Analisis Kelayakan Investasi Antara Bangun Baru dan Bangunan Existing Ombudsman RI di Kawasan Kuningan Jakarta

Sunaryo Sunaryo; Wati Asriningsih Pranoto; Mark Setiadi

doi:10.29103/tj.v15i1.1204

Analisis Kelayakan Investasi Antara Bangun Baru dan Bangunan Existing Ombudsman RI di Kawasan Kuningan Jakarta

Sunaryo Sunaryo, Wati Asriningsih Pranoto, Mark Setiadi

Abstract

Abstrak

Studi kelayakan investasi dilakukan dengan metode discounted cash flow (DCF). Hasil perhitungan dengan metode DCF disimulasikan dengan metode monte carlo. Indikator-indikator yang digunakan adalah tingkat okupansi, kenaikan biaya konstruksi, kenaikan biaya sewa dan service charge. Arus kas bangunan existing dan bangunan baru dibuat untuk menghitung nilai NPV dan IRRnya. Perhitungan metode DCF pada bangunan existing dengan nilai MARR sebesar 7,47%, didapatkan nilai NPV positif sebesar Rp.155.274.649.791 dan nilai IRR sebesar 31,5%, waktu pengembalian selama 6 tahun 4 bulan. Perhitungan bangunan baru didapatkan nilai NPV positif sebesar Rp.184.233.384.822 dan nilai IRR sebesar 17,5%, waktu pengembalian selama 8 tahun 8 bulan. Perbandingan perhitungan antara bangunan existing dan bangunan baru didapatkan nilai NPV positif sebesar Rp.28.958.735.031 dan nilai IRR sebesar 18,88%, waktu pengembalian 9 tahun 1 bulan. Hasil perhitungan dengan metode DCF dilakukan simulasi monte carlo, sehingga didapatkan nilai NPV rata-rata positif sebesar Rp.21.854.144.293 dan nilai IRR rata-rata sebesar sebesar 11,4% dengan waktu pengembalian rata-rata 8 tahun 11 bulan. Nilai standar deviasi untuk NPV sebesar Rp.6.457.269.316 dan nilai standar deviasi untuk IRR sebesar 1,34%. Perbandingan NPV positif dan nilai IRR lebih besar dari MARR, sehingga alternatif bangun baru layak dilaksanakan. Mempertahankan bangunan existing perlu dilakukan analisis teknik terkait keandalan bangunan existing.

Kata kunci: studi kelayakan, metode DCF, metode monte carlo

Abstract

An investment feasibility study was conducted using the discounted cash flow (DCF) method. The results of the DCF method were simulated using the Monte Carlo method. The indicators used were occupancy rate, construction cost increases, rental cost increases, and service charge increases. Cash flows for existing and new buildings were created to calculate their NPV and IRR. The DCF method calculation for the existing building, with a MARR of 7.47%, resulted in a positive NPV of Rp.155,274,649,791 and an IRR of 31.5%, with a payback period of 6 years and 4 months. The calculation for the new building resulted in a positive NPV of Rp.184,233,384,822 and an IRR of 17.5%, with a payback period of 8 years and 8 months. The comparison between the existing and new buildings resulted in a positive NPV of Rp.28,958,735,031 and an IRR of 18.88%, with a payback period of 9 years and 1 month. The DCF method results were simulated using the Monte Carlo method, resulting in an average positive NPV of Rp.21,854,144,293 and an average IRR of 11.4% with an average payback period of 8 years and 11 months. The standard deviation for NPV is Rp.6,457,269,316 and for IRR is 1.34%. The positive NPV comparison and IRR value greater than the MARR indicate that the new building alternative is feasible. Maintaining the existing building requires a technical analysis related to its reliability.

Keywords: feasibility study, DCF method, monte carlo method

Keywords

feasibility study, DCF method, monte carlo method

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References

Agarwal, R., & Virine, L. (2017). Monte Carlo project risk analysis. In Handbook of research on leveraging risk and uncertainties for effective project management (pp. 109–129). IGI Global.

Badan Pusat Statistik. (2024a). indeks-kemahalan-konstruksi-provinsi-dan-kabupaten-kota-2024. https://www.bps.go.id/id/publication/2024/10/01/a0ce996786e332d81a43d95f/indeks-kemahalan-konstruksi-provinsi-dan-kabupaten-kota-2024.html

Badan Pusat Statistik. (2024b). Inflasi 1 Agustus 2024. https://www.bps.go.id/id/pressrelease/2024/08/01/2306/inflasi-year-on-year--y-on-y--pada-juli-2024-sebesar-2-13-persen-dengan-indeks-harga-konsumen--ihk--sebesar-106-09-.html

Blank, L., & Tarquin, A. (2014). Basics of Engineering Economy. McGrawHill.

Bodie, Z., Kane, A., & Marcus, A. (2014). Ebook: Investments-global edition. McGraw Hill.

Bridgwater, A. V. (1995). The technical and economic feasibility of biomass gasification for power generation. Fuel, 74(5), 631–653.

Colliers Indonesia. (2024a). Q2-2024-ColliersQuarterly-Jakarta-Office. https://www.colliers.com/id-id

Colliers Indonesia. (2024b). Q2-2024-Retail Services Forecast Report. https://www.colliers.com/id-id

Gitman, L. J., Juchau, R., & Flanagan, J. (2015). Principles of managerial finance. Pearson Higher Education AU.

Harahap, S. S. (2003). Teori akuntansi. RajaGrafindo Persada.

Harahap, S. S. (2011). Analisis kritis atas laporan keuangan. Rajawali Pers.

Indonesia, I. A. (2015). Pernyataan standar akuntansi keuangan. Jakarta: Ikatan Akuntan Indonesia, 96.

Kementerian Koordinator Bidang Perekonomian. (2021, May 1). keketuaan-indonesia-di-asean-2023-konektivitas-solidaritas-dan-sinergi-asean-dalam-pemulihan-ekonomi-kawasan_2024-10-29 23_20_42.

Kroese, D. P., Brereton, T., Taimre, T., & Botev, Z. I. (2014). Why the Monte Carlo method is so important today. Wiley Interdisciplinary Reviews: Computational Statistics, 6(6), 386–392.

Kwak, Y. H., & Ingall, L. (2007). Exploring Monte Carlo simulation applications for project management. Risk Management, 9, 44–57.

Metropolis, N., & Ulam, S. (1949). The Monte Carlo Method Journal of the American Statistical Association, vol. 44, no 247. septembre.

Mukherjee, M. (2017). Entrepreneurial Judgment and Analysis for Successful Strategy Implementation. International Journal of Advanced Engineering and Management, 2(1), 1–8.

Newnan, D. G., Eschenbach, T. G., & Lavelle, J. P. (2004). Engineering economic analysis (Vol. 1). Oxford University Press.

Porter, M. E. (2004). Estratégia Competitiva-Técnicas para análise de indústrias e da concorrência. Elsevier Brasil.

Purnomo, R. A., Riawan, R., & Sugiharto, L. A. O. D. E. (2018). Studi Kelayakan Bisnis. Unmuh Ponorogo Press.

Salkeld, D. (2016). Project risk analysis: techniques for forecasting funding requirements, costs and timescales. Routledge.

Subri, M. (2003). Ekonomi SDM dalam perspektif Pembangunan. Jakarta: PT. Rajagrafindo Persada.

Swan, J. (2015). Practical financial modelling: the development and audit of cash flow models. Butterworth-Heinemann.

Unctad. (2023). World Investment Report 2023: Investment and sustainable energy.

Verbeeten, F. H. M. (2006). Do organizations adopt sophisticated capital budgeting practices to deal with uncertainty in the investment decision: A research note. Management Accounting Research, 17(1), 106–120.

Williams, T. (2003). The contribution of mathematical modelling to the practice of project management. IMA Journal of Management Mathematics, 14(1), 3–30.

DOI: https://doi.org/10.29103/tj.v15i1.1204