Probabilistic Modeling and Prediction in the Processing Industry: A Monte Carlo Simulation Approach

Febi Febrianti, Syaharuddin Syaharuddin, Vera Mandailina

Abstract


This finding indicates that the developed model is able to capture historical growth patterns quite precisely. The implicationThis research is motivated by the high uncertainty of the global and domestic economy which requires the availability of adaptive prediction models to support strategic decision making, especially in the manufacturing sector. The purpose of this study is to design and evaluate a Monte Carlo simulation-based prediction model in forecasting growth data for the next five years. This research is quantitative and uses an experimental design, with secondary data for the period 2015-2024 obtained from the Central Bureau of Statistics (BPS). The model was developed through a logarithmic approach to annual change, which was then simulated using the Monte Carlo method to generate thousands of predictive scenarios. The simulation results show that the model has a high level of accuracy, with a Mean Absolute Percentage Error (MAPE) value of 6.27%. This finding indicates that the developed model is able to capture historical growth patterns quite precisely.  of this study is that the Monte Carlo simulation-based predictive approach can be adopted as a tool in data-driven industrial policy planning and formulation, with the caveat that regular data monitoring and updating are important to maintain the model's accuracy to the latest dynamics.

Keywords


Probabilistic Model, Monte Carlo, Forecasting, Manufacturing Industry, Stochastic Simulation.

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References


Friskarini, K., & Sundari, T. R. (2020). Pelaksanaan Cuci Tangan Pakai Sabun ( Tantangan dan Peluang) Sebagai Upaya Kesehatan Sekolah di Sekolah Dasar Negeri Kecamatan Bogor Utara Kota Bogor Implementation of Handwashing with Soap ( Challenges and Opportunities ) as A School Health Effort of Ele. Jurnal Ekologi Kesehatan, 19(1), 21–34.

Giuffrida, N., Fajardo-Calderin, J., Masegosa, A. D., Werner, F., Steudter, M., & Pilla, F. (2022). Optimization and Machine Learning Applied to Last-Mile Logistics: A Review. Sustainability (Switzerland), 14(9). https://doi.org/10.3390/su14095329

Gunawan Aji, Natalia Casha, Siti Fatimah, & Allisa Qotrunnada Munawaroh. (2023). Pengaruh Budaya Terhadap Penerapan Strategi Pemasaran Internasional. Jurnal Ekonomi, Manajemen Pariwisata Dan Perhotelan, 2(2), 159–169. https://doi.org/10.55606/jempper.v2i2.1427

Jansson, T. (2024). Permanent residence permits and demands for integration: a genealogical analysis of Swedish immigration policy. Journal of Ethnic and Migration Studies, 50(12), 3091–3109. https://doi.org/10.1080/1369183X.2023.2290451

Lepikhin, D., Lee, H., Xu, Y., Chen, D., Firat, O., Huang, Y., Krikun, M., Shazeer, N., & Chen, Z. (2020). GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding. http://arxiv.org/abs/2006.16668

Marvasti, T. B., Alibhai, F. J., Weisel, R. D., & Li, R. K. (2019). CD34+ Stem Cells: Promising Roles in Cardiac Repair and Regeneration. Canadian Journal of Cardiology, 35(10), 1311–1321. https://doi.org/10.1016/j.cjca.2019.05.037

Pipit Muliyah, Dyah Aminatun, Sukma Septian Nasution, Tommy Hastomo, Setiana Sri Wahyuni Sitepu, T. (2020). No Title No Title No Title. Journal GEEJ, 7(2).

Prakoso, A. D., & Agustina, N. (2022). Inclusive Growth Analysis in Central Sulawesi, The Eastern Province of Indonesia 2015-2019. Asian Journal of Business Environment, 12(2), 1–12. https://doi.org/10.13106/ajbe.2022.vol12.no2.1

Prianto, R., Lawira, K., & Patodo, J. (2024). Pengetahuan, Teknologi, dan Kehidupan Manusia dalam Perspektif Teologis. Te Deum (Jurnal Teologi Dan Pengembangan Pelayanan), 13(2), 209–226. https://doi.org/10.51828/td.v13i2.390

Simulasi, A., Carlo, M., Evaluasi, D., & Konstruksi, P. P. (2025). Anna Rosytha. 1–17.

Sperry, M. F., Silva, H. L. A., Balthazar, C. F., Esmerino, E. A., Verruck, S., Prudencio, E. S., Neto, R. P. C., Tavares, M. I. B., Peixoto, J. C., Nazzaro, F., Rocha, R. S., Moraes, J., Gomes, A. S. G., Raices, R. S. L., Silva, M. C., Granato, D., Pimentel, T. C., Freitas, M. Q., & Cruz, A. G. (2018). Probiotic Minas Frescal cheese added with L. casei 01: Physicochemical and bioactivity characterization and effects on hematological/biochemical parameters of hypertensive overweighted women – A randomized double-blind pilot trial. Journal of Functional Foods, 45(January), 435–443. https://doi.org/10.1016/j.jff.2018.04.015

Sucipto, L., & Syaharuddin, S. (2018). Konstruksi forecasting system multi-model untuk pemodelan matematika pada peramalan indeks pembangunan manusia provinsi nusa tenggara barat. Register: Jurnal Ilmiah Teknologi Sistem Informasi, 4(2), 114–124. https://doi.org/10.26594/register.v4i2.1263

Tahar, A., Setiadi, P. B., Rahayu, S., Stie, M. M., & Surabaya, M. (2022). Strategi Pengembangan Sumber Daya Manusia dalam Menghadapi Era Revolusi Industri 4.0 Menuju Era Society 5.0. Jurnal Pendidikan Tambusai, 6(2), 12380–12381.


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