Sensitivity analysis of coal mine project investment using fuzzy model

Hasrin citra utami, Tedy Agung Cahyadi, Rika Ernawati

Abstract


Investment analysis needs to be done to determine the feasibility of a project from an economic perspective. In this research, an investment analysis were applied in a coal mine project. The analysis were considering the results of NPV and IRR. NPV is the result of subtracting discounted costs [8]. IRR is an interest rate that shows the net present value is equal to the total amount of business investment [9]. The methods used in the analysis are the conventional method and the Fuzzy method. Conventional method is done by using NPV and IRR formula in Ms.Excel while Matlab for Fuzzy. The Fuzzy method apply a membership functions, namely triangular fuzzy number. The results of the analysis using conventional methods show an NPV value of $ 14,900,691 or IDR 223 Million with an IRR value of 69.8%. The results of the analysis using the fuzzy method with triangular membership functions showed the NPV values of IDR 232 Million and IRR 40.1 %. From the analysis, it can be seen that the fuzzy method is able to produce a larger NPV but a smaller IRR value whose value is close to conventional methods with the same input variables. So it can be concluded that the fuzzy method is quite well applied in investment analysis and it can help for the final decision of a project

Full Text:

PDF

References


Achmadi A., and Narbuko. (2015). Metodologi Penelitian. Jakarta: Bumi Aksara.

Brigham, Eugene F, and Joel F. Houston. (2006). Dasar-Dasar Manajemen Keuangan. Edisi Sepuluh, Salemba Empat, Jakarta.

Farida Y. (2015). Pengembangan Model Fuzzy Project Evaluation untuk Analisis Kelayakan Finansial Pabrik Baru. Prodi Matematika Fakultas Sains dan Teknologi, Universitas Islam Negeri Sunan Ampel Surabaya, Surabaya.

Hellman, M. (2001). Fuzzy Logic Introduction. Laboratoire Antennes Radar Telecom, Equipe Radar Polarimetrie,Universit´e de Rennes. France.

J. Jang, Chuen-Tsai Sun and E. Mizutani. (1997). Neuro Fuzzy and Soft Computing. UK: Prentice Hall.

Kahraman C. (2001). Fuzzy Versus Probabilistic Benefit/Cost Ratio Analysis For Public Work Project. Int J App Math Comput Sci. 1 (3) : 705-718.

Karsak and Tolga. (2001). Fuzzy multi-criteria decision-making procedure for evaluating advanced manufacturing system investments. Industrial Engineering Department, Galatasaray University, Ortakoy, Istanbul, Turkey.

Khotimah, H. and Sutiyono. (2014). Analisis Kelayakan Finansial Usaha Budidaya Bambu. Jurnal Ilmu Kehutanan. 08. 14-24.

Pahlevi, R., Zakaria, W. A., dan Kalsum, U. (2014). Analisis Kelayakan Usaha Agroindustri Kopi Luwak di Kecamatan Balik Bukit Kabulapen Lampung Barat.

Umar H. (2009). Metode Penelitian Untuk Skripsi dan Tesis Bisnis. Jakarta: Rajawali Persada.

Sri Kusuma Dewi, Hari Purnomo. (2004). Aplikasi Logika Fuzzy Untuk Pendukung Keputusan. Penerbit Graha Ilmu.




DOI: https://doi.org/10.31315/jmel.v8i1.12396

DOI (PDF): https://doi.org/10.31315/jmel.v8i1.12396.g6561

Refbacks

  • There are currently no refbacks.




This Journal indexed to :

 

Crossref Content Registration JMEL on GS    

 

====================================================

Jurnal Mineral, Energi, dan Lingkungan

Published By: Universitas Pembangunan Nasional Veteran Yogyakarta

Addres: Jl. Padjajaran Jl. Ring Road Utara No.104, Ngropoh, Condongcatur, Sleman, Yogyakarta

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. Statistik Jurnal Statistik Jurnal

slot gacor slot