Using classification and prediction algorithms to process surveys in the Altair® RapidMiner data mining software

Gabriela Pazmiño Moreira; Olga Lilian Mendoza Talledo; Homero Mendoza Rodríguez; María José Pazmiño Moreira; Jonathan Josué Proaño Morales

doi:10.47606/ACVEN/PH0319

Autores/as

Gabriela Pazmiño Moreira Department of data processing and survey Design, prodata & Desing, 130103 https://orcid.org/0000-0002-8443-9189
Olga Lilian Mendoza Talledo Universidad Técnica de Manabí https://orcid.org/0000-0001-6053-562X
Homero Mendoza Rodríguez Universidad Técnica de Manabí https://orcid.org/0009-0004-9049-4207
María José Pazmiño Moreira Department of data processing and survey Design, prodata & Desing, 130103 https://orcid.org/0000-0001-6035-4909
Jonathan Josué Proaño Morales Universidad Técnica de Manabí https://orcid.org/0000-0002-7140-5318

DOI:

https://doi.org/10.47606/ACVEN/PH0319

Palabras clave:

Data, productivity, big data, marketing, population behavior

Resumen

Currently, analyzing and processing surveys to look for patterns has become essential to solve and find new product distribution strategies. For this reason, surveys have been analyzed using classification and prediction algorithms to look for patterns. To do this, the free software Altair® RapidMiner Studio Version 2024 was applied to the information extracted from surveys carried out through Google Forms and distributed online throughout the country. The surveys consisted of 30 questions, most of which were multiple choice. AdaBoost, Naive Bayes and deep learning algorithms were used to classify, analyze and find patterns between the questions. Thus, the vaccines used varied according to the age groups and the media in which the advertisements were shown. In conclusion, this tool is considered easy to use due to its simplicity, as it offers algorithms that allow accurate classification and prediction of surveys, as well as the search and visualization of patterns.

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