SKRIPSI IF

PERBANDINGAN KINERJA ALGORITMA DECISION TREE DAN NAIVE BAYES DALAM KLASIFIKASI STRATA POSYANDU DI KECAMATAN ANTAPANI

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ABSTRAK

Pos Pelayanan Terpadu (Posyandu) merupakan salah satu bentuk pelayanan
kesehatan masyarakat yang berperan penting dalam meningkatkan derajat
kesehatan masyarakat. Dalam pelaksanaannya, Posyandu menghasilkan berbagai
data operasional yang dapat dimanfaatkan untuk mendukung proses evaluasi dan
pengambilan keputusan. Namun, data tersebut umumnya hanya digunakan sebagai
arsip administratif sehingga pemanfaatannya belum optimal. Penelitian ini
bertujuan untuk membandingkan kinerja algoritma Decision Tree dan Naive Bayes
dalam mengklasifikasikan strata Posyandu di Kecamatan Antapani.
Penelitian menggunakan data sekunder Posyandu Kecamatan Antapani.
Tahapan penelitian meliputi preprocessing data, pembagian data menjadi data latih
dan data uji, pelatihan model, serta evaluasi menggunakan Confusion Matrix,
Accuracy, Precision, Recall, dan F1-Score. Implementasi dilakukan menggunakan
bahasa pemrograman Python dengan pustaka Scikit-learn.
Hasil penelitian menunjukkan bahwa algoritma Decision Tree memperoleh
nilai Accuracy sebesar 48,28%, Precision sebesar 47,62%, Recall sebesar 48,28%,
dan F1-Score sebesar 47,57%. Sementara itu, algoritma Naive Bayes memperoleh
nilai Accuracy sebesar 43,68%, Precision sebesar 48,07%, Recall sebesar 43,68%,
dan F1-Score sebesar 38,61%. Berdasarkan hasil evaluasi tersebut, algoritma
Decision Tree menunjukkan performa yang lebih baik dibandingkan algoritma
Naive Bayes karena memperoleh nilai Accuracy, Recall, dan F1-Score yang lebih
tinggi.
Kata Kunci: Data Analytics, Decision Tree, Naive Bayes, Klasifikasi, Strata
Posyandu

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ABSTRACT

Integrated Healthcare Centers (Pos Pelayanan Terpadu or Posyandu) play
an important role in improving community health services. In their operations,
Posyandu generate various types of data that can be utilized to support evaluation
and decision-making processes. However, these data are generally used only for
administrative purposes, resulting in limited utilization. This study aims to compare
the performance of the Decision Tree and Naive Bayes algorithms in classifying
Posyandu strata in Antapani District.
This research utilized secondary Posyandu data collected in Antapani
District. The research stages included data preprocessing, dataset splitting into
training and testing sets, model training, and evaluation using a Confusion Matrix,
Accuracy, Precision, Recall, and F1-Score. The implementation was carried out
using the Python programming language and the Scikit-learn library.
The results showed that the Decision Tree algorithm achieved an Accuracy
of 48.28%, Precision of 47.62%, Recall of 48.28%, and F1-Score of 47.57%.
Meanwhile, the Naive Bayes algorithm achieved an Accuracy of 43.68%, Precision
of 48.07%, Recall of 43.68%, and F1-Score of 38.61%. Based on these evaluation
results, the Decision Tree algorithm demonstrated better performance than the
Naive Bayes algorithm, as indicated by its higher Accuracy, Recall, and F1-Score
values.
Keywords: Data Analytics, Decision Tree, Naive Bayes, Classification, Posyandu
Strata.

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Ketersediaan

S260908025

607.2 MUH p

Perpustakaan STMIK AMIKBANDUNG

Tersedia

Informasi Detil

Judul Seri

-

No. Panggil

607.2 MUH p

Penerbit

: ., 2026

Deskripsi Fisik

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Bahasa

Indonesia

ISBN/ISSN

-

Klasifikasi

NONE

Tipe Isi

-

Tipe Media

-

Tipe Pembawa

-

Edisi

-

Subyek

SKRIPSI IF

Info Detil Spesifik

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Pernyataan Tanggungjawab

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Versi lain/terkait

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