Asas- asas Sains Data Dalam Pengangkutan

1. LMCP 1352 ASAS-ASAS SAINS DATA
DALAM PENGANGKUTAN
MODUL 9:
TugasanPisahragaman
NAMA : SARASVATHI A/P K SIVARAMAN
NO MATRIKS:A168202
PENSYARAH : PROF DR RIZA ATIQ ABDULLAH

2. Soalan 1

3. a)Model Fungsi Logistik
𝑃 =
1
1+𝑒𝛼 𝑘𝑎𝑑𝑎𝑟 𝑝𝑎𝑟𝑘𝑖𝑟 +𝐶
1−𝑃
𝑃
= 𝑒𝛼 𝑘𝑎𝑑𝑎𝑟 𝑝𝑎𝑟𝑘𝑖𝑟 +𝐶
ln
1−𝑃
𝑃
= 𝛼 𝑘𝑎𝑑𝑎𝑟 𝑝𝑎𝑟𝑘𝑖𝑟 + 𝐶

4. b)Graf
0.04
0.06
0.10
0.17
0.28
0.39
0.50
0.65
0.75
0.80
0.83
0.86
0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00 5.50 6.00
Kebarangkalian
Peralih
kepada
Pengangkutan
Awam
Kadar Parkir 1 jam

5. c)Pertukaran Data ke bentuk ln(log e)
Kadar Parkir 1 jam Kebarangkalian(P)
1 − 𝑃
𝑃
ln(
1−𝑃
𝑃
)
0.50 0.04 24.0000 3.1781
1.00 0.06 15.6667 2.7515
1.50 0.10 9.0000 2.1972
2.00 0.17 4.8824 1.5856
2.50 0.28 2.5714 0.9445
3.00 0.39 1.5641 0.4473
3.50 0.50 1.0000 0.0000
4.00 0.65 0.5385 -0.6190
4.50 0.75 0.3333 -1.0986
5.00 0.80 0.2500 -1.3863
5.50 0.83 0.2048 -1.5856
6.00 0.86 0.1628 -1.8153

6. d) Grag & Persamaan Regressi
y = -0.9623x + 3.5107
R² = 0.9834
-3.0000
-2.0000
-1.0000
0.0000
1.0000
2.0000
3.0000
4.0000
0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00
LN(1-P)/P
KEBARANGKALIAN

7. e) Angka-angka parameter fungsi logistik
y = -0.9623(kadar parkir) + 3.5107
𝛼 = 0.9623
C = 3.5107
𝑃 =
1
1+𝑒0.9623 𝑘𝑎𝑑𝑎𝑟 𝑝𝑎𝑟𝑘𝑖𝑟 +3.5107

8. f) Kebarangkalian Peralihan
Kadar Parkir 1 jam ln(1-P)/P P
0.50 3.1781 0.046109
1.00 2.7515 0.072534
1.50 2.1972 0.112321
2.00 1.5856 0.169933
2.50 0.9445 0.248814
3.00 0.4473 0.348918
3.50 0.0000 0.464398
4.00 -0.6190 0.583826
4.50 -1.0986 0.694162
5.00 -1.3863 0.78597
5.50 -1.5856 0.855937
6.00 -1.8153 0.905775

9. Soalan 2

10. a) Fungsi Logistik Sesuai
𝑃 =
1
1+𝑒𝛼 𝑡𝑎𝑚𝑏𝑎𝑛𝑔 +𝛽(𝑚𝑎𝑠𝑎)+𝐶
1−𝑃
𝑃
= 𝑒𝛼 𝑡𝑎𝑚𝑏𝑎𝑛𝑔 +𝛽(𝑚𝑎𝑠𝑎)+𝐶
ln
1−𝑃
𝑃
= 𝛼 𝑡𝑎𝑚𝑏𝑎𝑛𝑔 + 𝛽(𝑚𝑎𝑠𝑎) + 𝐶

11. b)Pertukaran Data kepada ln(log e)
Tambang bas Jimat Masa Kebarangkalian(P)
1 − 𝑃
𝑃
ln(
1−𝑃
𝑃
)
2.90 0 0.10 9.00 2.1972
2.90 5 0.14 6.14 1.8153
2.90 10 0.19 4.26 1.4500
2.90 15 0.25 3.00 1.0986
2.90 20 0.32 2.13 0.7538
2.90 25 0.40 1.50 0.4055
2.90 30 0.48 1.08 0.0800
2.00 20 0.35 1.86 0.6190
2.25 20 0.34 1.94 0.6633
2.50 20 0.33 2.03 0.7082
2.75 20 0.32 2.13 0.7538
3.00 20 0.31 2.23 0.8001
3.25 20 0.31 2.23 0.8001
3.50 20 0.30 2.33 0.8473
3.75 20 0.29 2.45 0.8954

12. c) Analisis Regressi
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.99964068
R Square 0.99928149
Adjusted R Square 0.99916174
Standard Error 0.01548873
Observations 15
ANOVA
df SS MS F Significance F
Regression 2 4.00378234 2.001891 8344.664 1.37588E-19
Residual 12 0.002878809 0.00024
Total 14 4.006661149
Coefficients Standard Error t Stat P-value Lower 95% Upper 95%
Lower
95.0% Upper 95.0%
Intercept 1.73347185 0.029611002 58.54148 4.08E-16 1.668955015 1.797988677
1.66895501
5 1.797988677
X Variable 1 0.15117974 0.009556105 15.82023 2.11E-09 0.130358776 0.172000703
0.13035877
6 0.172000703
X Variable 2 -0.0704171 0.000549934 -128.046 3.45E-20
-
0.071615309 -0.069218902 -0.07161531 -0.069218902

13. d)Model logistic dengan parameter
y = 0.15118(tambang) - 0.07042(masa) + 1.73347
𝛼 = 0.15118
𝛽 = −0.07042
C = 1.73347
𝑃 =
1
1+𝑒0.15118 𝑡𝑎𝑚𝑏𝑎𝑛𝑔 −0.07042 𝑚𝑎𝑠𝑎 +1.,73347