Abstract
In this decade, e-commerce is one of media to conduct sale and purchase transactions. The seller must maintain e-commerce service so that consumer will comfort to shop. One of the services is provide product that consumer interested. There are many ways to get consumer interest in product. Give rating to product or using click-stream data. But both need the interaction of consumer to click product rating or to click product that consumer interested. With the development of sensor technology, consumer interest in e-commerce products can be collected by eye tracking method. Eye tracking method is one way to get consumer interest in product through attention, without requiring consumer interaction with the system. The model of consumer interest in product uses time until first fixation, fixation count, and fixation duration to measure whether the object is attractive and whether the consumer is interested in the product. The measurement variable based on Aga Bojko taxonomy. The value of variable is displayed in graphical form because in graphical form the analysis of consumer interest in e-commerce product more easily to be done. Implementation of modeling consumer interest uses Ogama, eye tracking software analysis by adding a feature of graphic of consumer interest. In the graph, we can see which products are interesting and which products are preferred by consumers. The contribution of this research is the modeling of consumer interest in the product and some procedure to add graphic feature in eye tracking software analysis, ogama.
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References
Horsley, M., Eliot, M., Knight, B.A., Ronan, R.: Current Trends in Eye Tracking Research (2014)
Courgeon, M., Rautureau, G., Martin, J.-C., Grynszpan, O.: Joint attention simulation using eye-tracking and virtual humans. IEEE Trans. Affect. Comput. 3045(3), 1–1 (2014)
Shahimin, M., Mohammed, Z., Saliman, N., Mohamad-Fadzil, N., Razali, N., Mutalib, H., Mennie, N.: The use of an infrared eye tracker in evaluating the reading performance in a congenital nystagmus patient fitted with soft contact lens : a case report. In: Horsley, M., Eliot, M., Knight, B.A., Ronan, R. (eds.) Current Trends in Eye Tracking Research, pp. 123–128. Springer (2014)
Mehigan, T.J., Barry, M., Kehoe, A., Pitt, I.: Using eye tracking technology to identify visual and verbal learners, Department of Computing, Maths & Physics, Waterford Institute of Technology, Ireland. IEEE (2011)
Borys, M.: Eye Tracking in Marketing Research: a Review of Recent Available Literature, pp. 939–941 (2014)
Bojko, A.: Eye Tracking the User Experience. Rosenfeld (2013)
Purbo, O., Wahyudi, A.: E-Commerce, Elex Media Komputindo (2001)
Zhao, X., Niu, Z., Chen, W.: Interest before liking: two-step recommendation approaches. Knowl.-Based Syst. 48, 46–56 (2013)
Su, Q., Chen, L.: A method for discovering clusters of e-commerce interest patterns using click-stream data. Electron. Commer. Res. Appl. 14(1), 1–13 (2015)
Sari, J.N., Nugroho, H.A., Nugroho, L.E., Santosa, P.I., Ferdiana, R.: A study on algorithms of pupil diameter measurement. In: Proceding of 2016 2nd International Conference on Science and Technology-Computer (ICST), pp. 0–5 (2016)
Gidlöf, K., Dewhurst, R., Holmqvist, K.: Using eye tracking to trace a cognitive process : gaze behaviour during decision making in a natural environment. 6(1), 1–14 (1995)
Chandon, P., Hutchinson, J.W., Bradlow, E.T., Young, S.H.: Measuring the value of point-of-purchase marketing with commercial eye-tracking data. INSEAD Bus. Sch. Res. Pap. (22), 55 (2007)
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This work was supported by RisteDikti of the Ministry of Research and Higher Education of the Republic of Indonesia under Doctoral Research Grant.
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Sari, J.N., Nugroho, L.E., Insap Santosa, P., Ferdiana, R. (2018). Modeling of Consumer Interest on E-commerce Products Using Eye Tracking Methods. In: Ghazali, R., Deris, M., Nawi, N., Abawajy, J. (eds) Recent Advances on Soft Computing and Data Mining. SCDM 2018. Advances in Intelligent Systems and Computing, vol 700. Springer, Cham. https://doi.org/10.1007/978-3-319-72550-5_15
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DOI: https://doi.org/10.1007/978-3-319-72550-5_15
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