* Corresponding Author
FACTOR ANALYSIS OF HEALTHY FOOD PHOTOGRAPH
https://doi.org/10.22146/ajse.v6i1.76128 Nindya Laksita Laras(1*), Mirwan Ushada(2), Titis Wijayanto(3)
(1) Universitas Gadjah Mada
(2) Universitas Gadjah Mada
(3) Universitas Gadjah Mada
(*) Corresponding Author
Abstract
Lockdown is one way to reduce the transmission rate of COVID-19. Nevertheless, on the other hand, lockdowns also increase human psychological problems to cause the emergence of emotional eating. In addition, social media exposure that presents food photos can trigger the desire to eat. However, this only applies to high-fat and high-calorie foods, while healthy foods do not have the same stimuli. Therefore, more research is needed on the properties of healthy food photos desired by consumers in order to be able to create or design healthy food photos with an effect that resembles photos of high-fat and high-calorie foods. This study employed the Kansei Engineering approach in designing healthy food photos. Through Kansei Engineering, we can determine the nature of healthy food photos consumers want. The type of Kansei engineering used in this study was Kansei Engineering Type I and was limited to the Semantic Space stage. The process of factor reduction from the results of the semantic differential was carried out by using factor analysis to obtain the most critical factors related to healthy food photos. The semantic space spanning resulted in 23 pairs of Kansei words that related and represented healthy food photos. Based on the factor analysis results, these Kansei words were then into 6-factor groups. Each of the factor groups was represented by the Kansei word pair with the highest loadings value. The selected pair of Kansei words showed that healthy food photos could be represented by Kansei words attractive, contrast, proper lighting, neat, high-quality image, and straightforward.
Keywords
Full Text:
PDFReferences
Adelabu, O. S., & Yamanaka, T. (2014). Kansei as a Function of Aesthetic Experience in Product Design. In J. Watada, H. Shiizuka, K.-P. Lee, T. Otani, & C.-P. Lim (Eds.), Industrial Applications of Affective Engineering. Springer. Andersen, T., Byrne, D. V., & Wang, Q. J. (2021). How Digital Food Affects Our Analog Lives: The Impact of Food Photography on Healthy Eating Behavior. Frontiers in Psychology, 12(April). https://doi.org/10.3389/fpsyg.2021.634261 Coary, S., & Poor, M. (2016). How Consumer-Generated Images Shape Important Consumption Outcomes in The Food Domain. Journal of Consumer Marketing, 33(1), 1–8. https://doi.org/https://doi.org/10.1108/JCM-02-2015-1337 Djaali, Muljono, P., & Sudarmanto. (2008). Pengukuran dalam Bidang Pendidikan. Grasindo. Hair, J. F. (Jr), Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate Data Analysis (7th ed.). Pearson Education Limited. Hardisman. (2021). Analisi Faktor, Analisis Jalur, dan Structural Equation Modelling dengan JASP. Bintang Pustaka Madani. Hassen, T. Ben, Bilali, H. El, & Allahyari, M. S. (2020). Impact of COVID-19 on Food Behavior and Consumption in Qatar. Sustainability, 12, 6973. Henry, C., Sharma, M., Lapenu, C., & Zeller, M. (2003). Microfinance Poverty Assesment Tool. The World Bank. Maltoni, G., Zioutas, M., Deiana, G., Biserni, G. B., Pession, A., & Stefano Zucchini. (2021). Gender Differences in Weight Gain during Lockdown Due to COVID-19 Pandemic in Adolescents with Obesity. Nutrition, Metabolism & Cardiovascular Disease, 31(7), 2181–2185. https://doi.org/https://doi.org/10.1016/j.numecd.2021.03.018 Nagamachi, M. (2011). Kansei/Affective Engineering. CRC Press. Sánchez, E., Lecube, A., Bellido, D., Monereo, S., Malagón, M. M., & Tinahones, F. J. (2021). Leading factors for weight gain during covid-19 lockdown in a Spanish population: A cross-sectional study. Nutrients, 13(3), 1–12. https://doi.org/10.3390/nu13030894 Scarmozzino, F., & Visioli, F. (2020). Covid-19 and the Subsequent Lockdown Modified Dietary Habits of Almost Half the Population in an Italian Sample. Foods, 9, 675. Schutte, S. (2002). Designing Feelings into Products. Institute of Technology Linkopings University. Spence, C., Okajima, K., Cheok, A. D., Petit, O., & Michel, C. (2016). Eating with our eyes: From visual hunger to digital satiation. Brain and Cognition, 110, 53–63. https://doi.org/10.1016/j.bandc.2015.08.006 Subroto, M. A. (2008). Real Food True Health (R. Armando (ed.)). AgroMedia Pustaka. Urzeala, C., Duclos, M., Ugbolue, U. C., Bota, A., Berthon, M., Kulik, K., Thivel, D., Bagheri, R., GU, Y., Baker, J. S., Andant, N., Pereira, B., Rouffiac, K., Clinchamps, M., & Dutheil, F. (2021). COVID-19 Lockdown Consequences on Body Mass Index and Perceived Fragility Related to Physical Activity: A Worldwide Cohort Study. Health Expectations, 1–10. Zhu, Q., Li, M., Ji, Y., Shi, Y., Zhou, J., Li, Q., Qin, R., & Zhuang, X. (2021). “Stay‐at‐Home” Lifestyle Effect on Weight Gain during the COVID‐19 Outbreak Confinement in China. International Journal of Environmental Research and Public Health, 18(4), 1–13. https://doi.org/10.3390/ijerph18041813
DOI: https://doi.org/10.22146/ajse.v6i1.76128
Article Metrics
Abstract views : 1924
| 
views : 720
Refbacks
- There are currently no refbacks.
Copyright (c) 2022 ASEAN Journal of Systems Engineering
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Universitas Gadjah Mada