(2) Jenis Kelamin : 1. Laki-laki Perempuan. (3) Kelompok Usia : tahun tahun B. Pemeriksaan Kategori Massa Tubuh

(1)

Lampiran 1 No.Kartu :

Tanggal :

,2016

DEPARTEMEN ILMU KEDOKTERAN GIGI ANAK

FAKULTAS KEDOKTERAN GIGI

UNIVERSITAS SUMATERA UTARA

HUBUNGAN SKOR PUFA/pufa DENGAN INDEKS MASSA TUBUH PADA ANAK

USIA 6-12 TAHUN DI SD KECAMATAN MEDAN KOTA DAN MEDAN PERJUANGAN

Nama : ...

Kelas : ………..

Tanggal Lahir : ………

(1) Usia : ……….

z: ;

A. Karakteristik Responden

(2) Jenis Kelamin

: 1. Laki-laki

2. 2. Perempuan

(3) Kelompok Usia

: 1. 6-8 tahun

3. 2. 9-12 tahun

B. Pemeriksaan Kategori Massa Tubuh

(4) Tinggi badan : …………...

4. (sentimeter)

(5) Berat badan : ………

5. (kilogram)

(7) Kategori Indeks Massa Tubuh :

1. Dibawah Normal (Z-Score <-2 SD)

2. Normal (Z-Score = -2 SD s.d 1 SD)

3. Diatas Normal (Z-Score > 1SD)

1.

6. ,

,

(2)

No. Kartu :

C. Pemeriksaan skor PUFA/pufa dan DMFT/deft

PUFA/pufa

DMFT/deft

17

16

15

14

13

12

11

21

22

23

24

25

26

27

55

54

53

52

51

61

62

63

64

65

85

84

83

82

81

71

72

73

74

75

47

46

45

44

43

42

41

31

32

33

34

35

36

37 DMFT/deft

PUFA/pufa

Ket:

P/p : karies melibatkan pulpa

D/d : karies belum ditambal

U/u : ulserasi

M/e : indikasi pencabutan atau telah

F/f : fistula

dicabut

A/a : abses

F/f : karies yang telah ditambal tetap

O : Belum erupsi

*Bila ada gigi persistensi, yang dicatat

X : Sudah hilang

adalah kedua gigi yang mengalami

infeksi odontogenik.

(8)

∑ P

8 (9)

∑ U

9 (10)

∑ F

10 (11)

∑ A

11 (12)

∑ PUFA

12 (13)

∑ p

13 (14)

∑ u

14 (15)

∑ f

15 (16)

∑ a

16

(3)

No. Kartu :

(19)

∑ D

19 (20)

∑ M

20 (21)

∑ F

21 (22)

∑ DMFT

22 (23)

∑ d

23 (24)

∑ e

24 (25)

∑ f

25 (26)

∑ deft

26 (27)

∑ DMFT + deft

27 (28) Kategori Anak:

1. PUFA+pufa = 0 dan DMFT+deft = 1-4

28 2. PUFA+pufa = 0 dan DMFT+deft > 4

3. PUFA+pufa

≥ 1

(4)

Nama saya Nur Hardiyanti mahasiswa yang sedang menjalani Pendidikan Dokter Gigi

di Fakultas Kedokteran Gigi Universitas Sumatera Utara. Saya akan mengadakan penelitian

dengan judul Hubungan Skor PUFA dengan Indeks Massa Tubuh pada Anak Usia 6-12

tahun di SD Kecamatan Medan Kota dan Perjuangan. Tujuan dari penelitian ini adalah

mengetahui perbedaan indeks massa tubuh pada kelompok anak usia 6-12 tahun yang memiliki

PUFA/pufa dibandingkan kelompok anak tanpa PUFA/pufa di SD Kecamatan Medan Kota dan

Kecamatan Medan Perjuangan. Manfaat dari penelitian ini adalah untuk memberikan informasi

mengenai hubungan antara kesehatan gigi anak dengan berat badan anak.

Subjek penelitian saya adalah anak usia 6-12 tahun di SDN 060820 dan SDS Al

Washliyah 09 di Kecamatan Medan Kota, dan SDN 060872 dan SDS Rolina di Kecamatan

Medan Perjuangan.

Prosedur penelitian adalah sebagai berikut :

1. Anak diperiksa indeks massa tubuh dengan menimbang berat badan dengan timbangan

digital dan tinggi badan menggunakan meteran gulung.

2. Anak diperiksa tingkat keparahan lubang gigi menggunakan indeks PUFA/pufa dan

DMFT/deft, alat yang digunakan kaca mulut, sonde, dan senter.

Partisipasi anak Bapak/Ibu dalam penelitian ini bersifat sukarela dan subjek tidak akan

dikenakan biaya apapun selama penelitian dilaksanakan. Identitas anak juga akan disamarkan

sehingga kerahasiaan data akan dijamin. Apabila terdapat keluhan ataupun untuk informasi lebih

lanjut mengenai pertanyaan yang berkaitan dengan penelitian ini, Bapak/Ibu dapat menghubungi

saya.

Keuntungan dari penelitian ini adalah orang tua dapat mengetahui seberapa parah

kerusakan dari gigi anak, selain itu orang tua juga bisa mengetahui apakah ada hubungan antara

tingkat keparahan lubang gigi dengan berat badan dan tinggi badan anak serta kategori indeks

massa tubuh anak. Adapun kerugian dari penelitian ini bagi anak yaitu mengambil waktu anak

(5)

Demikian penjelasan mengenai penelitian yang akan saya lakukan. Bila ada yang ingin

ditanyakan atau hendak mendapatkan informasi silahkan menghubungi saya. Atas partisipasi dan

kesediaan waktu Bapak/Ibu, saya ucapkan terima kasih.

Medan,...2016

Nur Hardiyanti

(6)

Lampiran 4

Tabel Standar Indeks Massa Tubuh Menurut Usia (IMT/U)

Anak Laki-Laki Usia 6-12 tahun

(7)

Tabel Standar Indeks Massa Tubuh Menurut Usia (IMT/U)

Anak Laki-Laki Usia 5-18 tahun

(8)

Tabel Standar Indeks Massa Tubuh Menurut Usia (IMT/U)

Anak Laki-Laki Usia 6-12 tahun

(9)

Tabel Standar Indeks Massa Tubuh Menurut Usia (IMT/U)

Anak Perempuan Usia 6-12 tahun

(10)

Tabel Standar Indeks Massa Tubuh Menurut Usia (IMT/U)

Anak Perempuan Usia 6-12 tahun

(11)

Tabel Standar Indeks Massa Tubuh Menurut Usia (IMT/U)

Anak Perempuan Usia 6-12 tahun

(12)

(13)

Lampiran

1 Usia 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

U Bulan JK KU TB BB IMT KIMT ∑ P ∑ U ∑ F ∑ A ∑ PUFA ∑ p ∑u ∑f ∑a ∑ pufa∑ PU∑ D ∑ M ∑ F ∑ DM∑ d ∑ e ∑ f ∑ def∑ DM KA

1 8 8,2 1 1 135 21.5 11.7 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 2 1 2 7 7,4 2 1 113 19.9 15.5 2 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 0 0 0 0 4 1 3 12 12,3 1 2 145 31.6 15 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 1 4 12 12,2 2 2 146 34.3 16 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 1 5 7 7,5 1 1 117 21.3 15.5 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 2 1 6 8 8,3 2 1 113 19.1 14.9 2 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 0 0 0 0 4 1 7 12 12,5 2 2 152 46.1 19.9 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 2 1 8 11 11,2 2 2 144 31.7 15.3 2 0 0 0 0 0 0 0 0 0 0 0 1 0 1 2 0 0 0 0 2 1 9 11 11,4 1 2 113 28.6 16.1 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 2 1 10 11 11,5 1 2 133 26.4 14.9 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 11 10 10,5 1 2 127 29.7 18.4 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 2 1 12 10 10,6 1 2 118 24.2 17.3 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 2 1 13 11 11,5 2 2 132 31.4 18 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 1 14 11 11,6 1 1 128 27.3 16.6 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 1 15 12 12,0 2 2 135 21.7 11.9 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 2 1 16 12 12,0 1 2 155 30 12.4 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 1 17 8 8,3 1 1 122 26.3 18.2 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 2 1 18 11 11,2 2 2 145 50.4 23.9 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 1 0 0 1 3 1 19 8 8,4 1 1 120 25 17.3 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 3 1 20 8 8,5 1 1 129 27 16.2 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 1 21 10 10,1 2 2 130 38.1 22.5 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 3 1 22 10 10,2 1 2 137 32.5 17.3 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 3 1 23 12 12,3 1 2 146 43.7 20.5 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 1 24 12 12,0 1 2 133 23.1 13 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 2 1 25 10 10,5 1 2 136 31.9 17.2 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 2 1 26 10 10,6 2 2 152 42.9 18.5 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 2 1 27 10 10,5 2 2 130 30.8 18.2 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 1 No.

(14)

28

10 10,6

2 2 136 31 17 2 0 0

0 0 0

1 0 0

0 0 1

1

29

12 12,4

1 2 145 32 15 2 0 0

0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 1

30

11 11,3

2 2 141 31 16 2 0 0

0 0 0

3 0 0

0 0 3

1

31

11 11,5

2 2 130 24 14 2 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 2 1

32

10 10,6

1 2 140 42 22 2 0 0

0 0 0

2 0 0

0 0 2

1

33

11 11,2

1 2 138 37 19 2 0 0

0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 2 1

34

7 7,8

2 1 122 31 21 3 0 0

0 0 0

0 2 0

0 2 2

1

35

8 8,5

2 1 114 23 18 2 0 0

0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 1

36

11 11,5

1 2 134 27 15 2 0 0

0 0 0

2 0 0

0 0 2

1

37

6 6,7

1 1 105 18 16 2 0 0

0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 2 1

38

7 7,2

2 1 106 17 15 2 0 0

0 0 0

1 0 0

0 0 1

1

39

7 7,8

1 1 111 21 17 2 0 0

0 0 0 0 0 0 0 0 0 3 0 0 3 0 0 0 0 3 1

40

12 12,5

2 2 127 26 16 2 0 0

0 0 0

0 2 0

0 2 2

1

41

10 10,6

2 2 128 28 17 2 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 1

42

12 12,5

2 2 136 38 20 2 0 0

0 0 0

0 1 0

0 1 1

1

43

12 12,4

1 2 125 26 17 2 0 0

0 0 0 0 0 0 0 0 0 4 0 0 4 0 0 0 0 4 1

44

12 12,3

1 2 149 34 15 2 0 0

0 0 0

0 4 0

0 4 4

1

45

10 10,2

1 2 152 45 19 2 0 0

0 0 0

2 0 0

2 0 0 0 0 2

1

46

11 11,3

2 2 132 28 16 2 0 0

0 0 0

0 1 0

0 1 1

1

47

12 12,5

1 2 138 30 16 2 0 0

0 0 0

1 0 0

1 2 0 0 2 3

1

48

12 12,6

2 2 151 42 19 2 0 0

0 0 0

3 0 0

3 1 0

0 1 4

1

49

11 11,5

1 2 133 31 18 2 0 0

0 0 0

0 4 0 0 4 4

1

50

9 9,11

2 2 118 18 13 1 0 0

0 0 0

0 3 0

0 3 3

1

51

11 11,2

1 2 142 45 22 2 0 0

0 0 0

0 1 0 0 1 1

1

(15)

63 10 10,5 2 2 129 25 15 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 0 0 0 0 3 1 64 10 10,3 2 2 129 32 19 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 2 0 0 2 3 1 65 9 9,2 2 2 134 24 13 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 4 1 66 6 6,5 1 1 115 19 14 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 1 67 10 10,3 2 2 133 30 17 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 2 1 68 10 10,3 1 2 150 55 24 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 1 69 12 12,3 2 2 149 42 19 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 1 70 11 11,2 2 2 144 32 15 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 2 1 71 10 10,2 2 2 134 33 18 2 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 0 0 0 0 4 1 72 10 10,6 2 2 159 59 23 3 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 1 73 11 11,5 1 2 134 27 15 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 3 1 74 11 11,5 1 2 141 27 14 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 3 1 75 12 12,5 1 2 145 35 17 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 1 76 12 12,4 1 2 135 27 15 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 1 77 11 11,5 1 2 142 29 14 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 1 78 11 11,6 1 2 139 31 16 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 0 0 0 0 3 1 79 11 11,7 1 2 127 25 15 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 0 0 0 0 3 1 80 9 9,0 1 2 115 15 11 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 5 5 1 81 9 9,8 1 2 118 23 16 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 1 82 6 6,4 1 1 117 18 13 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 2 1 83 6 6,5 1 1 113 17 13 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 1 84 6 6,8 1 1 121 24 16 2 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 2 1 85 11 11,5 2 2 127 25 15 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 86 8 8,6 2 1 120 26 18 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 1 87 12 12,5 2 2 147 37 17 2 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 1 88 12 12,4 2 2 152 44 19 2 0 0 0 0 0 0 0 0 0 0 0 1 2 0 3 1 0 0 1 4 1 89 6 6,4 2 1 116 19 14 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 0 0 1 1 4 1 90 6 6,5 2 1 115 20 15 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 1 1 2 1 91 11 11,2 1 2 131 27 16 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 1 0 0 1 3 1 92 11 11,3 1 2 135 34 18 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 0 0 1 1 93 9 9,8 1 2 135 37 20 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 2 1 94 12 12,3 1 2 147 28 13 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 95 12 12,4 1 2 128 21 13 1 0 0 0 0 0 0 0 0 0 0 0 1 2 1 3 0 0 1 1 4 1

(16)

98 12 12,6 1 2 130 30 18 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 2 1 99 11 11,5 1 2 133 27 15 2 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 0 0 0 0 4 1 100 11 11,4 2 2 137 32 17 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 1 101 12 12,5 1 2 138 28 15 2 0 0 0 0 0 0 0 0 0 0 0 0 2 0 2 0 0 0 0 2 1 102 11 11,5 2 2 135 34 18 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 2 1 103 10 10,5 2 2 132 29 16 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 1 0 0 1 3 1 104 12 2,5 1 2 134 28 16 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 2 1 105 10 10,3 1 2 130 31 18 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 0 0 0 0 2 1 106 10 10,5 1 2 137 29 15 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 0 0 0 0 3 1 107 7 7,8 2 1 121 21 15 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 1 0 0 1 3 1 108 6 6,4 2 1 108 16 13 2 0 0 0 0 0 0 0 0 0 0 0 1 0 1 2 0 0 0 0 2 1 109 6 6,5 2 1 107 16 14 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 2 0 0 2 3 1 110 6 6,2 2 1 125 21 13 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 1 0 0 1 3 1 111 6 6,7 2 1 101 16 16 2 0 0 0 0 0 0 0 0 0 0 0 0 0 2 2 0 0 0 0 2 1 112 10 10,7 2 2 131 26 15 2 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 0 1 1 113 8 8,7 2 1 122 30 20 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 1 0 0 1 3 1 114 10 10,6 1 2 127 26 16 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 1 1 115 10 10,7 1 2 136 31 17 2 0 0 0 0 0 0 0 0 0 0 0 2 1 0 3 1 0 0 1 4 1 116 11 11,5 1 2 137 34 18 2 0 0 0 0 0 0 0 0 0 0 0 1 1 0 2 0 0 0 0 2 1 117 9 9,8 1 2 146 45 21 3 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 2 1 118 12 12,3 2 2 166 47 17 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 1 0 0 1 3 1 119 10 10,5 1 2 134 30 17 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1 0 0 1 2 1 120 8 8,7 2 1 121 22 15 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 2 0 0 2 4 1 121 9 9,4 1 2 127 25 16 2 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 1 0 0 1 5 2 122 10 10,6 1 2 135 36 20 2 0 0 0 0 0 0 0 0 0 0 0 5 0 0 5 1 0 0 1 6 2 123 9 9,5 1 2 117 20 14 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 4 0 0 4 7 2 124 9 9,8 1 2 121 23 16 2 0 0 0 0 0 0 0 0 0 0 0 2 0 1 3 2 0 0 2 5 2

(17)

132 8 8,5 1 1 122 20 13 2 0 0 0 0 0 0 0 0 0 0 0 5 0 0 5 1 0 0 1 6 2 133 8 8,7 1 1 130 28 17 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 2 0 0 2 5 2 134 7 7,4 1 1 119 20 14 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 3 2 0 5 7 2 135 7 7,5 1 1 108 16 13 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 4 3 0 7 8 2 136 7 7,6 1 1 115 15 11 1 0 0 0 0 0 0 0 0 0 0 0 2 0 1 3 2 0 0 2 5 2 137 7 7,4 1 1 116 18 14 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 3 1 0 4 6 2 138 7 7,5 1 1 110 16 14 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 2 1 0 3 5 2 139 7 7,6 1 1 117 20 14 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 4 1 0 5 6 2 140 7 7,8 1 1 111 16 13 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 2 0 0 2 5 2 141 8 8,5 1 1 130 31 18 2 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 2 0 0 2 6 2 142 8 8,7 1 1 128 26 16 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 1 0 1 2 5 2 143 8 8,6 1 1 129 24 14 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 4 0 0 4 6 2 144 8 8,0 1 1 135 20 11 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 2 0 0 2 5 2 145 7 7,6 1 1 130 26 15 2 0 0 0 0 0 0 0 0 0 0 0 1 1 0 2 3 0 0 3 5 2 146 11 11,5 2 2 127 21 13 2 0 0 0 0 0 0 0 0 0 0 0 5 0 0 5 0 0 0 0 5 2 147 11 11,4 2 2 138 27 14 2 0 0 0 0 0 0 0 0 0 0 0 4 1 0 5 2 0 0 2 7 2 148 12 12,5 1 2 119 29 20 2 0 0 0 0 0 0 0 0 0 0 0 3 2 0 5 2 0 0 2 7 2 149 8 8,7 2 1 114 22 17 2 0 0 0 0 0 0 0 0 0 0 0 3 0 1 4 4 0 0 4 8 2 150 8 8,5 2 1 114 17 13 2 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 2 0 0 2 6 2 151 8 8,4 2 1 122 21 14 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 2 0 0 2 5 2 152 10 10,7 2 2 143 52 25 3 0 0 0 0 0 0 0 0 0 0 0 5 0 0 5 1 0 1 2 7 2 153 9 9,8 2 2 127 24 15 2 0 0 0 0 0 0 0 0 0 0 0 4 0 2 6 2 0 0 2 8 2 154 7 7,6 2 1 119 21 14 2 0 0 0 0 0 0 0 0 0 0 0 2 0 1 3 3 0 0 3 6 2 155 9 9,8 2 2 121 22 24 3 0 0 0 0 0 0 0 0 0 0 0 3 0 1 4 2 0 0 2 6 2 156 9 9,2 2 2 127 24 15 2 0 0 0 0 0 0 0 0 0 0 0 3 2 0 5 1 0 0 1 6 2 157 11 11,5 1 2 137 33 17 2 0 0 0 0 0 0 0 0 0 0 0 5 0 0 5 0 0 0 0 5 2 158 7 7,6 2 1 121 20 13 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 4 0 0 4 6 2 159 8 8,4 2 1 122 24 16 2 0 0 0 0 0 0 0 0 0 0 0 3 0 1 4 4 0 0 4 8 2 160 8 8,6 2 1 123 21 14 2 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 5 0 0 5 9 2 161 7 7,6 2 1 109 17 14 2 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 2 0 0 2 6 2 162 9 9,7 2 2 136 40 22 2 0 0 0 0 0 0 0 0 0 0 0 5 0 0 5 0 0 0 0 5 2

(18)

163 10 10,0 1 2 132 23 13 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 5 0 0 5 6 2 164 8 8,2 2 1 127 19 12 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 6 6 2 165 6 6,5 2 1 105 14 13 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 11 0 0 11 11 2 166 12 12,4 1 2 133 23 13 1 0 0 0 0 0 0 0 0 0 0 0 2 2 0 4 2 0 0 2 6 2 167 11 11,5 1 2 136 32 17 2 0 0 0 0 0 0 0 0 0 0 0 1 2 0 3 2 0 0 2 5 2 168 11 11,4 2 2 152 43 19 2 0 0 0 0 0 0 0 0 0 0 0 1 1 0 2 3 0 1 4 6 2 169 11 11,6 2 2 130 31 18 2 0 0 0 0 0 0 0 0 0 0 0 2 2 0 4 1 0 1 2 6 2 170 11 11,7 2 2 136 31 17 2 0 0 0 0 0 0 0 0 0 0 0 2 1 0 3 1 0 1 2 5 2 171 7 7,2 2 1 122 31 21 3 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 3 1 0 4 6 2 172 8 8,7 2 1 114 23 18 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 3 0 0 3 5 2 173 7 7,6 2 1 110 19 16 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 1 0 5 5 2 174 6 6,4 1 1 105 18 16 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 5 0 0 5 7 2 175 7 7,5 2 1 106 17 15 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 6 6 2 176 6 6,5 2 1 120 18 15 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 6 0 0 6 8 2 177 10 10,5 1 2 121 22 15 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 6 6 2 178 10 10,6 1 2 130 30 18 2 0 0 0 0 0 0 0 0 0 0 0 6 0 0 6 0 0 0 0 6 2 179 10 10,7 1 2 131 20 12 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 1 0 0 1 5 2 180 12 12,5 2 2 152 46 20 2 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 3 0 0 3 7 2 181 7 7,5 2 1 115 18 14 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 16 0 0 16 18 2 182 8 8,5 2 1 127 24 15 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 4 0 0 4 5 2 183 8 8,6 2 1 127 25 15 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 7 7 2 184 8 8,7 2 1 124 22 14 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 7 0 0 7 10 2 185 9 9,7 2 2 118 18 13 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 3 0 1 4 6 2 186 10 10,4 2 2 136 33 18 2 0 0 0 0 0 0 0 0 0 0 0 5 0 0 5 0 0 0 0 5 2 187 10 10,5 2 2 131 31 18 2 0 0 0 0 0 0 0 0 0 0 0 6 0 1 7 1 0 0 1 8 2 188 10 10,5 1 2 133 26 15 2 0 0 0 0 0 0 0 0 0 0 0 5 0 0 5 0 0 0 0 5 2 189 9 9,7 1 1 119 37 26 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 7 0 0 7 7 2

(19)

196 12 12,5 1 2 130 31 18 2 0 0 0 0 0 0 0 0 0 0 0 6 0 0 6 1 0 0 1 7 2 197 6 6,5 1 1 120 20 14 2 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 3 0 0 3 7 2 198 7 7,6 1 1 129 42 25 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 12 0 0 12 12 2 199 9 9,3 1 2 128 26 16 2 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 4 0 0 4 5 2 200 11 11,6 1 2 142 44 22 2 0 0 0 0 0 0 0 0 0 0 0 5 0 0 5 0 0 0 0 5 2 201 10 10,8 1 2 149 43 19 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 2 0 0 2 5 2 202 11 11,2 2 2 121 22 15 2 0 0 0 0 0 0 0 0 0 0 0 5 0 0 5 0 0 0 0 5 2 203 11 11,3 2 2 135 26 14 2 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 2 0 0 2 6 2 204 8 8,5 2 1 120 22 15 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 2 0 0 2 5 2 205 8 8,5 1 1 122 22 15 2 0 0 0 0 0 0 0 0 0 0 0 6 0 0 6 4 0 0 4 10 2 206 8 8,4 2 1 118 17 12 1 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 4 0 0 4 5 2 207 7 7,0 1 1 122 30 20 3 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 9 0 0 9 10 2 208 12 12,4 1 2 130 26 15 2 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 1 0 0 1 5 2 209 11 11,3 1 2 130 26 15 2 0 0 0 0 0 0 0 0 0 0 0 6 0 0 6 0 0 0 0 6 2 210 6 6,5 2 1 100 17 17 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 5 5 2 211 7 7,6 2 1 107 16 14 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 0 0 9 9 2 212 10 10,6 2 2 132 27 15 2 0 0 0 0 0 0 0 0 0 0 0 5 0 0 5 0 0 0 0 5 2 213 10 10,5 1 2 132 35 20 2 0 0 0 0 0 0 0 0 0 0 0 8 0 0 8 0 0 0 0 8 2 214 10 10,7 2 2 135 27 15 2 0 0 0 0 0 0 0 0 0 0 0 8 0 0 8 0 0 0 0 8 2 215 7 7,4 1 1 125 19 12 2 0 0 0 0 0 0 0 0 0 0 0 6 0 0 6 6 0 0 6 12 2 216 6 6,5 1 1 112 17 13 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 13 13 2 217 8 8,4 2 1 130 29 17 2 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 4 1 0 5 9 2 218 12 12,3 2 2 166 47 17 2 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 0 1 0 1 5 2 219 11 11,3 2 2 152 46 20 2 0 0 0 0 0 0 0 0 0 0 0 6 2 0 8 0 0 0 0 8 2 220 10 10,9 2 2 130 23 13 2 0 0 0 0 0 0 0 0 0 0 0 5 0 0 5 0 0 0 0 5 2 221 6 6,5 2 1 111 18 15 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 13 0 0 13 13 2

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222 6 6,7 2 1 109 18 15 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 9 1 0 10 10 2 223 12 12,4 2 2 144 37 18 2 0 0 0 0 0 0 0 0 0 0 0 5 0 0 5 3 0 0 3 8 2 224 7 7,5 2 1 111 18 15 2 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 2 1 1 4 5 2 225 7 7,6 1 1 114 18 14 2 0 0 0 0 0 0 0 0 0 0 0 2 1 0 3 2 2 0 4 7 2 226 7 7,7 1 1 117 21 16 2 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 1 0 0 1 5 2 227 8 8,8 2 1 113 19 15 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 3 0 0 3 6 2 228 8 8,6 1 1 120 25 17 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 5 0 0 5 5 2 229 8 8,5 1 1 129 27 16 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 3 0 0 3 5 2 230 11 11,2 2 2 130 38 23 2 0 0 0 0 0 0 0 0 0 0 0 1 1 1 3 2 0 0 2 5 2 231 11 11,4 1 2 137 33 17 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 1 2 0 3 5 2 232 7 7,6 1 1 117 20 14 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 4 0 0 4 6 2 233 7 7,7 1 1 111 16 13 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 2 0 0 2 5 2 234 8 8,7 1 1 130 31 18 2 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 2 1 2 5 7 2 235 8 7,6 1 1 128 26 16 2 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 4 0 0 4 7 2 236 7 7,1 2 1 121 16 11 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 7 0 0 7 10 2 237 8 8,10 2 1 124 19 12 1 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 4 0 0 4 8 2 238 7 7,6 2 1 123 17 11 1 0 0 0 0 0 0 0 0 0 0 0 3 0 0 3 5 1 0 6 9 2 239 7 7,8 2 1 121 16 11 1 0 0 0 0 0 0 0 0 0 0 0 2 0 0 2 4 1 0 5 7 2 240 8 8,8 2 1 125 22 14 2 0 0 0 0 0 0 0 0 0 0 0 4 0 0 4 4 1 0 5 9 2 241 7 7,3 2 1 110 16 13 2 0 0 0 0 0 3 0 0 1 4 4 0 0 0 0 2 2 0 4 4 3 242 7 7,2 2 1 121 16 11 1 0 0 0 0 0 4 0 0 0 4 4 1 0 0 1 4 4 0 8 9 3 243 9 9,10 1 2 146 45 21 2 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 2 1 0 3 3 3 244 7 7,1 2 1 122 15 10 1 0 0 0 0 0 3 0 0 0 3 3 0 0 0 0 3 2 0 5 5 3 245 10 10,2 1 2 134 30 17 2 0 0 0 0 0 2 0 0 0 2 2 0 0 0 0 5 2 0 7 7 3

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252 9 9,3 1 2 140 28.5 15 2 1 0 0 0 1 0 0 0 0 0 1 1 1 0 2 0 0 0 0 2 3 253 6 6,2 1 1 107 13.8 12 1 1 0 0 0 1 4 0 0 0 4 5 1 0 0 1 6 0 0 6 7 3 254 6 6,5 1 1 112 17.7 14 2 0 0 0 0 0 3 0 0 0 3 3 0 0 0 0 3 1 0 4 4 3 255 6 6,8 1 1 118 21.8 16 2 0 0 0 0 0 4 0 0 0 4 4 0 0 0 0 6 3 0 9 9 3 256 9 9,2 1 2 135 22.8 13 1 2 0 1 0 3 0 0 0 0 0 3 5 0 0 5 0 0 0 0 5 3 257 9 9,5 1 2 144 31.7 15 2 0 0 0 0 0 6 0 0 0 6 6 3 0 0 3 4 2 0 6 9 3 258 9 9,0 1 1 114 16.9 13 1 0 0 0 0 0 3 1 0 0 4 4 4 0 0 4 4 1 0 5 9 3 259 9 9,7 1 1 130 28.4 17 2 0 0 0 0 0 4 0 1 0 5 5 4 0 0 4 5 1 0 6 10 3 260 6 6,4 1 1 119 19.8 14 2 0 0 0 0 0 2 0 0 0 2 2 2 0 0 2 4 1 0 5 7 3 261 6 6,2 1 1 114 16.5 13 1 0 0 0 0 0 3 1 1 0 5 5 2 0 0 2 6 2 0 8 10 3 262 6 6,4 1 1 108 15.5 13 2 0 0 0 0 0 2 1 0 0 3 3 2 0 0 2 6 1 0 7 9 3 263 6 6,2 1 1 115 14.5 11 1 0 0 0 0 0 4 0 0 0 4 4 0 0 0 0 5 2 0 7 7 3 264 6 6,5 1 1 114 15.2 12 1 0 0 0 0 0 5 0 0 2 7 7 0 0 0 0 7 2 0 9 9 3 265 6 6,5 1 1 110 16.4 14 2 0 0 0 0 0 3 0 0 0 3 3 0 0 0 0 4 2 0 6 6 3 266 7 7,2 1 1 117 19.6 14 2 0 0 0 0 0 2 0 1 1 4 4 2 0 0 2 7 2 0 9 11 3 267 7 7,5 1 1 111 16.3 13 2 0 0 0 0 0 5 0 0 1 6 6 0 0 0 0 7 3 0 10 10 3 268 8 8,6 1 1 130 30.5 18 2 0 0 0 0 0 3 0 0 0 3 3 0 0 0 0 4 1 0 5 5 3 269 8 8,4 1 1 128 26.3 16 2 0 0 0 0 0 4 0 1 1 6 6 0 0 0 0 6 2 0 8 8 3 270 8 8,2 1 1 129 23.7 14 2 0 0 0 0 0 5 0 0 1 6 6 3 0 0 3 5 1 0 6 9 3 271 8 8,0 1 1 125 19 12 1 0 0 0 0 0 4 1 1 1 7 7 3 0 0 3 5 3 0 8 11 3 272 7 7,6 1 1 130 25.8 15 2 0 0 0 0 0 7 0 2 0 9 9 0 0 0 0 7 2 0 9 9 3 273 9 9,0 2 2 127 21.4 13 2 0 0 0 0 0 3 0 0 0 3 3 0 0 0 0 2 2 0 4 4 3 274 9 9,1 2 2 138 26.5 14 2 0 0 0 0 0 2 0 0 0 2 2 3 0 0 3 0 2 0 2 5 3 275 12 12,0 1 2 119 28.6 20 2 1 0 0 0 1 0 0 0 0 0 1 3 0 0 3 0 0 0 0 3 3 276 8 8,3 2 1 114 21.7 17 2 0 0 0 0 0 3 1 1 1 6 6 2 0 0 2 4 3 0 7 9 3 277 8 8,1 2 1 114 16.9 13 2 0 0 0 0 0 3 0 2 0 5 5 4 0 0 4 6 2 0 8 12 3 278 8 8,4 2 1 122 21.2 14 2 0 0 0 0 0 5 0 0 0 5 5 2 0 0 2 4 3 0 7 9 3

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279 9 9,2 2 2 144 30.7 14.8 2 0 0 0 0 0 1 0 0 0 1 1 2 0 0 2 3 0 0 3 5 3 280 9 9,3 2 2 145 25.7 12.2 1 0 0 0 0 0 2 0 0 0 2 2 0 0 0 0 4 0 0 4 4 3 281 12 12,1 2 2 146 34.3 16 2 1 0 0 0 1 0 0 0 0 0 1 6 0 0 6 0 0 0 0 6 3 282 9 9,5 2 2 128 24.6 14.7 2 2 0 0 0 2 0 0 0 0 0 2 2 0 0 2 0 0 0 0 2 3 283 6 6,0 2 1 109 14 11.7 1 0 0 0 0 0 4 0 0 0 4 4 0 0 0 0 2 4 0 6 6 3 284 6 6,5 2 1 106 17 15.2 2 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 5 1 0 6 6 3 285 6 6,0 2 1 123 19.2 12.6 1 0 0 0 0 0 2 0 0 0 2 2 0 0 0 0 5 2 0 7 7 3 286 6 6,2 2 1 112 18.2 14.5 2 0 0 0 0 0 4 0 0 0 4 4 0 0 0 0 7 2 0 9 9 3 287 6 6,5 2 1 114 19.4 14.9 2 0 0 0 0 0 2 0 0 0 2 2 0 0 0 0 2 1 0 3 3 3 288 6 6,4 2 1 111 14 11.3 1 0 0 0 0 0 3 0 0 0 3 3 0 0 0 0 6 3 0 9 9 3 289 7 7,2 2 1 121 21.4 14.6 2 0 0 0 0 0 3 0 0 0 3 3 0 0 0 0 4 3 0 7 7 3 290 6 6,3 2 1 108 15.6 13.3 2 0 0 0 0 0 5 0 0 0 5 5 0 0 0 0 8 2 0 10 10 3 291 6 6,5 2 1 107 15.6 13.6 2 0 0 0 0 0 4 0 0 0 4 4 0 0 0 0 4 2 0 6 6 3 292 6 6,6 2 1 125 20.5 13.1 2 2 0 0 0 2 3 0 0 0 3 5 2 0 0 2 4 3 0 7 9 3 293 6 6,7 2 1 101 16.1 15.7 2 0 0 0 0 0 4 0 0 0 4 4 0 0 0 0 3 2 0 5 5 3 294 10 10,4 2 2 131 25.7 14.9 2 0 0 0 0 0 3 0 0 1 4 4 0 0 1 1 6 1 0 7 8 3 295 8 8,11 2 1 122 29.7 19.9 3 0 0 0 0 0 3 0 0 0 3 3 2 0 0 2 5 0 0 5 7 3 296 9 9,0 1 2 145 26.2 12.4 1 0 0 0 0 0 0 1 1 0 2 2 2 0 0 2 2 2 0 4 6 3 297 10 10,10 1 2 136 31.3 16.9 2 1 0 0 0 1 1 0 0 0 1 2 2 0 0 2 0 1 0 1 3 3 298 9 10,0 1 2 145 25.1 11.9 1 0 0 0 0 0 2 0 0 0 2 2 2 0 0 2 2 2 0 4 6 3 299 10 10,0 1 2 122 18.9 12.6 1 0 0 0 0 0 4 0 0 0 4 4 0 0 0 0 3 1 0 4 4 3 300 10 10,2 2 2 130 30.5 18 2 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 2 0 0 2 2 3 301 12 12,0 1 2 127 20.1 12.4 1 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 1 1 0 2 2 3 302 10 10,2 2 2 130 27.1 16 2 0 0 0 0 0 1 0 0 1 2 2 3 0 0 3 3 1 0 4 7 3 303 9 9,3 2 2 138 20.5 10.7 1 0 0 0 0 0 1 0 0 0 1 1 1 0 0 1 0 1 0 1 2 3 304 9 9,2 2 2 145 25.6 12.1 1 1 0 0 0 1 0 0 0 0 0 1 3 0 0 3 0 0 0 0 3 3

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307 9 9,4 1 1 127 22.2 13.7 2 1 0 0 0 1 0 0 0 0 0 1 4 1 0 5 0 0 0 0 5 3 308 10 10,2 2 2 145 25.5 12.1 1 0 0 0 0 0 1 0 0 0 1 1 3 0 0 3 1 0 0 1 4 3 309 9 9,11 1 2 123 20.9 13.8 2 0 0 0 0 0 1 0 0 0 1 1 1 0 0 1 2 0 0 2 3 3 310 9 9,10 1 2 124 26.3 17.1 2 0 0 0 0 0 1 0 0 0 1 1 1 0 0 1 1 1 0 2 3 3 311 7 7,10 1 1 112 18.1 14.4 2 0 0 0 0 0 2 0 0 0 2 2 0 0 0 0 4 2 0 6 6 3 312 7 7,5 2 1 110 17 14 2 0 0 0 0 0 1 0 0 0 1 1 1 0 0 1 0 1 0 1 2 3 313 6 6,5 1 1 102 15.1 14.5 2 0 0 0 0 0 4 0 0 1 5 5 0 0 0 0 8 1 0 9 9 3 314 9 9,5 2 2 127 24.2 15 2 0 0 0 0 0 4 0 0 0 4 4 1 0 0 1 3 3 0 6 7 3 315 7 7,4 2 1 119 20.5 14.4 2 0 0 0 0 0 3 0 0 0 3 3 0 0 0 0 8 0 0 8 8 3 316 9 9,2 2 2 138 22.2 11.6 1 2 0 0 0 2 1 0 0 0 1 3 5 0 0 5 3 1 0 4 9 3 317 9 9,5 2 2 120 21.5 14.9 2 0 0 0 0 0 5 0 0 1 6 6 0 0 0 0 4 3 0 7 7 3 318 6 6,5 1 1 119 22.5 15.8 2 0 0 0 0 0 4 0 0 0 4 4 2 0 0 2 5 2 0 7 9 3 319 6 6,7 2 1 120 21.5 14.9 2 0 0 0 0 0 3 0 0 0 3 3 0 0 0 0 4 3 1 8 8 3 320 7 7,2 2 1 128 28.6 17.4 2 0 0 0 0 0 1 0 1 0 2 2 2 0 0 2 2 1 0 3 5 3 321 6 6,7 2 1 115 18.3 13.8 2 0 0 0 0 0 3 1 1 0 5 5 0 0 0 0 7 2 0 9 9 3 322 8 8,5 2 1 118 19.6 14 2 0 0 0 0 0 4 0 0 1 5 5 0 0 0 0 7 2 0 9 9 3 323 10 10,0 1 2 145 25 11.8 1 0 1 0 1 2 2 0 0 0 2 4 2 1 0 3 3 0 0 3 6 3 324 12 12,7 1 2 125 28.6 18.3 2 2 0 0 0 2 0 0 0 0 0 2 5 0 0 5 0 0 0 0 5 3 325 9 9,0 1 2 150 27 12 1 3 0 1 0 4 1 0 0 0 1 5 5 1 0 6 2 0 0 2 8 3 326 9 9,2 1 2 131 27.5 16 2 1 1 0 0 2 0 0 0 0 0 2 2 1 0 3 0 0 0 0 3 3 327 9 9,5 2 2 133 27 15.2 2 1 0 0 0 1 0 0 0 0 0 1 3 0 0 3 0 0 0 0 3 3 328 9 9,11 1 2 128 27.2 16.6 2 1 0 0 0 1 0 0 0 0 0 1 2 0 0 2 0 0 0 0 2 3 329 9 9,0 1 2 140 22 11.2 1 3 0 0 0 3 0 0 0 0 0 3 4 0 0 4 0 0 0 0 4 3 330 10 10,4 2 2 130 26.8 15.8 2 2 0 0 0 2 0 0 0 0 0 2 5 0 0 5 0 0 0 0 5 3 331 9 9,0 2 2 120 26.1 18.1 2 3 0 0 0 3 0 0 0 0 0 3 4 0 0 4 0 0 0 0 4 3 332 9 9,0 1 2 141 25 12.5 1 1 0 0 1 2 0 0 0 0 0 2 2 1 0 3 0 0 0 0 3 3 333 9 9,11 2 2 130 28.8 17 2 1 1 0 0 2 0 0 0 0 0 2 4 1 0 5 0 0 0 0 5 3

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334 12 12,2 1 2 127 24.8 15.3 2 2 0 0 0 2 0 0 0 0 0 2 5 0 0 5 0 0 0 0 5 3 335 12 12,5 1 2 130 29.8 17.6 2 1 2 0 0 3 0 0 0 0 0 3 6 2 0 8 0 0 0 0 8 3 336 11 11,5 1 2 133 26.6 15 2 1 0 0 0 1 0 0 0 0 0 1 5 0 0 5 0 0 0 0 5 3 337 11 11,4 2 2 137 31.7 16.8 2 4 0 0 0 4 0 0 0 0 0 4 5 0 0 5 0 0 0 0 5 3 338 12 12,6 1 2 138 27.8 14.5 2 2 0 0 0 2 0 0 0 0 0 2 3 0 0 3 0 0 0 0 3 3 339 11 11,5 2 2 135 33.7 18.4 2 0 0 0 0 0 2 0 0 0 2 2 0 0 0 0 0 2 1 3 3 3 340 10 10,5 2 2 132 28.5 16.3 2 0 0 0 0 0 4 0 0 0 4 4 0 0 0 0 5 1 0 6 6 3 341 12 12,5 1 2 134 27.9 15.5 2 1 0 0 0 1 0 0 0 0 0 1 3 0 0 3 0 0 0 0 3 3 342 12 12,5 1 2 130 30.5 18 2 1 0 0 0 1 0 0 0 0 0 1 5 0 1 6 0 0 0 0 6 3 343 12 12,4 1 2 137 28.8 15.3 2 0 0 0 0 0 1 0 0 0 1 1 1 0 0 1 0 1 0 1 2 3 344 12 12,0 1 2 132 22 12.6 1 1 0 0 0 1 0 0 0 0 0 1 2 0 0 2 2 0 0 1 3 3 345 12 12,6 1 2 139 27.8 14.3 2 0 0 0 1 1 0 0 0 0 0 1 4 0 0 4 0 0 0 0 4 3 346 7 7,3 2 1 115 21.1 15.9 2 0 0 0 0 0 0 1 1 0 2 2 0 0 0 0 1 2 0 3 3 3 347 8 8,6 2 1 114 19.4 14.9 2 0 0 0 0 0 3 0 0 1 4 4 1 0 0 1 3 1 0 4 5 3 348 7 7,5 2 1 111 17.6 14.2 2 0 0 0 0 0 3 0 0 0 3 3 2 0 0 2 2 1 0 3 5 3 349 7 7,2 1 1 113 18 14 2 0 0 0 0 0 4 0 0 0 4 4 0 0 0 0 5 1 0 6 6 3 350 6 6,5 1 1 109 18.8 15.8 2 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 5 1 1 7 7 3 351 7 7,6 1 1 115 20.7 15.6 2 0 0 0 0 0 3 0 0 0 3 3 2 0 0 2 8 2 0 10 12 3 352 7 7,0 1 1 115 14.9 11.2 1 0 0 0 0 0 1 0 0 0 1 1 0 0 0 0 7 1 0 8 8 3 353 7 7,4 1 1 108 19.3 16.5 2 0 0 0 0 0 2 0 0 0 2 2 1 0 0 1 8 0 0 8 9 3 354 6 6,5 1 1 110 19.3 15.9 2 0 0 0 0 0 2 0 0 0 2 2 0 0 0 0 6 1 0 7 7 3 355 7 7,11 2 1 104 15.9 14.7 2 0 0 0 0 0 3 1 0 0 4 4 0 0 0 0 7 1 0 8 8 3 356 7 7,5 1 1 116 22.3 16.5 2 0 0 0 0 0 2 0 0 0 2 2 0 0 0 0 3 2 0 5 5 3 357 8 8,5 1 1 108 18.6 15.9 2 0 0 0 0 0 2 0 0 0 2 2 2 0 0 2 5 2 0 7 9 3 358 7 7,5 1 1 112 19.5 15.9 2 0 0 0 0 0 3 0 0 0 3 3 0 0 0 0 3 2 0 5 5 3 359 9 9,6 2 2 113 15.6 12.2 1 3 0 0 0 3 2 0 0 0 2 5 4 0 0 4 1 2 0 3 7 3 360 7 7,4 1 1 114 19.1 14.6 2 0 0 0 0 0 3 2 0 0 5 5 2 0 0 2 5 2 0 7 9 3

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Lampiran 7

HASIL SPSS

Frequency Table

Usia

Frequency Percent Valid Percent Cumulative Percent

Valid 6 49 13.6 13.6 13.6 7 57 15.8 15.8 29.4 8 52 14.4 14.4 43.9 9 50 13.9 13.9 57.8 10 53 14.7 14.7 72.5 11 50 13.9 13.9 86.4 12 49 13.6 13.6 100.0 Total 360 100.0 100.0 Jenis Kelamin

Frequency Percent Valid Percent Cumulative Percent

Valid laki-laki 193 53.6 53.6 53.6 perempuan 167 46.4 46.4 100.0 Total 360 100.0 100.0

Means

Kategori PUFA Total d-t Total e-t Total f-t Total deft Total D-T Total M-T Total F-t Total DMFT Total DMFT+deft DMFT+deft=1-4 Mean .68 .00 .06 .7333 1.29 .11 .07 1.46 2.1917 N 120 120 120 120 120 120 120 120 120 Std. Deviation 1.062 .000 .269 1.05904 1.103 .406 .282 1.084 1.02322 DMFT+deft>4 Mean 3.26 .23 .08 3.5583 2.85 .16 .10 3.11 6.6667 N 120 120 120 120 120 120 120 120 120 Std. Deviation 2.955 .557 .295 2.99522 1.939 .485 .328 1.995 2.08771 PUFA+pufa>=1 Mean 3.22 1.24 .02 4.4833 1.65 .09 .02 1.76 6.2417 N 120 120 120 120 120 120 120 120 120

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Total Mean 2.39 .49 .05 2.9250 1.93 .12 .06 2.11 5.0333 N 360 360 360 360 360 360 360 360 360 Std. Deviation 2.639 .880 .248 3.05245 1.755 .415 .262 1.830 2.86541

Means

Kategori PUFA Total p Total u Total f Total a Total pufa Total P Total U Total F Total A Total PUFA Total PUFA+pufa DMFT+deft=1-4 Mean .00 .00 .00 .00 .00 .00 .00 .00 .00 .00 .00 N 120 120 120 120 120 120 120 120 120 120 120 Std. Deviation .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 DMFT+deft>4 Mean .00 .00 .00 .00 .00 .00 .00 .00 .00 .00 .00 N 120 120 120 120 120 120 120 120 120 120 120 Std. Deviation .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 PUFA+pufa>=1 Mean 2.25 .10 .13 .14 2.62 .43 .04 .02 .02 .51 3.13 N 120 120 120 120 120 120 120 120 120 120 120 Std. Deviation 1.835 .328 .379 .373 2.147 .837 .239 .129 .157 .953 1.868 Total Mean .75 .03 .04 .05 .87 .14 .01 .01 .01 .17 1.04 N 360 360 360 360 360 360 360 360 360 360 360 Std. Deviation 1.498 .195 .226 .225 1.747 .522 .139 .074 .091 .599 1.826

Explore

Case Processing Summary

Cases

Valid Missing Total

N Percent N Percent N Percent

Kategori IMT 360 100.0% 0 .0% 360 100.0%

Descriptives

Statistic Std. Error

Kategori IMT Mean 1.89 .022

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Std. Deviation .416 Minimum 1 Maximum 3 Range 2 Interquartile Range 0 Skewness -.701 .129 Kurtosis 2.127 .256 Tests of Normality Kolmogorov-Smirnova Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

Kategori IMT .456 360 .000 .564 360 .000

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Crosstabs

Case Processing Summary

Cases

Valid Missing Total

N Percent N Percent N Percent

Kategori PUFA * Kategori IMT 360 100.0% 0 .0% 360 100.0%

Kategori PUFA * Kategori IMT Crosstabulation

Kategori IMT Total dibawah normal (IMT< 5 persentil) normal (IMT 5-85 persentil) diatas normal (IMT>85)

Kategori PUFA DMFT+deft=1-4 Count 8 106 6 120

Expected Count 17.3 98.0 4.7 120.0 DMFT+deft>4 Count 13 100 7 120 Expected Count 17.3 98.0 4.7 120.0 PUFA+pufa>=1 Count 31 88 1 120 Expected Count 17.3 98.0 4.7 120.0 Total Count 52 294 14 360 Expected Count 52.0 294.0 14.0 360.0

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Chi-Square Tests Value df Asymp. Sig. (2-sided) Exact Sig. (2-sided) Exact Sig.

(1-sided) Point Probability

Pearson Chi-Square 23.027a 4 .000 .000

Likelihood Ratio 23.538 4 .000 .000

Fisher's Exact Test 22.405 .000

Linear-by-Linear Association 18.918b 1 .000 .000 .000 .000

N of Valid Cases 360

a. 3 cells (33.3%) have expected count less than 5. The minimum expected count is 4.67.

b. The standardized statistic is -4.350.

Nonparametric Correlations

Correlations

Total PUFA+pufa IMT

Spearman's rho Total PUFA+pufa Correlation Coefficient 1.000 -.279**

Sig. (2-tailed) . .000

N 360 360

IMT Correlation Coefficient -.279** 1.000

Sig. (2-tailed) .000 .

N 360 360

**. Correlation is significant at the 0.01 level (2-tailed).

Nonparametric Correlations

Correlations

IMT Total DMFT+deft

Spearman's rho IMT Correlation Coefficient 1.000 -.225**

Sig. (2-tailed) . .000

N 240 240

Total DMFT+deft Correlation Coefficient -.225** 1.000

Sig. (2-tailed) .000 .

N 240 240

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Mann-Whitney Test

Ranks

Kelompok

Usia N Mean Rank Sum of Ranks

Total PUFA 6-8 tahun 62 46.65 2892.50

9-12 58 75.30 4367.50

Total 120

Total pufa 6-8 tahun 62 79.10 4904.00

9-12 58 40.62 2356.00

Total 120

Total PUFA+pufa 6-8 tahun 62 73.31 4545.00

9-12 58 46.81 2715.00

Total 120

Test Statisticsa

Total PUFA Total pufa Total PUFA+pufa

Mann-Whitney U 939.500 645.000 1004.000

Wilcoxon W 2892.500 2356.000 2715.000

Z -5.743 -6.132 -4.243

Asymp. Sig. (2-tailed) .000 .000 .000

a. Grouping Variable: Kelompok Usia

Group Statistics

Kelompok

Usia N Mean Std. Deviation Std. Error Mean

Total PUFA 6-8 tahun 62 .06 .307 .039

9-12 58 .98 1.162 .153

Total pufa 6-8 tahun 62 3.66 1.774 .225

9-12 58 1.50 1.949 .256

Total PUFA+pufa 6-8 tahun 62 3.73 1.757 .223

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Mann-Whitney Test

Ranks

Jenis Kelamin N Mean Rank Sum of Ranks

Total PUFA laki-laki 67 63.28 4239.50

perempuan 53 56.99 3020.50

Total 120

Total pufa laki-laki 67 59.73 4002.00

perempuan 53 61.47 3258.00

Total 120

Total PUFA+pufa laki-laki 67 60.66 4064.00

perempuan 53 60.30 3196.00

Total 120

Test Statisticsa

Total PUFA Total pufa Total PUFA+pufa

Mann-Whitney U 1589.500 1724.000 1765.000

Wilcoxon W 3020.500 4002.000 3196.000

Z -1.252 -.276 -.056

Asymp. Sig. (2-tailed) .211 .783 .955

a. Grouping Variable: Jenis Kelamin

Group Statistics

Jenis Kelamin N Mean Std. Deviation Std. Error Mean

Total PUFA laki-laki 67 .57 .957 .117

perempuan 53 .43 .951 .131

Total pufa laki-laki 67 2.67 2.439 .298

perempuan 53 2.55 1.727 .237

Total PUFA+pufa laki-laki 67 3.24 2.133 .261

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