PUBLIC SENTIMENT ANALYSIS OF PASAR LAMA TANGERANG  USING K-NEAREST NEIGHBOR METHOD AND PROGRAMMING LANGUAGE R

Hustinawaty Hustinawaty; Rama Al Azis Dwiputra; Tavipia Rumambi

doi:10.35760/ik.2019.v24i2.2367

PUBLIC SENTIMENT ANALYSIS OF PASAR LAMA TANGERANG USING K-NEAREST NEIGHBOR METHOD AND PROGRAMMING LANGUAGE R

Hustinawaty Hustinawaty
Department of Information Systems, Faculty of Computer Science and Information Technology, Universitas Gunadarma
Indonesia

Rama Al Azis Dwiputra
Department of Information Systems, Faculty of Computer Science and Information Technology, Universitas Gunadarma
Indonesia

Tavipia Rumambi
Department of Information Systems, Faculty of Computer Science and Information Technology, Universitas Gunadarma
Indonesia

DOI: http://dx.doi.org/10.35760/ik.2019.v24i2.2367

Article Submitted: 06 February 2020

Article Published: 08 February 2020

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.

Keywords

Classification,KNN,Opinion,Pasar Lama, Sentiment

References

R. R. Sani, J. Zeniarza, and A. Luthfiarta, “Pengembangan aplikasi penentuan tema tugas akhir berdasarkan data abstrak menggunakan algoritma K-Nearest Neighbor”, In Prosiding Seminar Nasional Multi Disiplin Ilmu & Call For Papers Unisbank (Sendi_U) ke-2, 2016, pp. 103 - 111.

Y. Samuel, R. Delima, and A. Rachmat, “Implementasi metode K-Nearest Neighbor dengan decision rule untuk klasifikasi subtopik berita”, Jurnal Informatika, vol. 10, no. 1, pp. 1 – 15, 2014.

I. Menarianti, “Klasifikasi data mining dalam menentukan pemberian kredit bagi nasabah koperasi“, Jurnal Ilmiah Teknosains, vol. 1 No. 1, pp. 36 – 45, 2015.

R. R. Sani, J. Zeniarza, and A. Luthfiarta, “Penerapan algoritma K-Nearest Neighbor pada information retrieval dalam penentuan topik referensi tugas akhir”, Journal of Applied Intelligent System, vol. 1, no. 2, pp. 123 – 133, 2016.

Mustakim and G. Oktaviani, “Algoritma K-Nearest Neighbor Classification sebagai sistem prediksi predikat prestasi mahasiswa”, Jurnal Sains, Teknologi dan Industri, vol. 13, no. 2, pp. 195–202, 2016.

F. Agus, H. R. Hatta, and Mahyudin, “Pengklasifikasian dokumen berbahasa Arab menggunakan K-Nearest Neighbor”, Jurnal SIFO Mikroskil, vol. 18, no. 1, pp. 43–56, 2017.