Toothpaste Brand Prediction Based on Analysis of Teeth Condition and Price Preferences Using the Random Forest Algorithm

Afiyati Afiyati, Rahma Farah Ningrum, Faaza Naima

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.

Full Text:

PDF

References


Perbandingan Efektivitas Pasta Gigi Herbal Dengan Pasta Gigi Non Herbal Terhadap Penurunan Indeks Plak Pada Siswa Sdn Angsau 4 Pelaihari. Widodo, Rahmah R, Rachmadi P. 2, Banjarmasin : Universitas Lambung Mangkurat, 2014, Vols. Dentino Jurnal Kedokteran Gigi, 2.

PENGGUNAAN Na - CMC ( GELLING AGENT) DALAM SEDIAAN PASTA GIGI EKSTRAK KAYU SIWAK ( Salvadora persica ) DAN EKSTRAK DAUN SIRIH MERAH ( Piper crocatum ). Sofyan, Van Fatkhan. Purwokerto : Universitas Muhammadiyah Purwokerto, 2017.

Annur, Cindy Mutia. Produk Konsumen. Katadata. [Online] Katadata Media Network, Maret 24, 2023. [Cited: 12 01, 2023.] https://databoks.katadata.co.id/datapublish/2023/03/24/pepsodent-merek-pasta-gigi-yang-paling-sering-digunakan-konsumen-indonesia.

PENERAPAN DATA MINING UNTUK PREDIKSI MEREK PAKAIAN YANG PALING DIMINATI DENGAN METODE K-NEAREST NEIGHBOR (STUDI KASUS : PT. MATAHARI DEPARTEMENT STORE BINJAI). Andrean Pratama, Budi Serasi Ginting, Nurhayati. 2, Jakarta : Panca Budi, 2021, Jurnal Panca Budi, Vol. 14, pp. 54-64. ISSN.

PENERAPAN METODE K-NEAREST NEIGHBOR UNTUK PREDIKSI PENJUALAN SEPEDA MOTOR TERLARIS. Rismala, Irfan Ali, Ade Rizki Rinaldi. 1, Cirebon : Institut Teknologi Malang, 2023, Vols. 7, pp. 585-590. ISSN.

ANALISIS DAN IMPLEMENTASI FRAMEWORK CRISP-DM UNTUK MENGETAHUI PERILAKU DATA TRANSAKSI PELANGGAN. Muhammad Zain Imtiyaz, Muhammad Nasrun S.Si, M.T., Umar Ali Ahmad S.T, M.T. 1, Jakarta : Telkom University, 2015, Vol. 2. ISSN: 2355-9365 .

“Prediksi Kinerja Penjualan Karya Musik Menggunakan Framework CRISP-DM (Studi Kasus: X Music Indonesia). Purwarianti, A. A. Prajitno dan A. Bandung : Institut Teknologi Bandung, 2011, Vols. Jurnal Institut Teknologi Bandung bidang Teknik Elektro dan Informatika,.

Implementasi Algoritma Random Forest Untuk Menentukan Penerima Bantuan Raskin. Ilham Kurniawan, Duwi Cahya Puri Buani, Abdussomad, Widya Apriliah, Rizal Amegia Saputra. 2, Jakarta Pusat : Jurnal Teknologi Informasi dan Ilmu Komputer, 2023, Vol. 10. ISSN.

Penerapan Klasifikasi Random Forest Terhadap Data Gangguan Spektrum Autisme (ASD) Pada Anak – Anak Menggunakan Seleksi Fitur Principal Component Analysis. Luthfiyah Amatullah, Yuni Widiastiwi, Nurul Chamidah. Jakarta : Seminar Nasional Mahasiswa Ilmu Komputer dan Aplikasinya (SENAMIKA), 2022. ISSN.


Refbacks

  • There are currently no refbacks.


Jurnal Collabits
Portal ISSNPrint ISSN: XXXX-XXXX
Online ISSN: 3046-6709

Sekretariat
Fakultas Ilmu Komputer
Universitas Mercu Buana
Jl. Raya Meruya Selatan, Kembangan, Jakarta 11650
Tlp./Fax: +62215871335

http://publikasi.mercubuana.ac.id/index.php/collabits

e-mail: [email protected]

Creative Commons Licence
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.