Theovito Joseph Melmambessy
Universitas Kristen Satya wacana

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

Analysis of the Opinion Students about The Online Learning System During the Pandemic Using The K-NN and Naïve Bayes Methods Theovito Joseph Melmambessy
Jurnal Teknologi Informasi dan Pendidikan Vol 16 No 1 (2023): Jurnal Teknologi Informasi dan Pendidikan
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jtip.v16i1.702

Abstract

Abstract— Coronavirus or known as Covid-19 is an outbreak that has spread to various parts of the world including Indonesia. Residents of Ambon city also felt the difficult times of surviving in the midst of a pandemic. The adverse impact of this pandemic has notharmed the people of A mbon city, especially the lower middle class. Since the entry of this pandemic into the city of Ambon, the local government has continuously taken steps to overcome the pandemic by conducting PSBB, PPKM, and implementing various rules aimed at limiting community activities outside the home so that crowds do not occur. The negative impact due to Covid-19 also spreads to all aspects such as economic, socio-cultural, tourism aspects, and also affects the learning process in the city of Ambon, where the learning process is carried out online. This online learning process is a problem for people who do not have the supporting means to learn online. Since the Ministry of Education and Culture made this online learning decision, there have been various student opinions in response to this, especially Pattimura University students. In this study, an analysis of student opinions was carried out to find out negative sentiment, positive or neutral sentiment in students related to the online learning process policy made by the government using the K-Nearest Neighbors method and the Naïve Bayes Classifier method. in this study produced an accuracy value from the classification obtained using the KNN method was 37.12%, and the Naïve Bayes method produced a greater accuracy value of about 42.89% which was positive. This shows that the student's response to the performance and rules of online learning at one of the state universities in Ambon, Pattimura University is felt to be good for the online teaching and learning process.