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LMCP 1352 ASAS-ASAS SAINS DATA DALAM PENGANGKUTAN - TUGASAN PISAH RAGAMAN
- 1. LMCP 1352 ASAS-ASAS SAINS DATA DALAM PENGANGKUTAN TUGASAN PISAH RAGAMAN NAMA : LOO CHANTEL NO. MATRIKS : A171019 NAMA PENSYARAH : PROF. DATO’ IR DR. RIZA ATIQ ABDULLAH BIN O.K. RAHMAT
- 2. SOALAN 1 Kadar Pakir Satu Jam Kebarangkalian peralih kepada pengangkutan awam 0.5 0.04 1 0.06 1.5 0.1 2 0.17 2.5 0.28 3 0.39 3.5 0.5 4 0.65 4.5 0.75 5 0.8 5.5 0.83 6 0.86
- 3. FUNGSI LOGISTIK 𝑃 = 1 1 + 𝑒𝛼 ∗ 𝑘𝑎𝑑𝑎𝑟 + 𝐶
- 4. GRAF
- 5. DATA DALAM BENTUK LN Kadar Pakir Satu Jam Kebarangkalian peralih kepada pengangkutan awam (1-p)/p ln[(1-p)/p] 0.5 0.04 24 3.1781 1 0.06 15.6667 2.7515 1.5 0.1 9 2.1972 2 0.17 4.8824 1.5856 2.5 0.28 2.5714 0.9445 3 0.39 1.5641 0.4473 3.5 0.5 1 0 4 0.65 0.5385 -0.619 4.5 0.75 0.3333 -1.0986 5 0.8 0.25 -1.3863 5.5 0.83 0.2048 -1.5856 6 0.86 0.1628 -1.8153
- 6. GRAF
- 7. MODEL FUNGSI LOGISTIK • 𝑃 = 1 1+𝑒𝛼 ∗ 𝑘𝑎𝑑𝑎𝑟 + 𝐶 • 𝛼 = −0.9623 • 𝐶 = 3.1507 • 𝑃 = 1 1+𝑒−0.9623 ∗ 𝑘𝑎𝑑𝑎𝑟 + 3.5107
- 8. KEBARANGKALIAN PENGGUNA BERALIH KEPADA PENGANGKUTAN AWAM Kadar Pakir Satu Jam Kebarangkalian peralih kepada pengangkutan awam (1-p)/p ln[(1-p)/p] P= 1/(1+e^(- 0.9623*kadar+3.5107)) 0.5 0.04 24 3.1781 0.0461 1 0.06 15.6667 2.7515 0.0725 1.5 0.1 9 2.1972 0.1123 2 0.17 4.8824 1.5856 0.1699 2.5 0.28 2.5714 0.9445 0.2488 3 0.39 1.5641 0.4473 0.3489 3.5 0.5 1 0 0.4644 4 0.65 0.5385 -0.619 0.5838 4.5 0.75 0.3333 -1.0986 0.6942 5 0.8 0.25 -1.3863 0.786 5.5 0.83 0.2048 -1.5856 0.8559 6 0.86 0.1628 -1.8153 0.9058
- 9. SOALAN 2 Tambang bas Jimat masa Kebarangkalian Pengguna kereta beralih kepada bas 2.9 0 0.1 2.9 5 0.14 2.9 10 0.19 2.9 15 0.25 2.9 20 0.32 2.9 25 0.4 2.9 30 0.48 2 20 0.35 2.25 20 0.34 2.5 20 0.33 2.75 20 0.32 3 20 0.31 3.25 20 0.31 3.5 20 0.3 3.75 20 0.29
- 10. FUNGSI LOGISTIK 𝑃 = 1 1 + 𝑒𝛼 ∗ 𝑡𝑎𝑚𝑏𝑎𝑛𝑔 + 𝛽 ∗𝑗𝑖𝑚𝑎𝑡 𝑚𝑎𝑠𝑎 + 𝐶
- 11. DATA DALAM BENTUK LN Tambang bas Jimat masa Kebarangkalian Pengguna kereta beralih kepada bas (1-p)/p ln[(1-p)/p] 2.9 0 0.1 9 2.1972 2.9 5 0.14 6.1429 1.8153 2.9 10 0.19 4.2632 1.45 2.9 15 0.25 3 1.0986 2.9 20 0.32 2.125 0.7538 2.9 25 0.4 1.5 0.4055 2.9 30 0.48 1.0833 0.08 2 20 0.35 1.8571 0.619 2.25 20 0.34 1.9412 0.6633 2.5 20 0.33 2.0303 0.7082 2.75 20 0.32 2.125 0.7538 3 20 0.31 2.2258 0.8001 3.25 20 0.31 2.2258 0.8001 3.5 20 0.3 2.3333 0.8473 3.75 20 0.29 2.4483 0.8954
- 12. ANALISIS REGRESI SUMMARY OUTPUT Multiple R 0.999640683 R Square 0.999281494 Adjusted R Square 0.999161743 Standard Error 0.01548873 Observations 15 ANOVA df SS MS F Significance F Regression 2 4.00378234 2.00189117 8344.664286 0 Residual 12 0.002878809 0.0002399 Total 14 4.006661149 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 1.733471846 0.029611002 58.541479 0 1.668955015 1.797988677 1.668955015 1.797988677 Tambang bas 0.151179739 0.009556105 15.8202264 2.11108E-09 0.130358776 0.172000703 0.130358776 0.172000703 Jimat masa -0.070417106 0.000549934 -128.046448 0 -0.071615309 -0.069218902 -0.071615309 -0.069218902 Regression Statistics
- 13. MODUL FUNGSI LOGISTIK • 𝑃 = 1 1+𝑒𝛼 ∗ 𝑡𝑎𝑚𝑏𝑎𝑛𝑔 + 𝛽 ∗ 𝑚𝑎𝑠𝑎 + 𝐶 • 𝛼 = 0.1512 • 𝛽 = −0.0704 • 𝐶 = 1.7335 • 𝑃 = 1 1+𝑒0.1512 ∗ 𝑡𝑎𝑚𝑏𝑎𝑛𝑔 −0.0704 ∗ 𝑚𝑎𝑠𝑎 +1.7335