Analisis Stunting pada Balita di Kota Baru, Bekasi Barat Menggunakan K-Nearest Neighbor dan Naive Bayes - Dalam bentuk pengganti sidang - Artikel Jurnal
LATIFA FIRDAUSI

Informasi Umum

Kode

25.04.1340

Klasifikasi

000 - General Works

Jenis

Karya Ilmiah - Skripsi (S1) - Reference

Subjek

Sains Data

Dilihat

43 kali

Informasi Lainnya

Abstraksi

Stunting is a condition caused by long-term malnu trition in children, leading to impaired cognitive abilities, speech difficulties, and learning challenges. In Indonesia, stunting is a significant concern, with the country ranking 27th out of 154 in prevalence according to UNICEF and WHO data. Early detection is vital for timely intervention. This study aims to compare the performance of the K-Nearest Neighbors (KNN) and Naive Bayes models in classifying stunting status in children. The analysis was conducted on a dataset collected from the Kota Baru Health Center in Bekasi Regency, which includes various features such as age, weight, height, gender, birth weight, and height-for-age ratio. Exploratory data analysis revealed a significant prevalence of stunting among children in the dataset, highlighting the urgent need for effective classification models. The analysis found KNN to outperform Naive Bayes across evaluation metrics, particularly on a balanced dataset with a 60:40 split, where KNN achieved an accuracy of 83.33% and an F1 score of 83.37%, compared to Naive Bayes’ accuracy of 73.08% and an F1 score of 70.98%. The results highlight KNN’s superior ability to handle class imbalance and its consistent per formance across various dataset splits. Based on these findings, KNN is recommended for stunting classification, particularly in situations involving class imbalance. Future research should explore optimization techniques such as feature selection and data augmentation to further improve model performance.

Koleksi & Sirkulasi

Tersedia 1 dari total 1 Koleksi

Pengarang

Nama	LATIFA FIRDAUSI
Jenis	Perorangan
Penyunting	Putu Harry Gunawan
Penerjemah

Penerbit

Nama	Universitas Telkom, S1 Data Sains
Kota	Bandung
Tahun	2025

Sirkulasi

Harga sewa	IDR 0,00
Denda harian	IDR 0,00
Jenis	Non-Sirkulasi

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