Clustered for Clarity: Leveraging AIO and K-Means to Decode the Modest Fashion Market for Indonesian Muslimah - Dinda R. Melati Mulia; Yati Rohayati; Tiara Verita Yastica (Universitas Islam Nahdlatul Ulama Jepara, 2025)
Objective: This study explores market segmentation within Indonesia’s modest fashion industry for Muslimah consumers by applying a psychographic approach, specifically the Activities, Interests, and Opinions (AIO) framework, combined with the k-means clustering algorithm. The aim is to develop detailed consumer profiles that support more targeted and culturally relevant marketing strategies for micro, small, and medium-sized enterprises (MSMEs). Research Design & Methods: A descriptive quantitative design was employed using an online questionnaire completed by 450 Muslim women who regularly purchase modest fashion. After data cleaning, 433 valid responses were analyzed. Psychographic indicators were measured with a seven-point Likert scale. K-means clustering, selected for its efficiency in unsupervised segmentation, was used alongside the Elbow and Silhouette methods to determine the optimal number of clusters. ANOVA and cross-tabulation analyses were applied to validate the segmentation. Findings: Three psychographic segments emerged: Value-Oriented Pragmatists, Trendy Realists, and Aspirational Stylists. These segments displayed distinct preferences regarding quality, trend adoption, and aspirational values. Each group also revealed different demographic and behavioral profiles, especially regarding spending patterns and purchase motivations. Implications & Recommendations: The resulting segmentation model offers practical guidance for MSMEs in customizing marketing strategies. For instance, emphasizing premium materials may appeal to Value-Oriented Pragmatists. Tailored messaging can improve brand positioning and customer retention. Contribution & Value Added: This study fills a gap in psychographic segmentation within Indonesia’s modest fashion sector. Integrating AIO profiling with machine learning provides a scalable model for MSMEs seeking culturally grounded, data-driven consumer insights in emerging markets.