Tugas – tugas
Kelompok 1
Fiqih
Hendry
Imam
Tsabitah
Bint
Kelompok 2
Kris
M. Zainul
Afrian
Muslikah
Ria
Kelompok 3
Novita
Ermita
Bikriyah
M. Yudithia
Lina
Kelompok 4
Fadh
Widyaningsih
Sumaya
Yeni
No. Absen 36
Kelompok 5
Dian
M. Luqman
Presiani
No. Absen 29
No. Absen 37
Kelompok 6
Natasya
Shahril
Ayu
Agung
Izzatul
Kelompok 7
Suci
Shilahul
Diwa
Arina
Dianita
Kelompok 8
Yashinta
Shulby
Rizky
Anggraeni
Tugas Kelompok 1
Modelkan Data berikut menggunakan Regresi Data Panel
Tulis dalam bentuk Makalah dan Presentasikan
Gunakan Excell
Variabel Y
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
Belgium
0.01352
1
0.01839
2
0.02167
6
0.02368
5
0.01334
0.01612
7
0.01489
2
0.00469
5
0.01212
0.00603
7
0.01559
6
0.03173
5
0.04203
2
0.03853
0.04370
2
0.04694
4
0.04702
9
0.03416
2
0.03643
3
0.04909
6
Denmar
k
0.00511
0.00191
4
0.00230
5
0.00207
4
0.00169
2
0.00235
4
0.00105
6
0.00027
0.00186
2
0.00193
5
0.00080
5
0.00452
7
0.01009
2
0.00846
7
0.01155
9
0.00689
5
0.01234
6
0.03288
3
0.02296
8
0.00422
German
y
0.00327
0.00215
8
0.00368
7
0.00078
8
0.00043
7
0.00113
9
0.00262
5
0.00086
4
0.00079
0.00114
4
0.00163
8
0.00085
0.00604
2
0.00168
2
0.00243
4
0.00130
3
0.00099
4
0.00092
2
0.00487
3
0.00269
6
Greece
0.01244
5
0.01467
0.01585
1
0.02657
5
0.01150
6
0.00925
2
0.01027
1
0.01167
0.01091
2
0.00971
6
0.01210
6
0.01384
5
0.01107
0.01193
6
0.01254
8
0.01144
2
0.01046
4
0.00977
5
0.00895
4
0.0085
Spain
0.00482
3
0.00573
8
0.01001
9
0.01308
7
0.00882
3
0.00950
9
0.00987
5
0.01067
0.01131
1
0.01428
1
0.01491
7
0.01948
5
0.02121
5
0.02714
7
0.02259
0.02196
5
0.01937
7
0.01819
8
0.01077
2
0.01115
7
Variabel X
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
Belgium
0.6
2.8
2.3
4.4
-1.2
1.4
0
2.5
1
1.5
2.4
4.7
3.6
2.7
2
1.6
-1.5
3
2.5
1
Denmar
k
1.6
1.5
3.5
-0.4
-0.9
3
2.5
4.4
4.3
3.6
0.3
1.2
0.3
1.2
1.4
1.3
0.8
5.8
3.7
2.8
German
y
2.8
3
4.2
1
0.1
-0.9
1.8
2.8
2
2.3
1.5
3.7
3.6
5.7
5
2.2
-1.1
2.3
1.7
0.8
Greece
2.9
7.2
3.3
0.7
-1.6
-1.1
-1.1
2
2.5
0.5
-2.3
4.3
3.8
0
3.1
0.7
-1.6
2
2.1
2.4
Spain
2.8
1.5
0
1.3
-0.2
1.6
2.2
1.5
2.6
3.2
5.6
5.2
4.7
3.7
2.3
0.7
-1.2
2.3
2.7
2.3
Tugas Kelompok 2
Modelkan Data Berikut menggunakan regresi berganda yang sesuai
Uji Asumsi dan jika ada yang tdak memenuhi, atasi masalah tersebut
Tulis dalam bentuk Makalah dan Presentasikan
Gunakan Excell
Tahun
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
Y
274246
291872
289086
291249
290001
284092
305163
322410
327732
326175
325339
333192
345191
356994
372426
385240
405462
423145
X1
39534
45236
52183
64207
74675
85270
98328
116686
135454
150391
164694
181047
193935
211950
235071
258136
291627
319995
X2
X3
5.91
10.19
10.06
5.87
5.06
7.19
11.69
14.5
17.75
13.63
9.25
9.94
8.69
7.94
6.31
7.38
9.25
8.34
8.48
12.82
11.3
10.93
14.09
6.39
11.91
16.49
13.45
15.35
9.96
9.04
9.33
11.49
10.94
8.38
12.91
15.02
X4
38156
46544
51671
57943
64538
74074
85090
97339
114149
137837
154865
175385
199158
225144
258208
304728
357765
425734
1990
1991
1992
1993
1994
1995
1996
1997
438935
445552
461964
475850
481924
494574
505392
523699
347247
368232
387312
412398
433829
454171
485418
516793
7.53
4.22
3.37
3.31
6.44
5.54
5.5
5.69
13.5
10.45
6.44
4.95
6
6.31
6.26
7.13
476690
503826
517579
543008
565728
621847
681903
719869
Tugas Kelompok 3
Modelkan data berikut dengan model regresi yang sesuai
JK = 1, Laki – laki
Ras =1, Putih
Tulis dalam bentuk Makalah dan Presentasikan
Gunakan Excell
WAGE
115
200
233
260
265
289
300
310
318
325
325
340
345
346
350
350
350
350
357
357
360
369
370
375
375
375
377
380
390
390
393
Jenis
Kelamin
RAS
1
1
1
1
1
1
1
0
1
1
1
1
1
1
1
1
0
1
1
1
0
0
1
1
0
1
0
1
1
1
1
0
1
0
1
0
0
1
0
1
1
1
1
1
1
0
0
1
1
1
1
0
0
1
1
0
1
1
1
1
1
1
400
400
400
400
400
400
402
403
409
1
1
1
1
1
0
1
1
0
0
0
0
1
1
1
0
1
1
Tugas Kelompok 4
Modelkan Data Berikut menggunakan regresi berganda yang sesuai
Uji Asumsi dan jika ada yang tdak memenuhi, atasi masalah tersebut
Tulis dalam bentuk Makalah dan Presentasikan
Gunakan Excell
liquidity
0.825
1.039
0.854
1.065
1.442
1.620
1.477
1.108
3.224
1.160
1.711
0.936
1.076
1.829
1.270
1.505
1.035
1.075
1.033
1.468
2.521
1.218
0.803
1.039
2.768
0.593
3.364
1.101
1.155
asset
structure
0.511
0.697
0.730
0.351
0.725
0.390
0.206
0.101
0.649
0.418
0.378
0.634
0.358
0.541
0.211
0.174
0.387
0.237
0.436
0.272
0.013
0.145
0.386
0.282
0.609
0.248
0.187
0.071
0.408
inventory turnover
66.1
66.5
52.0
68.4
54.6
29.5
63.0
105.1
40.0
72.7
75.0
36.6
49.5
30.8
86.5
77.7
48.6
90.2
99.6
104.3
45.9
58.6
41.0
78.2
48.5
37.9
57.0
54.0
69.3
net profit/sales
0.028
0.017
-0.121
-0.102
0.022
0.003
0.000
-0.019
-0.028
0.036
0.084
0.026
0.018
0.167
-0.021
0.056
0.009
0.047
-0.020
0.020
0.009
0.036
0.087
0.022
0.226
0.180
0.078
0.008
0.067
1.242
1.383
1.478
1.350
3.386
4.016
2.333
0.654
2.031
1.485
1.142
2.067
1.408
1.280
3.291
2.308
3.180
0.941
0.603
4.388
1.281
2.768
1.362
3.191
0.511
2.706
1.458
4.812
1.194
1.089
1.501
3.484
2.082
1.187
3.167
2.498
1.549
3.176
3.837
4.174
1.244
1.283
0.205
1.137
1.225
1.168
1.439
1.477
2.635
1.742
0.116
0.219
0.236
0.245
0.581
0.048
0.109
0.349
0.171
0.225
0.022
0.096
0.863
0.033
0.226
0.257
0.232
0.360
0.093
0.522
0.425
0.561
0.675
0.410
0.206
0.402
0.301
0.735
0.216
0.630
0.135
0.098
0.134
0.014
0.536
0.015
0.434
0.978
0.116
0.611
0.150
0.012
0.561
0.201
0.296
0.437
0.509
0.359
0.493
0.391
77.3
32.6
81.9
59.7
96.8
59.7
81.5
62.4
93.2
71.5
53.1
60.8
79.9
11.5
73.3
39.7
50.7
100.2
48.1
85.2
92.6
88.8
46.8
81.9
46.3
48.9
41.5
96.0
25.0
26.9
16.8
15.0
30.3
1.2
6.8
7.0
18.6
15.1
15.2
32.7
28.1
45.0
6.5
12.9
7.7
27.8
5.8
38.6
4.8
40.8
0.054
0.093
0.032
-0.078
0.002
0.165
0.196
0.031
0.217
0.055
0.013
-0.111
-0.023
0.009
0.134
0.121
-0.023
-0.027
0.020
-0.009
0.073
0.008
0.025
0.084
-0.200
0.036
0.060
0.011
0.189
0.016
0.044
0.055
0.167
0.115
0.113
0.080
0.048
0.112
0.116
0.096
0.041
0.013
0.015
-0.024
0.083
0.058
0.011
0.086
0.074
0.136
1.164
1.461
1.097
1.292
2.194
0.774
0.661
5.200
1.575
1.144
0.939
1.992
1.558
1.286
1.286
0.509
5.200
5.200
1.646
2.940
1.495
4.222
1.056
3.459
1.561
1.925
0.933
1.196
1.176
1.264
0.488
1.566
1.967
0.961
0.865
1.192
1.259
1.163
1.231
1.151
4.478
2.066
1.954
1.577
2.645
1.183
1.254
1.552
0.562
1.090
0.469
0.064
0.328
0.027
0.148
0.275
0.327
0.586
0.393
0.307
0.321
0.418
0.671
0.406
0.824
0.204
0.465
0.403
0.516
0.399
0.329
0.836
0.443
0.463
0.326
0.371
0.096
0.378
0.489
0.226
0.437
0.743
0.596
0.419
0.107
0.323
0.152
0.615
0.629
0.352
0.159
0.735
0.309
0.516
0.413
0.573
0.248
0.110
0.284
0.575
27.3
33.9
23.7
37.4
12.0
0.2
11.6
3.0
20.6
13.2
27.1
23.8
31.1
31.6
30.0
15.1
135.5
142.4
124.8
168.2
198.8
183.5
330.0
251.2
212.6
192.7
190.8
215.4
302.1
143.9
330.0
150.8
330.0
165.6
120.5
119.5
149.7
127.1
155.1
243.7
127.6
193.5
189.7
140.2
138.7
228.4
198.5
137.5
120.0
136.6
0.146
0.034
0.220
0.018
0.022
-0.005
0.001
0.035
0.087
0.021
0.006
0.139
0.176
0.136
0.088
0.050
-0.200
0.154
0.076
0.048
0.279
0.042
0.051
0.001
0.070
0.069
0.001
0.040
0.054
0.052
-0.200
0.001
0.001
0.004
0.017
-0.108
0.033
-0.033
0.034
0.061
0.084
-0.093
0.047
0.050
0.008
-0.034
0.052
0.164
-0.211
-0.106
4.628
1.830
2.440
4.650
2.875
1.130
0.721
2.283
1.599
5.200
1.099
1.237
0.800
1.338
0.432
0.495
0.131
0.166
0.295
0.306
0.655
0.330
0.120
0.465
0.582
0.440
0.297
0.646
122.1
161.6
330.0
118.7
175.0
214.0
195.9
151.9
203.7
199.4
156.9
265.6
330.0
114.8
0.020
0.004
0.218
0.067
0.123
-0.200
-0.204
-0.082
0.005
0.028
0.040
0.013
0.078
0.014
Tugas Kelompok 5
Modelkan Data Berikut menggunakan regresi berganda yang sesuai
Uji Asumsi dan jika ada yang tdak memenuhi, atasi masalah tersebut
Tulis dalam bentuk Makalah dan Presentasikan
Gunakan Excell
Obs
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
liquidit
y (Y)
0.825
1.039
0.854
1.065
1.442
1.620
1.477
1.108
3.224
1.160
1.711
0.936
1.076
1.829
1.270
1.505
1.035
1.075
1.033
1.468
2.521
1.218
0.803
1.039
2.768
0.593
Sector
(X1)
food
food
food
food
food
food
food
food
food
food
drinks
drinks
drinks
drinks
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
Region(X2)
Athens
Athens
Larissa
Athens
Ahaia
Athens
Kalamata
Piraeus
Salonica
Komotini
Athens
Creta
Creta
Ioannina
Athens
Athens
Serres
Athens
Kilkis
Salonica
Athens
Athens
athens
Fthiotis
salonica
athens
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
3.364
1.101
1.155
1.242
1.383
1.478
1.350
3.386
4.016
2.333
0.654
2.031
1.485
1.142
2.067
1.408
1.280
3.291
2.308
3.180
0.941
0.603
4.388
1.281
2.768
1.362
3.191
0.511
2.706
1.458
4.812
1.194
1.089
1.501
3.484
2.082
1.187
3.167
2.498
1.549
3.176
3.837
4.174
1.244
1.283
0.205
1.137
1.225
1.168
1.439
textiles
garments
garments
garments
garments
garments
garments
garments
garments
garments
garments
garments
garments
garments
garments
garments
garments
leather
leather
leather
leather
wood
wood
wood
furniture
furniture
furniture
furniture
paper
paper
paper
paper
paper
printing
printing
printing
printing
printing
printing
printing
printing
printing
printing
plastics
plastics
plastics
plastics
plastics
plastics
plastics
athens
athenw
creta
athens
salonica
athens
athenw
athens
,athens
salonica
kastoria
athens
athens
salonica
athens
salonica
athens
athens
kastoria
athens
viotia
lamia
athens
Trikala
serres
athens
salonica
athens
salonica
athens
athens
athens
athens
piraeus
athens
athens
athens
attica
athens
athens
athens
athens
athens
athens
piraeus
naousa
athens
athens
salonica
salonica
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
1.477
2.635
1.742
1.164
1.461
1.097
1.292
2.194
0.774
0.661
5.200
1.575
1.144
0.939
1.992
1.558
1.286
94
1.286
95
0.509
96
5.200
97
5.200
98
1.646
99
2.940
100
1.495
101
4.222
102
1.056
103
3.459
104
1.561
105
1.925
106
0.933
107
1.196
108
1.176
109
1.264
110
0.488
111
1.566
plastics
plastics
plastics
plastics
chemicals
chemicals
chemicals
chemicals
chemicals
chemicals
chemicals
chemicals
chemicals
chemicals
chemicals
petroleum
petroleum
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
basic
metal
basic
metal
metal
prod
metal
prod
metal
prod
metal
prod
larissa
athens
athens
athens
athens
athens
athens
athens
attica
Korinth
athens
athens
athens
attica
attica
attica
attica
serres
lamia
creta
kozani
volos
thassos
lamia
athens
attica
salonica
attica
larissa
larissa
athens
creta
salonica
attica
komotini
112
1.967
113
0.961
114
0.865
115
1.192
116
1.259
117
1.163
118
1.231
119
1.151
120
4.478
121
2.066
122
1.954
123
1.577
124
2.645
125
1.183
126
1.254
127
1.552
128
0.562
129
1.090
130
4.628
131
1.830
132
2.440
133
4.650
134
2.875
135
136
137
138
139
140
141
1.130
0.721
2.283
1.599
5.200
1.099
1.237
metal
prod
metal
prod
metal
prod
metal
prod
metal
prod
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
sundry
sundry
sundry
sundry
sundry
sundry
attica
attica
piraeus
piraeus
attica
salonica
attica
attica
salonica
amficlia
athens
kilkis
athens
salonica
athens
athens
attica
attica
viotia
koropi
halkida
trikala
viotia
piraeus
salonica
attica
attica
attica
athens
athens
142
143
0.800
1.338
sundry
sundry
salonica
patras
Tugas Kelompok 6
Obs
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
Modelkan Data Berikut menggunakan regresi berganda yang sesuai
Uji Asumsi dan jika ada yang tdak memenuhi, atasi masalah tersebut
Tulis dalam bentuk Makalah dan Presentasikan
Gunakan Excell
liquidit
y (Y)
0.825
1.039
0.854
1.065
1.442
1.620
1.477
1.108
3.224
1.160
1.711
0.936
1.076
1.829
1.270
1.505
1.035
1.075
1.033
1.468
2.521
1.218
0.803
1.039
2.768
0.593
3.364
1.101
1.155
1.242
1.383
1.478
1.350
3.386
4.016
2.333
0.654
2.031
Sector
(X1)
food
food
food
food
food
food
food
food
food
food
drinks
drinks
drinks
drinks
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
garments
garments
garments
garments
garments
garments
garments
garments
garments
garments
garments
No empl.
(X2)
15
48
30
32
38
24
20
60
60
22
40
30
50
60
3
10
5
38
25
75
10
37
8
70
75
140
15
18
33
40
55
29
45
40
14
40
8
20
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
1.485
1.142
2.067
1.408
1.280
3.291
2.308
3.180
0.941
0.603
4.388
1.281
2.768
1.362
3.191
0.511
2.706
1.458
4.812
1.194
1.089
1.501
3.484
2.082
1.187
3.167
2.498
1.549
3.176
3.837
4.174
1.244
1.283
0.205
1.137
1.225
1.168
1.439
1.477
2.635
1.742
1.164
1.461
1.097
1.292
2.194
0.774
0.661
5.200
1.575
garments
garments
garments
garments
garments
leather
leather
leather
leather
wood
wood
wood
furniture
furniture
furniture
furniture
paper
paper
paper
paper
paper
printing
printing
printing
printing
printing
printing
printing
printing
printing
printing
plastics
plastics
plastics
plastics
plastics
plastics
plastics
plastics
plastics
plastics
plastics
chemicals
chemicals
chemicals
chemicals
chemicals
chemicals
chemicals
chemicals
65
80
85
50
33
15
60
65
11
14
20
46
36
45
42
45
18
18
35
60
40
18
9
19
35
28
12
47
32
70
12
10
11
9
12
32
18
32
40
40
55
65
26
4
38
24
28
35
25
15
89
90
91
92
93
1.144
0.939
1.992
1.558
1.286
94
1.286
95
0.509
96
5.200
97
5.200
98
1.646
99
2.940
100
1.495
101
4.222
102
1.056
103
3.459
104
1.561
105
1.925
106
0.933
107
1.196
108
1.176
109
1.264
110
0.488
111
1.566
112
1.967
113
0.961
114
0.865
115
1.192
116
1.259
117
118
1.163
1.231
chemicals
chemicals
chemicals
petroleum
petroleum
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
basic
metal
basic
metal
metal
prod
metal
prod
metal
prod
metal
prod
metal
prod
metal
prod
metal
prod
metal
prod
metal
prod
machiner
y
machiner
60
70
30
20
49
14
25
30
25
40
70
40
32
50
25
38
70
30
35
25
27
25
16
27
35
35
20
30
8
18
119
1.151
120
4.478
121
2.066
122
1.954
123
1.577
124
2.645
125
1.183
126
1.254
127
1.552
128
0.562
129
1.090
130
4.628
131
1.830
132
2.440
133
4.650
134
2.875
135
136
137
138
139
140
141
142
143
1.130
0.721
2.283
1.599
5.200
1.099
1.237
0.800
1.338
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
sundry
sundry
sundry
sundry
sundry
sundry
sundry
sundry
13
20
17
50
50
50
30
35
10
16
30
43
55
50
6
24
30
15
34
50
21
12
20
20
36
Tugas Kelompok 7
Modelkan Data Berikut menggunakan regresi berganda yang sesuai
Uji Asumsi dan jika ada yang tdak memenuhi, atasi masalah tersebut
Tulis dalam bentuk Makalah dan Presentasikan
Gunakan Excell
Obs
liquidity
age(X1)
Region(X2)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
(Y)
0.825
1.039
0.854
1.065
1.442
1.620
1.477
1.108
3.224
1.160
1.711
0.936
1.076
1.829
1.270
1.505
1.035
1.075
1.033
1.468
2.521
1.218
0.803
1.039
2.768
0.593
3.364
1.101
1.155
1.242
1.383
1.478
1.350
3.386
4.016
2.333
0.654
2.031
1.485
1.142
2.067
1.408
1.280
3.291
2.308
3.180
0.941
0.603
4.388
4
21
2
15
43
59
30
20
12
8
12
24
11
30
2
48
2
13
4
38
40
26
18
30
9
38
9
1
2
2
6
9
32
2
2
3
1
19
13
1
25
12
8
2
8
11
29
18
25
Athens
Athens
Larissa
Athens
Ahaia
Athens
Kalamata
Piraeus
Salonica
Komotini
Athens
Creta
Creta
Ioannina
Athens
Athens
Serres
Athens
Kilkis
Salonica
Athens
Athens
athens
Fthiotis
salonica
athens
athens
athenw
creta
athens
salonica
athens
athenw
athens
,athens
salonica
kastoria
athens
athens
salonica
athens
salonica
athens
athens
kastoria
athens
viotia
lamia
athens
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
1.281
2.768
1.362
3.191
0.511
2.706
1.458
4.812
1.194
1.089
1.501
3.484
2.082
1.187
3.167
2.498
1.549
3.176
3.837
4.174
1.244
1.283
0.205
1.137
1.225
1.168
1.439
1.477
2.635
1.742
1.164
1.461
1.097
1.292
2.194
0.774
0.661
5.200
1.575
1.144
0.939
1.992
1.558
1.286
1.286
0.509
5.200
5.200
1.646
2.940
78
21
16
12
10
11
8
6
18
2
14
8
3
2
18
58
7
22
9
2
13
2
3
1
19
13
21
19
29
28
10
11
11
24
9
19
4
2
4
19
13
58
26
26
4
13
11
2
30
6
Trikala
serres
athens
salonica
athens
salonica
athens
athens
athens
athens
piraeus
athens
athens
athens
attica
athens
athens
athens
athens
athens
athens
piraeus
naousa
athens
athens
salonica
salonica
larissa
athens
athens
athens
athens
athens
athens
athens
attica
Korinth
athens
athens
athens
attica
attica
attica
attica
serres
lamia
creta
kozani
volos
thassos
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
1.495
4.222
1.056
3.459
1.561
1.925
0.933
1.196
1.176
1.264
0.488
1.566
1.967
0.961
0.865
1.192
1.259
1.163
1.231
1.151
4.478
2.066
1.954
1.577
2.645
1.183
1.254
1.552
0.562
1.090
4.628
1.830
2.440
4.650
2.875
1.130
0.721
2.283
1.599
5.200
1.099
1.237
0.800
1.338
5
19
14
15
19
29
10
13
13
7
18
1
6
7
1
49
6
6
35
1
7
1
19
5
40
19
2
2
10
22
3
14
2
2
7
40
9
1
2
1
9
16
2
11
lamia
athens
attica
salonica
attica
larissa
larissa
athens
creta
salonica
attica
komotini
attica
attica
piraeus
piraeus
attica
salonica
attica
attica
salonica
amficlia
athens
kilkis
athens
salonica
athens
athens
attica
attica
viotia
koropi
halkida
trikala
viotia
piraeus
salonica
attica
attica
attica
athens
athens
salonica
patras
Tugas Kelompok 8
Modelkan Data Berikut menggunakan regresi berganda yang sesuai
Uji Asumsi dan jika ada yang tdak memenuhi, atasi masalah tersebut
Tulis dalam bentuk Makalah dan Presentasikan
Gunakan Excell
Obs
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
liquidity
(Y)
0.825
1.039
0.854
1.065
1.442
1.620
1.477
1.108
3.224
1.160
1.711
0.936
1.076
1.829
1.270
1.505
1.035
1.075
1.033
1.468
2.521
1.218
0.803
1.039
2.768
0.593
3.364
1.101
1.155
1.242
1.383
1.478
1.350
3.386
4.016
2.333
0.654
2.031
1.485
1.142
2.067
1.408
1.280
3.291
2.308
3.180
0.941
Net Profit / Total
Assets (X1)
0.039
0.008
-0.078
-0.141
0.036
0.009
0.000
-0.029
-0.033
0.031
0.108
0.039
0.031
0.291
-0.039
0.064
0.017
0.052
-0.021
0.031
0.013
0.065
0.188
0.034
0.209
0.119
0.250
0.011
0.092
0.139
0.191
0.042
-0.093
0.001
0.166
0.224
0.038
0.287
0.094
0.021
-0.188
-0.025
0.064
0.165
0.307
-0.024
-0.022
Region(X2)
Athens
Athens
Larissa
Athens
Ahaia
Athens
Kalamata
Piraeus
Salonica
Komotini
Athens
Creta
Creta
Ioannina
Athens
Athens
Serres
Athens
Kilkis
Salonica
Athens
Athens
athens
Fthiotis
salonica
athens
athens
athenw
creta
athens
salonica
athens
athenw
athens
,athens
salonica
kastoria
athens
athens
salonica
athens
salonica
athens
athens
kastoria
athens
viotia
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
0.603
4.388
1.281
2.768
1.362
3.191
0.511
2.706
1.458
4.812
1.194
1.089
1.501
3.484
2.082
1.187
3.167
2.498
1.549
3.176
3.837
4.174
1.244
1.283
0.205
1.137
1.225
1.168
1.439
1.477
2.635
1.742
1.164
1.461
1.097
1.292
2.194
0.774
0.661
5.200
1.575
1.144
0.939
1.992
1.558
1.286
1.286
0.509
5.200
5.200
0.017
-0.009
0.057
0.015
0.043
0.085
-0.250
0.027
0.074
0.010
0.213
0.033
0.080
0.056
0.163
0.207
0.266
0.201
0.123
0.182
0.169
0.129
0.111
0.055
0.019
-0.027
0.186
0.097
0.019
0.143
0.168
0.233
0.165
0.079
0.241
0.034
0.045
-0.010
0.003
0.036
0.060
0.071
0.011
0.198
0.360
0.205
0.230
0.101
-0.169
0.098
lamia
athens
Trikala
serres
athens
salonica
athens
salonica
athens
athens
athens
athens
piraeus
athens
athens
athens
attica
athens
athens
athens
athens
athens
athens
piraeus
naousa
athens
athens
salonica
salonica
larissa
athens
athens
athens
athens
athens
athens
athens
attica
Korinth
athens
athens
athens
attica
attica
attica
attica
serres
lamia
creta
kozani
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
1.646
2.940
1.495
4.222
1.056
3.459
1.561
1.925
0.933
1.196
1.176
1.264
0.488
1.566
1.967
0.961
0.865
1.192
1.259
1.163
1.231
1.151
4.478
2.066
1.954
1.577
2.645
1.183
1.254
1.552
0.562
1.090
4.628
1.830
2.440
4.650
2.875
1.130
0.721
2.283
1.599
5.200
1.099
1.237
0.800
1.338
0.055
0.047
0.158
0.033
0.027
0.001
0.064
0.084
0.001
0.043
0.033
0.036
-0.078
0.001
0.000
0.001
0.016
-0.121
0.032
-0.064
0.033
0.045
0.133
-0.074
0.029
0.099
0.009
-0.009
0.029
0.164
-0.075
-0.071
0.009
0.002
0.046
0.060
0.067
-0.145
-0.182
-0.065
0.005
0.006
0.029
0.010
0.028
0.011
volos
thassos
lamia
athens
attica
salonica
attica
larissa
larissa
athens
creta
salonica
attica
komotini
attica
attica
piraeus
piraeus
attica
salonica
attica
attica
salonica
amficlia
athens
kilkis
athens
salonica
athens
athens
attica
attica
viotia
koropi
halkida
trikala
viotia
piraeus
salonica
attica
attica
attica
athens
athens
salonica
patras
Fiqih
Hendry
Imam
Tsabitah
Bint
Kelompok 2
Kris
M. Zainul
Afrian
Muslikah
Ria
Kelompok 3
Novita
Ermita
Bikriyah
M. Yudithia
Lina
Kelompok 4
Fadh
Widyaningsih
Sumaya
Yeni
No. Absen 36
Kelompok 5
Dian
M. Luqman
Presiani
No. Absen 29
No. Absen 37
Kelompok 6
Natasya
Shahril
Ayu
Agung
Izzatul
Kelompok 7
Suci
Shilahul
Diwa
Arina
Dianita
Kelompok 8
Yashinta
Shulby
Rizky
Anggraeni
Tugas Kelompok 1
Modelkan Data berikut menggunakan Regresi Data Panel
Tulis dalam bentuk Makalah dan Presentasikan
Gunakan Excell
Variabel Y
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
Belgium
0.01352
1
0.01839
2
0.02167
6
0.02368
5
0.01334
0.01612
7
0.01489
2
0.00469
5
0.01212
0.00603
7
0.01559
6
0.03173
5
0.04203
2
0.03853
0.04370
2
0.04694
4
0.04702
9
0.03416
2
0.03643
3
0.04909
6
Denmar
k
0.00511
0.00191
4
0.00230
5
0.00207
4
0.00169
2
0.00235
4
0.00105
6
0.00027
0.00186
2
0.00193
5
0.00080
5
0.00452
7
0.01009
2
0.00846
7
0.01155
9
0.00689
5
0.01234
6
0.03288
3
0.02296
8
0.00422
German
y
0.00327
0.00215
8
0.00368
7
0.00078
8
0.00043
7
0.00113
9
0.00262
5
0.00086
4
0.00079
0.00114
4
0.00163
8
0.00085
0.00604
2
0.00168
2
0.00243
4
0.00130
3
0.00099
4
0.00092
2
0.00487
3
0.00269
6
Greece
0.01244
5
0.01467
0.01585
1
0.02657
5
0.01150
6
0.00925
2
0.01027
1
0.01167
0.01091
2
0.00971
6
0.01210
6
0.01384
5
0.01107
0.01193
6
0.01254
8
0.01144
2
0.01046
4
0.00977
5
0.00895
4
0.0085
Spain
0.00482
3
0.00573
8
0.01001
9
0.01308
7
0.00882
3
0.00950
9
0.00987
5
0.01067
0.01131
1
0.01428
1
0.01491
7
0.01948
5
0.02121
5
0.02714
7
0.02259
0.02196
5
0.01937
7
0.01819
8
0.01077
2
0.01115
7
Variabel X
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
Belgium
0.6
2.8
2.3
4.4
-1.2
1.4
0
2.5
1
1.5
2.4
4.7
3.6
2.7
2
1.6
-1.5
3
2.5
1
Denmar
k
1.6
1.5
3.5
-0.4
-0.9
3
2.5
4.4
4.3
3.6
0.3
1.2
0.3
1.2
1.4
1.3
0.8
5.8
3.7
2.8
German
y
2.8
3
4.2
1
0.1
-0.9
1.8
2.8
2
2.3
1.5
3.7
3.6
5.7
5
2.2
-1.1
2.3
1.7
0.8
Greece
2.9
7.2
3.3
0.7
-1.6
-1.1
-1.1
2
2.5
0.5
-2.3
4.3
3.8
0
3.1
0.7
-1.6
2
2.1
2.4
Spain
2.8
1.5
0
1.3
-0.2
1.6
2.2
1.5
2.6
3.2
5.6
5.2
4.7
3.7
2.3
0.7
-1.2
2.3
2.7
2.3
Tugas Kelompok 2
Modelkan Data Berikut menggunakan regresi berganda yang sesuai
Uji Asumsi dan jika ada yang tdak memenuhi, atasi masalah tersebut
Tulis dalam bentuk Makalah dan Presentasikan
Gunakan Excell
Tahun
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
Y
274246
291872
289086
291249
290001
284092
305163
322410
327732
326175
325339
333192
345191
356994
372426
385240
405462
423145
X1
39534
45236
52183
64207
74675
85270
98328
116686
135454
150391
164694
181047
193935
211950
235071
258136
291627
319995
X2
X3
5.91
10.19
10.06
5.87
5.06
7.19
11.69
14.5
17.75
13.63
9.25
9.94
8.69
7.94
6.31
7.38
9.25
8.34
8.48
12.82
11.3
10.93
14.09
6.39
11.91
16.49
13.45
15.35
9.96
9.04
9.33
11.49
10.94
8.38
12.91
15.02
X4
38156
46544
51671
57943
64538
74074
85090
97339
114149
137837
154865
175385
199158
225144
258208
304728
357765
425734
1990
1991
1992
1993
1994
1995
1996
1997
438935
445552
461964
475850
481924
494574
505392
523699
347247
368232
387312
412398
433829
454171
485418
516793
7.53
4.22
3.37
3.31
6.44
5.54
5.5
5.69
13.5
10.45
6.44
4.95
6
6.31
6.26
7.13
476690
503826
517579
543008
565728
621847
681903
719869
Tugas Kelompok 3
Modelkan data berikut dengan model regresi yang sesuai
JK = 1, Laki – laki
Ras =1, Putih
Tulis dalam bentuk Makalah dan Presentasikan
Gunakan Excell
WAGE
115
200
233
260
265
289
300
310
318
325
325
340
345
346
350
350
350
350
357
357
360
369
370
375
375
375
377
380
390
390
393
Jenis
Kelamin
RAS
1
1
1
1
1
1
1
0
1
1
1
1
1
1
1
1
0
1
1
1
0
0
1
1
0
1
0
1
1
1
1
0
1
0
1
0
0
1
0
1
1
1
1
1
1
0
0
1
1
1
1
0
0
1
1
0
1
1
1
1
1
1
400
400
400
400
400
400
402
403
409
1
1
1
1
1
0
1
1
0
0
0
0
1
1
1
0
1
1
Tugas Kelompok 4
Modelkan Data Berikut menggunakan regresi berganda yang sesuai
Uji Asumsi dan jika ada yang tdak memenuhi, atasi masalah tersebut
Tulis dalam bentuk Makalah dan Presentasikan
Gunakan Excell
liquidity
0.825
1.039
0.854
1.065
1.442
1.620
1.477
1.108
3.224
1.160
1.711
0.936
1.076
1.829
1.270
1.505
1.035
1.075
1.033
1.468
2.521
1.218
0.803
1.039
2.768
0.593
3.364
1.101
1.155
asset
structure
0.511
0.697
0.730
0.351
0.725
0.390
0.206
0.101
0.649
0.418
0.378
0.634
0.358
0.541
0.211
0.174
0.387
0.237
0.436
0.272
0.013
0.145
0.386
0.282
0.609
0.248
0.187
0.071
0.408
inventory turnover
66.1
66.5
52.0
68.4
54.6
29.5
63.0
105.1
40.0
72.7
75.0
36.6
49.5
30.8
86.5
77.7
48.6
90.2
99.6
104.3
45.9
58.6
41.0
78.2
48.5
37.9
57.0
54.0
69.3
net profit/sales
0.028
0.017
-0.121
-0.102
0.022
0.003
0.000
-0.019
-0.028
0.036
0.084
0.026
0.018
0.167
-0.021
0.056
0.009
0.047
-0.020
0.020
0.009
0.036
0.087
0.022
0.226
0.180
0.078
0.008
0.067
1.242
1.383
1.478
1.350
3.386
4.016
2.333
0.654
2.031
1.485
1.142
2.067
1.408
1.280
3.291
2.308
3.180
0.941
0.603
4.388
1.281
2.768
1.362
3.191
0.511
2.706
1.458
4.812
1.194
1.089
1.501
3.484
2.082
1.187
3.167
2.498
1.549
3.176
3.837
4.174
1.244
1.283
0.205
1.137
1.225
1.168
1.439
1.477
2.635
1.742
0.116
0.219
0.236
0.245
0.581
0.048
0.109
0.349
0.171
0.225
0.022
0.096
0.863
0.033
0.226
0.257
0.232
0.360
0.093
0.522
0.425
0.561
0.675
0.410
0.206
0.402
0.301
0.735
0.216
0.630
0.135
0.098
0.134
0.014
0.536
0.015
0.434
0.978
0.116
0.611
0.150
0.012
0.561
0.201
0.296
0.437
0.509
0.359
0.493
0.391
77.3
32.6
81.9
59.7
96.8
59.7
81.5
62.4
93.2
71.5
53.1
60.8
79.9
11.5
73.3
39.7
50.7
100.2
48.1
85.2
92.6
88.8
46.8
81.9
46.3
48.9
41.5
96.0
25.0
26.9
16.8
15.0
30.3
1.2
6.8
7.0
18.6
15.1
15.2
32.7
28.1
45.0
6.5
12.9
7.7
27.8
5.8
38.6
4.8
40.8
0.054
0.093
0.032
-0.078
0.002
0.165
0.196
0.031
0.217
0.055
0.013
-0.111
-0.023
0.009
0.134
0.121
-0.023
-0.027
0.020
-0.009
0.073
0.008
0.025
0.084
-0.200
0.036
0.060
0.011
0.189
0.016
0.044
0.055
0.167
0.115
0.113
0.080
0.048
0.112
0.116
0.096
0.041
0.013
0.015
-0.024
0.083
0.058
0.011
0.086
0.074
0.136
1.164
1.461
1.097
1.292
2.194
0.774
0.661
5.200
1.575
1.144
0.939
1.992
1.558
1.286
1.286
0.509
5.200
5.200
1.646
2.940
1.495
4.222
1.056
3.459
1.561
1.925
0.933
1.196
1.176
1.264
0.488
1.566
1.967
0.961
0.865
1.192
1.259
1.163
1.231
1.151
4.478
2.066
1.954
1.577
2.645
1.183
1.254
1.552
0.562
1.090
0.469
0.064
0.328
0.027
0.148
0.275
0.327
0.586
0.393
0.307
0.321
0.418
0.671
0.406
0.824
0.204
0.465
0.403
0.516
0.399
0.329
0.836
0.443
0.463
0.326
0.371
0.096
0.378
0.489
0.226
0.437
0.743
0.596
0.419
0.107
0.323
0.152
0.615
0.629
0.352
0.159
0.735
0.309
0.516
0.413
0.573
0.248
0.110
0.284
0.575
27.3
33.9
23.7
37.4
12.0
0.2
11.6
3.0
20.6
13.2
27.1
23.8
31.1
31.6
30.0
15.1
135.5
142.4
124.8
168.2
198.8
183.5
330.0
251.2
212.6
192.7
190.8
215.4
302.1
143.9
330.0
150.8
330.0
165.6
120.5
119.5
149.7
127.1
155.1
243.7
127.6
193.5
189.7
140.2
138.7
228.4
198.5
137.5
120.0
136.6
0.146
0.034
0.220
0.018
0.022
-0.005
0.001
0.035
0.087
0.021
0.006
0.139
0.176
0.136
0.088
0.050
-0.200
0.154
0.076
0.048
0.279
0.042
0.051
0.001
0.070
0.069
0.001
0.040
0.054
0.052
-0.200
0.001
0.001
0.004
0.017
-0.108
0.033
-0.033
0.034
0.061
0.084
-0.093
0.047
0.050
0.008
-0.034
0.052
0.164
-0.211
-0.106
4.628
1.830
2.440
4.650
2.875
1.130
0.721
2.283
1.599
5.200
1.099
1.237
0.800
1.338
0.432
0.495
0.131
0.166
0.295
0.306
0.655
0.330
0.120
0.465
0.582
0.440
0.297
0.646
122.1
161.6
330.0
118.7
175.0
214.0
195.9
151.9
203.7
199.4
156.9
265.6
330.0
114.8
0.020
0.004
0.218
0.067
0.123
-0.200
-0.204
-0.082
0.005
0.028
0.040
0.013
0.078
0.014
Tugas Kelompok 5
Modelkan Data Berikut menggunakan regresi berganda yang sesuai
Uji Asumsi dan jika ada yang tdak memenuhi, atasi masalah tersebut
Tulis dalam bentuk Makalah dan Presentasikan
Gunakan Excell
Obs
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
liquidit
y (Y)
0.825
1.039
0.854
1.065
1.442
1.620
1.477
1.108
3.224
1.160
1.711
0.936
1.076
1.829
1.270
1.505
1.035
1.075
1.033
1.468
2.521
1.218
0.803
1.039
2.768
0.593
Sector
(X1)
food
food
food
food
food
food
food
food
food
food
drinks
drinks
drinks
drinks
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
Region(X2)
Athens
Athens
Larissa
Athens
Ahaia
Athens
Kalamata
Piraeus
Salonica
Komotini
Athens
Creta
Creta
Ioannina
Athens
Athens
Serres
Athens
Kilkis
Salonica
Athens
Athens
athens
Fthiotis
salonica
athens
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
3.364
1.101
1.155
1.242
1.383
1.478
1.350
3.386
4.016
2.333
0.654
2.031
1.485
1.142
2.067
1.408
1.280
3.291
2.308
3.180
0.941
0.603
4.388
1.281
2.768
1.362
3.191
0.511
2.706
1.458
4.812
1.194
1.089
1.501
3.484
2.082
1.187
3.167
2.498
1.549
3.176
3.837
4.174
1.244
1.283
0.205
1.137
1.225
1.168
1.439
textiles
garments
garments
garments
garments
garments
garments
garments
garments
garments
garments
garments
garments
garments
garments
garments
garments
leather
leather
leather
leather
wood
wood
wood
furniture
furniture
furniture
furniture
paper
paper
paper
paper
paper
printing
printing
printing
printing
printing
printing
printing
printing
printing
printing
plastics
plastics
plastics
plastics
plastics
plastics
plastics
athens
athenw
creta
athens
salonica
athens
athenw
athens
,athens
salonica
kastoria
athens
athens
salonica
athens
salonica
athens
athens
kastoria
athens
viotia
lamia
athens
Trikala
serres
athens
salonica
athens
salonica
athens
athens
athens
athens
piraeus
athens
athens
athens
attica
athens
athens
athens
athens
athens
athens
piraeus
naousa
athens
athens
salonica
salonica
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
1.477
2.635
1.742
1.164
1.461
1.097
1.292
2.194
0.774
0.661
5.200
1.575
1.144
0.939
1.992
1.558
1.286
94
1.286
95
0.509
96
5.200
97
5.200
98
1.646
99
2.940
100
1.495
101
4.222
102
1.056
103
3.459
104
1.561
105
1.925
106
0.933
107
1.196
108
1.176
109
1.264
110
0.488
111
1.566
plastics
plastics
plastics
plastics
chemicals
chemicals
chemicals
chemicals
chemicals
chemicals
chemicals
chemicals
chemicals
chemicals
chemicals
petroleum
petroleum
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
basic
metal
basic
metal
metal
prod
metal
prod
metal
prod
metal
prod
larissa
athens
athens
athens
athens
athens
athens
athens
attica
Korinth
athens
athens
athens
attica
attica
attica
attica
serres
lamia
creta
kozani
volos
thassos
lamia
athens
attica
salonica
attica
larissa
larissa
athens
creta
salonica
attica
komotini
112
1.967
113
0.961
114
0.865
115
1.192
116
1.259
117
1.163
118
1.231
119
1.151
120
4.478
121
2.066
122
1.954
123
1.577
124
2.645
125
1.183
126
1.254
127
1.552
128
0.562
129
1.090
130
4.628
131
1.830
132
2.440
133
4.650
134
2.875
135
136
137
138
139
140
141
1.130
0.721
2.283
1.599
5.200
1.099
1.237
metal
prod
metal
prod
metal
prod
metal
prod
metal
prod
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
sundry
sundry
sundry
sundry
sundry
sundry
attica
attica
piraeus
piraeus
attica
salonica
attica
attica
salonica
amficlia
athens
kilkis
athens
salonica
athens
athens
attica
attica
viotia
koropi
halkida
trikala
viotia
piraeus
salonica
attica
attica
attica
athens
athens
142
143
0.800
1.338
sundry
sundry
salonica
patras
Tugas Kelompok 6
Obs
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
Modelkan Data Berikut menggunakan regresi berganda yang sesuai
Uji Asumsi dan jika ada yang tdak memenuhi, atasi masalah tersebut
Tulis dalam bentuk Makalah dan Presentasikan
Gunakan Excell
liquidit
y (Y)
0.825
1.039
0.854
1.065
1.442
1.620
1.477
1.108
3.224
1.160
1.711
0.936
1.076
1.829
1.270
1.505
1.035
1.075
1.033
1.468
2.521
1.218
0.803
1.039
2.768
0.593
3.364
1.101
1.155
1.242
1.383
1.478
1.350
3.386
4.016
2.333
0.654
2.031
Sector
(X1)
food
food
food
food
food
food
food
food
food
food
drinks
drinks
drinks
drinks
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
textiles
garments
garments
garments
garments
garments
garments
garments
garments
garments
garments
garments
No empl.
(X2)
15
48
30
32
38
24
20
60
60
22
40
30
50
60
3
10
5
38
25
75
10
37
8
70
75
140
15
18
33
40
55
29
45
40
14
40
8
20
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
1.485
1.142
2.067
1.408
1.280
3.291
2.308
3.180
0.941
0.603
4.388
1.281
2.768
1.362
3.191
0.511
2.706
1.458
4.812
1.194
1.089
1.501
3.484
2.082
1.187
3.167
2.498
1.549
3.176
3.837
4.174
1.244
1.283
0.205
1.137
1.225
1.168
1.439
1.477
2.635
1.742
1.164
1.461
1.097
1.292
2.194
0.774
0.661
5.200
1.575
garments
garments
garments
garments
garments
leather
leather
leather
leather
wood
wood
wood
furniture
furniture
furniture
furniture
paper
paper
paper
paper
paper
printing
printing
printing
printing
printing
printing
printing
printing
printing
printing
plastics
plastics
plastics
plastics
plastics
plastics
plastics
plastics
plastics
plastics
plastics
chemicals
chemicals
chemicals
chemicals
chemicals
chemicals
chemicals
chemicals
65
80
85
50
33
15
60
65
11
14
20
46
36
45
42
45
18
18
35
60
40
18
9
19
35
28
12
47
32
70
12
10
11
9
12
32
18
32
40
40
55
65
26
4
38
24
28
35
25
15
89
90
91
92
93
1.144
0.939
1.992
1.558
1.286
94
1.286
95
0.509
96
5.200
97
5.200
98
1.646
99
2.940
100
1.495
101
4.222
102
1.056
103
3.459
104
1.561
105
1.925
106
0.933
107
1.196
108
1.176
109
1.264
110
0.488
111
1.566
112
1.967
113
0.961
114
0.865
115
1.192
116
1.259
117
118
1.163
1.231
chemicals
chemicals
chemicals
petroleum
petroleum
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
non
metalic
basic
metal
basic
metal
metal
prod
metal
prod
metal
prod
metal
prod
metal
prod
metal
prod
metal
prod
metal
prod
metal
prod
machiner
y
machiner
60
70
30
20
49
14
25
30
25
40
70
40
32
50
25
38
70
30
35
25
27
25
16
27
35
35
20
30
8
18
119
1.151
120
4.478
121
2.066
122
1.954
123
1.577
124
2.645
125
1.183
126
1.254
127
1.552
128
0.562
129
1.090
130
4.628
131
1.830
132
2.440
133
4.650
134
2.875
135
136
137
138
139
140
141
142
143
1.130
0.721
2.283
1.599
5.200
1.099
1.237
0.800
1.338
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
machiner
y
sundry
sundry
sundry
sundry
sundry
sundry
sundry
sundry
13
20
17
50
50
50
30
35
10
16
30
43
55
50
6
24
30
15
34
50
21
12
20
20
36
Tugas Kelompok 7
Modelkan Data Berikut menggunakan regresi berganda yang sesuai
Uji Asumsi dan jika ada yang tdak memenuhi, atasi masalah tersebut
Tulis dalam bentuk Makalah dan Presentasikan
Gunakan Excell
Obs
liquidity
age(X1)
Region(X2)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
(Y)
0.825
1.039
0.854
1.065
1.442
1.620
1.477
1.108
3.224
1.160
1.711
0.936
1.076
1.829
1.270
1.505
1.035
1.075
1.033
1.468
2.521
1.218
0.803
1.039
2.768
0.593
3.364
1.101
1.155
1.242
1.383
1.478
1.350
3.386
4.016
2.333
0.654
2.031
1.485
1.142
2.067
1.408
1.280
3.291
2.308
3.180
0.941
0.603
4.388
4
21
2
15
43
59
30
20
12
8
12
24
11
30
2
48
2
13
4
38
40
26
18
30
9
38
9
1
2
2
6
9
32
2
2
3
1
19
13
1
25
12
8
2
8
11
29
18
25
Athens
Athens
Larissa
Athens
Ahaia
Athens
Kalamata
Piraeus
Salonica
Komotini
Athens
Creta
Creta
Ioannina
Athens
Athens
Serres
Athens
Kilkis
Salonica
Athens
Athens
athens
Fthiotis
salonica
athens
athens
athenw
creta
athens
salonica
athens
athenw
athens
,athens
salonica
kastoria
athens
athens
salonica
athens
salonica
athens
athens
kastoria
athens
viotia
lamia
athens
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
1.281
2.768
1.362
3.191
0.511
2.706
1.458
4.812
1.194
1.089
1.501
3.484
2.082
1.187
3.167
2.498
1.549
3.176
3.837
4.174
1.244
1.283
0.205
1.137
1.225
1.168
1.439
1.477
2.635
1.742
1.164
1.461
1.097
1.292
2.194
0.774
0.661
5.200
1.575
1.144
0.939
1.992
1.558
1.286
1.286
0.509
5.200
5.200
1.646
2.940
78
21
16
12
10
11
8
6
18
2
14
8
3
2
18
58
7
22
9
2
13
2
3
1
19
13
21
19
29
28
10
11
11
24
9
19
4
2
4
19
13
58
26
26
4
13
11
2
30
6
Trikala
serres
athens
salonica
athens
salonica
athens
athens
athens
athens
piraeus
athens
athens
athens
attica
athens
athens
athens
athens
athens
athens
piraeus
naousa
athens
athens
salonica
salonica
larissa
athens
athens
athens
athens
athens
athens
athens
attica
Korinth
athens
athens
athens
attica
attica
attica
attica
serres
lamia
creta
kozani
volos
thassos
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
1.495
4.222
1.056
3.459
1.561
1.925
0.933
1.196
1.176
1.264
0.488
1.566
1.967
0.961
0.865
1.192
1.259
1.163
1.231
1.151
4.478
2.066
1.954
1.577
2.645
1.183
1.254
1.552
0.562
1.090
4.628
1.830
2.440
4.650
2.875
1.130
0.721
2.283
1.599
5.200
1.099
1.237
0.800
1.338
5
19
14
15
19
29
10
13
13
7
18
1
6
7
1
49
6
6
35
1
7
1
19
5
40
19
2
2
10
22
3
14
2
2
7
40
9
1
2
1
9
16
2
11
lamia
athens
attica
salonica
attica
larissa
larissa
athens
creta
salonica
attica
komotini
attica
attica
piraeus
piraeus
attica
salonica
attica
attica
salonica
amficlia
athens
kilkis
athens
salonica
athens
athens
attica
attica
viotia
koropi
halkida
trikala
viotia
piraeus
salonica
attica
attica
attica
athens
athens
salonica
patras
Tugas Kelompok 8
Modelkan Data Berikut menggunakan regresi berganda yang sesuai
Uji Asumsi dan jika ada yang tdak memenuhi, atasi masalah tersebut
Tulis dalam bentuk Makalah dan Presentasikan
Gunakan Excell
Obs
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
liquidity
(Y)
0.825
1.039
0.854
1.065
1.442
1.620
1.477
1.108
3.224
1.160
1.711
0.936
1.076
1.829
1.270
1.505
1.035
1.075
1.033
1.468
2.521
1.218
0.803
1.039
2.768
0.593
3.364
1.101
1.155
1.242
1.383
1.478
1.350
3.386
4.016
2.333
0.654
2.031
1.485
1.142
2.067
1.408
1.280
3.291
2.308
3.180
0.941
Net Profit / Total
Assets (X1)
0.039
0.008
-0.078
-0.141
0.036
0.009
0.000
-0.029
-0.033
0.031
0.108
0.039
0.031
0.291
-0.039
0.064
0.017
0.052
-0.021
0.031
0.013
0.065
0.188
0.034
0.209
0.119
0.250
0.011
0.092
0.139
0.191
0.042
-0.093
0.001
0.166
0.224
0.038
0.287
0.094
0.021
-0.188
-0.025
0.064
0.165
0.307
-0.024
-0.022
Region(X2)
Athens
Athens
Larissa
Athens
Ahaia
Athens
Kalamata
Piraeus
Salonica
Komotini
Athens
Creta
Creta
Ioannina
Athens
Athens
Serres
Athens
Kilkis
Salonica
Athens
Athens
athens
Fthiotis
salonica
athens
athens
athenw
creta
athens
salonica
athens
athenw
athens
,athens
salonica
kastoria
athens
athens
salonica
athens
salonica
athens
athens
kastoria
athens
viotia
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
0.603
4.388
1.281
2.768
1.362
3.191
0.511
2.706
1.458
4.812
1.194
1.089
1.501
3.484
2.082
1.187
3.167
2.498
1.549
3.176
3.837
4.174
1.244
1.283
0.205
1.137
1.225
1.168
1.439
1.477
2.635
1.742
1.164
1.461
1.097
1.292
2.194
0.774
0.661
5.200
1.575
1.144
0.939
1.992
1.558
1.286
1.286
0.509
5.200
5.200
0.017
-0.009
0.057
0.015
0.043
0.085
-0.250
0.027
0.074
0.010
0.213
0.033
0.080
0.056
0.163
0.207
0.266
0.201
0.123
0.182
0.169
0.129
0.111
0.055
0.019
-0.027
0.186
0.097
0.019
0.143
0.168
0.233
0.165
0.079
0.241
0.034
0.045
-0.010
0.003
0.036
0.060
0.071
0.011
0.198
0.360
0.205
0.230
0.101
-0.169
0.098
lamia
athens
Trikala
serres
athens
salonica
athens
salonica
athens
athens
athens
athens
piraeus
athens
athens
athens
attica
athens
athens
athens
athens
athens
athens
piraeus
naousa
athens
athens
salonica
salonica
larissa
athens
athens
athens
athens
athens
athens
athens
attica
Korinth
athens
athens
athens
attica
attica
attica
attica
serres
lamia
creta
kozani
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
1.646
2.940
1.495
4.222
1.056
3.459
1.561
1.925
0.933
1.196
1.176
1.264
0.488
1.566
1.967
0.961
0.865
1.192
1.259
1.163
1.231
1.151
4.478
2.066
1.954
1.577
2.645
1.183
1.254
1.552
0.562
1.090
4.628
1.830
2.440
4.650
2.875
1.130
0.721
2.283
1.599
5.200
1.099
1.237
0.800
1.338
0.055
0.047
0.158
0.033
0.027
0.001
0.064
0.084
0.001
0.043
0.033
0.036
-0.078
0.001
0.000
0.001
0.016
-0.121
0.032
-0.064
0.033
0.045
0.133
-0.074
0.029
0.099
0.009
-0.009
0.029
0.164
-0.075
-0.071
0.009
0.002
0.046
0.060
0.067
-0.145
-0.182
-0.065
0.005
0.006
0.029
0.010
0.028
0.011
volos
thassos
lamia
athens
attica
salonica
attica
larissa
larissa
athens
creta
salonica
attica
komotini
attica
attica
piraeus
piraeus
attica
salonica
attica
attica
salonica
amficlia
athens
kilkis
athens
salonica
athens
athens
attica
attica
viotia
koropi
halkida
trikala
viotia
piraeus
salonica
attica
attica
attica
athens
athens
salonica
patras