Analisis Topik Tagar Covidindonesia pada Instagram Menggunakan Latent Dirichlet Allocation
In this era, technology is increasingly sophisticated, this is evidenced by the number of people using the internet via cell phones, laptops, and other communication tools. One of the developments of this technology is social media such as Instagram. Along with technological developments, Instagram...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Universitas Islam Negeri Sunan Kalijaga Yogyakarta
2022-01-01
|
| Series: | JISKA (Jurnal Informatika Sunan Kalijaga) |
| Subjects: | |
| Online Access: | http://ejournal.uin-suka.ac.id/saintek/JISKA/article/view/2415 |
| _version_ | 1797725974913089536 |
|---|---|
| author | Kevin Rafi Adjie Putra Santoso Asmaul Husna Nadia Widyawati Putri Nur Aini Rakhmawati |
| author_facet | Kevin Rafi Adjie Putra Santoso Asmaul Husna Nadia Widyawati Putri Nur Aini Rakhmawati |
| author_sort | Kevin Rafi Adjie Putra Santoso |
| collection | DOAJ |
| description | In this era, technology is increasingly sophisticated, this is evidenced by the number of people using the internet via cell phones, laptops, and other communication tools. One of the developments of this technology is social media such as Instagram. Along with technological developments, Instagram users can upload and share photos and videos using hashtags (#) so that other users can find the results of their posts. Instagram has now become one of the social media used by more than 1 billion people in the world. In this study, the authors wanted to know the dominant topics discussed through the hashtag covidindonesia. This research was conducted using the Latent Dirichlet Allocation (LDA) method. The analysis was carried out after doing text mining on 84 captions from various users on Instagram. To determine the optimal number of topics, by looking at the value of perplexity and topic coherence. The results obtained are the top 5 topics that are the content material in the uploaded video. These topics include covidindonesia, covid_19, pandemics in Indonesia, and discussion of covid-19 virus mutations. |
| first_indexed | 2024-03-12T10:39:02Z |
| format | Article |
| id | doaj.art-cba372161f744d40bf07ca3b2c64f6b0 |
| institution | Directory Open Access Journal |
| issn | 2527-5836 2528-0074 |
| language | English |
| last_indexed | 2024-03-12T10:39:02Z |
| publishDate | 2022-01-01 |
| publisher | Universitas Islam Negeri Sunan Kalijaga Yogyakarta |
| record_format | Article |
| series | JISKA (Jurnal Informatika Sunan Kalijaga) |
| spelling | doaj.art-cba372161f744d40bf07ca3b2c64f6b02023-09-02T08:26:41ZengUniversitas Islam Negeri Sunan Kalijaga YogyakartaJISKA (Jurnal Informatika Sunan Kalijaga)2527-58362528-00742022-01-017110.14421/jiska.2022.7.1.1-9Analisis Topik Tagar Covidindonesia pada Instagram Menggunakan Latent Dirichlet AllocationKevin Rafi Adjie Putra Santoso0Asmaul Husna1Nadia Widyawati Putri2Nur Aini Rakhmawati3Institut Teknologi Sepuluh NopemberInstitut Teknologi Sepuluh NopemberInstitut Teknologi Sepuluh NopemberInstitut Teknologi Sepuluh NopemberIn this era, technology is increasingly sophisticated, this is evidenced by the number of people using the internet via cell phones, laptops, and other communication tools. One of the developments of this technology is social media such as Instagram. Along with technological developments, Instagram users can upload and share photos and videos using hashtags (#) so that other users can find the results of their posts. Instagram has now become one of the social media used by more than 1 billion people in the world. In this study, the authors wanted to know the dominant topics discussed through the hashtag covidindonesia. This research was conducted using the Latent Dirichlet Allocation (LDA) method. The analysis was carried out after doing text mining on 84 captions from various users on Instagram. To determine the optimal number of topics, by looking at the value of perplexity and topic coherence. The results obtained are the top 5 topics that are the content material in the uploaded video. These topics include covidindonesia, covid_19, pandemics in Indonesia, and discussion of covid-19 virus mutations.http://ejournal.uin-suka.ac.id/saintek/JISKA/article/view/2415Data CrawlingInstagramLatent Dirichlet AllocationCovid IndonesiaTopic Modeling |
| spellingShingle | Kevin Rafi Adjie Putra Santoso Asmaul Husna Nadia Widyawati Putri Nur Aini Rakhmawati Analisis Topik Tagar Covidindonesia pada Instagram Menggunakan Latent Dirichlet Allocation JISKA (Jurnal Informatika Sunan Kalijaga) Data Crawling Latent Dirichlet Allocation Covid Indonesia Topic Modeling |
| title | Analisis Topik Tagar Covidindonesia pada Instagram Menggunakan Latent Dirichlet Allocation |
| title_full | Analisis Topik Tagar Covidindonesia pada Instagram Menggunakan Latent Dirichlet Allocation |
| title_fullStr | Analisis Topik Tagar Covidindonesia pada Instagram Menggunakan Latent Dirichlet Allocation |
| title_full_unstemmed | Analisis Topik Tagar Covidindonesia pada Instagram Menggunakan Latent Dirichlet Allocation |
| title_short | Analisis Topik Tagar Covidindonesia pada Instagram Menggunakan Latent Dirichlet Allocation |
| title_sort | analisis topik tagar covidindonesia pada instagram menggunakan latent dirichlet allocation |
| topic | Data Crawling Latent Dirichlet Allocation Covid Indonesia Topic Modeling |
| url | http://ejournal.uin-suka.ac.id/saintek/JISKA/article/view/2415 |
| work_keys_str_mv | AT kevinrafiadjieputrasantoso analisistopiktagarcovidindonesiapadainstagrammenggunakanlatentdirichletallocation AT asmaulhusna analisistopiktagarcovidindonesiapadainstagrammenggunakanlatentdirichletallocation AT nadiawidyawatiputri analisistopiktagarcovidindonesiapadainstagrammenggunakanlatentdirichletallocation AT nurainirakhmawati analisistopiktagarcovidindonesiapadainstagrammenggunakanlatentdirichletallocation |