EXPLORING DYNAMIC PROGRAMMING ALGORITHMS FOR IMPROVED ACCURACY IN FAKE NEWS DETECTION

PUTRA, AURELIO FIORENTINO (2023) EXPLORING DYNAMIC PROGRAMMING ALGORITHMS FOR IMPROVED ACCURACY IN FAKE NEWS DETECTION. Skripsi thesis, UNIVERSITAS KATOLIK SOEGIJAPRANATA.

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Abstract

The upturn of technology made radical changes in human life. Shame that a lot of us don’t use it wisely. Fake news or hoaxes are examples. Fake news detection is one solution to this problem. Dynamic programming is an old algorithm for optimization problems. Dynamic programming works by breaking a problem into subproblems. Dynamic programming has some types like memoization, tabulation, etc. Dynamic programming will be a good pairing with fake news detection because it makes the program easier to generate accuracy. For that choose some dynamic programming algorithms to compare better results. In this experiment, memoization, tabulation, and 1D memoization are some examples. The results are memoization checks the lowest score, meanwhile, tabulation checks the highest score, and 1D memoization checks the highest consistency score. Even though it has good results, this program wouldn’t run on a high tempo because it made the program miscalculate on accuracy.

Item Type: Thesis (Skripsi)
Subjects: 000 Computer Science, Information and General Works > 005 Computer programming, programs & data
Divisions: Faculty of Computer Science > Department of Informatics Engineering
Depositing User: Mr Yosua Norman Rumondor
Date Deposited: 16 Apr 2024 01:11
Last Modified: 16 Apr 2024 01:11
URI: http://repository.unika.ac.id/id/eprint/35158

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