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Analisis Sentimen pada Acara Televisi Menggunakan Improved K-Nearest Neighbor
| Content Provider | Semantic Scholar |
|---|---|
| Author | Oktinas, Willa |
| Copyright Year | 2017 |
| Abstract | Public sentiment can be used as one of the indicator by tv stations to determine the quality of their tv programme. On twitter, information extraction of this public sentiment can be done to determine their tv programme’s quality too. One of the method to do the information extraction on twitter is by using sentiment analysis method. In this research, sentiment analysis method is applied and it consists of 3 stages. The first stage is pre-processing which consists of cleansing, case folding, tokenizing, stopword removal, stemming, and redundancy filtering. The second stage is weighting process for every single word by using TF-IDF method. Then, the last stage is the sentiment classification process which is divided into 3 sentiment category specifically positive, negative and neutral, this process is done using the improved knearest neighbor method. The result obtained from this research generated the highest accuracy with k=10 as big as 90%. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://repositori.usu.ac.id/bitstream/handle/123456789/2416/121402091.pdf?isAllowed=y&sequence=1 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
