Data-Driven Decision Making: Financial and Risk Analysis on Equipment Procurement at PT ABC Using Predictive Data Estimation, NPV Analysis, Owner Estimate, and Monte Carlo Simulation

: This research delves into strategic financial management solutions for PT ABC during the COVID-19 pandemic, concentrating on the procurement of vital airport equipment. It examines the feasibility of securing essential equipment such as ARFF vehicles, X-ray machines, ambulances, and narcotics & explosive detectors amidst financial challenges. Utilizing financial models like predictive data estimation, Net Present Value (NPV) analysis, owner estimates, and Monte Carlo simulations, the study evaluates risk probabilities and distributions linked to different procurement strategies. The research underscores the pandemic's profound impact on the global aviation sector, notably the steep decline in passenger traffic and resulting financial strains on PT ABC. Facing stringent regulatory obligations and the urgent need for equipment upgrade, the study investigates cost-effective procurement avenues, weighing the benefits of leasing against purchasing, given the company's constrained cash flow. The study navigates through the challenges of limited RFI data and internal corporate regulations that restrict leasing durations. It provides a detailed financial analysis to pinpoint the most economical vendors and procurement approaches, leveraging owner estimates as a negotiation tool. Risk evaluation is conducted via Monte Carlo simulation, offering insights into the likelihood and impact of procurement-related risks. Concluding, the research finds that PT ABC can best manage its procurement needs by opting for leasing over buying. This approach aligns with the company's financial strategy amidst the crisis, allowing for the acquisition of necessary equipment within financial limits. The study identifies Vendor A for ARFF vehicles, Vendor D for X-ray machines, Vendor E for ambulances, and Vendor G for narcotics & explosive detectors as the most cost-effective choices. Leasing, particularly on a 3-year term, emerges as the most viable financial option, in compliance with PT ABC's internal regulations and operational requirements. Utilizing owner estimates for negotiations ensures more cost-effective procurement. The Monte Carlo simulation proves invaluable in evaluating procurement risks, indicating a higher risk associated with buying than leasing. This research aids PT ABC in strategic decision-making for equipment procurement, offering lessons for the broader aviation sector navigating post-pandemic recovery.


INTRODUCTION
Navigating through the turbulence of a global health crisis, the aviation industry finds itself at a critical juncture, facing unprecedented challenges that call for strategic financial acumen and decisive action.This thesis embarks on an analytical journey to examine the financial strategies that PT ABC, a key player in the nation's aviation landscape, must consider to weather the storm.It delves into the application of various financial models and strategies to strike a balance between the pressing need for essential equipment procurement and the stark reality of reduced cash flow brought about by the pandemic.Through a lens that focuses on predictive data estimation, net present value (NPV) analysis, owner estimate, and Monte Carlo simulation, this study aims to chart the most feasible financial courses for the company while maintaining the risk.The ensuing chapters unfold the narrative of PT ABC's financial and operational odyssey during these trying times, exploring the impact of the COVID-19 pandemic on the global aviation industry, the specific financial and operational predicaments faced by the company, and the regulatory backdrop mandating the procurement of critical airport equipment.

A. Impact of COVID-19 on the Global Aviation Industry
In recent years, the world has struggled with COVID-19 pandemic, originated from Wuhan, China.The COVID-19 pandemic, has unleashed an unparalleled global crisis, affecting various sectors with the aviation industry being one of the hardest hits.This pandemic, caused by the novel coronavirus SARS-CoV-2, led to countries implementing strict measures like travel bans and lockdowns, significantly reducing air travel and disrupting global connectivity.Because of this, the COVID-19 is heavily impacted the financial of companies in the aviation industry, with massive net loss in 2020 in their income statements (Bouwer et al., 2022).
The COVID-19 pandemic significantly impacted the financial stability of airlines, airports, and air navigation service providers (ANSPs).Airlines, in particular, faced a sharp decline in demand and had very low cash reserves, with most having only two months' worth of cash or less available.The global economic impact of COVID-19 on civil aviation in 2020 and 2021 can be summarised as follow (International Civil Aviation Organization (ICAO), 2023): • 2020 vs 2019: seats offered -50%; passengers flown -2.703 million; airline revenue loss USD 372 billion.
From the monthly passenger perspective, as seen on the Figure 1, the total number of passenger when the pandemic happens, which is on 2020 until 2022, is far lower than the total monthly passenger before the pandemic in 2019, showing how impactful COVID-19 impacting the civil aviation industry.The COVID-19 pandemic has greatly reduced travel demand, affected investor expectations, and caused a negative impact on airline stock (Atems & Yimga, 2021).In 2020, global passenger demand in RPK (revenue passenger kilometer) dropped by 65.9% compared to 2019, resulting in a decrease of airline passenger revenue by USD 418 billion, a 68.9% drop compared to the previous year.This led to airlines posting the largest ever collective net loss of USD 126.4 billion in 2020.Other than that, the reduction in air travel was not gradual but a steep decline, as fear of the virus's spread and government-imposed travel restrictions led to a sudden and significant drop in passenger numbers (International Civil Aviation Organization (ICAO), 2023).In summary, the COVID-19 pandemic had a profound impact on the financial stability of airlines, airports, and ANSPs, leading to revenue losses, reduced air traffic, and the need for financial support to prevent bankruptcy and ensure the survival of these critical stakeholders in the aviation industry.

B. Financial and Operational Problem at PT ABC
In the context of Indonesia, PT ABC, a key player in the nation's aviation landscape, faced severe impacts from the pandemic.These impacts were multifaceted, affecting various aspects of its operations.The most immediate and noticeable effect was the sharp decline in passenger traffic.As international and domestic travel dwindled, the company witnessed a drastic drop in its primary revenue source, leading to significant financial challenges.The decrease in passenger numbers had a direct and profound impact on PT ABC's finances.Airlines, being key customers, reduced their operations, thereby affecting the company's revenue from landing fees, parking charges, and passenger service charges.However, despite the reduced income, the fixed costs associated with airport maintenance and operations remained largely unchanged (Choi, 2021).These costs include personnel expenses, routine maintenance, and essential operational services, creating a financial strain on the company.Moreover, the pandemic did not alleviate PT ABC's obligations to comply with safety and operational regulations.Ensuring the safety and security of passengers and staff remained a top priority.This compliance involves maintaining and operating critical equipment, such as Aircraft Rescue and Fire Fighting (ARFF) vehicles, sophisticated X-ray machines for security screening, well-equipped ambulances for medical emergencies, and sensitive narcotics and explosive detectors.A significant challenge that emerged for PT ABC during the pandemic was the need for procurement and maintenance of heavy equipment.The existing infrastructure, including critical safety and security apparatus, was aging and in need of upgrades or replacements.However, the reduced cash flow due to the pandemic made it challenging to allocate funds for new procurements or even for the maintenance of existing equipment.The necessity to adhere to stringent safety standards and government regulations added another layer of complexity to this already challenging situation.

C. Indonesia Government Regulation of Mandatory Airport Equipment
In order to fulfill the need for maintaining certain safety standards in airports, the government of Indonesia has published several ministerial regulations (Peraturan Pemerintah).

D. Strategic Financial Management for PT ABC Case
This thesis aims to delve into the strategic financial management decisions that PT ABC must consider to navigate this crisis.It will explore various financial models and strategies that can be employed to balance the urgent need for equipment procurement and maintenance with the reality of reduced cash flow due to the pandemic (Vinod, 2020).The analysis will focus on predictive data estimation, net present value (NPV) analysis, and owner estimate to provide insights into the most feasible financial pathways for the company.While and Monte Carlo simulation is used to evaluate the impact of risk factors on the total risk exposure of the procurement.
In essence, PT ABC's situation is part of the challenges faced by the global aviation industry in the wake of the COVID-19 pandemic.By exploring and addressing these challenges through the lens of strategic financial management, this thesis aims to contribute valuable insights and potential solutions not just for PT ABC but for the aviation sector at large in navigating through and beyond the pandemic, especially in term of maintaining and procuring mandatory heavy equipment in an airport.

BUSINESS ISSUES
PT ABC is currently grappling with a significant financial crisis, a direct result of the disruptions caused by the COVID-19 pandemic.One of the pressing challenges the company faces is the urgent need to procure new heavy equipment.This includes Advanced Rapid Vendor H E2n Given the high cost of heavy equipment like Aircraft Rescue and Fire Fighting (ARFF) vehicles, ambulance cars, X-ray machines, narcotics & explosive detector, it is crucial to identify the most cost-effective options.Decisions will also consider factors such as the average number passengers at each airport to determine its difference in urgency.Lastly, scenario planning will be carried out to mitigate risks, such as a vendor choosing to terminate negotiations or not agreeing in ABC's offers.

METHODOLOGY
The research design adopted in this study is crafted as a mixed-method approach, where both quantitative and qualitative data play pivotal roles in achieving a holistic view of the equipment procurement process at PT ABC.The chosen framework allows for the incorporation of a diverse range of data types and sources, ensuring a comprehensive analysis of the financial and risk-related aspects of procurement.
Quantitatively, the study leverages predictive data estimation techniques to anticipate future costs and benefits, NPV (Net Present Value) analysis to assess the value of procurement over time.Qualitative insights are gathered through an owner's estimate, providing context and depth to the numerical data.This multifaceted approach is further enriched by the application of Monte Carlo simulation, which aids in risk assessment by exploring a multitude of possible outcomes and their probabilities.This combination of methods enables the study to not only predict financial outcomes with a degree of precision but also to capture the nuanced perspectives of stakeholders involved in the procurement process.By engaging with both the statistical probabilities and the subjective estimates of costs and risks, the research design ensures a thorough and balanced investigation, conducive to strategic decision-making within PT ABC's procurement framework.The research is mainly divided into two parts, financial analysis (Figure 2) and risk analysis (Figure 3).

A. Predictive Data Analysis
Predictive data analysis plays a crucial role in supplementing missing essential data for conducting financial analysis.Within the scope of this study, particularly in relation to the procurement activities at PT ABC, the absent data that can be estimated through mathematical modelling encompasses the monthly payment details.To achieve this, it is first necessary to ascertain the leasing rate corresponding to the unspecified monthly payment duration using Solver adds-in and linear interpolation.Subsequently, this leasing rate is converted into the monthly payment amount using PMT formula from excel.The predictive data analysis can be summarized in diagram from Figure 4.

1) Finding Known Leasing Rate with Solver Add-in for Excel
In the research methodology section of the thesis, the Solver add-in for Excel is utilized to calculate the optimal monthly leasing rate for equipment procurement.Solver is an Excel feature that performs what-if analysis, optimizing the value in a specific cell by varying values in other cells within a defined constraint.For this analysis, the objective is to set the value of cell C4, which represents the monthly leasing payment, to IDR 200,000,000 (see Figure 5).The payment value in C4 is calculated using the PMT function in Excel, which computes the payment for a loan based on constant payments and a constant interest rate.The formula =ABS(PMT(C6/12, C3, C2)) in cell C4 is designed to calculate the absolute value of the monthly payment.Here, C6 represents the yearly leasing rate, C3 is the leasing period in months, and C2 is the purchasing cost.
The ABS function is used to ensure the payment value is a positive number, which reflects a cash outflow.
To find the required yearly leasing rate, the Solver adjusts the value in cell C6.This variable is altered iteratively by the Solver until the PMT function yields the target leasing payment of IDR 200,000,000.The goal is to determine the annual interest rate that, when divided by 12 to obtain a monthly rate and applied over the leasing period, results in the desired monthly payment amount.The next step is to find the desired leasing rate of the missing data by using linear interpolation.

2) Finding Missing Leasing Rate with Linear Interpolation
Linear interpolation is an interpolation method for one-dimensional data.It estimates the data value based on input of two data points adjacent to the point that needs to be interpolated (Noor et al., 2014).The simple visual explanation can be seen on Figure 6, while the formula is on Figure 7.In the context of this research, the linear interpolation is used to determine missing monthly lease expense, by determining the leasing rate of missing monthly payment data.with x-axis is the expense and the y-axis is the year period.For example, the RFI contained data monthly lease expense for 10-year period and 5-year period, while the internal regulation restricts the procurement period to 3-

3) Converting Leasing Rate with PMT Excel Formula
The determination of the monthly leasing cost in the financial analysis of equipment procurement is conducted using the PMT function in Excel.This function is pivotal in calculating the monthly cost based on the initial investment value, the lease rate, and the number of payment periods.To employ this function, the following formula is input into Excel: =PMT(rate, nper, pv) Here, 'rate' refers to the monthly lease rate, which is derived by converting the annual lease rate through a process of linear interpolation and then dividing it by 12 to get the monthly equivalent.The 'nper' stands for the total number of monthly payment periods, and 'pv' represents the present value or the initial cost of purchasing the equipment.By applying this formula, the study can ascertain the incomplete monthly lease costs from vendors, which can then be further analyzed using Net Present Value (NPV) analysis.This step is crucial in ensuring that all financial calculations regarding leasing are grounded in systematic and replicable quantitative methods, thereby providing a reliable foundation for subsequent NPV analysis in the thesis.

B. NPV Analysis
Incorporating the additional factor of inflation into the NPV analysis methodology, the approach accounts for the future increase in maintenance costs within the purchasing scheme.Recognizing that inflation impacts both material and labor costs, an annual inflation rate of 2  Indonesia, 2021).This adjustment ensures a more realistic and context-specific projection of the cash outflows associated with equipment maintenance.
The NPV analysis steps are as follows: 1) Annualization of Monthly Leasing Payments: Convert the monthly leasing payments, calculated through predictive data analysis, into an annual figure to represent the yearly leasing cash flow.2) Incorporation of Inflation in Maintenance Costs: Apply the 2.28% annual inflation rate to project the future value of maintenance costs for spare parts and technician labor in the purchasing scenario.This step ensures that the cash outflows for maintenance in future years are adjusted for inflation, reflecting the expected rise in costs due to economic factors.3) Determination of Cash Flows: Identify the detailed cash flows for each procurement option.For leasing, include the annual lease payments and tax benefits from deductions.For purchasing, consider the initial purchase cost, inflation-adjusted yearly maintenance costs, and annual depreciation.4) Tax Shield Calculation: Calculate the tax benefits using the corporate tax rate of 22%, applied to the leasing payments and the sum of maintenance plus depreciation costs in the purchasing option.By methodically incorporating these steps, the NPV analysis aims to provide a comprehensive, financially sound comparison of leasing versus purchasing, factoring in both immediate costs and future economic changes like inflation.This approach ensures that the final decision is well-informed and reflective of the real-world financial implications for PT ABC.For clarity, the process can be summarized in the Figure 9.

C. Owner Estimate
The methodology for generating owner estimate in the procurement process at PT ABC is structured to ensure a comprehensive and realistic assessment of potential costs.This assessment is critical for negotiating with vendors and confirming that no unnecessary markups are included in the vendor's pricing.The owner estimate components include Cost of Finance, Insurance, Depreciation Cost, Maintenance Cost, Value Added Tax (VAT), Shipment, and Profit Margin.
The methodology of generating owner estimate involves the following steps: 1. Research and Benchmarking: Conduct extensive research to find benchmarks for each component of the owner estimate.This involves reviewing regulations, laws, and financial data from similar companies and industries to determine standard costs and rates.Online resources, industry reports, and financial publications are crucial for gathering this data.2. Application of Corporate Regulations: Integrate PT ABC's internal corporate regulations into the estimation process.For instance, if the internal regulation stipulates that leasing periods are valid for a maximum of three years, this factor is incorporated into the cost of finance calculations.This ensures that the estimates align with company policies and operational constraints.3. Cost of Finance Calculation: Determine the financial cost associated with procurement, taking into account the interest rates and financing terms available in the market, and ensuring they align with internal guidelines.4. Insurance Cost Estimation: Estimate the insurance costs based on the type of equipment, its value, and the risks associated with its operation and maintenance.5. Depreciation Cost Assessment: Calculate the depreciation expense based on the expected life span of the equipment and its residual value, adhering to standard accounting practices.6. Maintenance Cost Projection: Project the costs of maintaining the equipment, including both labor and spare parts, based on industry standards and previous maintenance data for similar equipment.7. Value Added Tax Calculation: Compute the VAT on the procurement as per the prevailing tax laws and rates, ensuring compliance with fiscal regulations.8. Shipment Cost Estimation: Estimate the costs associated with the transportation and delivery of the equipment.9. Profit Margin Analysis: Assess a reasonable profit margin based on industry norms, and internal corporate regulations.
By following these steps, the owner estimate methodology provides a robust, data-driven framework for negotiating with vendors.It ensures that PT ABC secures the best possible terms for equipment procurement, grounded in realistic cost assessments and adherence to both external regulations and internal policies.

D. Monte Carlo Simulation Using RStudio
An approach of Monte Carlo Simulation using RStudio is employed to rigorously assess risks and mapping out the possibilities that the risk will occurs at PT ABC.This methodology leverages the statistical capabilities of RStudio, a platform renowned for its robust data analysis and modeling features, to offer a comprehensive understanding of the procurement risk.Monte Carlo simulation will result in histogram distribution chart to show the distribution of risk possibilities outcomes in happening.
To assess the financial risk associated with the equipment procurement options of leasing and buying, a Monte Carlo simulation approach is implemented using the R programming language.The simulation involves a quantitative analysis where risk is calculated by multiplying the likelihood of occurrence by its potential impact, with data drawn from a defined risk matrix for both leasing and buying scenarios.
In this methodology, the R environment is prepared by loading necessary libraries such as 'tidyverse' for data manipulation, 'purrr' for functional programming, and 'ggplot2' for data visualization.A data frame is created for each procurement option, encapsulating the likelihood and impact scores of identified risks.The risk values are then computed through element-wise multiplication of the likelihood and impact for each risk factor.The core of the Monte Carlo simulation is a user-defined function, run_monte_carlo, which accepts the risk data and the number of simulations as arguments.The function uses stochastic sampling methods to simulate the total risk value over a series of iterations, replicating the randomness inherent in real-world scenarios.For this research, a substantial number of simulations-10,000 iterations-are set to run, which provides a robust representation of the potential risk distributions for both leasing and buying.
The simulation results are subjected to statistical analysis to determine the 95% confidence interval for the mean total risk value, providing insights into the variability and the potential range of risk outcomes.Additionally, the probability of exceeding a predefined risk threshold is calculated, which serves as a pivotal indicator of the likelihood of encountering risks beyond the company's risk appetite.
To visualize the distribution of risk values, histograms are generated using the ggplot function from the 'ggplot2' library.The histograms offer a visual representation of the frequency distribution of the total risk values for both leasing and buying, rendered in blue and red respectively, aiding in the visual comparison of risk profiles.Finally, the main results of the simulation, including the confidence intervals and probabilities of exceeding the risk thresholds, are printed out.These results encapsulate the essence of the Monte Carlo simulation, providing a clear, quantified picture of the risk landscape faced by PT ABC in their procurement decision-making process.

A. Estimating Incomplete RFI Data Using Predictive Data Analysis
The available data that is gathered by the internal procurement team of PT ABC can be seen in Figure 10.Based on the internal corporate regulations of PT ABC, procurement through leasing is restricted to a 3-year period.However, much of the data for this duration is missing.To address this gap, predictive data analysis is conducted to estimate the missing 3-year period data, enabling the execution of NPV analysis for the leasing option over this specific timeframe.Although the 5-year and 10-year leasing period does not comply with the internal corporate regulations, it is still essential to determine the missing monthly payment data to provide decision-makers with comprehensive information for evaluation.An example of this is the monthly payment data for a 5-year leasing period for an ARFF from Vendor A. By using solver, linear interpolation, and PMT formula in excel, the missing data can be predicted, and the summary of completed data can be seen in Figure 11.

B. NPV Analysis for the Best Vendor and Procuring Option
To find the best vendor, NPV analysis is conducted to every equipment and vendor, both for leasing and buying scheme.The NPV analysis for leasing option can be seen on Figure 12, while the analysis for buying option can be seen on Figure 13.The NPV analysis is conducted to find the most cost-efficient vendor for each equipment and the best procuring option between leasing and buying the equipment, in this case, this means the vendor and procurement that has the lowest negative NPV value, since the analysis is cost-centric.

Figure 12.
NPV analysis for leasing (Author, 2023) Based solely on the analysis from the figure above on ARFF NPV analysis comparison, the best vendor would be to lease the ARFF for 3-year period from vendor A. This is because the option has the lowest negative NPV value.The analysis then conducted for other equipment type, such as X-ray machine, ambulance car, and narcotics & explosive detector.The summary of the NPV analysis results can be seen on Figure 14.

NPV Buying Analysis Results
Vendor Based on the summary, the best vendor and scheme can be concluded in Table 2.

C. Owner Estimation for Negotiating Basis
The owner estimate (OE) is mainly conducted by finding regulation and company data that can justify the OE component.The component can be summarized in Table 3.The owner estimate percentage then used to calculate the cost breakdown of the vendor price offering, by multiplying the percentage with the purchasing cost for shipment and depreciation, and with annual lease payment for the remaining component, the calculation can be seen on Table 4.

Table 4. Owner estimate component calculation (Author, 2023)
The next step is to generate every possible scenario of each equipment procurement with various different cost breakdown, which is the depreciation and profit margin.From this, there are 6 different scenario that can be seen on  To assess the owner estimate, we need to calculate the difference in monthly payment, that eventually lead to the difference of profit margin from vendor data and the predicted real profit margin that the vendor takes.The calculation formula to gain those insight can be found in Figure 15.The chosen vendors of each equipment to be calculated is based on the NPV analysis result of Table IV.1.For example, the calculation for ARFF equipment on vendor A can be seen in Figure 16.The internal corporate regulation restricts the profit margin that the vendor can take into 10%, and for leasing term 3-year period.
The best scenario that adheres to internal rules is scenario 5, with profit margin 10% and leasing term 3 year.Based on the owner estimate analysis in scenario 6, PT ABC could negotiate to vendor A to reduce the monthly leasing payment from Rp700,000,000 to Rp527,333,333.33.This will lead to Rp6,216,000,000 reduced cost.The summary of owner estimate analysis and the reduced cost can be seen on Table 6. 8524

D. Risk Analysis Using Monte Carlo
The internal team of PT ABC has done conducting their research on the risk related to procurement by buying and leasing, the analysis are stated on Figure 17 and Figure 18.And the output of the buying option is: • 95% Confidence Interval: For the buying option, the 95% confidence interval for the total risk value lies between 75 and 110.This wider range suggests a higher variability in risk outcomes compared to leasing.• Probability of Exceeding Threshold: The probability of the total risk value exceeding the threshold is around 45.15%.This implies a slightly higher risk level than leasing, indicating a nearly 45.15% likelihood that the risks in the buying option will exceed the threshold.

E. Business Solutions
Based on the analysis, the most cost-effective vendor is listed below: 1. ARFF: Vendor A with leasing term of 3 year provide the lowest negative-valued NPV with value of IDR (17,923,239,669).2. X-ray machine: Vendor D with leasing term of 3 year provide the lowest negative-valued NPV with value of IDR (4,851,765,780).3. Ambulance car: Vendor E with leasing term of 3 year provide the lowest negative-valued NPV with value of IDR (4,567,778,069) 4. Narcotics & explosive detector: Vendor G with leasing term of 3 year provide the lowest negative-valued NPV with value of IDR (1,001,851,015).Since all the leasing option result are 3-year period, the result adds a feasibility aspect since the internal corporation regulation of PT ABC currently only allows leasing of heavy equipment in 3-year terms.The summarized owner estimate calculation for each vendor already showed in Table 6.For clarity, the value for negotiation and the reduced cost from the difference in value between owner estimate and vendor monthly payment is summarized in Table 7.

Table 7. Monthly payment reduction and its effect on total cost reduction
In summary, PT ABC should do a procurement of ARFF to vendor A, X-ray machine to vendor D, ambulance car vendor E, and narcotics & explosive detector.Fortunately, all the equipment procurement NPV value shows the lowest negative-valued on the 3year term, which is following the internal corporate regulation to PT ABC.To further saving cost for PT ABC, the result of owner estimate monthly payment can be applied as negotiation basis to the vendors when procurement occurs.The risk analysis also showed that leasing has lower risk compared to buying, further indicating that 3-year leasing term for each equipment is the best option.

5 )
Discount Rate Application: Discount all future cash flows at the company's WACC of 10%, aligning the time value of money and the investment's inherent risk.6) Present Value Computation: Calculate the present value of each cash flow with the formula PV = Cash Flow / (1 + WACC)^n, standardizing the value to the present day.7) Summation of NPV: Finally, sum up the present values of all cash flows for each year to arrive at the total NPV for each procurement option.This cumulative figure represents the net value today of all future cash flows, both inflows, and outflows, associated with each procurement strategy.

Figure 10 .
Figure 10.RFI data from internal PT ABC procurement team (PT ABC internal data)

Figure 16 .
Figure 16.Owner estimate calculation for ARFF equipment on vendor A (Author, 2023)

ISSN: 2581-8341 Volume 06 Issue 12 December 2023 DOI: 10.47191/ijcsrr/V6-i12-98, Impact Factor: 6.789 IJCSRR @ 2023 www.ijcsrr.org 8512
* Corresponding Author: Ahmad Rizki Firdaus Volume 06 Issue 12 December 2023 Available at: www.ijcsrr.orgPage No. 8510-8529 In the context of firefighting and airport rescue, the Ministerial Regulation of the Republic of Indonesia Number PM 83 of 2017 on Civil Aviation Safety Regulation Part 139 Regarding Aerodromes mandates the operation of Airport Rescue and Firefighting (ARFF) services to prevent further damage in the event of an accident (Ministry of

Table 1 .
List of vendor and model name of each equipment(Author, 2023)

Table 2 .
Best vendor and procuring option based on NPV analysis(Author, 2023)

Table 5
. The owner estimate lease payment can be generated by summing all the OE component, from A to E. 8523 * Corresponding Author: Ahmad Rizki Firdaus Volume 06 Issue 12 December 2023 Available at: www.ijcsrr.orgPage No. 8510-8529

Table 5 .
Various scenario of different OE percentage (Author, 2023)

Table 6 .
Suggested monthly payment from OE and its implication to profit margin difference(Author, 2023)

Total Cost Reduction IDR 1,940,506,187.21 Ambulance Vendor E
A