Kuantifikasi Prioritas Pengembangan Fitur Aplikasi dengan Kerangka Outcome-Driven Innovation: Studi Kasus Aplikasi Pembelajaran Bahasa Asing - Kevin Bastian Sirait; Dickson, Nicholas; Romindo, Romindo (INSOLOGI: Jurnal Sains dan Teknologi, 2025)
This study aims to identify user satisfaction, importance, and development priorities for the English Language Speech Assistant (ELSA) application by integrating Outcome-Driven Innovation (ODI) and sentiment analysis methods. Using reviews collected from the Google Play Store via ScrapeStorm, two sentiment models were applied. Namely, Valance Aware Dictionary and sEntiment Reasoner (VADER) for overall sentiment polarity and Aspect-Based Sentiment Analysis (ABSA) for feature-spesific sentiment extraction. The result show that 86.23% of user reviews express positive sentiments, reflecting high satisfaction with ELSA’s functionality and learning experience. Correlation testing confirms strong validity between VADER and ABSA models (r = 0.98), and moderate alignment with user rating (r  0.55), confirming both construct and external validity. The ODI analysis further identifies Pronunciation as the highest-priority aspect (opportunity = 12.1), followed by Learning (opportunity = 2.6), highlighting key areas for innovation. Other aspects, such as Support and Subscription, show balanced performance with low opportunity values. The integration of ODI and sentiment analysis provide a data-driven framework for product improvement, enabling developers to prioritize enhancements based on user-perceived value. The findings contribute to informed strategic decision-making in the development of digital language-learning applications.