Survey Data: User Acceptance of AI-Based Recommendation Systems in Indonesian E-Commerce

This dataset contains survey responses from 416 Indonesian internet users residing in the Jabodetabek region (Jakarta, West Java, and Banten), collected between March–April 2026 to examine factors influencing user acceptance of AI-based recommendation systems on e-commerce platforms. Respondents were selected through purposive sampling, with a screening question ensuring prior exposure to AI-based product recommendations on platforms such as Shopee, Tokopedia, Lazada, and TikTok Shop. The survey instrument comprises 31 Likert-scale items (1–5) measuring ten constructs based on an extended UTAUT2 framework: Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Hedonic Motivation, Price Value, Habit, Trust, Perceived Risk, and Personal Innovativeness, alongside Behavioral Intention and Use Behavior as outcome variables. The dataset includes demographic information (gender, age, domicile, primary platform used, browsing and purchase frequency) and raw indicator responses. A separate questionnaire file documents the full survey instrument in the original Bahasa Indonesia.