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All Journal Inventa: Journal of Science, Technology, and Innovation
Laili Afiatur Rosidah
Universitas Pamulang
Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Penerapan Deep Learning untuk Analisis Sentimen Ulasan Produk dalam Memprediksi Perubahan Permintaan Pasar pada Platform E-Commerce Harwati Harwati; Laili Afiatur Rosidah; Rika Rahmawati Milya
Journal of Science, Technology, and Innovation Vol 1 No 2 (2025): December: Inventa: Journal of Science, Technology, and Innovation
Publisher : CV SCRIPTA INTELEKTUAL MANDIRI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65310/v7bm9213

Abstract

High competition in the e-commerce sector demands superior user experience as the key to retention. The research adopts a quantitative approach, testing hypotheses using Structural Equation Modeling (SEM) on data from active platform users. The analysis confirms that Information System Quality significantly influences User Satisfaction, and Satisfaction exerts a strong influence on Customer Loyalty. The most crucial finding is the confirmation of partial mediation by User Satisfaction in transmitting the effect of Information System Quality to Loyalty. This highlights that technology investment must translate into a satisfying experience to effectively drive Loyalty. Managerial implications suggest the platform should prioritize optimizing usability and service responsiveness to bolster Satisfaction, which is the primary factor in maintaining a stable customer base.
Co-Authors Harwati Harwati Rika Rahmawati Milya