Klasifikasi data Twitter dalam bahasa Indonesia untuk tema konten pada aplikasi Fajr: Studi kasus XYZ = Classification of Twitter data in indonesian languange for content theme Fajr application: Case study XYZ / Ilham Aulia Malik
| Main Authors: | Ilham Aulia Malik, author, Add author: Wahyu Catur Wibowo, supervisor, Add author: Yova Ruldeviyani, supervisor, Add author: Indra Budi, examiner, Add author: Mohamad Ivan Fanany, co-promotor |
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| Format: | Bachelors |
| Terbitan: |
, 2015
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| Subjects: | |
| Online Access: |
https://lib.ui.ac.id/detail?id=20416213 |
Daftar Isi:
- [<b>ABSTRAK</b><br> Aplikasi Fajr merupakan aplikasi mobile yang memiliki konten islami dengan fitur utama yaitu Fajr Cards. Namun, Fajr Cards belum mampu menarik perhatian pengguna dengan minimnya jumlah pengguna fitur ini. Fajr Cards sebagai fitur yang berbasiskan kepada konten dapat ditingkatkan dengan memberikan konten yang relevan dengan pengguna. Twitter sebagai media sosial memiliki data real-time dan jumlah yang banyak sehingga dapat menjadi sumber data aktual untuk dianalisa. Data Twitter dapat dianalisa dengan menggunakan text mining. Salah satunya yaitu text classification atau klasifikasi teks Tujuan penelitian ini adalah untuk menentukan metode klasifikasi apa yang terbaik untuk klasifikasi tema konten Fajr Cards. Metodologi yang digunakan menggunakan tahapan preprocess Text Mining dan penggunaan metode Text Mining yaitu Text Classification. Hasil yang diharapkan adalah gambaran bagaimana data Twitter diproses untuk proses klasifikasi dan metode klasifikasi apa yang terbaik untuk klasifikasi tema konten Fajr Cards. <hr> <b>ABSTRACT</b><br> Fajr application is a mobile application that contains Islamic contents for moslem daily life. To get more users, the developers create a main feature called Fajr Cards. But, Fajr Cards has not been able to attract users. It is based on the minimum of users that using Fajr Cards. Fajr Cards as a feature based on contents can be improved by adding more content that have relevance value to users. Twitter as microblog social media have real time and a lot of data. Those data can be used as an actual source data for analyze. Text mining such as text classification will be used to analyze the data. The purpose of this research is to get what classification method that suited best for this classification. Methodology that used in this research is Text Mining including preprocess and Text Classification. The expected results is to know what classification method that suited best for Fajr Card?s theme classification.;Fajr application is a mobile application that contains Islamic contents for moslem daily life. To get more users, the developers create a main feature called Fajr Cards. But, Fajr Cards has not been able to attract users. It is based on the minimum of users that using Fajr Cards. Fajr Cards as a feature based on contents can be improved by adding more content that have relevance value to users. Twitter as microblog social media have real time and a lot of data. Those data can be used as an actual source data for analyze. Text mining such as text classification will be used to analyze the data. The purpose of this research is to get what classification method that suited best for this classification. Methodology that used in this research is Text Mining including preprocess and Text Classification. The expected results is to know what classification method that suited best for Fajr Card?s theme classification.;Fajr application is a mobile application that contains Islamic contents for moslem daily life. To get more users, the developers create a main feature called Fajr Cards. But, Fajr Cards has not been able to attract users. It is based on the minimum of users that using Fajr Cards. Fajr Cards as a feature based on contents can be improved by adding more content that have relevance value to users. Twitter as microblog social media have real time and a lot of data. Those data can be used as an actual source data for analyze. Text mining such as text classification will be used to analyze the data. The purpose of this research is to get what classification method that suited best for this classification. Methodology that used in this research is Text Mining including preprocess and Text Classification. The expected results is to know what classification method that suited best for Fajr Card?s theme classification., Fajr application is a mobile application that contains Islamic contents for moslem daily life. To get more users, the developers create a main feature called Fajr Cards. But, Fajr Cards has not been able to attract users. It is based on the minimum of users that using Fajr Cards. Fajr Cards as a feature based on contents can be improved by adding more content that have relevance value to users. Twitter as microblog social media have real time and a lot of data. Those data can be used as an actual source data for analyze. Text mining such as text classification will be used to analyze the data. The purpose of this research is to get what classification method that suited best for this classification. Methodology that used in this research is Text Mining including preprocess and Text Classification. The expected results is to know what classification method that suited best for Fajr Card’s theme classification.]