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All Journal JOIV : International Journal on Informatics Visualization Jurnal Manajemen Indonesia International Journal Of Science, Technology & Management (IJSTM) Journal of Economics and Business UBS Jurnal Ekonomi, Teknologi dan Bisnis
Sugiat, Maria
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Transportation

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Journal : JOIV : International Journal on Informatics Visualization

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Omni-Channel Service Analysis of Purchase Intention Sugiat, Maria; Saabira, Nadia; Witarsyah, Deden
JOIV : International Journal on Informatics Visualization Vol 7, No 4 (2023)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.7.4.2442

Abstract

The COVID-19 pandemic has caused a decline in various aspects of the economy, including the fashion sector. Many fashion retailers have closed, so sales have fallen. However, many retailers can also adapt and change using new communication channels. This change presents new challenges for fashion companies and retailers to integrate channels into omnichannel services. This study aims to analyze the factors influencing customer behavior in omnichannel services through their intention to accept and use new technology in shopping. This study adopts the UTAUT2 model by adding two new variables: personal innovation and perceived security. This model was tested on 353 samples from Uniqlo customers residing in Indonesia. This research method uses a Quantitative PLS-SEM approach. This study tested the outer model, inner model, and hypothesis t-test with a bootstrap procedure using SmartPLS software. The results showed that the performance expectation factor did not affect the omnichannel purchase intention variable because the t-statistic value is less than 1.65. Meanwhile, other factors such as effort expectation, social influences, habits, hedonic motivation, perceived security, and personal innovativeness affect omnichannel purchase intentions because the t-statistic value is more than 1.65. The most positive and significant factor is personal innovativeness. Based on the results of this study, it is revealed that digitalization creates challenges for companies in maintaining digital businesses. Through various omnichannel service channels, this research can identify the factors influencing consumers' purchase intention
Cluster Analysis of Japanese Whiskey Product Review Using K-Means Clustering Witarsyah, Deden; Akbar, Moh Adli; Praditha, Villy Satria; Sugiat, Maria
JOIV : International Journal on Informatics Visualization Vol 8, No 1 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.1.2601

Abstract

Since 2008, the Japanese whiskey business has grown steadily. Overall, the whiskey market (at factory price) is expected to reach $2.95 billion in 2019, accounting for 8.6 percent of the entire alcoholic beverage industry. The rise in popularity of Japanese whiskey is associated with the country's growing international reputation. Founded 1985 as an independent bottler, Master of Malt was the first company to service clients who ordered single malt whiskey through the mail-order system. Master of Malt's omnichannel approach encompasses all channels available to the company. Known as their 'omnichannel,' this refers to the organization's capability to provide speed and precision from any place at any time. As their brand has grown over the years, they have used various marketing strategies, including a website redesign and rebuild that involved the creation of all relevant content and designing and constructing landing pages for their website. Following a clustering technique, we discovered that the data is being divided into four distinct groups and that these clusters may serve as a recommender system based on the occurrence of terms in each of the categories. Our summarizing component combined phrases related to the exact subtopics and provided users with a concise summary and sentimental information about the group of phrases.
Co-Authors Acai Sudirman Adiyati, Ria Risti Akbar, Moh Adli Deden Witarsyah Firmansyah, Fandi Irni Yunita Praditha, Villy Satria Qinthara Konjala, Wafda Rina Djunita Pasaribu Saabira, Nadia Sundari, Laisitha