Articles

Investment Analysis of LNG Storage Facility Development in Indonesia

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The gas industry has had remarkable growth in recent years due to cleaner combustion, and LNG stands at the top of the gas industry as its flexibility and transportability made it an attractive option. Indonesia that has geographical advantage provides natural advantage to become a central player in the global LNG market. However, investment decisions related to new LNG storage facilities are faced with uncertainties and challenges including volatile energy markets, fluctuating LNG prices, geopolitical risks, evolving environmental regulations, and technological changes. This study assesses the feasibility of developing an LNG storage facility in Indonesia. Commercially, it is feasible due to growing LNG demand and Indonesia’s strategic advantages. An LNG storage facility with 180.000 m³ capacity is feasible, showing an NPV of $33.7 million, an IRR of 10.96%, a payback period of 14.61 years, and a Profitability Index (PI) of 1.26. Increasing the tank capacity to 200.000 m³ improves feasibility with an NPV of $44.3 million, an IRR of 11.61%, a payback period of 13.67 years, and a PI of 1.32. Integrating with existing infrastructure further enhances feasibility, yielding an NPV of $77.7 million, an IRR of 14.10%, a payback period of 11.04 years, and a PI of 1.56.

Determining of Well Drilling Sequence for Investment Analysis using Monte Carlo Simulation in Upstream Oil and Gas Company in East Kalimantan, Indonesia

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Electrical construction company that experienced in making Well Head Control Panels (WHCP) has difficulties to decide acceptance of investment in WHCP contracts raised with their client in upstream oil and gas company. The difficulty mostly due to uncertainty of client well drilling sequence. The electrical construction company need to financial investment analysis includes material purchasing, shipping, fabrication and delivery of WHCPs need to be done to make sure they make a profit. It is crucial for electrical construction company used correct forecasting method to determine schedule of client’s request. Monte carlo forecasting method is used to predict the well drilling sequence. The well drilling sequence data for 12 months is used to determine 24 months well drilling sequence operation with result 179 wells with normal distribution and 167 wells with triangular distribution.

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

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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.

Proposed Capital Budgeting: Should PT.FST Close its Kelambu Division?

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In 2021, the manufacturing industry is Indonesia’s most significant contributor to its Gross Domestic Product (GDP). Within the manufacturing industry, there is a sub-industry called the textile industry. The textile industry in Indonesia is highly fragmented. For instance, there are three niche textile markets: textile for households, textile for clothing, and textile for agriculture. The three segments have different growth of 4%, 7.5%, and 5%, respectively, and this difference in growth rate will create a dilemma for companies. For instance, companies must decide which segment needed to be perused or avoid since each segment will have its opportunities and threats.

PT. FST also faces this dilemma. The differences in each segment’s growth rate are reflected by the company’s sales growth of each product. The sales of plastic products Waring and Benang growth rates are 34% and 52% five years CAGR, respectively. Those are substantial growth compared to the textile products of Kelambu with only 23% five years CAGR. From there, the company’s owner and CEO see a shift in the growth of products sold, from textile products to plastic products. To capture the shifts in demand within the market, he decided to close the Kelambu division to make the company leaner and will be able to focus its resources on the products that will generate revenue the most.

From capital budgeting analysis, the plan of shutting down the Kelambu division will result in a faster payback period of 7.2 years compared to 8 years for the regular cash flow and 8.05 years compared to 8.12 years for the regular cash flow the discounted cash flows. More importantly, it generates a higher NPV of IDR 1,087 bio than IDR 976 bio. In addition, the plan also has a higher Profitability Index and IRR of 6.04 and 25% compared to 5.01 and 22%. From risk analysis, the expected value of the project’s is IDR 1,457 bio, with a probability of NPV less than zero is 8%.

Lastly, this final project contributes to the literature by providing an alternative framework on how to use capital budgeting techniques to compare two expansion plans or closing down divisions within a company. Moreover, other textile industry players, especially SMEs could also refer to this final project if they face a similar dilemma.