Combating Hoax and Misinformation in Indonesia Using Machine Learning What is Missing and Future Directions
DOI:
https://doi.org/10.21512/emacsjournal.v6i2.11556Keywords:
Hoax, Misinformation, Detection Process, Machine LearningAbstract
According to survey from several organizations in Indonesia to 10.000 respondents with age range from 13-70 years at 2022 and 2023, 56% respondents are mainly found hoax and misinformation on social media and online media platform with 45% respondents are hesitant with their ability to differentiate true information with hoax. Most of the hoax and false information researchers in Indonesia also still have some challenges such as on the dataset detection method. This research will use the systematic literature review using PICOC, inclusion-exclusion rules, and quality’s checklist. The results based on 20 papers are data crawler’s application usage, labelling, and text pre-processing are the major steps to improve the dataset with more than 10.000 data. There are also already some advance methodologies for hoax and misinformation detection in text form such as graph-based learning and special architecture design, yet there’s still a little number for the detection in media form. The recommendation includes the dataset improvement steps, literature, and methodologies in media form.
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