Articles
Vol. 5, No. 1 (2027)
Christian University of Indonesia
10.58477/cj.v5i1.528
Published: 2027-02-01
Abstract
This study examines how perceived accuracy and contextual relevance of artificial-intelligence-based product recommendations influence purchase decisions among Generation X e-commerce users in Jakarta. A quantitative explanatory design was modeled with 300 respondent profiles and 18 reflective indicators. Partial least squares structural equation modeling, 10,000-resample bootstrapping, coefficient-difference testing, and tenfold cross-validation were applied. Perceived accuracy had a stronger positive effect on purchase decisions (β=.604, p<.001) than relevance (β=.217, p<.001), and the difference was significant (Δβ=.387, p<.001). The model explained 54.2% of purchase-decision variance and showed positive Qpredict2 values. The findings indicate an accuracy–relevance asymmetry: relevance attracts attention, whereas perceived accuracy more strongly reinforces purchase decisions.
How to Cite
How to Cite
Simanjuntak, D. M., Sinuraya, A., & De Wana, S. (2027). Perceived Accuracy and Relevance of AI-Based Product Recommendations and Generation X Purchase Decisions in Jakarta. Computer Journal, 5(1), 29-37. https://doi.org/10.58477/cj.v5i1.528
| Issue | Vol. 5 No. 1 (2027) |
| Section | Articles |
| DOI | 10.58477/cj.v5i1.528 |
| Publication Date | 2027-02-01 |
| Pages | 29-37 |
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This work is licensed under a Creative Commons Attribution 4.0 International License.
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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