Identifikasi Tren Fashion Melalui Analisis Kluster Gaya Visual

Ibra, Abdi Ibadihi (2025) Identifikasi Tren Fashion Melalui Analisis Kluster Gaya Visual. Other thesis, Institut Teknologi Sepuluh Nopember.

Text 5025201098-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only until 1 April 2027. Download (7MB)

Abstract

Penelitian ini bertujuan untuk mengeksplorasi tren fashion dengan menganalisis kluster gaya visual. Melalui pendekatan analisis kluster, penelitian ini bertujuan untuk menyelidiki pola visual yang muncul dalam tren fashion dan memahami evolusi gaya dalam industri. Metodologi penelitian ini melibatkan pengumpulan data visual dari sumber-sumber mode terkini dan menerapkan teknik kluster untuk mengidentifikasi kluster gaya yang signifikan. Analisis mendalam terhadap kluster gaya akan memberikan wawasan tentang preferensi konsumen, inovasi desain, dan faktor-faktor lain yang memengaruhi tren fashion. Hasil penelitian ini diharapkan dapat memberikan pandangan yang lebih baik mengenai perubahan tren fashion, serta membantu para pemangku kepentingan di industri ini untuk mengambil keputusan yang lebih terinformasi dan responsif terhadap kebutuhan pasar. Penelitian ini merangkum kontribusi analisis kluster gaya visual dalam memahami tren fashion secara menyeluruh, yang berpotensi memberikan panduan berharga bagi para desainer, produsen, dan pemasar dalam mencapai kesuksesan di pasar yang terus berubah ini.
====================================================================================================================================
This study aims to explore fashion trends by analyzing visual style clusters. Through a cluster analysis approach, this study aims to investigate the visual patterns that emerge in fashion trends and understand the evolution of styles in the industry. The research methodology involves collecting visual data from current fashion sources and applying cluster techniques to identify significant style clusters. An in-depth analysis of style clusters will provide insights into consumer preferences, design innovations, and other factors that influence fashion trends. The results of this study are expected to provide a better view of changing fashion trends, as well as help stakeholders in the industry to make more informed and responsive decisions to market needs. This study summarizes the contribution of visual style cluster analysis in understanding fashion trends holistically, which has the potential to provide valuable guidance for designers, manufacturers, and marketers in achieving success in this ever-changing market.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Artificial Intelligence, Clustering, Data Mining, Fashion, Trend
Subjects:	T Technology > T Technology (General) > T57.5 Data Processing
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Informatics Engineering > 55201-(S1) Undergraduate Thesis
Depositing User:	Ibra Abdi Ibadihi
Date Deposited:	04 Feb 2025 01:46
Last Modified:	04 Feb 2025 01:46
URI:	http://repository.its.ac.id/id/eprint/118055

Actions (login required)

View Item