Simulation Modeling System in Determining the Amount of Oil Inventory

Okta Veza; Larisang; Albertus L. Setyabudhi; Nofri Yudi Arifin; Sherly Agustini

doi:10.47709/cnahpc.v5i1.2009

Authors

Okta Veza Universitas Ibnu Sina
Larisang Universitas Ibnu Sina
Albertus L. Setyabudhi Universitas Ibnu Sina
Nofri Yudi Arifin Universitas Ibnu Sina
Sherly Agustini Universitas Ibnu Sina

DOI:

10.47709/cnahpc.v5i1.2009

Keywords:

BBM, Modeling, Simulation, Monte Carlo, Java Programming

Dimension Badge Record

Abstract

Currently, XYZ Gas Stations, in carrying out fuel sales activities, have not yet used a simulation of calculating fuel supply needs at gas stations which functions to support decision making by the leadership, this causes frequent stock shortages at each XYZ gas station branch. because of that the authors are interested in creating a modeling system for calculating fuel inventory simulations using the Monte Carlo method and the LCM pattern. The purpose of this research is to produce a simulated calculation of the supply of purchased fuel so that management knows how much stock of fuel must be provided at each gas station and also to prevent empty fuel stocks at each gas station in the XYZ branch. The data collection methods used in this study were interviews, observations, and literature studies. The system is designed using the JAVA Programming Language. The data processed in this study is transaction activity data for January and February 2022 to determine the amount of inventory that must be provided in March 2022. The final results of the data processing that has been carried out with the trial purchase data transactions for the two current months, namely January and February 2022 to get the simulation results of fuel oil (BBM) supplies in March whose activation has been running with simulation predictions using the Monte Carlo Algorithm.

Downloads

Download data is not yet available.

Google Scholar Cite Analysis
Abstract viewed = 469 times

References

Apri, M., Aldo, D., & Hariselmi, H. (2019). Simulasi Monte Carlo untuk Memprediksi Jumlah Kunjungan Pasien. JURSIMA (Jurnal Sistem Informasi Dan Manajemen), 7(2), 92–106.

Izquierdo, M. A., García, M., Pontón, J. L., Martínez, M., Valentí, V., Navarro, M., Gil, M., Cardenal, F., Mesía, R., & Pérez, X. (2006). A phase I clinical and pharmacokinetic study of paclitaxel and docetaxel given in combination in patients with solid tumours. European Journal of Cancer, 42(12), 1789–1796.

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.

Muhaimin, A., Sumijan, S., & Santony, J. (2020). Pemodelan dan simulasi pengelolaan persedian alat tulis kantor dengan metode Monte Carlo. JSR: Jaringan Sistem Informasi Robotik, 4(1), 1–6.

Naim, M. A., & Donoriyanto, D. S. (2020). Pengendalian Persediaan Obat di Apotek XYZ dengan Menggunakan Simulasi Monte Carlo. JUMINTEN, 1(2), 1–11.

Nashrulhaq, M. I., Nugraha, C., & Imran, A. (2014). Model Simulasi Sistem Antrean Elevator. REKA INTEGRA, 2(1).

Nasution, K. N. (2016). Prediksi penjualan barang pada koperasi pt. perkebunan silindak dengan menggunakan metode monte carlo. JURIKOM (Jurnal Riset Komputer), 3(6).

Peranginangin, K. (2006). Aplikasi WEB dengan PHP dan MySQL. Yogyakarta: Andi, 2.

Prajoko, A., & Manurung, E. (2018). Analisis Penjadwalan Proyek Konstruksi Menggunakan Simulasi Monte Carlo (Studi Kasus Pembangunan Gedung Di Bintaro, Jakarta). PROSIDING SEMINAR NASIONAL CENDEKIAWAN, 27–32.

Prawita, R. (2021). Simulasi Metode Monte Carlo dalam Menjaga Persediaan Alat Tulis Kantor. Jurnal Informatika Ekonomi Bisnis, 72–77.

Rahayu, T. K. (2019). Simulasi Monte Carlo Untuk Memprediksi Keuntungan Penjualan. Musamus Journal Of Research Information and Communication Technology, 2(1), 1–6.

Santony, J. (2020). Simulasi penjadwalan proyek pembangunan jembatan gantung dengan metode Monte Carlo. Jurnal Informasi Dan Teknologi, 30–35.

Saragih, O., Sianturi, L. T., Siburian, H. K., & Suginam, S. (2016). Simulasi Antrian Penerimaan Bantuan Langsung Tunai (Blt) Dengan Menerapkan Algoritma First In First Out (Studi Kasus: Pt. Pos Indonesia (Persero) Lubuk Pakam. Jurikom (Jurnal Riset Komputer), 3(6).

Sriwana, I. K., Sukania, I. W., & Christianto, S. (2018). Optimasi Persediaan Spare Part untuk Meningkatkan Total Penjualan Dengan Menggunakan Simulasi Monte Carlo (Studi Kasus di PT. ZXC). Jurnal Ilmiah Teknik Industri, 4(3).

Yanuarsyah, M. R., Muhaqiqin, M., & Napianto, R. (2021). Arsitektur Informasi Pada Sistem Pengelolaan Persediaan Barang (Studi Kasus: Upt Puskesmas Rawat Inap Pardasuka Pringsewu). Jurnal Teknologi Dan Sistem Informasi, 2(2), 61–68.