基于支持向量机的雅加达快速公交服务情感分析

Zayyana Nurthohari, D. I. Sensuse, Sofian Lusa
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引用次数: 2

摘要

雅加达快速公交公司是一家国有公司,提供公共交通服务。2021年10月,雅加达快速公交公司最近在推特上成为热门话题。Twitter公众意见可以作为公司的决策支持系统,用于提高和评估公司的服务。可以使用情感分析方法来检查公众意见,特别是Twitter上雅加达快速公交的用户。本研究的目的是为了更好地了解雅加达关于服务业的民意趋势。研究人员手动将推文分类为Informasi、apressiasi、Saran和complain。专业人士会将情绪分为有利、消极和中性。然后对数据进行预处理,以消除重复和无关信息。然后将使用机器学习来预测新数据的情绪。然后使用一系列测试来检查机器学习算法,以发现哪些核和特征提供了最佳的准确性。结果表明,该方法的准确率为92.00%,精密度为91.00%,召回率为92.00%,支持度为2123。数据显示,大多数雅加达人对快速公交印象不佳。大多数顾客对服务感到失望。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sentiment Analysis of Jakarta Bus Rapid Transportation Services using Support Vector Machine
Jakarta Bus Rapid Transportation is state-own company which have services in public transportation. On October 2021, Jakarta Bus Rapid Transportation was recently trending on Twitter. Twitter public views might be utilized for the company as a decision support system for enhance and evaluate the services of the company. A sentiment analysis method may be used to examine public opinion especialy users of Jakarta Bus Rapid Transportation on Twitter. The goal of this research is to better understand Jakarta's public opinion trends about services. The researchers manually classified tweets from the Tweepy collection as Informasi, Apresiasi, Saran, or Komplain. Professionals will classify the sentiment as favorable, negative, or neutral. The data was then pre-processed to eliminate duplicates and extraneous information. The sentiment of fresh data will then be predicted using machine learning. The machine learning algorithms were then examined using a number of tests to discover which kernels and features provided the best accuracy. The result of this method shows of 92.00 percent of accuracy, 91.00 percent of precision, 92.00 percent of recall, and 2123 of support. The majority of Jakartans, according to the data, have an unfavorable impression of bus rapid transit. The majority of customers were disappointed with the services.
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