Implementasi Metode K-Nearest Neighbor Untuk Mengklasifikasi Jenis Penyakit Katarak

Safaat, M; Sahari, A; Lusiyanti, D

doi:10.22487/2540766x.2020.v17.i1.15184

Cited by 2 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Algoritma Nearest Neighbour merupakan teknik sederhana untuk mencari jarak terdekat dari tiap -tiap kasus (cases) yang ada di dalam database, dan seberapa mirip ukuran kemiripan (similarity) setiap source case yang ada di dalam database dengan target case [11]. Dengan fungsi similarity sebagai berikut [12], [13]:…”

Section: Algoritma K-nearest Neighbourunclassified

Analisis K-Nearest Neighbour Dalam Mendiagnosa Grandemultipara

Nasyuha¹,

Zunaidi²,

Purwadi³

2022

json

View full text Add to dashboard Cite

Grandemultipara are women who give birth more than four times usually experience complications in pregnancy and childbirth. Grandemultipara or better known as mothers who give birth more than 4 times can cause various pregnancy complications that will be experienced by the mother, one of which is bleeding. Grandemultipara pregnancies are included in high-risk pregnancies, because complications can occur either during pregnancy or childbirth. The K-NN algorithm can be applied in the process of diagnosing human diseases, so several references are taken including those used in diagnosing several diseases. With the K-NN algorithm that will be used in this study, where data on symptoms of Grandemultipara disease obtained from an expert is processed according to the algorithm to produce accurate diagnostic information for Grandemultipara disease. Analysis of the K-NN method is able to provide information and solutions in solving the problems of Grandemultipara disease.

show abstract

Section: Algoritma K-nearest Neighbourunclassified

Analisis K-Nearest Neighbour Dalam Mendiagnosa Grandemultipara

Nasyuha¹,

Zunaidi²,

Purwadi³

2022

json

View full text Add to dashboard Cite

show abstract

“…Dalam penelitian ini akan digunakan dua algoritma, yaitu K-Nearest Neighbor (K-NN) dan Single Layer Perceptron (SLP). K-Nearest Neighbor (K-NN) adalah suatu metode untuk mengklasifikasikan objek berdasarkan data training yang jaraknya paling dekat dengan objek tersebut (Safaat et al, 2020). Sedangkan, Single Layer Perceptron merupakan jenis jaringan saraf yang paling sederhana terdiri dari satu lapisan yang terdiri atas satu lapisan input dan satu lapisan output (Muhammad Varriel Avenazh Nizar et al, 2022).…”

unclassified

Algoritma K-Nearest Neighbor (K-Nn) Dan Single Layer Perceptron (Slp) Untuk Klasifikasi Penyakit Alzheimer

Dewi,

Desiani,

Salamah

et al. 2023

JTT

View full text Add to dashboard Cite

Alzheimer's disease is a brain disorder that causes memory loss, decreased thinking skills, communication difficulties, and behavioral changes. Early detection of this disease is very important for proper treatment and planning of medical needs. However, there is currently no drug that can cure Alzheimer's. Therefore, this study aims to develop accurate early predictions for Alzheimer's disease by comparing two algorithms: K-Nearest Neighbor (KNN) and Single Layer Perceptron (SLP) using the percentage split method. The results showed that testing using the K-NN algorithm resulted in an accuracy of 96%. The precision and recall values for class 0 (nondemented) are 93% and 100%, respectively, while for class 1 (demented) are 100% and 91%. On the other hand, testing using the SLP algorithm produces an accuracy of 99%. The precision and recall values for class 0 (nondemented) are 97% and 100% respectively, while for class 1 (demented) are 100% and 98%. Based on a comparison of the values for accuracy, precision, and recall, as well as the performance of the two classification methods, it can be concluded that the implementation of the Single Layer Perceptron algorithm provides the best prediction for early detection of Alzheimer's disease. These findings provide potential use of this algorithm in facilitating early diagnosis and timely intervention for patients with Alzheimer's.

show abstract

Implementasi Metode K-Nearest Neighbor Untuk Mengklasifikasi Jenis Penyakit Katarak

Cited by 2 publications

References 0 publications

Analisis K-Nearest Neighbour Dalam Mendiagnosa Grandemultipara

Analisis K-Nearest Neighbour Dalam Mendiagnosa Grandemultipara

Algoritma K-Nearest Neighbor (K-Nn) Dan Single Layer Perceptron (Slp) Untuk Klasifikasi Penyakit Alzheimer

Contact Info

Product

Resources

About