Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Journal Collabits
Ningrum, Rahma Farah
Unknown Affiliation
Computer Science & IT Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Journal Collabits

 1 
Toothpaste Brand Prediction Based on Analysis of Teeth Condition and Price Preferences Using the Random Forest Algorithm Afiyati, Afiyati; Ningrum, Rahma Farah; Naima, Faaza
Journal Collabits Vol 1, No 1 (2024)
Publisher : Journal Collabits

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/collabits.v1i1.25560

Abstract

This study aimed to predict toothpaste brands based on an analysis of dental conditions and price preferences using the Random Forest algorithm and the CRISP-DM approach. The research results indicated that the variables of tooth color range and frequency of toothache had the highest influence, suggesting that consumers were more likely to choose a brand based on tooth color and sensitivity. Evaluation using the Confusion Matrix and Classification Report models demonstrated good performance with an accuracy of 91.3%. Based on the result, the model could serve as a robust foundation for developing a GUI-based Toothpaste Brand Prediction Application using the tkinter library, assisting users in making more informed decisions.
Co-Authors Afiyati, Afiyati Naima, Faaza