Analysis of Artificial Neural Networks Method Backpropagation to Improve the Understanding Student in Algorithm and Programming

Lubis, Muhammad Ridwan; Saputra, Widodo; Wanto, Anjar; Andani, Sundari Retno; Poningsih, P

doi:10.1088/1742-6596/1255/1/012032

Cited by 2 publications

(1 citation statement)

References 8 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Untuk hasil normalisasi data pengujian dapat dilihat pada tabel berikut ini. Adapun kode program pelatihan dan pengujian yang digunakan pada software Matlab sebagai berikut: >> net=newff(minmax(P), [20,1] Perintah yang digunakan untuk menampilkan frekuensi perubahan MSE.…”

Section: Metodologi Penelitianunclassified

Penerapan Jaringan Syaraf Tiruan dalam Memprediksi Tingkat Kriminal di Kabupaten Simalungun Menggunakan Algoritma Backpropagation

et al. 2019

Self Cite

View full text Add to dashboard Cite

The number of criminal rates that occur in the area of Simalungun Regency each year experiences an increase and decrease in crime cases each year. For example in the types of gambling crimes, in 2012 there were 89 cases, in 2013 there were 102 cases, in 2014 there were 92 cases, in 2015 there were 102 cases, in 2016 there were 94 cases, and in 2017 there were 86 cases. Then this problem is used as a basis in this study, which aims to provide information in the form of prediction data to the police in an effort to anticipate the rise in cases of types of crime in the following year. Efforts are being made to predict the level of crime in Simalungun Regency by applying the Bacpropagation algorithm ANN method. This research uses MATLAB R2011b and uses 5 architectural models to test the data that will be used for etimation / prediction, namely models 4-20-1, 4-30-1, 4-40-1, 4-50-1, 4- 70-1. Then the best architectural model results obtained are architectural models 4-20-1 with an accuracy of 93%, with the number of epochs 4575 in 51 seconds and MSE of 0,0009995011. This model will be used to predict Criminal Levels in Simalungun District from 2018 to 2022 with an accuracy of 93%.

show abstract

Section: Metodologi Penelitianunclassified

Penerapan Jaringan Syaraf Tiruan dalam Memprediksi Tingkat Kriminal di Kabupaten Simalungun Menggunakan Algoritma Backpropagation

et al. 2019

Self Cite

View full text Add to dashboard Cite

show abstract

Analysis of Deep Learning Cyclical order for Prediction of Fresh Milk Production in Sumatera

Saefullah¹,

Hendri²,

Lindawati³

et al. 2020

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

Milk is one of the most preferred and most easily absorbed nutrients. This drink naturally contains important nutrients, such as vitamins A, D, B12, protein, calcium, magnesium, phosphorus, and zinc, and others. Milk is also beneficial for children and adults. Starting from maintaining healthy bones and teeth, as a source of energy, and so on. In Indonesia, especially on the island of Sumatra, fresh milk production is carried out by cattle and goat farmers in cooperation with milk companies. This research have a purpose is to predict the production of fresh milk on the island of Sumatra so that the local government, as well as cattle and goat breeders on the island of Sumatra, have benchmarks to further increase the production of fresh milk in their respective regions in the future. The method that will be used in this research is Deep Learning Cyclical order which is the development of ANN. The research data used were data on the production of fresh milk on the island of Sumatra in 2009-2018 sourced from the Indonesian Statistics Agency. This research will be analyzed using 3 network architecture models, namely 4-5-1, 4-10-1 and 4-5-10-1 with the best network model chosen is 4-5-10-1 with an accuracy level of 90% and MSE value of 0.0157179042. Based on this best model a prediction of fresh milk production in Sumatra will be carried out in 2019-2020.

show abstract

Analysis of Artificial Neural Networks Method Backpropagation to Improve the Understanding Student in Algorithm and Programming

Cited by 2 publications

References 8 publications

Penerapan Jaringan Syaraf Tiruan dalam Memprediksi Tingkat Kriminal di Kabupaten Simalungun Menggunakan Algoritma Backpropagation

Penerapan Jaringan Syaraf Tiruan dalam Memprediksi Tingkat Kriminal di Kabupaten Simalungun Menggunakan Algoritma Backpropagation

Analysis of Deep Learning Cyclical order for Prediction of Fresh Milk Production in Sumatera

Contact Info

Product

Resources

About