JURNAL MEDIA INFORMATIKA BUDIDARMA
Vol 7, No 3 (2023): Juli 2023

Analisis Sentimen Terhadap Pemindahan Ibu Kota Negara Menggunakan Algoritma Naive Bayes Classifier dan K-Nearest Neightbors

Dedi Pramana (Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru)
M Afdal (Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru)
Mustakim Mustakim (Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru)
Inggih Permana (Universitas Islam Negeri Sultan Syarif Kasim Riau, Pekanbaru)



Article Info

Publish Date
23 Jul 2023

Abstract

The relocation of Indonesia's capital city is a hot topic of discussion at the moment. So that this government policy reaps a lot of reactions from various parties, especially the general public in Indonesia. Various reactions were shown with various expressions on various social media. One of the social media that has become a place for people to express themselves in responding to this government policy is Instagram. The comments poured by the community on posts on Instagram are very diverse ranging from positive, negative, and neutral comments. If these comments are processed properly, they can be used as evaluation material for the relocation of the State capital. Seeing this, a sentiment analysis is needed which is intended to classify the various comments so that they can be presented into information which will be intended to help the government make considerations in carrying out policies towards moving the national capital. In this study, data processing was carried out with the Naive Bayes Classifier and K-Nearest Neightbors algorithms with Instagram comment data on posts related to moving the national capital. Where the amount of data used is 2,404 comments. It was found that the accuracy of the NBC algorithm was 63.09% and K-Nearest Neightbors was 69.23% so it can be concluded that KNN is better than NBC. In addition, the popularity of public sentiment towards the relocation of the National Capital was also obtained with a positive sentiment of 28% totaling 643 comments, a neutral sentiment of 42% totaling 1025 comments, and a negative sentiment of 30% totaling 730 comments.

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Journal Info

Abbrev

mib

Publisher

Subject

Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering

Description

Decission Support System, Expert System, Informatics tecnique, Information System, Cryptography, Networking, Security, Computer Science, Image Processing, Artificial Inteligence, Steganography etc (related to informatics and computer ...