Impact Evaluation of PNPM Generasi Program 2008-2009, Second Wave
Indonesia, 2008 - 2009
Get Microdata
Reference ID
IDN_2008_PNPM_v01_M_v01_A_PUF
Producer(s)
Susan Wong, Junko Onishi, Ben Olken, Ministry of Home Affairs
Created on
Aug 30, 2012
Last modified
Sep 26, 2013
Page views
1071912
Downloads
2614967
- Data files
- A
- A_CP
- A_CP_fin
- A_DLA1TYPE
- A_DLA1TYPE_fin
- A_DLA2TYPE
- A_DLA2TYPE_fin
- A_DLA23
- A_DLA23_fin
- A_fin
- B_AM_fin
- B_fin
- B_LG_fin
- B_OV_fin
- B_PG_fin
- B_PH02_fin
- B_PHTYPE_fin
- B_YK1TYPE_fin
- B_YK04_fin
- I_CH_fin
- I_fin
- I_RH07_fin
- I_RH13_fin
- I_RH19_fin
- I_RH23_fin
- K_AMP_fin
- K_fin
- K_JP_fin
- k_old
- K_PG_fin
- K_PM_fin
- K_TK_fin
- L_DN_fin
- L_fin
- L_FKS1TYPE_fin
- L_FPD04_fin
- L_FPDTYPE_fin
- L_GE_fin
- L_PAP_fin
- L_PG_fin
- m_dk_fin
- m_fin
- P_IP22_fin
- P_KF1TYPE_fin
- P_KF2TYPE_fin
- P_KF3TYPE_fin
- P_KG02TYPE_fin
- P_KGTYPE_fin
- P_KP_fin
- P_old
- P_OV_fin
- P_PG_fin
- P_TKS04_fin
- P_TKSTYPE_fin
- R_AKTYPE_fin
- R_AR_01_fin
- R_AR_18_fin
- R_AR_26_fin
- R_AR_40_fin
- R_AR_48_fin
- R_GE_fin
- R_HR1TYPE_fin
- R_HR2TYPE_fin
- R_KS1TYPE_fin
- R_KS2TYPE_fin
- R_MA_fin
- R_PG_fin
- R_PM02_fin
- R_PM2TYPE_fin
- R_PM14_fin
- R_PPK_fin
- R_RJ1TYPE_fin
- R_RJ2TYPE_fin
- S_AS1TYPE_fin
- S_AS2TYPE_fin
- S_AW1TYPE_fin
- S_DS2TYPE_fin
- S_DS3TPE_fin
- S_DS3TYPE_fin
- S_DS4ATYPE_fin
- S_DS4TYPE_fin
- S_DS5TYPE_fin
- S_DS6ATYPE_fin
- S_DS6TYPE_fin
- S_DS7TYPE_fin
- S_DS_23_fin
- S_fin
- S_GR1TYPE_fin
- S_GR03_fin
- S_IRTYPE_fin
- S_MSTYPE_fin
- S_OLTYPE_fin
- S_PGTYPE_fin
- T_fin
- T_IM1TYPE_fin
- T_IM13_fin
- T_NATYPE_fin
- T_PG_fin
- T_US_fin
- P_fin
- R_fin
Suku terbesar pertama (lid05a)
Data file: L_fin
Overview
Valid:
2312
Invalid:
0
Type:
Discrete
Start:
72
End:
95
Width:
24
Range:
-
Format:
character
Questions and instructions
Categories
| Value | Category | Cases | |
|---|---|---|---|
| ADONARA | 1 |
0%
|
|
| AFEANPAH | 1 |
0%
|
|
| ANAKAE | 1 |
0%
|
|
| ARANG | 1 |
0%
|
|
| ATAWUWUR | 1 |
0%
|
|
| BADIN | 1 |
0%
|
|
| BAHI | 3 |
0.1%
|
|
| BAJO | 5 |
0.2%
|
|
| BALAWALA | 1 |
0%
|
|
| BALAWELING | 1 |
0%
|
|
| BALI | 1 |
0%
|
|
| BALIBO | 1 |
0%
|
|
| BALIMULA | 1 |
0%
|
|
| BANA | 1 |
0%
|
|
| BELA TELO | 1 |
0%
|
|
| BELANG | 2 |
0.1%
|
|
| BEREWU MAKING | 1 |
0%
|
|
| BESITEING | 1 |
0%
|
|
| BIBI MANEK | 1 |
0%
|
|
| BIKAR | 1 |
0%
|
|
| BIMA | 1 |
0%
|
|
| BINONGKO | 1 |
0%
|
|
| BNANI LAOT (TIMOR) | 1 |
0%
|
|
| BOLUK | 1 |
0%
|
|
| BORGO (MINAHASA-BELANDA) | 1 |
0%
|
|
| BUTON | 1 |
0%
|
|
| BUYANAYA | 1 |
0%
|
|
| COLO | 1 |
0%
|
|
| COMPANG TENDA | 1 |
0%
|
|
| CUMBI | 1 |
0%
|
|
| DA SILVA | 1 |
0%
|
|
| DANGA DOTONG | 1 |
0%
|
|
| DATON | 1 |
0%
|
|
| DAWAN | 1 |
0%
|
|
| DENGKA | 1 |
0%
|
|
| DERU | 1 |
0%
|
|
| DIAZ | 1 |
0%
|
|
| DIAZ ALFI | 1 |
0%
|
|
| DOLU OBENG | 1 |
0%
|
|
| EKOKOLO | 1 |
0%
|
|
| ELLO/ROTE | 1 |
0%
|
|
| EMBARO MESE | 1 |
0%
|
|
| EMPU TUA | 1 |
0%
|
|
| FERNANDES | 1 |
0%
|
|
| FLORES | 24 |
1%
|
|
| FOESURU | 1 |
0%
|
|
| GAPUN | 1 |
0%
|
|
| GORNTALO | 1 |
0%
|
|
| GORONG MENI | 1 |
0%
|
|
| GORONTALO | 203 |
8.8%
|
|
| GORORONTALO | 1 |
0%
|
|
| GUNUNG | 1 |
0%
|
|
| HAONTEI | 1 |
0%
|
|
| HEKASE | 1 |
0%
|
|
| HENUTEIN | 1 |
0%
|
|
| HOKON | 1 |
0%
|
|
| HUANUMBUK | 1 |
0%
|
|
| HULENG | 1 |
0%
|
|
| HUREK MAKING | 1 |
0%
|
|
| JATON | 1 |
0%
|
|
| JAWA | 534 |
23.1%
|
|
| JAWA TONDANO | 2 |
0.1%
|
|
| JAWAN | 1 |
0%
|
|
| KAIDIPANG | 1 |
0%
|
|
| KAMANDA LORANG | 1 |
0%
|
|
| KARINDING | 1 |
0%
|
|
| KASONG | 1 |
0%
|
|
| KEDANG | 1 |
0%
|
|
| KEIN | 1 |
0%
|
|
| KELEN | 1 |
0%
|
|
| KELENG | 1 |
0%
|
|
| KEMPO | 1 |
0%
|
|
| KETANG | 1 |
0%
|
|
| KINA | 3 |
0.1%
|
|
| KINA KEKER | 1 |
0%
|
|
| KIUKANAK | 1 |
0%
|
|
| KLEDEN | 1 |
0%
|
|
| KOREBIMA | 1 |
0%
|
|
| KOSAT ROME | 1 |
0%
|
|
| KOTAGEWETE | 1 |
0%
|
|
| KOTAINGO | 1 |
0%
|
|
| KOTEN | 3 |
0.1%
|
|
| KULENG | 1 |
0%
|
|
| KUPALAISOLO | 1 |
0%
|
|
| KURMAN | 1 |
0%
|
|
| LADJAR | 1 |
0%
|
|
| LALIAN | 1 |
0%
|
|
| LAMA TOKAN | 2 |
0.1%
|
|
| LAMABORAK | 1 |
0%
|
|
| LAMAHOLOT | 39 |
1.7%
|
|
| LAMAKRAJAN | 1 |
0%
|
|
| LAMALOHOT | 1 |
0%
|
|
| LAMAPAHA | 1 |
0%
|
|
| LAMATOKAN | 1 |
0%
|
|
| LAMAWITAK | 1 |
0%
|
|
| LAMBA | 1 |
0%
|
|
| LAMPAO | 1 |
0%
|
|
| LANGO BRUING | 1 |
0%
|
|
| LANGODAI | 1 |
0%
|
|
| LANGUIKU | 1 |
0%
|
|
| LAVI | 1 |
0%
|
|
| LAWANG HOLOR | 1 |
0%
|
|
| LEBA KARUKU (SUMBA) | 1 |
0%
|
|
| LEDA | 1 |
0%
|
|
| LENGUMAU | 1 |
0%
|
|
| LEO BESAR | 1 |
0%
|
|
| LEO INA AI DULU | 1 |
0%
|
|
| LEO TUTUDILA | 1 |
0%
|
|
| LEOANAN | 1 |
0%
|
|
| LEOKUNAK | 1 |
0%
|
|
| LEOLULU | 1 |
0%
|
|
| LERANG | 1 |
0%
|
|
| LETON | 1 |
0%
|
|
| LEUBATANG | 1 |
0%
|
|
| LEULALENG | 1 |
0%
|
|
| LEUWERUNG | 1 |
0%
|
|
| LEWA | 1 |
0%
|
|
| LEWOEMA | 1 |
0%
|
|
| LEWOHALA | 1 |
0%
|
|
| LEWOHAYON | 1 |
0%
|
|
| LIWU | 2 |
0.1%
|
|
| LMAHOLOT | 1 |
0%
|
|
| LOCE | 1 |
0%
|
|
| LOGE | 1 |
0%
|
|
| MAADURA | 1 |
0%
|
|
| MADURA | 104 |
4.5%
|
|
| MAKIN | 1 |
0%
|
|
| MAKING | 1 |
0%
|
|
| MALAKA | 1 |
0%
|
|
| MALARI (SUMBA) | 1 |
0%
|
|
| MANADO | 1 |
0%
|
|
| MANDATO | 1 |
0%
|
|
| MANGGARAI | 26 |
1.1%
|
|
| MANGOLA | 1 |
0%
|
|
| MARAN | 2 |
0.1%
|
|
| MARAS | 1 |
0%
|
|
| MAYELI | 1 |
0%
|
|
| MEKO ANIN | 1 |
0%
|
|
| MELARI | 1 |
0%
|
|
| MELENG | 1 |
0%
|
|
| MERA | 1 |
0%
|
|
| MINAHASA | 38 |
1.6%
|
|
| MINAHASA (TONSEA) | 1 |
0%
|
|
| MUDA | 1 |
0%
|
|
| MUKIN | 1 |
0%
|
|
| NAO | 1 |
0%
|
|
| NAREK | 1 |
0%
|
|
| NDEHES | 1 |
0%
|
|
| NDOULU | 1 |
0%
|
|
| NGENCUNG | 1 |
0%
|
|
| NGGAUPANDI | 1 |
0%
|
|
| NINU | 1 |
0%
|
|
| NITJANO | 1 |
0%
|
|
| NONDE | 1 |
0%
|
|
| NTALA | 2 |
0.1%
|
|
| OLIN | 1 |
0%
|
|
| OPEN | 1 |
0%
|
|
| PALAI MALAMBA | 1 |
0%
|
|
| PESEK | 1 |
0%
|
|
| POKA | 1 |
0%
|
|
| PONGITEN | 1 |
0%
|
|
| PONGKOR | 1 |
0%
|
|
| PUNTU | 1 |
0%
|
|
| PUPUNG | 1 |
0%
|
|
| RACANG | 1 |
0%
|
|
| RAHONG | 1 |
0%
|
|
| RAJA | 1 |
0%
|
|
| RAJONG | 1 |
0%
|
|
| RATUNG | 1 |
0%
|
|
| RENGGAS | 1 |
0%
|
|
| RESING | 1 |
0%
|
|
| RIANTOBI | 1 |
0%
|
|
| RITAWOLO | 1 |
0%
|
|
| RIWU | 1 |
0%
|
|
| RODA MUDE | 1 |
0%
|
|
| RONGAN | 1 |
0%
|
|
| RONGGA | 1 |
0%
|
|
| ROTE | 14 |
0.6%
|
|
| ROTE DENGKA | 1 |
0%
|
|
| RUIS | 1 |
0%
|
|
| RUKE | 1 |
0%
|
|
| SABU | 5 |
0.2%
|
|
| SAITEIN | 1 |
0%
|
|
| SAKERA | 1 |
0%
|
|
| SALEM | 1 |
0%
|
|
| SANGER | 1 |
0%
|
|
| SANGIHE | 1 |
0%
|
|
| SANGIR | 15 |
0.6%
|
|
| SANGIR-TALAUD | 1 |
0%
|
|
| SANGIR-TALAUT | 1 |
0%
|
|
| SANTE | 1 |
0%
|
|
| SAPE | 1 |
0%
|
|
| SESA MAKING | 1 |
0%
|
|
| SIFA | 1 |
0%
|
|
| SOGE | 1 |
0%
|
|
| SOGEN MAKING | 1 |
0%
|
|
| SOLOTEIN | 1 |
0%
|
|
| SON | 1 |
0%
|
|
| SUKU BOLENG | 1 |
0%
|
|
| SUKU CABELLEN | 1 |
0%
|
|
| SUKU DARILSO | 1 |
0%
|
|
| SUKU ENE | 2 |
0.1%
|
|
| SUKU FLORES | 2 |
0.1%
|
|
| SUKU GORONTALO | 1 |
0%
|
|
| SUKU JAWA | 1 |
0%
|
|
| SUKU KOLIN | 1 |
0%
|
|
| SUKU LADA | 1 |
0%
|
|
| SUKU LENANG | 1 |
0%
|
|
| SUKU MANGGARAI | 2 |
0.1%
|
|
| SUKU MARO | 1 |
0%
|
|
| SUKU MATOLA | 1 |
0%
|
|
| SUKU NEBENTA | 1 |
0%
|
|
| SUKU PONCUNG | 1 |
0%
|
|
| SUKU PUPUNG | 1 |
0%
|
|
| SUKU REMBONG | 1 |
0%
|
|
| SUKU ROTE | 1 |
0%
|
|
| SUKU SANAK | 1 |
0%
|
|
| SUKU SUKA | 1 |
0%
|
|
| SUKU SUMBA | 2 |
0.1%
|
|
| SUKU SUNDA | 7 |
0.3%
|
|
| SUKU TAGA | 1 |
0%
|
|
| SUKU TIMOR | 1 |
0%
|
|
| SUKU TO | 1 |
0%
|
|
| SUMBA | 92 |
4%
|
|
| SUMBA BARAT | 1 |
0%
|
|
| SUMBA TIMUR | 2 |
0.1%
|
|
| SUMBA/MARONGGA | 1 |
0%
|
|
| SUNDA | 890 |
38.5%
|
|
| SUSUK | 1 |
0%
|
|
| TAKATEIN | 2 |
0.1%
|
|
| TANA MAING | 1 |
0%
|
|
| TANAGGOE | 1 |
0%
|
|
| TAPOBALI | 2 |
0.1%
|
|
| TELUMA | 1 |
0%
|
|
| TEMALURU | 1 |
0%
|
|
| TEME | 1 |
0%
|
|
| TENGGER | 1 |
0%
|
|
| TIDAH | 1 |
0%
|
|
| TIMOR | 46 |
2%
|
|
| TOBI | 1 |
0%
|
|
| TOD0 | 1 |
0%
|
|
| TOEBKAE | 1 |
0%
|
|
| TONSEA | 1 |
0%
|
|
| TONSEA/MINAHASA | 2 |
0.1%
|
|
| TUKAN | 2 |
0.1%
|
|
| TUKAN DOTONG | 1 |
0%
|
|
| TUKE | 1 |
0%
|
|
| UISKONO | 1 |
0%
|
|
| UNARAJA | 1 |
0%
|
|
| URAN | 1 |
0%
|
|
| WAJANG | 1 |
0%
|
|
| WAKE | 1 |
0%
|
|
| WALING | 1 |
0%
|
|
| WANA | 1 |
0%
|
|
| WANGKO | 1 |
0%
|
|
| WATO | 1 |
0%
|
|
| WATO UTAN | 1 |
0%
|
|
| WEOL | 2 |
0.1%
|
|
| WERANG FLORES | 1 |
0%
|
|
| WILU | 1 |
0%
|
|
| WUDI | 1 |
0%
|
|
| WUNGBOLO | 1 |
0%
|
|
| WUTUN | 1 |
0%
|
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.