Simulasi Monte Carlo dalam Mengidentifikasi Peningkatan Penjualan Tanaman Mawar
Keywords:
Simulation, Monte Carlo, Identify, Selling, Rose.
AbstractRoses are one of the most popular types of plants in the community. The sale of roses at the flower shop of 5 siblings is increasingly in demand. Identifying the increase in sales is important in analyzing sales progress. At the present time the seller can only see a manual increase in sales that are most in demand. This study aims to determine predictions of the increase in sales of rose flowers with a monte carlo simulation accurately and accurately. The data that will be processed in this study in the last 2 years, namely 2018 and 2019, rose plants obtained at the 5 Brothers Flower Shop in Solok City. There are several types of roses in the predicted sales level. Then the data will be converted into the probability distribution into cumulative frequency and followed by generating random numbers so that they can determine random numbers. Next, we will group the boundary intervals of the random numbers that have been obtained and continue with the simulation process so that the simulation results and percentage accuracy are obtained using the Monte Carlo method. The results of this study on data processing from 2019 to 2020 have an accuracy of 90%. So this research is very appropriate in identifying the increase in sales for the following year. The design of this system determines the amount of increased sales of goods using the monte carlo method in a flower shop of 5 siblings. Monte Carlo simulations can be used to identify specific sales increases. The results obtained are quite accurate using the Monte Carlo method. Downloads
Download data is not yet available.
ReferencesAstia, R. Y., Santony, J., & Sumijan, S. (2019). Prediction of Amount of Use of Planning Family Contraception Equipment Using Monte Carlo Method (Case Study In Linggo Sari Baganti District). Indonesian Journal of Artificial Intelligence and Data Mining, 2(1), 28-36. DOI: http://dx.doi.org/10.24014/ijaidm.v2i1.5825 . Nasution, K. N. (2016). Prediksi Penjualan Barang Pada Koperasi PT. Perkebunan Silindak dengan Menggunakan Metode Monte Carlo. JURIKOM (Jurnal Riset Komputer), 3(6). Dedrizaldi, D., Masdupi, E., & Linda, M. R. (2019). Analisis Perencanaan Persediaan Air Mineral dengan Pendekatan Metode Monte Carlo pada PT. Agrimitra Utama Persada. Jurnal Kajian Manajemen dan Wirausaha, 1(1). Manurung, K. H., & Santony, J. (2019). Simulasi Pengadaan Barang menggunakan Metode Monte Carlo. Jurnal Sistim Informasi dan Teknologi, 1(3), 7-11. DOI: https://doi.org/10.35134/jsisfotek.v1i3.3 . Novák, J., Georgiev, I., Hanika, J., & Jarosz, W. (2018). Monte Carlo Methods for Volumetric Light Transport Simulation. In Computer Graphics Forum, 37(2), 551-576. DOI: https://doi.org/10.1111/cgf.13383 . Kyprianou, A. E., Osojnik, A., & Shardlow, T. (2018). Unbiased ‘walk-on-spheres’ Monte Carlo Methods for the Fractional Laplacian. IMA Journal of Numerical Analysis, 38(3), 1550-1578. DOI: https://doi.org/10.1093/imanum/drx042 . Liu, C. Q., Wei, Z., Han, C., Huang, C., Huang, Z. W., Ma, Z. W., Zhang, S. J., Peng, S. H., Li, W. M., Bai, X. H., Wang, J. R., Lu, X. L., Zhang, Y., Xu, D. P., Su, X. D., & Yao, Z. E. (2019). Monte Carlo Simulation of Fast Neutron-Induced Fission of 237Np. Chinese Physics C, 43(6). DOI: https://doi.org/10.1088/1674-1137/43/6/064001 . Hutahaean, H. D. (2018). Analisa Simulasi Monte Carlo untuk Memprediksi Tingkat Kehadiran Mahasiswa dalam Perkuliahan (Studi Kasus: STMIK Pelita Nusantara). Journal of Informatic Pelita Nusantara, 3(1). Abedi, A., & Sharifi, M. J. (2018). Quantum Monte Carlo Simulation of Dissipative Transport using Bohmian Trajectories. Journal of Computational Electronics, 17(1), 68-75. DOI: https://doi.org/10.1007/s10825-017-1117-1 . Fujimoto, R., Bock, C., Chen, W., Page, E., & Panchal, J. T. (2017). Research Challenges in Modeling and Simulation for Engineering Complex Systems. Springer, Cham, 1–11. DOI: http://doi.org/10.1007/978-3-319-58544-4 . Mahessya, R. A. (2017). Pemodelan dan Simulasi Sistem Antrian Pelayanan Pelanggan Menggunakan Metode Monte Carlo Pada PT Pos Indonesia (Persero) Padang. Jurnal Ilmu Komputer, 6(1), 15-24. DOI: https://doi.org/10.33060/JIK/2017/Vol6.Iss1.41 . Simamora, R. J., & Jamaluddin. (2017). Simulasi Monte Carlo dengan Model Persediaan Stokastik Pada PT. Bingei Medan. JTIK (Jurnal Teknik Informatika Kaputama), 1(2), 30-35. |
Published
2021-06-30
Section
Articles
How to Cite
Dewi, D. C., & Sumijan. (2021). Simulasi Monte Carlo dalam Mengidentifikasi Peningkatan Penjualan Tanaman Mawar. Jurnal Informatika Ekonomi Bisnis, 3(2), 60-65. https://doi.org/10.37034/infeb.v3i2.67
![]() This work is licensed under a Creative Commons Attribution 4.0 International License. |