Analysis Learners’ Preference in E-Learning System Using Kansei Approach

Hadiana, Asep Id

doi:10.5772/intechopen.75620

Cited by 6 publications

(5 citation statements)

References 16 publications

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“…The goal is to provide analysis results from Kansei Engineering using Analytical Hierarchy Process decision support system methods that are able to provide decisions to users without ignoring aspects of the user's feelings towards a product. The Kansei Engineering method was chosen because it was proven to be able to describe in detail the feelings and expectations of consumers towards the product [3][4]. The flow of research explains the stages of research in analyzing Kansei using the AHP method in Fig 3 .1.…”

Section: Resultsmentioning

confidence: 99%

“…Kansei Engineering (KE) is a method for translating feelings, emotions, and impressions into product parameters. [2] The main key to the success of a KE product is feeling, so to realize a quality product that is truly in accordance with feelings is very important to know all aspects of feelings that are expected to appear in a product [3][4][5].…”

Section: Introductionmentioning

confidence: 99%

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Kansei Analysis using Analytical Hierarchy Process

Huda¹,

Hadiana²

2020

Proceedings of the International Conference on Business, Economic, Social Science, and Humanities – Economics, Business and Man

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In determining a choice that is not based on specifications, it is important to know the aspects of feelings in a product. Kansei is a technology that translates feelings into product design. The application of Kansei in the development of decision support systems can help facilitate decision making based on feelings. Decision support system development certainly involves a decision support system method. One method that is often applied in decision support systems is the Analytical Hierarchy Process (AHP), as many decision support systems have been applied in the industrial world referring to the evaluation of a number of criteria to evaluate a number of existing criteria used the AHP method which able to approach the assessment of qualitative and quantitative criteria. AHP method is the right solution for the case of product selection based on feelings that have the same specifications. This research aims to choose IT Helpdesk based on feelings. For now, there are several recommended options for a helpdesk that can serve properly. The result of this research is to produce the best alternative recommendations with the criteria that influence. The results obtained from this research are to produce the selection of helpdesk with the highest weight, which the C-Desk alternative with a value of 0.2119 and influenced by Classical criteria with a value of 0.0242 as the main factor.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Kansei Analysis using Analytical Hierarchy Process

Huda¹,

Hadiana²

2020

Proceedings of the International Conference on Business, Economic, Social Science, and Humanities – Economics, Business and Man

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“…In this study, Factor Analysis (FA) is detailed and strengthens the results of PCA analysis [12] by providing recommendations for the highest Kansei Word value, which is then referred to as The emotion factor [13], so that not all emotional factors are involved in user interface design. FA using varimax rotation for getting the accuracy result and then resulting factor 1 with percentage contribution 62.38% and factor 2 with percentage 20.44%.…”

Section: Factor Analysis (Famentioning

confidence: 99%

Kansei Engineering in Designing Web-Based e-Commerce UMKM Product

Isa¹,

Ariyanti²

2021

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Human-Computer Interaction (HCI) is a part of the development of a system in addition to the usability factor. Several methods were developed in HCI to produce a User Interface design that persuasively attracts the user’s interest. One of these methods was Kansei Engineering which involved psychological factors and user emotions in the stage. The study focused on developing the e-commerce User Interface for UMKM products which based on how to maximize the service and quality of e-Commerce because so far the development of the web-based UMKM e-Commerce product user interface has not paid attention to psychological factors. The Research followed Kansei Engineering Type 1 (KEPack) with the stages: (1) Research Initiation, (2) Collecting Kansei Words (KW), (3) Translating KW into SD scale, (4) Collecting Specimens, (5) Classifying Item / Category Specimens, (6) Evaluating Questionnaire Participants’ Data, (7) Multivariate Statistical Analysis, (8) Translating Statistical Data into Design Elements, (9) Creating Guideline Matrix Kansei Engineering. This study involved 40 participants, 20 Kansei Words, and ten specimens of UMKM e-Commerce products. The final result is the Kansei e-Commerce matrix guideline for web-based UMKM products, which had two main concepts, they were complexity consisting of formal, natural and simple emotion factors; and Uniqueness consisting of Comfortable, Soft, and Unique which consists of 8 main parts which divided into 65 design elements. The contribution of this Research in the informatics area is to provide recommendations for the appearance of web-based UMKM e-Commerce products based on the psychological factors of the user through the Kansei Engineering Stages.

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“…Our focus for this study is political security which is one of the elements of national security. The Kansei evaluation measurements are based on responses gathered using the Kansei Checklist, a form of a questionnaire that includes emotional keywords or known as Kansei Words (KW) [33]. The evaluation was done in four phases.…”

Section: B Emotion Assessment Using Kanseimentioning

confidence: 99%

Assessment of Emotion in Online News based on Kansei Approach for National Security

Razali¹,

Malizan²,

Hasbullah³

et al. 2021

IJACSA

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Securing a nation is more complicated in modern days than how it was decades ago. In the era of big data, massive information is constantly being shared in cyberspace. Online rumours and fake news could evoke negative emotions and disruptive behaviours that possibly can jeopardize national security. Real-time detection and monitoring of unsettling emotions and potential national security threats should be further developed to help authorities manage the situation early. Text in the online news could be weighted with emotions that possibly lead to a misunderstanding that can affect national security and trigger chaos. Thus, understanding the emotion included in the online news and the relationship with national security is crucial. Kansei approach was determined as a methodology capable of interpreting human emotions towards an artefact. This research explores the emotion assessment using Kansei for text in online news and summarized the emotion variable factors that are likely to have a relationship with an individual state of mind towards one of the national security elements which are political security. The result determines that the identified variables of factors were "Frustrated," Consent," Resentful" and "Attentive". This gives an understanding of the significant effect of people's emotions represented in the text for political security elements.

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Analysis Learners’ Preference in E-Learning System Using Kansei Approach

Cited by 6 publications

References 16 publications

Kansei Analysis using Analytical Hierarchy Process

Kansei Analysis using Analytical Hierarchy Process

Kansei Engineering in Designing Web-Based e-Commerce UMKM Product

Assessment of Emotion in Online News based on Kansei Approach for National Security

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