Kebenaran dalam Perspektif Filsafat Ilmu Pengetahuan dan Implementasi dalam Data Science dan Machine Leaning - Mohamad Idris; Riza Ibnu Adam; Yulrio Brianorman; Rinaldi Munir; Dimitri Mahayana (Undiksha, 2022)
The development of data science or machine learning is experiencing swift growth. This development can become a pseudoscience due to the process of collecting, using algorithms, and processing data that are not per research standards. Machine learning is one of numerous artificial intelligence (AI) techniques that allow a machine to learn independently. Several machine learning implementations include consulting robots, process optimization, credit scoring, security, and services. Data science often uses supervised learning algorithms, which can be trapped intopseudoscience due to errors in the use and processing of data in research. The solution to avoid this is to apply the epistemological concept of Karl Popper, which is related to the falsification ofscience to solve the problem of demarcation. To enhance it, you can also use the principles of the Four Theory of Truth, namely coherence, correspondence, pragmatism, and consensus.