Single Exponential Smoothing: Metode Peramalan Kebutuhan Vaksin Campak

Authors

  • Annisa Azzahra Program Studi Sistem Informasi, STMIK Royal Kisaran
  • William Ramdhan Program Studi Sistem Informasi, STMIK Royal Kisaran
  • Wan Mariatul Kifti Program Studi Sistem Informasi, STMIK Royal Kisaran

DOI:

https://doi.org/10.29408/edumatic.v6i2.6299

Keywords:

single exponential smoothing, forecasting, measles vaccine

Abstract

The importance of the measles immunization vaccine for children up to the age of 9 months to prevent children from getting sick with measles or reduce the transmission rate in the surrounding environment, especially at the Gambir Health Center.  This demand is still considered ineffective and there is often an oversupply of vaccines, which results in a buildup of vaccines in storage. The purpose of this study was to create a measles vaccine needs forecasting system using the Single Exponential Smoothing (SES) method. The model used to build this system is the Systems Development Life Cycle (SDLC) with stages of analysis, design, implementation, and trial. Data collection techniques use observation, interviews, or smart phones for shooting or sound recording. The analysis technique for system forecasting uses the SES method, while the system testing uses a Blackbox. Our findings show that the lowest MAPE value was obtained at 49.8%. The results of testing the system using a Blackbox that all components in this system are already functioning properly. With this system, it can make it easier for related parties to predict the number of measles vaccines in the new Gambir health center.

References

Adanna, A. A., & Nonyelum, O. F. (2020). Criteria for choosing the right software development life cycle method for the success of software project. IUP Journal of Information Technology, 16(2), 39–65.

Ahmad, F. (2020). Penentuan Metode Peramalan Pada Produksi Part New Granada Bowl ST Di PT. X. JISI: Jurnal Integrasi Sistem Industri, 7(1), 31–39.

Al Ihsan, N. H. A. S., Dzakiyah, H. H., & Liantoni, F. (2020). Perbandingan Metode Single Exponential Smoothing dan Metode Holt untuk Prediksi Kasus COVID-19 di Indonesia. Ultimatics: Jurnal Teknik Informatika, 12(2), 89–94. https://doi.org/10.31937/ti.v12i2.1689

Apriani, W. (2022). Analisis Pengguna Pil KB pada Puskesmas Kejuruan Muda dengan Metode Single Eksponensial Smoothing. Amalgamasi: Journal of Mathematics and Applications, 1(1), 1–7. https://doi.org/10.55098/amalgamasi.v1.i1.pp1-7

Barabanov, A. V, Markov, A. S., Grishin, M. I., & Tsirlov, V. L. (2018). Current taxonomy of information security threats in software development life cycle. 2018 IEEE 12th International Conference on Application of Information and Communication Technologies (AICT), 1–6. https://doi.org/10.1109/ICAICT.2018.8747065

Buchori, M., & Sukmono, T. (2018). Peramalan Produksi Menggunakan Metode Autoregressive Integrated Moving Average (ARIMA) di PT. XYZ. PROZIMA (Productivity, Optimization and Manufacturing System Engineering), 2(1), 27–33. https://doi.org/10.21070/prozima.v2i1.1290

de Vicente Mohino, J., Bermejo Higuera, J., Bermejo Higuera, J. R., & Sicilia Montalvo, J. A. (2019). The application of a new secure software development life cycle (S-SDLC) with agile methodologies. Electronics, 8(11), 1218. https://doi.org/10.3390/electronics8111218

Fahrudin, R., & Sumitra, I. D. (2020). Peramalan Inflasi Menggunakan Metode SARIMA dan Single Exponential Smoothing (Studi Kasus: Kota Bandung). Majalah Ilmiah UNIKOM, 17(2), 111–120. https://doi.org/10.34010/miu.v17i2.3180

Fauziah, F., Ningsih, Y. I., & Setiarini, E. (2019). Analisis peramalan (forecasting) penjualan jasa pada Warnet Bulian City di Muara Bulian. Eksis: Jurnal Ilmiah Ekonomi Dan Bisnis, 10(1), 61–67. https://doi.org/10.33087/eksis.v10i1.160

Ginantra, N. L. W. S. R., & Anandita, I. B. G. (2019). Penerapan Metode Single Exponential Smoothing Dalam Peramalan Penjualan Barang. J-SAKTI (Jurnal Sains Komputer Dan Informatika), 3(2), 433–441.

Handoko, W. (2019). Prediksi Jumlah Penerimaan Mahasiswa Baru Dengan Metode Single Exponential Smoothing (Studi Kasus: Amik Royal Kisaran). JURTEKSI (Jurnal Teknologi Dan Sistem Informasi), 5(2), 125–132. https://doi.org/10.33330/jurteksi.v5i2.356

Hendrik, H., & Kurniawan, W. J. (2021). Perbandingan Metode Ses Dan Sma Dalam Peramalan Data Covid. Jurnal Mahasiswa Aplikasi Teknologi Komputer Dan Informasi (JMApTeKsi), 3(3), 102–109.

Hudaningsih, N., Utami, S. F., & Jabbar, W. A. A. (2020). Perbandingan Peramalan Penjualan Produk Aknil Pt. Sunthi Sepurimengguanakan Metode Single Moving Average Dan Single Exponential Smooting. Jurnal Informatika Teknologi Dan Sains, 2(1), 15–22. https://doi.org/10.51401/jinteks.v2i1.554

Lawalata, F., Sediyono, E., & Purnomo, H. (2021). Analisis Prediksi Jumlah Pasien Rawat Inap di Rumah Sakit GMIM Siloam Sonder Menggunakan Metode Triple Exponential Smoothing. Jointer-Journal of Informatics Engineering, 2(01), 26–32. https://doi.org/10.53682/jointer.v2i01.28

Rosa, D. U., Alan, M. S., Wulandari, H., & Ramadhan, S. (2019). Metode exponential smoothing dalam memproyeksikan jumlah penduduk miskin di nusa tenggara barat. Jurnal Pemikiran Dan Penelitian Pendidikan Matematika (JP3M), 2(1), 42–53.

Santoso, A. B., Rumetna, M. S., & Isnaningtyas, K. (2021). Penerapan Metode Single Exponential Smoothing Untuk Analisa Peramalan Penjualan. Jurnal Media Informatika Budidarma, 5(2), 756–761. https://doi.org/10.30865/mib.v5i2.2951

Setiawan, A. (2021). Aplikasi Prediksi Tingkat Kesembuhan Covid di DKI Jakarta Dengan Metode Exponensial Smoothing. JATISI (Jurnal Teknik Informatika Dan Sistem Informasi), 8(4), 2187–2197. https://doi.org/10.35957/jatisi.v8i4.1104

Smyl, S. (2020). A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting. International Journal of Forecasting, 36(1), 75–85. https://doi.org/10.1016/j.ijforecast.2019.03.017

Su, Y., Gao, W., Guan, D., & Su, W. (2018). Dynamic assessment and forecast of urban water ecological footprint based on exponential smoothing analysis. Journal of Cleaner Production, 195, 354–364. https://doi.org/10.1016/j.jclepro.2018.05.184

Thonemann, N., Maga, D., & Petermann, C. (2018). Integration of Results from the Energy System Development Plan into Life Cycle Assessment. Chemie Ingenieur Technik, 90(10), 1587–1593.

Tran, Q. T., Hao, L., & Trinh, Q. K. (2019). Cellular network traffic prediction using exponential smoothing methods. Journal of Information and Communication Technology, 18(1), 1–18. https://doi.org/10.32890/jict2019.18.1.1

Waslin, T. T. A., Sulaiman, O. K., & Haramaini, T. (2022). Aplikasi Prakiraan Perkembangan Covid-19 Di Indonesia Menggunakan Metode Single Exponential Smoothing Berbasis Web. Jurnal Media Informatika Budidarma, 6(3), 1509–1516. https://doi.org/10.30865/mib.v6i3.4408

Zaen, M. T. A., Patoni, M., & Fadli, S. (2018). Implementasi System Development Life Cycle Dalam Perancangan Penyebaran Informasi Pada Madrasah Aliyah Nw Puyung. Jurnal Manajemen Informatika Dan Sistem Informasi, 2(1), 43–49. https://doi.org/10.36595/misi.v2i1.78

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Published

2022-12-20