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Implementation of Forecasting with the Monte Carlo Simulation Method to Predict Supply and Demand for Psychotropic Drug Products

Authors

  • Alim Citra Aria Bima Universitas PGRI Madiun, Indonesia
  • Pratiwi Susanti Universitas PGRI Madiun, Indonesia
  • Moch Yusuf Asyhari Universitas PGRI Madiun, Indonesia

DOI:

10.47709/brilliance.v3i2.3515

Keywords:

Predict Supply, Forecasting, Psychotropic Drug, EOQ

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Abstract

The availability of drugs is one of the needs that supports the presence of health in the community. Patient certainty regarding the availability of drugs becomes increasingly important for patients who use psychotropic drugs. This type is a dangerous drug and needs to be controlled. Control is carried out to avoid drug abuse outside of medical purposes. Two conflicting sides between the importance of ensuring the availability and controlling their use can be resolved, one of which is by measuring supply and demand. The availability of psychotropic drugs should be adjusted to demand. The problem is that we cannot know demand that has not yet occurred, drugs have an expiration date, and procuring drugs takes time. One way is to predict the demand when supplying drugs so that the order quantity is appropriate. The prediction method used is the Monte Carlo Simulation Method. One example of implementation is the Economic Order Quantity (EOQ) Method. As a result, the Monte Carlo method successfully made predictions based on existing data. In addition, it was found that the Monte Carlo Method tended to the distribution of the data used. The closer the distance between the data, the higher the prediction accuracy obtained. Uncertainty in actual demand is also a big challenge for producing accurate predictions based on patterns. Prediction results will be more accurate with more data patterns and variations. Implementation of prediction results with EOQ makes the number of drugs that should be ordered based on demand that is likely to occur.

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References

Adnan Fajar, Aplikasi Simulasi Monte Carlo Dalam Estimasi Biaya Proyek, Jurnal SMARTek, Vol. 6, No. 4, Nopember 2008: 222 – 227.

Asti R.Y., Santony J., Sumijan (2019). Prediction of Amount Of Use of Planning Family Contraception Equipment Using Monte Carlo Method (Case Study in Linggo Sari Baganti District). Indonesia Journal of Artificial Intelligence and Data Mining, 2(1), 3.

Biao X., Tailiang S., Junhai C., Yuanseing D., & Kail (2017). Research on Equipment Support Activity Process Simulation Based on Monte Carlo Method. Shanghai Jiao Ton University (Science), 23(2), 251. DOI: https://doi.org/10.1007/s12204-017-1901.

Bahadori R., Gutierrez H., Manikonda S., & Meinke R. (2017). Monte Carlo method simulation for two dimensional heat transfer in homogenous medium and proposed application to quench propagation simulation. IEEE Transactions on Applied Superconductivity, 27(4), 1. DOI: http://doi.org/10.1109/TASC.2017.2651360.

Eunike, A., Widha, N. S., Yuniarti, R., Hamdala, I., Lukodono, R. P., & Fanani, A. A. (2018). Perencanaan Produksi dan Pengendalian Persediaan. Universitas Brawijaya Press.

Caesarramzy, D., Andrawina, L., & ... (2018). … Kebijakan Persediaan Produk Kategori Suplemen Dan Kebutuhan Harian Di Bm Pt Xyz Untuk Mengurangi Total Biaya Persediaan Menggunakan Metode Periodic …. JISI: Jurnal Integrasi Sistem …, 4(2), 107–118.

Cruz-Nájera, M. A., Treviño-Berrones, M. G., Ponce-Flores, M. P., Terán-Villanueva, J. D., Castán-Rocha, J. A., Ibarra-Martínez, S., … Laria-Menchaca, J. (2022). Short Time Series Forecasting: Recommended Methods and Techniques. Symmetry, 14(6). https://doi.org/10.3390/sym14061231

Ilmi, M., Hakim, Z. P., Qodri, Y. P., & Darma, M. (2021). Monte Carlo’ Simulation Predicting on the Movement of Investments-During the Covid Pandemic in Indonesia. Jurnal Dinamika Manajemen, 12(2), 262–274. http://jdm.unnes.ac.id

Mulia, J. R., & Nurcahyo, G. W. (2022). Prediksi Pemakaian Obat Kronis Menggunakan Metode Monte Carlo. Jurnal Informasi Dan Teknologi, 4(2), 81–85. https://doi.org/10.37034/jidt.v4i2.198

Rani Purbaningtyas. (2023). Penerapan Metode Monte Carlo Untuk Mendukung Estimasi Stok Produksi Kue Kering. Universitas Bhayangkara Surabaya, Vol 3.

Richard F. 2017. Research Challenges in Modeling and Simulation for Engineering Complex. USA. Georgia Institute of Technology. DOI: https://doi.org/10.1007/978-3-319-58544-4.

Harvei, D. S., (2018). Analisa Simulasi Monte Carlo Untuk Memprediksi Tingkat Kehadiran Mahasiswa Dalam Perkuliahan, (Studi Kasus : STMIK PELITA NUSANTARA), Journal Of Informatic Pelita Nusantara Volume 3 No 1 Maret 2018 e-ISSN 2541-3724. Indonesia.

Li Y., Ren D., & Yang Z. (2018). A Monte Carlo SimulationBased Algorithm for a Repairable System in GO Methodology. IEEE International Conference on Dependable Systems and Their Applications (DS). 120. DOI: https://doi.org/10.1109/DSA.2018.00029.

Syahrin E., Santony J., & Na’am J. (2019). Pemodelan Penjualan Produk Herbal Menggunakan Metode Monte Carlo. Jurnal KomtekInfo,4(3), 34.

Richard F. 2017. Research Challenges in Modeling and Simulation for Engineering Complex. USA. Georgia Institute of Technology. DOI: https://doi.org/10.1007/978-3-319-58544-4.

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ARTICLE Published HISTORY

Submitted Date: 2024-01-26
Accepted Date: 2024-01-26
Published Date: 2024-01-30

How to Cite

Bima, A. C. A., Susanti, P. ., & Asyhari, M. Y. . (2024). Implementation of Forecasting with the Monte Carlo Simulation Method to Predict Supply and Demand for Psychotropic Drug Products. Brilliance: Research of Artificial Intelligence, 3(2), 441-448. https://doi.org/10.47709/brilliance.v3i2.3515