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All Journal Format : Jurnal Imiah Teknik Informatika Sistemasi: Jurnal Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA IJISTECH (International Journal Of Information System & Technology) JUTEKIN (Jurnal Manajemen Informatika) Abdimasku : Jurnal Pengabdian Masyarakat Jurnal Sistem Komputer dan Informatika (JSON) Journal of Computer Networks, Architecture and High Performance Computing IJISTECH KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Sains Teknologi dan Sistem Informasi Jurnal Dinamika Informatika (JDI) Eduvest - Journal of Universal Studies
Sumarno Sumarno
STIKOM Tunas Bangsa
Aerospace Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Neuroscience Social Sciences

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Journal : IJISTECH

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Increasing Prediction Accuracy with the Backpropagation Algorithm (Case Study: Pematangsiantar City Rainfall) Yogi Prayoga; Dedy Hartama; Jalaluddin Jalaluddin; Sumarno Sumarno; Zulaini Masuro Nasution
IJISTECH (International Journal of Information System and Technology) Vol 3, No 1 (2019): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v3i1.27

Abstract

The more advanced science and technology from various disciplines, currently rainfall can be predicted by carrying out various empirical approaches, one of which is by using Artificial Neural Networks (ANN). This study aims to apply ANN with backpropogation algorithm in predicting rainfall. The research data used is BPS data of the transfer city. The results of the study state that of the 6 models (4-5-1, 4-10-1, 4-25-1, 4-5-10-1, 4-5-25-1 and 4-5-50-1) architecture that was trained and tested using Matlab 6.1 application software, the results showed that the 4-5-25-1 architectural model was the best model for making predictions with 75% truth accuracy, Training MSE 0.001004582, Testing MSE 0.021882712 and Epoch 59,076 . It is expected that research can provide input to the government, especially BMKG Pematangsiantar city in predicting Rainfall based on computer science so as to improve the quality of services in the fields of Meteorology, Climatology, Air Quality and Geophysics in accordance with applicable laws and regulations.
Improving Adaptive Learning Rate With Backpropogation on Retail Rice Price Prediction in Traditional Markets Erwin Binsar Hamonangan Ompusunggu; Solikhun Solikhun; Iin Parlina; Sumarno Sumarno; Indra Gunawan
IJISTECH (International Journal of Information System and Technology) Vol 3, No 1 (2019): November
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v3i1.26

Abstract

Rice is the most important staple food and carbohydrate food in the world especially people in Indonesia. This study aims to predict the retail price of rice in traditional markets using backpropogation by improvising Adaptive Learning Rate to increase the value of accuracy. Data sources were obtained from the Central Statistics Agency (BPS) in 33 provinces in Indonesia for the retail price of rice in the traditional market (Rupiah / kg) for the past 6 years (2011-2016). The results of the study state that the improvised learning rate uses 2 models: 2-10-1 and 2-15-1 (LR= 0,1; 0,5; 0,9) that the best architectural models are 4-15-1 (LR= 0.9) with an accuracy of 82%, Training MSE 0,000999936, Testing MSE 0.016051433 and Epoch 20515. The results of this study are expected to provide input to the government in providing input on predictions of retail rice prices that have an impact on the stability of rice prices in Indonesia.
Co-Authors Achmad Noerkhaerin Putra Budi Paul Sitompul Daniel Marpaung Dedy Hartama Erwin Binsar Hamonangan Ompusunggu Fatimah Putri Arfani Hasibuan Heru Satria Tambunan Iin Parlina Iin Parlina Ika Purnama Sari Indra Gunawan Jalaluddin Jalaluddin khairul zannah Solikhun Solikhun Solikhun Solikhun Titin Handayani Sinaga Wanto, Anjar Widodo Saputra Yogi Prayoga Zulaini Masruro Nasution Zulaini Masuro Nasution