Prediction of Life Expectancy in Aceh Province by District City Using the Cyclical Order Algorithm

Teuku Afriliansyah(1*), Z Zulfahmi(2),

(1) STKIP Bumi Persada Lhokseumawe, Aceh, Indonesia
(2) STKIP Bumi Persada Lhokseumawe, Aceh, Indonesia
(*) Corresponding Author

Abstract


Indicators to evaluate the role of the local and central government in the welfare of its population, especially in the health sector, can be seen from the life expectancy of the community. Therefore the aim of this study is to predict the life expectancy of the Acehnese using the Cyclical Order Weight / Bias Algorithm. This study uses life expectancy data for the population of Aceh in 2010-2019 based on city districts consisting of 23 regions, which were obtained from the Aceh Central Statistics Agency. This study uses 6 architectural models, including: 8-5-1, 8-6-1, 8-7-1, 8-8-1, 8-9-1 and 8-10-1. After analyzing and calculating the 6 architectural models, the 8-9-1 model was chosen as the best with an accuracy rate of 91% and MSE testing 0.0010800577. The results of this study are in the form of the best architectural model that can be used to predict the life expectancy of the Acehnese people.


Full Text:

PDF

References


S. P. Sinaga, A. Wanto, and S. Solikhun, “Implementasi Jaringan Syaraf Tiruan Resilient Backpropagation dalam Memprediksi Angka Harapan Hidup Masyarakat Sumatera Utara,” Jurnal Infomedia, vol. 4, no. 2, pp. 81–88, 2019.

A. L. Ginting, “Dampak Angka Harapan Hidup dan Kesempatan Kerja Terhadap Kemiskinan,” EcceS (Economics, Social, and Development Studies), vol. 7, no. 1, pp. 42–61, 2020.

BPS, “[Metode Baru] Angka Harapan Hidup Provinsi Aceh Menurut Kabupaten/Kota, 2010-2019,” Badan Pusat Statistik (BPS) Indonesia. [Online]. Available: https://aceh.bps.go.id/linkTableDinamis/view/id/155.

M. K. Z. Sormin, P. Sihombing, A. Amalia, A. Wanto, D. Hartama, and D. M. Chan, “Predictions of World Population Life Expectancy Using Cyclical Order Weight / Bias,” Journal of Physics: Conference Series, vol. 1255, no. 1, pp. 1–6, 2019.

P. Parulian et al., “Analysis of Sequential Order Incremental Methods in Predicting the Number of Victims Affected by Disasters,” Journal of Physics: Conference Series, vol. 1255, no. 1, pp. 1–6, 2019.

A. Wanto et al., “Forecasting the Export and Import Volume of Crude Oil , Oil Products and Gas Using ANN,” Journal of Physics: Conference Series, vol. 1255, no. 1, pp. 1–6, 2019.

T. Afriliansyah et al., “Implementation of Bayesian Regulation Algorithm for Estimation of Production Index Level Micro and Small Industry,” Journal of Physics: Conference Series, vol. 1255, no. 1, pp. 1–6, 2019.

A. Wanto and J. T. Hardinata, “Estimations of Indonesian poor people as poverty reduction efforts facing industrial revolution 4.0,” IOP Conference Series: Materials Science and Engineering, vol. 725, no. 1, pp. 1–8, 2020.

A. Wanto et al., “Analysis of the Accuracy Batch Training Method in Viewing Indonesian Fisheries Cultivation Company Development,” Journal of Physics: Conference Series, vol. 1255, no. 1, pp. 1–6, 2019.

A. P. Windarto et al., Jaringan Saraf Tiruan: Algoritma Prediksi dan Implementasi. 2020.

M. O. Shabani and A. Mazahery, “Prediction Performance of Various Numerical Model Training Algorithms in Solidification Process of A356 Matrix Composites,” Indian Journal of Engineering and Materials Sciences, vol. 19, no. 2, pp. 129–134, 2012.

A. Saefullah, M. Hendri, S. Lindawati, M. Badaruddin, and J. Hutahaean, “Analysis of Deep Learning Cyclical order for Prediction of Fresh Milk Production in Sumatera,” Journal of Physics: Conference Series, vol. 1566, no. 1, pp. 1–6, 2020.

A. Wanto et al., “Model of Artificial Neural Networks in Predictions of Corn Productivity in an Effort to Overcome Imports in Indonesia,” Journal of Physics: Conference Series, vol. 1339, no. 1, pp. 1–6, 2019.

I. S. Purba et al., “Accuracy Level of Backpropagation Algorithm to Predict Livestock Population of Simalungun Regency in Indonesia Accuracy Level of Backpropagation Algorithm to Predict Livestock Population of Simalungun Regency in Indonesia,” Journal of Physics: Conference Series, vol. 1255, no. 1, pp. 1–6, 2019.

M. R. Lubis, W. Saputra, A. Wanto, S. R. Andani, and P. Poningsih, “Analysis of Artificial Neural Networks Method Backpropagation to Improve the Understanding Student in Algorithm and Programming,” Journal of Physics: Conference Series, vol. 1255, no. 1, pp. 1–6, 2019.

W. Saputra, J. T. Hardinata, and A. Wanto, “Implementation of Resilient Methods to Predict Open Unemployment in Indonesia According to Higher Education Completed,” JITE (Journal of Informatics and Telecommunication Engineering), vol. 3, no. 1, pp. 163–174, 2019.

G. W. Bhawika et al., “Implementation of ANN for Predicting the Percentage of Illiteracy in Indonesia by Age Group,” Journal of Physics: Conference Series, vol. 1255, no. 1, pp. 1–6, 2019.

S. Setti and A. Wanto, “Analysis of Backpropagation Algorithm in Predicting the Most Number of Internet Users in the World,” JOIN (Jurnal Online Informatika), vol. 3, no. 2, pp. 110–115, 2018.

W. Saputra, J. T. Hardinata, and A. Wanto, “Resilient method in determining the best architectural model for predicting open unemployment in Indonesia,” IOP Conference Series: Materials Science and Engineering, vol. 725, no. 1, pp. 1–7, 2020.

S. P. Siregar and A. Wanto, “Analysis of Artificial Neural Network Accuracy Using Backpropagation Algorithm In Predicting Process (Forecasting),” International Journal Of Information System & Technology, vol. 1, no. 1, pp. 34–42, 2017.




DOI: https://doi.org/10.30645/ijistech.v3i2.59

Refbacks

  • There are currently no refbacks.







Jumlah Kunjungan:

View My Stats

Published Papers Indexed/Abstracted By: