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All Journal International Journal of Electrical and Computer Engineering Jurnal Ilmiah Informatika Komputer MediaTor: Jurnal Komunikasi Jurnal KOMUNIKA Perfecting a Video Game with Game Metrics Bulletin of Electrical Engineering and Informatics Jurnal Ilmu Komunikasi Jurnal Kajian Komunikasi Jurnal Ilmiah FIFO Jurnal ASPIKOM Khadimul Ummah Journal of Social Dedication Komunika: Jurnal Dakwah dan Komunikasi Jurnal Pengabdian Kepada Masyarakat Darma Saskara
Hustinawaty Hustinawaty, Hustinawaty
Universitas Gunadarma
Religion Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Languange, Linguistic, Communication & Media Library & Information Science Public Health Social Sciences Other

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Journal : Jurnal Ilmiah Informatika Komputer

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PUBLIC SENTIMENT ANALYSIS OF PASAR LAMA TANGERANG USING K-NEAREST NEIGHBOR METHOD AND PROGRAMMING LANGUAGE R Hustinawaty, Hustinawaty; Dwiputra, Rama Al Azis; Rumambi, Tavipia
Jurnal Ilmiah Informatika Komputer Vol 24, No 2 (2019)
Publisher : Universitas Gunadarma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35760/ik.2019.v24i2.2367

Abstract

Pasar Lama Tangerang is a tourist attraction in the city of Tangerang. With the development of current technology, the public can provide an overview of how the facilities and services are provided by expressing opinions on the internet. However, it is difficult to distinguish which opinions belong to positive or negative opinions. Sentiment analysis is needed to overcome this problem. The stage in sentiment analysis starts with collecting data first, then the data is processed. Furthermore, the data that has been propagated is given a sentiment classification using the K-Nearest Neighbor (KNN) algorithm. Then the classification results obtained an accuracy of 83% with a value of k = 1 of 120 data divided by 92 positive and 28 negative comments. Sentiment analysis is made using the R and Rstudio programming languages as supporting software.
Co-Authors Abdullah Abdullah Abdullah Abdullah Abdullah Abdullah Achmad Benny Mutiara Ary Bima Kurniawan Baby Lolita B., Baby Lolita Dewi Agushinta R. Dwiputra, Rama Al Azis Edy Prihantoro Eldianisa Adesita Eri Prasetyo Wibowo, Eri Prasetyo Faisal Arkan Henny Medyawati Herik Suger Ihsan Jatnika Nur Sultan Salahuddin Rifiana Arief Rila Setyaningsih Rila Setyaningsih Sarifuddin Madenda Setyaningsih, Rila Sri Purnomo Sari Sulardi Sulardi Supiani Supiani Suryarini Widodo Tavipia Rumambi Tavipia Rumambi, Tavipia Tubagus Maulana Kusuma