Decision Making Prentice Hall, Inc. A 1

Transkripsi

1 Decision Making Product Design of ITATS Module based on Operation Management, 9e PowerPoint presentation to accompany Heizer/Render Lecturer: F. Priyo Suprobo, ST, MT 2008 Prentice Hall, Inc. A 1

2 Permasalahan Konsultan desain HCID-ITATS ITATS bekerja untuk Healthy Pillow Company sedang mengusulkan rancangan Alas Tidur Kesehatan yang mutakhir dengan beberapa pilihan. Bekerjasama dengan tenaga pemasaran Healthy Pillow dirumuskanlah beberapa alternatif berikut peluang keberhasilannya sebagai berikut: Selanjutnya, terhadap alternatif yang ada, apakah saran Anda sebagai staf HCID-ITATS ITATS untuk Healthy Pillow ini? 2008 Prentice Hall, Inc. A 2

3 Outline Proses Keputusan Dasar-Dasar Pengambilan Keputusan Tabel Keputusan 2008 Prentice Hall, Inc. A 3

4 Outline Continued Tipe Pengambilan Keputusan Pengambilan Keputusan dalam Ketidakpastian Pengambilan Keputusan dengan Resiko Pengambilan Keputusan dalam Kepastian Expected Value of Perfect Information (EVPI) 2008 Prentice Hall, Inc. A 4

5 Outline Continued Pohon Keputusan Pohon Keputusan Sederhana Pohon Keputusan yang lebih Kompleks 2008 Prentice Hall, Inc. A 5

6 Learning Objectives When you complete this module you should be able to: 1. Membuat sebuah pohon keputusan sederhana 2. Membangun tabel keputusan 3. Menjelaskan kapan menggunakan salah satu tipe dalam pengambilan keputusan 4. Menghitung expected monetary value (EMV) 2008 Prentice Hall, Inc. A 6

7 Learning Objectives When you complete this module you should be able to: 5. Menghitung expected value of perfect information (EVPI) 6. Mengevaluasi titik-titik dalam Pohon Keputusan 7. Membuat Pohon Keputusan dengan penyelesaian berurutan 2008 Prentice Hall, Inc. A 7

8 The Decision Process in Operations 1. Clearly define the problems and the factors that influence it 2. Develop specific and measurable objectives 3. Develop a model 4. Evaluate each alternative solution 5. Select the best alternative 6. Implement the decision and set a timetable for completion 2008 Prentice Hall, Inc. A 8

9 Fundamentals of Decision Making 1. Terminologi/Istilah: a. Alternative Sebuah tindakan atau strategi yang dapat dipilih oleh pengambil keputusan b. State of nature/kondisi Alami Sebuah kejadian atau kondisi dimana pengambil keputusan hanya punya sedikit kendali atau tidak sama sekali 2008 Prentice Hall, Inc. A 9

10 Fundamentals of Decision Making 2. Symbols dalam Pohon Keputusan: a. Sebuah titik keputusan dimana terdapat satu atau lebih alternatif yang dapat dipilih b. sebuah simbol titik kondisi alami yang mungkin terjadi 2008 Prentice Hall, Inc. A 10

11 Decision Tree Example Titik Keputusan Titik Kondisi Alami Pasar sesuai harapan Pasar tidak sesuai harapan Desain TPC Pasar sesuai harapan Pasar tidak sesuai harapan Figure A Prentice Hall, Inc. A 11

12 Decision Table Example Alternatives Pasar sesuai Kondisi Alami Pasar TidakSesuai Desain UMPC $200,000 $180,000 Desain Tablet PC $100,000 $ 20,000 Do nothing $ 0 $ 0 Table A Prentice Hall, Inc. A 12

13 Decision-Making Environments Pengambilan Keputusan dalam Ketidakpastian Kondisi alami tidak dapat diperkirakan Pengambilan Keputusan dengan Resiko Beberapa kondisi alami mungkin terjadi Tetapi masing-masing pilihan tetap berpeluang Pengambilan Keputusan dalam Kepastian Kondisi alami diketahui pasti 2008 Prentice Hall, Inc. A 13

14 Ketidakpastian 1. Maximax Find the alternative that maximizes the maximum outcome for every alternative Pick the outcome with the maximum number Highest possible gain This is viewed as an optimistic approach 2008 Prentice Hall, Inc. A 14

15 Ketidakpastian 2. Maximin Find the alternative that maximizes the minimum outcome for every alternative Pick the outcome with the minimum number Least possible loss This is viewed as a pessimistic approach 2008 Prentice Hall, Inc. A 15

16 Ketidakpastian 3. Equally likely (Sama rata) Find the alternative with the highest average outcome Pick the outcome with the maximum number Assumes each state of nature is equally likely to occur 2008 Prentice Hall, Inc. A 16

17 Uncertainty Example Alternatives Kondisi alamiah Pasar sesuai Pasar tidak Harapan sesuai Maximum in Row Minimum in Row Row Average Desain UMPC $200,000 -$180,000 $200,000 -$180,000 $10,000 Desain Tablet PC $100,000 -$20,000 $100,000 -$20,000 $40,000 Do nothing $0 $0 $0 $0 $0 Maximax Maximin 1. Maximax choice is to construct a UMPC Design 2. Maximin choice is to do nothing 3. Equally likely choice is to construct a Tablet PC Equally likely 2008 Prentice Hall, Inc. A 17

18 Beresiko Each possible state of nature has an assumed probability States of nature are mutually exclusive Probabilities must sum to 1 Determine the expected monetary value (EMV) for each alternative 2008 Prentice Hall, Inc. A 18

19 Expected Monetary Value EMV (Alternative i) = (Payoff of 1 st state of nature) x (Probability of 1 st state of nature) + (Payoff of 2 nd state of nature) x (Probability of 2 nd state of nature) + + (Payoff of last state of nature) x (Probability of last state of nature) 2008 Prentice Hall, Inc. A 19

20 EMV Example Table A.3 Alternatives Pasar sesuai Harapan Kondisi Alamiah Pasar tidak sesuai harapan Desain UMPC (A1) $200,000 -$180,000 Desain Tablet PC (A2) $100,000 -$20,000 Do nothing (A3) $0 $0 Probabilities EMV(A 1 ) = (.5)($200,000) + (.5)(-$180,000) = $10, EMV(A 2 ) = (.5)($100,000) + (.5)(-$20,000) = $40, EMV(A 3 ) = (.5)($0) + (.5)($0) = $ Prentice Hall, Inc. A 20

21 EMV Example Table A.3 Alternatives Pasar Sesuai Harapan Kondisi Alamiah Pasar tidak Sesuai Harapan Desain UMPC (A1) $200,000 -$180,000 Desain Tablet PC (A2) $100,000 -$20,000 Do nothing (A3) $0 $0 Probabilities EMV(A 1 ) = (.5)($200,000) + (.5)(-$180,000) = $10, EMV(A 2 ) = (.5)($100,000) + (.5)(-$20,000) = $40, EMV(A 3 ) = (.5)($0) + (.5)($0) = $0 Best Option 2008 Prentice Hall, Inc. A 21

22 Kepastian Is the cost of perfect information worth it? Determine the expected value of perfect information (EVPI) 2008 Prentice Hall, Inc. A 22

23 Expected Value of Perfect Information EVPI is the difference between the payoff under certainty and the payoff under risk Expected value Maximum EVPI = with perfect EMV information Expected value with perfect information (EVwPI) = (Best outcome or consequence for 1 st state of nature) x (Probability of 1 st state of nature) + Best outcome for 2 nd state of nature) x (Probability of 2 nd state of nature) + + Best outcome for last state of nature) x (Probability of last state of nature) 2008 Prentice Hall, Inc. A 23

24 EVPI Example 1. Hasil terbaik untuk kondisi alamiah Pasar yang sesuai Harapan adalah Desain UMPC dengan payoff of $200,000. Hasil terbaik untuk Pasar yang Tidak sesuai Harapan adalah do nothing dengan payoff of $0. Expected value with perfect information (EVwPI) = ($200,000)(.50) + ($0)(.50) = $100, Prentice Hall, Inc. A 24

25 EVPI Example 2. Maximum EMV is $40,000, yang adalah hasil harapan terbaik tanpa informasi sempurna. Sehingga: EVPI = EVwPI Maximum EMV = $100,000 $40,000 = $60,000 The most the company should pay for perfect information is $60, Prentice Hall, Inc. A 25

26 Pohon Keputusan Information in decision tables can be displayed as decision trees A decision tree is a graphic display of the decision process that indicates decision alternatives, states of nature and their respective probabilities, and payoffs for each combination of decision alternative and state of nature Appropriate for showing sequential decisions 2008 Prentice Hall, Inc. A 26

27 Decision Trees 2008 Prentice Hall, Inc. A 27

28 Pohon Keputusan 1. Mendefinisikan Masalah 2. Menggambar Pohon Keputusan 3. Menentukan Peluang bagi Kondisi Alamiah 4. Memperkirakan imbalan bagi setiap kombinasi alternatif keputusan dan kondisi alamiah yang mungkin 5. Menyelesaikan permasalahan dengan mengerjakan dari belakang ke depan melalui perhitungan EMV untuk masing- masing titik kondisi alamiah Prentice Hall, Inc. A 28

29 Decision Tree Example EMV for node 1 = $10,000 = (.5)($200,000) + (.5)(-$180,000) Pasar sesuai harapan (.5) Payoffs $200,000 Desain Tablet PC 1 2 Pasar tidak sesuai (.5) Pasar sesuai harapan (.5) Pasar tidak sesuai (.5) -$180,000 $100,000 -$20,000 EMV for node 2 = $40,000 = (.5)($100,000) + (.5)(-$20,000) Figure A.2 $ Prentice Hall, Inc. A 29

30 Complex Decision Tree Example Figure A Prentice Hall, Inc. A 30

31 Complex Example 1. Given favorable survey results EMV(2) = (.78)($190,000) + (.22)(-$190,000) = $106,400 EMV(3) = (.78)($90,000) + (.22)(-$30,000) = $63,600 The EMV for no plant = -$10,000 so, if the survey results are favorable, build the large plant 2008 Prentice Hall, Inc. A 31

32 Complex Example 2. Given negative survey results EMV(4) = (.27)($190,000) + (.73)(-$190,000) = -$87,400 EMV(5) = (.27)($90,000) + (.73)(-$30,000) = $2,400 The EMV for no plant = -$10,000 so, if the survey results are negative, build the small plant 2008 Prentice Hall, Inc. A 32

33 Complex Example 3. Compute the expected value of the market survey EMV(1) = (.45)($106,400) + (.55)($2,400) = $49, If the market survey is not conducted EMV(6) = (.5)($200,000) + (.5)(-$180,000) = $10,000 EMV(7) = (.5)($100,000) + (.5)(-$20,000) = $40,000 The EMV for no plant = $0 so, given no survey, build the small plant 2008 Prentice Hall, Inc. A 33

34 The end Pokok Bahasan Selanjutnya: Teknik Peramalan (F O R E C A S T I N G) 2008 Prentice Hall, Inc. A 34