Determining Kansei Words in Chocolate Product Development Model Design Based on Social Media Trend by Using Key Element Extraction (KEE) Algorithm

Sembiring, Mariani; Adhinata, Kevin; Wahyuni, Dini; Hadi, M. Zaky

doi:10.1088/1757-899x/505/1/012031

Cited by 4 publications

(3 citation statements)

References 1 publication

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“…On the other hand, Kansei Engineering Type III employs a mathematical structure as its model. This study selected Kansei Engineering Type I to help define customers' desires (Chiu & Lin, 2018;Ishihara et al, 2019;Sembiring et al, 2019).…”

Section: Methodsmentioning

confidence: 99%

“…Engineering is the statistical modeling to extract the Kansei words to consumers' perceptions. Several studies combined text mining from Korean Restaurants' Consumer Needs Based on Marketing….. (Afiani, Ushada, Ainuri, and Falah) online reviews or social media with Kansei Engineering (KE) (S. Ali, Wang, & Riaz, 2020;Chiu & Lin, 2018;Ishihara, Nagamachi, & Tsuchiya, 2019;Sembiring, Adhinata, Wahyuni, & Hadi, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Extracting Consumers’ Perceptions for Indonesian Spice Drinks Using Social Media Data Mining and Kansei Engineering

Alfiani,

Ushada,

Ainuri

et al. 2023

AGRARIS

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Local factors and global influences shape consumers’ perceptions through social media. In this regard, spice drinks as an agribusiness product have received increasing attention due to the Covid-19 pandemic. Therefore, understanding consumers’ perceptions is crucial for promoting the development of spice drinks. This study aims to (1) extract consumers’ perceptions of spice drinks based on discussions on social media using sentiment analysis and (2) classify the factors influencing their perceptions using factor analysis. The input dataset was obtained through Twitter data to acquire Kansei words. The results disclosed that Twitter could extract Kansei words and validate consumers’ perceptions of spice drinks as an agribusiness product. The sentiment analysis revealed 78% positive and 13% neutral tweets. Subsequently, an online survey was conducted among 495 respondents aged 18 to 41, distributed through various social media platforms from June to August 2022. The respondents were Generation Z and Millennials, with Generation Z referring to individuals born between 1997 and 2012 and Millennials born between 1981 and 1996. Factor analysis identified four principal components influencing consumers’ perceptions toward spice drinks: positive attitudes were associated with the quick, milky, mixed, healthy, quality, energy, fresh, warm, and safe; benefits were affiliated with the words enjoy, rest, life, smile, and story; quality concerned easy, flavour, and spicy; and sensory dealt with sweet, aroma, and bitter.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Extracting Consumers’ Perceptions for Indonesian Spice Drinks Using Social Media Data Mining and Kansei Engineering

Alfiani,

Ushada,

Ainuri

et al. 2023

AGRARIS

View full text Add to dashboard Cite

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“…In recent years, scholars focused on quantitative analysis of Kansei images [6]. In the realm of image extraction, Sembiring et al [7] studied chocolate image demand through bloggers' data. Chen and Sun [8] used a survey to extract elderly sleep product image demand.…”

Section: Introductionmentioning

confidence: 99%

Research on Artificial Intelligence Painting APP Interface Design Based on Kansei Engineering

Wang,

Ye,

Zheng

et al. 2024

Frontiers in Artificial Intelligence and Applications

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Amidst the global dissemination of information and the rapid advancement of AI technology, AI painting has received extensive attention within the industry. Increasingly, designers are leveraging AI painting to enhance both the quality and efficiency of their designs. However, prevalent AI painting designs often neglect users’ genuine needs and psychological considerations. In response to this issue, the entropy weight-TOPSIS method and Kansei engineering theory have been employed to construct a technical architecture for the interface design of AI painting APPs. Through a comprehensive assessment encompassing user perceptual cognition and interface functionality, the effectiveness and practicability of the proposed method are validated using a case study involving an AI painting APP. The findings indicate that the method effectively evaluates the interface design, optimizes the design scheme, enhances user experience, and serves as a valuable reference for the future interface designs of AI painting APPs.

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Kansei Engineering in Malaysia and Indonesia: A Systematic Literature Review

Lokman

Ismail

Hadiana

2020

Advances in Intelligent Systems and Computing

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Determining Kansei Words in Chocolate Product Development Model Design Based on Social Media Trend by Using Key Element Extraction (KEE) Algorithm

Cited by 4 publications

References 1 publication

Extracting Consumers’ Perceptions for Indonesian Spice Drinks Using Social Media Data Mining and Kansei Engineering

Extracting Consumers’ Perceptions for Indonesian Spice Drinks Using Social Media Data Mining and Kansei Engineering

Research on Artificial Intelligence Painting APP Interface Design Based on Kansei Engineering

Kansei Engineering in Malaysia and Indonesia: A Systematic Literature Review

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