Rintyarna, Bagus Setya (2021) (Similarity) Mapping Acceptance of Indonesian Organic Food Consumption under Covid-19 Pandemic using Sentiment Analysis of Twitter Dataset. Journal of Theoretical and Applied Information Technology.
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Abstract
Computational intelligence based technique becomes popular lately for many application including revealing trend in healthy food consumption. Healthy alternative food that insures the basic physical needs of mankind becomes more popular among people worldwide nowadays. Organic food is believed as alternative food providing sustainable benefit for mankind especially under the pandemic situation that body urgently needs to maintain optimal immune system. Organic food helps to supply sufficient nutrients that is important for body to cope with virus infection. Previously, many studies have been conducted worldwide to exhibit organic foods consumption pattern. The approach can be categorized into two types. The first approach relies on pencil survey and focus group discussion involving a certain number of respondents. The analysis commonly applies statistical techniques. This approach has been considered time consuming and costly. A more sophisticated and time saving technique commonly make use social media platform as the primary tool for revealing the pattern. This study is an initial study to provide model of Indonesian organic food consumer considering that Indonesia is potential for both producer and consumer of organic food. The analysis is based on Twitter dataset and applying computational based technique using Lexicon Based Sentiment Analysis using VADER. Beforehand, we perform text analysis using Force Atlas2 to reveal spatial representation of both attraction force and repulsion force of words. To extent VADER, we employ Indonesian sentiment lexicon namely INSET. The sentiment analysis result confirms that 64% user accept positively organic food as healthy dietary food highlighting the importance of organic food for people to maintain optimal immune system in Covid-19 Pandemic Circumstances. Most of the user that positively post organic food, associate the food with “kesehatan”, “praktis”, and “diet”. Meanwhile, the rest post negatively and regard organic food as having expensive price compared with another kind of food
| Item Type: | Peer Review |
|---|---|
| Uncontrolled Keywords: | Sentiment Analysis, Text Mining, Lexicon-Based, Organic Food, Covid-19 Pandemic, Twitter |
| Subjects: | 600 Technology and Applied Science > 620 Engineering |
| Divisions: | Faculty of Engineering > Department of Electronics Engineering (S1) |
| Depositing User: | Bagus Setya Rintyarna |
| Date Deposited: | 23 Dec 2022 01:20 |
| Last Modified: | 24 Jan 2023 04:32 |
| URI: | http://repository.unmuhjember.ac.id/id/eprint/15667 |
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