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Initial Purchase Decision: A Gender Differences Perspective Besli, Eugenius; Chandra, Maria Helena; Sami'un, Defitroh Chen
JHSS (JOURNAL OF HUMANITIES AND SOCIAL STUDIES) Vol. 9 No. 3 (2025): JHSS (Journal of Humanities and Social Studies)
Publisher : UNIVERSITAS PAKUAN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33751/jhss.v9i3.108

Abstract

This study aims to investigates gender differences in online purchase decision-making by analysing the influence of key factors among men and women. An independent t-test is employed to examine behavioural distinctions, while multiple regression is used to assess the strength of these influencing variables. The findings reveal only slight differences between men and women in their online shopping behaviour. However, the order of influence is consistent across both genders, with store ratings having the strongest impact, followed by live streaming shopping and consumer reviews. Despite the similar order, women are found to be more actively involved in online shopping and show a higher sensitivity to these factors compared to men. These findings highlight gender's influence on consumer behaviour and help businesses refine digital design, marketing, and service strategies to suit each group's preferences.
Lexicon-Based, Naïve Bayes, C4.5 for Analyzing Visitor Data Reviews as Recommendations for Priority Development of Labuan Bajo Tourism Dahur, Arnoldus Janssen; Sami'un, Defitroh Chen
Jurnal IPTEK Vol 29, No 2 (2025): December
Publisher : LPPM Institut Teknologi Adhi Tama Surabaya (ITATS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.iptek.2025.v29i2.8178

Abstract

Labuan Bajo is one of Indonesia’s national priority destinations, known for its natural beauty and unique ecosystem. However, several issues raised by tourists—such as complaints regarding prices, infrastructure, and environmental cleanliness—may affect its image and tourism sustainability. This study aims to analyze tourist perceptions of Labuan Bajo based on 7,000 reviews from TripAdvisor and Google Maps obtained through web crawling. Sentiment labeling was conducted using a Lexicon-Based approach, while classification was performed using the Naïve Bayes and C4.5 algorithms, both with and without the Synthetic Minority Oversampling Technique (SMOTE). The results showed 4,374 positive, 2,769 negative, and 1,804 neutral reviews. Based on the CRISP-DM method, Naïve Bayes achieved the highest accuracy of 88%, compared to 78% for C4.5. Dominant positive terms such as beautiful, stunning, and sustainable highlight Labuan Bajo’s natural strengths, while negative terms like price, toilet, and trash indicate areas requiring improvement. The findings provide strategic recommendations to enhance tourism management and service quality toward sustainable tourism development.