Implementation of the Weighted Moving Average Method for Forecasting the Production of Manila Duck meat in Indonesia

Authors

  • Diana Pratiwi STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
  • Riki Winanjaya STIKOM Tunas Bangsa, Pematangsiantar
  • Irawan Irawan STIKOM Tunas Bangsa, Pematangsiantar

DOI:

https://doi.org/10.55123/jomlai.v1i3.916

Keywords:

Manila Duck, Forecasting, Weighted Moving Average

Abstract

Manila duck is a waterfowl originating from South America, through the Philippines this type of duck entered Indonesia and has a large distribution in various regions of Indonesia the production on manila duck meat and from 2019-2020 has decreased due to the covid-19 pandemic which resulted in economic difficulties. And the lack of demand from restaurants and households so that the amount of production decrease. However, in 2020-2021 production will increase due to the relaxation from the previous pandemic and the demand and marketing has increased to that the number of production has increased from the previous year. The Weighted Moving Average method is a method used to determine the latest trend with a moving average value. The purpose of this study was to analyses the amount of production of manila duck meat in solving the problem. The result obtained with the smallest error percentage are at F128 in the province of North Maluku with MAPE value of 0,003 or equal to 0,3% with a bias of -0,25, MAD 0,25, MSE 0,06, with a forecasting value of 83,29 which is close to the original data, namely 83,04 so that the forecast value for 2022 is 83,24 tons.

References

R. R. Depawole and M. A. Sudarma, “Pengaruh Pemberian Level Protein Berbeda terhadap Performans Produksi Itik Umur 2-10 Minggu di Sumba Timur,” Jurnal Sain Peternakan Indonesia, vol. 15, no. 3, pp. 320–326, 2020.

J. Anugrah and D. Lestari, “‘ Strategi Ketahanan Pangan Masa New Normal Covid-19 ’ Potensi Ternak Entok ( Cairina Moschata ) Sebagai Sumber Daging Alternatif Dalam Mendukung Ketahanan Pangan Nasional,” vol. 4, no. 1, pp. 479–490, 2020.

A. A. Susila and M. Rofi’i, “Potensi Usaha Ternak Itik Pedaging Dalam Meningkatkan Pendapatan Masyarakat Desa Selokgondang,” Iqtishodiyah : Jurnal Ekonomi dan Bisnis Islam, vol. 6, no. 2, pp. 109–133, 2020.

BPS, “Produksi Daging Itik/Itik Manila Menurut Provinsi (Ton),” Badan Pusat Statistik Indonesia, 2021. [Online]. Available: https://www.bps.go.id/indicator/24/489/1/produksi-daging-itik-itik-manila-menurut-provinsi.html. [Accessed: 09-Aug-2021].

V. V. Sianipar, A. Wanto, and M. Safii, “Decision Support System for Determination of Village Fund Allocation Using AHP Method,” The IJICS (International Journal of Informatics and Computer Science) ISSN, vol. 4, no. 1, pp. 20–28, 2020.

R. Simarmata, R. W. Sembiring, R. Dewi, A. Wanto, and E. Desiana, “Penentuan Masyarakat Penerima Bantuan Perbaikan Rumah di Kecamatan Siantar Barat Menggunakan Metode ELECTRE,” Journal of Computer System and Informatics (JoSYC), vol. 1, no. 2, pp. 68–75, 2020.

R. Watrianthos, W. A. Ritonga, A. Rengganis, A. Wanto, and M. Isa Indrawan, “Implementation of PROMETHEE-GAIA Method for Lecturer Performance Evaluation,” Journal of Physics: Conference Series, vol. 1933, no. 1, p. 012067, 2021.

S. R. Ningsih, D. Hartama, A. Wanto, I. Parlina, and Solikhun, “Penerapan Sistem Pendukung Keputusan Pada Pemilihan Objek Wisata di Simalungun,” in Seminar Nasional Teknologi Komputer & Sains (SAINTEKS), 2019, pp. 731–735.

N. Nasution, G. W. Bhawika, A. Wanto, N. L. W. S. R. Ginantra, and T. Afriliansyah, “Smart City Recommendations Using the TOPSIS Method,” IOP Conference Series: Materials Science and Engineering, vol. 846, no. 1, pp. 1–6, 2020.

R. A. Hutasoit, S. Solikhun, and A. Wanto, “Analisa Pemilihan Barista dengan Menggunakan Metode TOPSIS (Studi Kasus: Mo Coffee),” KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer), vol. 2, no. 1, pp. 256–262, 2018.

I. M. Muhamad, S. A. Wardana, A. Wanto, and A. P. Windarto, “Algoritma Machine Learning untuk penentuan Model Prediksi Produksi Telur Ayam Petelur di Sumatera,” Journal of Informatics, Electrical and Electronics Engineering, vol. 1, no. 4, pp. 126–134, 2022.

M. Mahendra, R. C. Telaumbanua, A. Wanto, and A. P. Windarto, “Akurasi Prediksi Ekspor Tanaman Obat , Aromatik dan Rempah-Rempah Menggunakan Machine Learning,” KLIK: Kajian Ilmiah Informatika dan Komputer, vol. 2, no. 6, pp. 207–215, 2022.

R. Puspadini, A. Wanto, and N. Arminarahmah, “Penerapan ML dengan Teknik Bayesian Regulation untuk Peramalan,” Journal of Computer System and Informatics (JoSYC), vol. 3, no. 3, pp. 147–155, 2022.

N. L. W. S. R. Ginantra, A. D. GS, S. Andini, and A. Wanto, “Pemanfaatan Algoritma Fletcher-Reeves untuk Penentuan Model Prediksi Harga Nilai Ekspor Menurut Golongan SITC,” Building of Informatics, Technology and Science (BITS), vol. 3, no. 4, pp. 679–685, 2022.

N. Arminarahmah, S. D. Rizki, O. A. Putra, U. Islam, K. Muhammad, and A. Al, “Performance Analysis and Model Determination for Forecasting Aluminum Imports Using the Powell-Beale Algorithm,” IJISTECH (International Journal of Information System & Technology), vol. 5, no. 5, pp. 624–632, 2022.

N. L. W. S. R. Ginantra et al., “Performance One-step secant Training Method for Forecasting Cases,” Journal of Physics: Conference Series, vol. 1933, no. 1, pp. 1–8, 2021.

A. Perdana, S. Defit, and A. Wanto, “Optimalisasi Parameter dengan Cross Validation dan Neural Back-propagation Pada Model Prediksi Pertumbuhan Industri Mikro dan Kecil,” Jurnal Sistem Informasi Bisnis, vol. 01, no. 11, pp. 34–42, 2021.

N. L. W. S. R. Ginantra, M. A. Hanafiah, A. Wanto, R. Winanjaya, and H. Okprana, “Utilization of the Batch Training Method for Predicting Natural Disasters and Their Impacts,” IOP Conf. Series: Materials Science and Engineering, vol. 1071, no. 1, p. 012022, 2021.

A. Wanto, S. Defit, and A. P. Windarto, “Algoritma Fungsi Perlatihan pada Machine Learning berbasis ANN untuk Peramalan Fenomena Bencana,” RESTI (Rekayasa Sistem dan Teknologi Informasi), vol. 5, no. 2, pp. 254–264, 2021.

V. V. Utari, A. Wanto, I. Gunawan, and Z. M. Nasution, “Prediksi Hasil Produksi Kelapa Sawit PTPN IV Bahjambi Menggunakan Algoritma Backpropagation,” Journal of Computer System and Informatics (JoSYC, vol. 2, no. 3, pp. 271–279, 2021.

N. Arminarahmah, A. D. GS, G. W. Bhawika, M. P. Dewi, and A. Wanto, “Mapping the Spread of Covid-19 in Asia Using Data Mining X-Means Algorithms,” IOP Conf. Series: Materials Science and Engineering, vol. 1071, no. 1, p. 012018, 2021.

J. Hutagalung, N. L. W. S. R. Ginantra, G. W. Bhawika, W. G. S. Parwita, A. Wanto, and P. D. Panjaitan, “COVID-19 Cases and Deaths in Southeast Asia Clustering using K-Means Algorithm,” Journal of Physics: Conference Series, vol. 1783, no. 1, p. 012027, 2021.

N. A. Febriyati, A. D. GS, and A. Wanto, “GRDP Growth Rate Clustering in Surabaya City uses the K- Means Algorithm,” International Journal of Information System & Technology, vol. 3, no. 2, pp. 276–283, 2020.

M. A. Hanafiah and A. Wanto, “Implementation of Data Mining Algorithms for Grouping Poverty Lines by District/City in North Sumatra,” International Journal of Information System & Technology, vol. 3, no. 2, pp. 315–322, 2020.

T. H. Sinaga, A. Wanto, I. Gunawan, S. Sumarno, and Z. M. Nasution, “Implementation of Data Mining Using C4.5 Algorithm on Customer Satisfaction in Tirta Lihou PDAM,” Journal of Computer Networks, Architecture, and High-Performance Computing, vol. 3, no. 1, pp. 9–20, 2021.

A. Wanto et al., Data Mining : Algoritma dan Implementasi. Yayasan Kita Menulis, 2020.

W. T. C. Gultom, A. Wanto, I. Gunawan, M. R. Lubis, and I. O. Kirana, “Application ofThe Levenberg Marquardt Method In Predict The Amount of Criminality in Pematangsiantar City,” Journal of Computer Networks, Architecture, and High-Performance Computing, vol. 3, no. 1, pp. 21–29, 2021.

A. Nasution, “Forecasting Produksi Karet Menggunakan,” vol. 9986, no. September, 2018.

Z. Silvya, A. Zakir, D. Irwan, P. Studi, S. Informasi, and U. H. Medan, “PENERAPAN METODE WEIGHTED MOVING AVERAGE UNTUK PERAMALAN,” vol. 8, no. 2, pp. 59–64, 2020.

M. Latif and R. Herdiansyah, “Peramalan Persediaan Barang Menggunakan Metode Weighted Moving Average dan Metode Double Exponential Smoothing,” vol. 3, no. 2, pp. 137–142, 2022.

“Produksi Daging Itik_Itik Manila menurut Provinsi.” .

D. Untuk, M. Salah, S. Syarat, M. Gelar, S. Komputer, and P. Studi, “Diajukan Untuk Memenuhi Salah Satu Syarat Memperoleh Gelar Sarjana Komputer Program Studi Informatika,” 2022.

F. Reba, A. Sroyer, S. M. Yokhu, and A. Langowuyo, “Perbandingan Metode Weighted Moving Average dan Single Exponential Smoothing Angka Partisipasi Sekolah Wilayah Adat , Papua,” vol. 18, no. 2, pp. 161–168, 2021.

J. T. Informatika, M. Weighted, M. Average, W. M. A. Pada, and T. Barang, “Jurnal Teknik Informatika, Vol. 13, No. 3, Agustus 2021,” vol. 13, no. 3, pp. 1–9, 2021.

A. K. Ekonomi and P. O. M. F. O. R. Windows, “Aplikasi komputer ekonomi pom for windows,” 2013.

Downloads

Published

2022-10-18

How to Cite

Pratiwi, D., Winanjaya, R., & Irawan, I. (2022). Implementation of the Weighted Moving Average Method for Forecasting the Production of Manila Duck meat in Indonesia. JOMLAI: Journal of Machine Learning and Artificial Intelligence, 1(3), 191–200. https://doi.org/10.55123/jomlai.v1i3.916

Issue

Section

Articles