JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI
Vol. 20 No. 2 (2024): JANUARY 2024

Comparison Predictions of the Demam Berdarah Dengue (DBD) using Model Exponential Smoothing: Pegel’s Classification and ChatGPT

Wiwik Wiyanti (Universitas Matana)
Bakti Siregar (Unknown)



Article Info

Publish Date
24 Dec 2023

Abstract

The evolution of AI since the Covid-19 pandemic has developed very rapidly. Until 2023, AI is claimed to be a threat to several professional jobs, especially data analysts and scientists. The purpose of this research is to check the effectiveness chat-GPT to predict about demam berdarah dengue (DBD) case. Method of the analyzing the data in this research is Mixed method. Quantitative method using exponential smoothing: pegel’s classification and qualitative method using GPT-3. The aim of this research is to check whether ChatGPT can predict the demam berdarah dengue (DBD) data time series. The prediction result are check it by exponential smoothing: pegel’s classification method. The benefit of this research is it can be used to reference how far the evolution of AI can be threaten the profession of data analyst or data scientist. The result of this study conclude that the ChatGPT (GPT-3) can’t predict DBD’d data correctly.

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Journal Info

Abbrev

jmsk

Publisher

Subject

Mathematics

Description

Jurnal ini mempublikasikan paper-paper original hasil-hasil penelitian dibidang Matematika, Statistika dan Komputasi ...