SKRIPSI Sistem Informasi

PERBANDINGAN AKURASI ANTARA METODE K-NEAREST NEIGHBORD (KNN) DAN ARTIFICIAL NEURAL NETWORK (ANN) UNTUK KLASIFIKASI INDEKS PEMBANGUNAN MANUSIA KABUPATEN/KOTA DI PULAU JAWA

---

PERBANDINGAN AKURASI ANTARA METODE K-NEAREST NEIGHBOR
(KNN) DAN ARTIFICIAL NEURAL NETWORK (ANN) UNTUK KLASIFIKASI
INDEKS PEMBANGUNAN MANUSIA KABUPATEN/KOTA DI PULAU JAWA
Garwita Widyadhana Putri1), Mochamad Husni2) , Rahayu Widayanti3)
Sistem Informasi, STMIK PPKIA Pradnya Paramita Malang
witawidyaa12@gmail.com 1)
, husni@stimata.ac.id 2)
, rahayu@stimata.ac.id 3)
Abstract
In 2021, 56.1% of Indonesia's population was on the Java Island, so the government needs to do
mapping for policy making in various fields. Classifying the Human Development Index (HDI) can
be done to assist the government in measuring the results of human resource development. The
purpose of this research is to compare the accuracy results of two methods, namely K-Nearest
Neighbor (KNN) and Artificial Neural Network (ANN) to classify the HDI of districts/cities in Java
Island. The results showed that the application of KNN and ANN methods on the same data resulted
in different accuracy values. In the KNN method, using 80%-20% training and testing data, the K=7
value shows the highest accuracy rate [95.83%]. While the ANN method with the split 70%-30%,
resulting in the highest accuracy value [94.44%]. By calculation, KNN method produces a higher
accuracy value. However, the evaluation results using Fold Cross Validation show that the best KNN
model is at K=3, with a mean score 84.85%. While in the model of the highest accuracy value of the
ANN method, there is overfitting. Based on this comparison, it can be concluded that the highest
accuracy value of both KNN and ANN methods both have weaknesses.

---

Ketersediaan

19510003

001.42 P Gar Skr SistemInfoermasi

Perpus STMIK

Tersedia

Informasi Detail

Judul Seri

-

No. Panggil

001.42 P Gar Skr SistemInfoermasi

Penerbit

: .,

Deskripsi Fisik

-

Bahasa

Indonesia

ISBN/ISSN

-

Klasifikasi

NONE

Tipe Isi

-

Tipe Media

-

Tipe Pembawa

-

Edisi

-

Subjek

-

Info Detail Spesifik

-

Pernyataan Tanggungjawab

Garwita Widyadhana Putri

Versi lain/terkait

Lampiran Berkas

Komentar

---

Anda harus login sebelum memberikan komentar