PREDIKSI HARGA SAHAM MENGGUNAKAN SENTIMEN PILKADA DKI JAKARTA 2017 DENGAN ALGORITMA SUPPORT VECTOR MACHINE
| Main Author: | Fadliansyah, Muhammad |
|---|---|
| Format: | Thesis NonPeerReviewed Book |
| Bahasa: | eng |
| Terbitan: |
, 2018
|
| Subjects: | |
| Online Access: |
http://eprints.umm.ac.id/47203/1/PENDAHULUAN.pdf http://eprints.umm.ac.id/47203/2/BAB%20I.pdf http://eprints.umm.ac.id/47203/3/BAB%20II.pdf http://eprints.umm.ac.id/47203/4/BAB%20III.pdf http://eprints.umm.ac.id/47203/5/BAB%20IV.pdf http://eprints.umm.ac.id/47203/6/BAB%20V.pdf http://eprints.umm.ac.id/47203/7/LAMPIRAN.pdf http://eprints.umm.ac.id/47203/ |
Daftar Isi:
- Twitter is one of the most widely used social media in Indonesia, not only as a means of sharing information related to personal matters but also as information. Not only as a center of information, twitter can also be as central data in the form of text. DKI Jakarta Election 2017 is one of the interesting topics to discuss. Not only as a determinant of Jakarta's leadership for the next 5 years, but because of the influence it has had on several sectors in Indonesia. A Tweet that discusses the topic of the 2017 DKI Jakarta Regional Election can be processed to get useful information, for example sentiments that occur during times. Sentiment that can be done in the context of prices during the election period. To be able to get sentiments from text data from twitter, anaylsis sentiment is to extract information from tweets that have been collected. To do sentiment analysis, the support vector machine algorithm is used to classify tweets in the target class. Results from the basis of sentiment as one weight in linear regression to predict prices. The results of the test show that the use of the DKI Jakarta Regional Election sentiment 2017 is to predict the stock price to be quite good. Where is the RMSE value that can be found by each different sector. BBRI 58,974, SRTG 101,188, WIKA 52,042, ADHI 93,420 and APLN 17,342.