Visualizing stemming techniques on online news articles text analytics

Stemming is the process to convert words into their root by stemming algorithm. It one of main processes in text analytics where data needs go through before proceeding further analysis. Text a very common practice nowadays that practiced toanalyze contents from various sources such as mass media and social. In this study, two different techniques; Porter Lancaster are evaluated. The differences outputs resulted techniques discussed based on error visualization. finding study shows performs better than stemming, 43%, produced. Visualization can still be accommodated stemmed but some understanding background needed tool users ensure correct interpretation made visualization outputs.