Implementation Of Artificial Neural Network (ANN) Classification In Type 2 Diabetes Mellitus Cases
Abstract
Machine learning is a type of artificial intelligence that provides computers with the ability to learn from data. There are three main branches of machine learning, namely supervised machine learning, unsupervised learning, and reinforcement learning. One of the categories in supervised machine learning is classification. An example of a classification algorithm is Artificial neural networks are information processing systems that have characteristics and capabilities that are generally similar to human neural networks. A neural network consists of an arrangement of connections between neurons which is called architecture, a method for determining weights on connections which is called a training process or algorithm, and an activation function. This algorithm is used to classify type 2 diabetes mellitus patients as having complications and no complications by dividing training data and testing data, namely 70:30, to get the best results, namely multi layer (3 Hidden Layers with number of nodes/neurons= 5,4,3) .
Machine Learning adalah jenis kecerdasan buatan yang memberi komputer kemampuan untuk belajar dari data. Ada tiga cabang utama pembelajaran mesin, yaitu pembelajaran mesin yang diawasi, pembelajaran tanpa pengawasan, dan pembelajaran penguatan. Salah satu kategori dalam pembelajaran mesin yang diawasi adalah klasifikasi. Contoh algoritma klasifikasi adalah Jaringan syaraf tiruan merupakan sistem pengolah informasi yang mempunyai karakteristik dan kemampuan yang umumnya mirip dengan jaringan syaraf manusia. Jaringan saraf terdiri dari susunan koneksi antar neuron yang disebut arsitektur, metode penentuan bobot koneksi yang disebut proses pelatihan atau algoritma, dan fungsi aktivasi. Algoritma ini digunakan untuk mengklasifikasikan pasien diabetes melitus tipe 2 memiliki komplikasi dan tanpa komplikasi dengan membagi data latih dan data uji yaitu 70:30, untuk mendapatkan hasil terbaik yaitu multi layer (3 Hidden Layer dengan jumlah node/neuron= 5,4,3).
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