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All Journal Jurnal Teknik Industri Terintegrasi (JUTIN)
zharif, Erza Arkan
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Decision Sciences, Operations Research & Management Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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Simulasi Prediksi Penjualan Harian Menggunakan Metode Monte Carlo pada Usaha Roti Skala UMKM Romatona, Rika; Naylah, Sabikah Nur; Lubis, Baitul Maharani; Gajah, Tika; Yuhani, Yuhani; Maha, Bidara Jelita; zharif, Erza Arkan
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 9 No. 1 (2026): January
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v9i1.55835

Abstract

This study aims to apply the Monte Carlo simulation method to predict daily sales in a small-scale bakery enterprise to support risk-based production planning. The data used consisted of historical daily sales records analyzed to obtain statistical parameters, including mean and standard deviation. The results indicate that daily demand follows a normal distribution with an average of 151.73 units. A Monte Carlo simulation with 10,000 iterations was conducted to estimate the distribution of daily profit and associated risk levels. The findings show an average daily profit of IDR 199,029 with a 95% Value at Risk (VaR) of IDR 99,952. Furthermore, a positive correlation of 0.629 was identified between demand and profit. These results demonstrate that the Monte Carlo method is effective in modeling demand uncertainty and supporting more optimal and efficient production decision-making in micro and small enterprises.
Simulasi Monte Carlo untuk Analisis Kinerja Sistem Antrian pada Operasional Coffee Shop Skala Kecil Zharif, Erza Arkan; Lubis, Putri Bintang; Najiha, Putri; Abdillah, Akbar; Mutiara, Tasya Dewi
Jurnal Teknik Industri Terintegrasi (JUTIN) Vol. 9 No. 1 (2026): January
Publisher : LPPM Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jutin.v9i1.55849

Abstract

This study aims to analyze the performance of a queueing system in a small-scale coffee shop operation using the Monte Carlo simulation method based on historical data from 2022–2026. Coffee shop operations exhibit stochastic characteristics influenced by fluctuations in customer arrivals and service time variability. Data on daily visitors, revenue, cost, and profit were processed using Microsoft Excel to construct empirical probability distributions. The simulation was executed through thousands of iterations to ensure statistical stability. The results indicate that the model effectively captures operational uncertainty, with convergent average daily profit and measurable downside risk assessed through percentile analysis and Value at Risk (VaR). The findings provide an analytical foundation for managerial decision-making regarding service capacity and cost control strategies. Monte Carlo simulation proves to be an effective tool for performance evaluation and risk management in small-scale service businesses.
Co-Authors Abdillah, Akbar Gajah, Tika Lubis, Baitul Maharani Lubis, Putri Bintang Maha, Bidara Jelita Mutiara, Tasya Dewi Najiha, Putri Naylah, Sabikah Nur Romatona, Rika Yuhani, Yuhani