Ali Ibrahim
Sriwijaya University

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Journal : Journal of Information Systems and Informatics

Evaluating Pinterest User Experience and Usability Using AttrakDiff and PLS-SEM Septhia Charenda Putri; Ali Ibrahim; Yadi Utama; Endang Lestari Ruskan; Fathoni Fathoni
Journal of Information System and Informatics Vol 8 No 1 (2026): February
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i1.1408

Abstract

The rapid development of visual platforms such as Pinterest necessitates a comprehensive understanding of how functional and emotional aspects jointly influence users’ perception and engagement. This research addresses the gap in user experience (UX) evaluation of visually rich applications by examining the effects of Pragmatic Quality, Hedonic Quality-Stimulation, and Hedonic Quality Identity on the perceived Attractiveness of the Pinterest application. A quantitative approach was employed using the 28-item AttrakDiff instrument, based on data collected from a final sample of 524 valid respondents, predominantly aged 18–25 years, and using Pinterest several times a week. The data analysis was conducted using Partial Least Squares Structural Equation Modeling (PLS-SEM) with the aid of SmartPLS to examine the relationships among latent variables. The findings demonstrate that the structural model exhibits a high level of explanatory capability, with an R² value of 0.684. With all three UX dimensions exerting positive and statistically significant effects on Attractiveness. PQ shows the strongest influence (path coefficient = 0.457), followed by HQS (0.391) and HQI (0.112). These findings confirm that functional usability remains the primary driver of attractiveness on Pinterest, while hedonic qualities play a complementary role in enhancing user experience. Practically, this research suggests that designers and developers of visual platforms should prioritize efficient functionality while maintaining stimulating and identity-supporting elements to improve overall user appeal.
Analyzing the Impact of Review Sentiment on Carpentry Product Sales: Evidence from Tokopedia Agung Chandra Kharisma; Muhammad Haykal Alfariz Saputra; Ali Ibrahim; Mira Afrina
Journal of Information System and Informatics Vol 8 No 1 (2026): February
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i1.1412

Abstract

The rapid growth of e-commerce in Indonesia has increased the importance of consumer reviews as signals influencing purchasing decisions. This study examines the relationship between review sentiment and sales performance in the carpentry tools category on Tokopedia. Using a 2019 Kaggle dataset consisting of 1,826 reviews across approximately 60 products, we apply an NLP-based pipeline to classify review sentiment into positive, neutral, and negative categories. Sentiment labeling combines rating-based rules and a TF-IDF + Logistic Regression baseline, with additional evaluation using IndoBERT. Product-level metrics—including the proportion of positive sentiment (pos_share), average rating, and units_sold (sales proxy)—are analyzed using descriptive statistics, correlation analysis, and cross-sectional OLS regression. The findings reveal that, in this snapshot dataset, the association between positive sentiment share and log(units_sold + 1) is weak and statistically limited, suggesting that sales variation cannot be explained solely by sentiment polarity or average ratings without considering other commercial factors. These results highlight the importance of incorporating contextual variables and temporal design in future research. Practically, the study suggests that sellers should monitor not only sentiment polarity but also the informational richness of reviews to strengthen reputation management strategies.