# W9_APE_Mining MARR in Indonesia Using AHP Tool

1. Problem Definition

I’ve been described the topic above during my previous class because there is not yet available intensive study concerning MARR (Minimum Attractive Rate of Return or “hurdle rate”) in Indonesia for mining. For Simatupang2014 class, I will use Analytic Hierarchy Process (AHP) based on risk of project location and type criteria for developing mining MARR.

Figure 1 Mining Activity

1. Identify the Feasible Alternatives

There is not yet standard for mining MARR in Indonesia which divided the MARR for project. For first approach I take MARR from reference[1] as follows:

• For high risk project type, the MARR value is 25%
• For moderate risk project type, the MARR value is 18%
• For low risk project type, the MARR value is 10%

These values will be compared later with result using AHP model[2].

1. Development of the Outcome for Alternatives

In sequences described the modelling for mining MARR as follows:

1. WACC Value-Cost from Capital

I take the WACC 12.40 % of P90 based on the previous simulation[3].

2. MARR Formula

The MARR formula reference for AHP model is:

MARR for mining = WACC + Country Risk + Project Risk

Country risk premium for Indonesia is 4.13%[4]

Project risk divided into project stage (exploration and operational), project location (Java, Sumatera, Kalimantan and Papua) and mining method (surface mining and underground mining)

3. AHP Diagram

AHP diagram developed for this simulation present in Figure 2:

Figure 2 AHP diagram for Mining Activity

4. AHP Model Result

AHP model gives the risk result for project present in Figure 3:

Figure 3 Project Risks Result

1. Selection Criteria

I want to find the range of mining MARR based on country and project risk in Indonesia using AHP tool and compare it with previous reference.

1.  Analysis and Comparison of the Alternatives

It shows on above Figure 3, Papua is the worst place concerning project risk compare to Java. It is logic considering infrastructure transport, field condition, labor force …etc. In other hand Java has low risk in project due to accessibility compare to Papua.

1.  Selection of the Preferred Alternatives

Finally I can develop the mining MARR range for Indonesia as follow:

Minimum mining MARR in Indonesia                       =          12.40% + 4.13% + 0.70% = 17.23% or rounded to 17%

Maximum mining MARR in Indonesia                      =          12.40% + 4.13% + 27.31% = 43.84% or rounded to 44%

In short the range for mining MARR in Indonesia is between 17% – 44%. The previous 18% – 25% MARR for moderate and high risk project is within this range but not the low risk project, 10% MARR it seem too low.

1. Performance Monitoring and the Post Evaluation of Result

This range of MARR could be used as 1st assessment and required further study for final confirmation. The simulation of Mining MARR using AHP could also extend for specific mining method such as drift wall, shaft, high wall and others.

References

[1]Sullivan, William G., Wicks, Elin M., & C.Patrick, Koelling. (2012), Engineering Economy (15th Edition) (pp.531-533). New Jersey, United States: Prentice Hall.

1 Comment

Filed under Arif P, Week 09

### One response to “W9_APE_Mining MARR in Indonesia Using AHP Tool”

1. WOW!!!! AWESOME posting Pak Arif!!!!

Too bad you didn’t cite Bu Lita’s work as well? Remember she did her CCC/E Paper on this topic? I am just waiting for her OK to submit it for publication.

Interesting for my SSK Migas guys that Indonesia uses 10% MARR correct? This same topic would be great for you to explore as well as the 10% Indonesia currently uses is GROSSLY lower than it should be and is causing you to undertake projects with returns far too low given the risks.

Keep up the good work, but I would hope that you will move to other tools besides just AHP? Clearly you have mastered this tool which is good, but I want you to push yourself to test drive some new tools and techniques.

BR,
Dr. PDG, Jakarta, Indonesia