycle; not having acne; have acne scars and comedo; no black spots; and do not experience itchy and reddish skin occasionally, has 193 customers, the second segment has 76 customers, and the third segment has 98 customers. Keywords: Customer Segmentation, K-Modes, Python

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