Integrating Sentiment Analysis and Quality Function Deployment for Product Development - 'Azzam, Abdullah; Mahardiningtyas, Syafira; Qurtubi, Qurtubi (Universitas Dharma Wacana, 2023)
The development of technology and media has made online data reviews a promising data source. Through machine learning utilizing text processing, data analysis of Ventela Public Low product reviews can be carried out—sentiment analysis is used to find class groups from each data. The classification algorithm is Naïve Bayes and Support Vector Machine (SVM). A classification model with the best performance and accuracy values will be selected. Word association is then applied to obtain information from the required class. Quality Function Deployment (QFD) is a tool used to assist designers in developing products. The results of the integration of sentiment analysis into QFD show that sentiment analysis produces information by the provisions of the QFD method and can support the product development process in terms of the amount of data various data topics and reduces the subjectivity of designers at the stage of determining Voice of Customer (VOC) and performance values of products and competitors