Kansei Mining-based in Services sebagai Alternatif Pengembangan Metodologi Affective Design
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Abstract
Abstract—Recent research in the field of affective design or known as Kansei engineering for affective design is faced with challenges and opportunities to obtain emotional needs (also called Kansei) that are valid and truly representative of the needs and experience of customer for certain products or services in a certain period. Kansei is indeed sensitive to objects, culture, time-based and the changes of the customer's emotional needs. The challenge so far has been to map the relationship between Kansei and service attributes correctly and representatively. Often what happens is that lack of the process of collecting and validating Kansei words which is limited to the number of samples and research methodology. Thus, this study was carried out by focusing on the study of literature and the development of Kansei engineering model using Kansei text-based mining approach applied to services.
Keywords: Affective design, Kansei engineering, services, text mining
Abstrak—Beberapa penelitian di bidang desain afektif atau dikenal dengan Kansei engineering for affective design dihadapkan pada tantangan dan peluang untuk mendapatkan kebutuhan emosional (disebut juga sebagai Kansei) yang valid dan benar-benar representatif terhadap kebutuhan dan pengalaman konsumen terhadap produk atau layanan tertentu dalam masa tertentu. Kansei memang sensitif terhadap obyek, kultur, waktu dan juga dinamika dari kebutuhan emosional pelanggan itu sendiri. Tantangan yang ada selama ini adalah memetakan hubungan secara benar dan representatif antara Kansei dan service attributes. Seringkali yang terjadi adalah adanya lacking dari proses pengumpulan dan validasi Kansei words yang terbatas pada jumlah sampel dan metodologinya. Dengan demikian, studi ini dilakukan dengan menitikberatkan pada studi literatur dan pengembangan model Kansei engineering menggunakan pendekatan text mining di industri jasa.
Kata kunci: Affective design, Kansei engineering, layanan, text mining
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References
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