Pendekatan Neural Network dalam Peramalan Jumlah Penduduk Kota Semarang dengan Menggunakan Metode Backpropagation

Article History

Submited : August 4, 2023
Published : July 27, 2024

The city of Semarang is one of the metropolitan cities that has a fairly dense population. During the years 2010-2021 the City of Semarang has a population fluctuation. It is necessary to make predictions of population data in order to plan the development in the City of Semarang can be better planned and can regulate the fluctuation of population in the future. In this study, the results of the prediction of the population of the City of Semarang were analyzed using the Neural Network approach with the backpropagation method. After training and testing, the best architectural model was obtained with 2 neurons on the input layer, 2 neurones on the hidden layer and 1 neuron on the output layer. Based on the results of the best architectural model, the MSE score was 9.39749 x 10-6 and the average MAPE value was 0.884552461%. The evaluation result with the MAPE value is very accurate because it is < 10%. In this study, the results of the forecast of the population of the city of Semarang in 2022-2025 consecutive are 1,863.121 people, 1,878.634 people, 1.891.865 people, and 1,902.947 people.

References

  1. Gurianto R. N., Purnamasari I., & Yuniarti D. Peramalan Jumlah Penduduk Kota Samarinda dengan Menggunakan Metode Pemulusan Eksponensial Ganda dan Tripel dari Brown. J. Eksponensial, vol. 7(1), pp. 23–32, 2016.
  2. Anitescu C., Atroshchenko E., Alajlan N., & Rabczuk T. Artificial Neural Network Methods For The Solution Of Second Order Boundary Value Problems. Comput. Mater. Contin, Vol. 59(1), pp. 345–359, 2019.
  3. Awodele O., & Jegede O. Neural Networks And Its Application In Engineering. Sci IT, pp. 83–95, 2009.
  4. Purwanto S. D. Implementasi Jaringan Syaraf Tiruan Backpropagation Sebagai Estimasi Laju Tingkat Pengangguran Terbuka Pada Provinsi Jawa Timur. Semin. Nas. Teknol. Inf. dan Multimed, Vol. 4(1), pp. 4–9, 2016.
  5. Siang J. J. Jaringan Syaraf Tiruan dan Pemrogramannya Menggunakan MATLAB. Yogyakarta: ANDI, 2009.
  6. Abiodun O. I. Comprehensive Review of Artificial Neural Network Applications to Pattern Recognition. Institute of Electrical and Electronics Engineers Inc, Vol. 7, pp. 158820–158846, 2019.
  7. Hardati P. Pertumbuhan Penduduk Dan Struktur Lapangan Pekerjaan Di Jawa Tengah. Forum Ilmu Sos, Vol. 40(2), pp. 219–229, 2013.
  8. BPS. Profil Kependudukan Kota Semarang 2019. Kota Semarang: BPS, 2019.
  9. BPS. Badan Pusat Statistik Provinsi Jawa Tengah Dalam Angka 2020. Jawa Tengah: BPS, 2020.
  10. BPS. Provinsi Jawa Tengah dalam Angka 2021. Semarang: BPS, 2021.
  11. Bappeda Kota Semarang. Rencana Pembangunan Jangka Menengah Daerah (Rpjmd) Kota Semarang Tahun 2016-2021. Kota Semarang: 2021.
  12. Arikunto S. Prosedur Penelitian Suatu Pendekatan Praktek (Edisi Revisi). Jakarta: Rineka Cipta, 2010.
  13. Arofah S. P. L., Wasono R., & Arum P. R. Peramalan Harga Beras di Provinsi Jawa Tengah Menggunakan Metode Backpropagation Neural Network dengan Optimasi Conjugate Gradient Beale-Powell Restars. 2020.

Downloads

Download data is not yet available.
Fulltext
statcounter