Data Provinsi, Kota/Kabupaten, Kecamatan, dan Kelurahan/Desa di Indonesia

Data ini diambil dari situs "http://mfdonline.bps.go.id/">Pemutakhiran MFD dan MBS Badan Pusat Statistik (http://mfdonline.bps.go.id/) pada 16 Oktober 2016.

Administrative Subdivisions of Indonesia (Provinces, Regencies/Cities, Districts, Villages)

The data were taken from Central Agency on Statistics (BPS) - MFD and MBS Update (http://mfdonline.bps.go.id/) on 16 October 2016.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Geographic coverage

National coverage

Analysis unit

households/individuals

Kind of data

survey

Frequency of data collection

Once a year: August

Sampling procedure

Sample size:

Abstract

The 2010 Population Census has been designed to meet various data needs, including as (1) the basis for updating population data bases up to the lowest level of administrative unit (village); (2) valuable input in monitoring the progress for achieving the Millennium Development Goals (MDGs); (3) the basis for preparing small area statistics; (4) basis for preparing population projection; (5) the basic data in developing sampling frame for various surveys conducted between 2010-2020.

During the 2010 Population Census it is estimated that the population of Indonesia would be around 232 million people who live in about 65 million households. Considering the huge number of population to be recorded the field enumeration will require more than 650.00 field workers, which consist about 450.000 enumerators, 150.000 team coordinators, and 15.000 field coordinators. Data collection is designed to be undertaken in groups, each group (team) consist of four persons, i.e. three numerators and one team coordinator. All field workers would have undertaken a three-day training before hand.

The peak of census operations will be during the months of May 2010 where field enumeration will be taking place simultaneously overall the geographical area of Indonesia. May 15 will be designated as the Census Date of the 2010 Population Census, therefore on the 15 of May 2010 the homeless and nomadic population will be canvassing.

Updating population data is a very crucial issue in the upcoming population census, in the sense that since the implementation of decentralization in 2001 the number of administrative units in the regions (province, district, sub district, and village) have been increasing tremendously, such that statistical measures could not appropriately follows the changes. Prior to decentralization the number of provinces was 27, districts 297, sub districts 4.200, and villages about 65.000. At present the number of provinces is 33, districts 497, sub districts about 7.000, and villages about 75.000.

Geographic coverage

National

Analysis unit

• Individuals;
• Households.

Kind of data

Sample survey data [ssd]

Mode of data collection

Face-to-face [f2f]

Research instrument

In the modern context there is always an increasing demand for data and information, and this is not an exception for the census as well. A census being a huge national undertaking incurring substantial amount of money, while the resources are always constrained and limited. The choice of topic to be covered in a census mainly depends upon the user needs. However, as society becomes complex the demand of population data for development plans is not only increasing but the level of such information is switching to smaller administrative levels, while census being a complex and large operation has its own limitations in meeting all the demands of data users. Another main consideration for determining census topic is to maintain comparability and continuity of the census information.

There are three kind of questionnaires will be used in the 2010 Population Census, namely C1 (42 questions) for enumerate regular household who live in the areas that are covered in the mapping, C2 (14 questions) for enumerate population who live in the areas which are not included in the mapping such as remote areas, Indonesia corps diplomatic who live abroad and L2 (number and sex) for enumerate homeless people, boat people, and tribes.

The questionnaires hopefully can accommodate the data required for the compilations of MDG Indicators, which is essential for national policy making and monitoring. The census questionnaires are presently being developed taking into considerations of the relevant United Nation recommendations as well as the suitability of the items collected to meet local conditions.

In the past population censuses, data were collected basically by face-to-face interviews, where enumerators visited all households to interview persons therein one by one. In light of the changing lifestyle of big cities people and advancement of technology, new and additional means for data collection from the households will be introduced in the 2010 Population Census. Under the new multi-modal data collection approach, e-census on the Internet and self-enumeration will be rolled out, along with the traditional “interviewer” method.

Cleaning operations

The processing of data collected in a census constitutes one of the most important and challenging activities that have to be undertaken efficiently and expeditiously in order to justify the immense resources invested in a census. This activity entailed several processes: manual editing of the questionnaires after enumeration, data capture, data cleaning and validation, and finally tabulation. Intelligence character recognition (ICR) technology will be employed for data capture.

Government’s commitment to provide provisional results within two and half months after enumeration and final results within another six months greatly influenced the strategies and actions adopted at every stage of data processing in order to adhere to the commitment.

Abstract

MICS is a rapid survey method developed by UNICEF in cooperation with other international organizations. In Indonesia, MICS was first conducted in 1995 under the name of Mother and Child Health Survey (SKIA); it aimed at providing some of the data, which was unavailable to meet the requirements of the mid-decade report (Mid-decade Goals/MDG). MICS 2000 was conducted under the name of Mother and Child Education and Health Survey (SPKIA). It aimed at providing new data/indicators, since data was unavailable from existing sources.

Geographic coverage

The sample aimed to produce national-level estimates which are disaggregated between urban and rural areas.

Analysis unit

Households, Women, Children.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample size of the 2000 SPKIA was 10,000 households, and the results were only representative at the national level. Results were disaggregated for urban and rural areas. The sample selection was identical to the sampling design applied in the the 2000 Susenas using a threestage sampling design.

Mode of data collection

Face-to-face [f2f]

Research instrument

Questionnaire includes sections: orphan status, birth registration, child health, malaria, education, HIV/AIDS, pregnancy information.

The data is available from BPS website: https://www.bps.go.id/dynamictable/2016/08/18/1219/persentase-penduduk-miskin-menurut-provinsi-2007---2018.html

Information about methodology on how to measure the poverty also available through this link: https://www.bps.go.id/subject/23/kemiskinan-dan-ketimpangan.html#subjekViewTab1

Abstract

In 2005 BPS won the trust of the government to implement the 2005 Population Socioeconomic Data Collection (PSE'05), the actual implementation is poor data collection. The data collection is to obtain information about the poor household complete with addresses and characteristics. The information is needed by the government for poverty countermeasures program and to help ease the burden of life of the poor by giving cash to the poor directly, due to rising fuel prices as much as 2 times in April 2005 (up an average of 33%) and in October 2005 (up an average of 87.5%).

PSE'05 outcome data have been used by the government in the distribution of fuel compensation fund or the so-called direct cash assistance (BLT) that would later be renewed as Cash Transfer Subsidy (SLT) Phase I in October 2005 and Phase II in January 2006 .

PSE'05 monitoring and evaluation of the implementation and monitoring of the implementation on the ground thawing SLT Phase I and II are important to be implemented. For this purpose as the funders World Bank in cooperation with BPS will conduct Poverty Program Evaluation Survey (SEPK) 2006 integrated with the implementation of the Consumer Panel Module SUSENAS 2006.

Geographic coverage

Nasional coverage, representative to village level

Analysis unit

Households receiving cash transfers

Kind of data

Sample survey data

Mode of data collection

Face-to-face [f2f]

Abstract

The IDHS is part of the worldwide Demographic and Health Surveys program, which is designed to collect data on fertility, family planning, and maternal and child health.

The main objective of 2007 IDHS was to provide detailed information on population, family planning, and health for policymakers and program managers. The 2007 IDHS was conducted in all 33 provinces in Indonesia. The survey collected information on respondents’ socioeconomic background, fertility levels, marriage and sexual activity, fertility preferences, knowledge and use of family planning methods, breastfeeding practices, childhood and adult mortality including maternal mortality, maternal and child health, and awareness and behavior regarding HIV/AIDS and other sexually-transmitted infections.

The 2007 IDHS was specifically designed to meet the following objectives: - Provide data concerning fertility, family planning, maternal and child health, maternal mortality, and awareness of AIDS/STIs to program managers, policymakers, and researchers to help them evaluate and improve existing programs; - Measure trends in fertility and contraceptive prevalence rates, analyze factors that affect such changes, such as marital status and patterns, residence, education, breastfeeding habits, and knowledge, use, and availability of contraception.; - Evaluate achievement of goals previously set by the national health programs, with special focus on maternal and child health; - Assess men’s participation and utilization of health services, as well as of their families; - Assist in creating an international database that allows cross-country comparisons that can be used by the program managers, policymakers, and researchers in the area of family planning, fertility, and health in general.

Geographic coverage

National

Analysis unit

• Household
• Children under five years
• Women age 15-49
• Men age 15-54

Kind of data

Sample survey data

Sampling procedure

Administratively, Indonesia is divided into 33 provinces. Each province is subdivided into districts (regency in areas mostly rural and municipality in urban areas). Districts are subdivided into subdistricts and each subdistrict is divided into villages. The entire village is classified as urban or rural.

The 2007 IDHS sample is designed to provide estimates with acceptable precision for the following domains: - Indonesia as a whole; - Each of 33 provinces covered in the survey, and - Urban and rural areas of Indonesia

The census blocks (CBs) are the primary sampling unit for the 2007 IDHS. The sample developed for the 2007 National Labor Force Survey (Sakernas) was used as a frame for the selection of the 2007 IDHS sample. Household listing was done in all CBs covered in the 2007 Sakernas. This eliminates the need to conduct a separate household listing for the 2007 IDHS.

A minimum of 40 CBs per province has been imposed in the 2007 IDHS design. Since the sample was designed to provide reliable indicators for each province, the number of CBs in each province was not allocated proportional to the population of the province nor proportional by urban-rural classification. Therefore, a final weighing adjustment procedure was done to obtain estimates for all domains.

The 2007 IDHS sample is selected using a stratified two-stage design consisting of 1,694 CBs. Once the number of households was allocated to each province by urban and rural areas, the number of CBs was calculated based on an average sample take of 25 selected households. All evermarried women age 15-49 and all unmarried persons age 15-24 in these households are eligible for individual interview. Eight households in each CB selected for the women sample were selected for male interview.

Note: See detailed description of sample design in APPENDIX B of the survey report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2007 IDHS used three questionnaires: the Household Questionnaire (HQ), the Ever-Married Women’s Questionnaire (EMWQ) and the Married Men’s Questionnaire (MMQ). In consultation with BKKBN and MOH, BPS made a decision to base the 2007 IDHS survey instruments largely on the questionnaires used in the 2002-03 IDHS to facilitate trend analysis. Input was solicited from other potential data users, and several modifications were made to optimize the draft 2007 IDHS instruments to collect the needs for population and health data. The draft IDHS questionnaires were also compared with the most recent version of the standard questionnaires used in the DHS program and minor modifications incorporated to facilitate international comparison.

The HQ was used to list all the usual members and visitors in the selected households. Basic information collected on each person listed includes: age, sex, education, and relationship to the head of the household. The main purpose of the HQ was to identify women and men who were eligible for the individual interview. Information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, construction materials used for the floor and outer walls of the house, and ownership of various durable goods were also recorded in the HQ. These items reflect the household’s socioeconomic status.

The EMWQ was used to collect information from all ever-married women age 15-49. These women were asked questions on the following topics:: - Background characteristics (marital status, education, media exposure, etc.) - Knowledge and use of family planning methods - Reproductive history and fertility preferences - Antenatal, delivery and postnatal care - Breastfeeding and infant feeding practices - Vaccinations and childhood illnesses - Practices related to the malaria prevention - Marriage and sexual activity - Woman’s work and husband’s background characteristics - Infant’s and children’s feeding practices - Childhood mortality - Awareness and behavior regarding AIDS and other sexually transmitted infections (STIs) - Sibling mortality, including maternal mortality.

The MMQ was administered to all currently married men age 15-54 living in every third household in the IDHS sample. The MMQ collected much of the same information included in the EMWQ, but was shorter because it did not contain questions on reproductive history, maternal and child health, nutrition and maternal mortality. Instead, men were asked about their knowledge and participation in health-care-seeking practices for their children.

Cleaning operations

All completed questionnaires for the IDHS, accompanied by their control forms, were returned to the BPS central office in Jakarta for data processing. This consisted of office editing, coding of openended questions, data entry, verification, and editing computer-identified errors. A team of 42 data entry clerks, data editors and data entry supervisors processed the data. Data entry and editing was carried using a computer package program called CSPro, which was specifically designed to process DHS-type survey data. During the preparation of the data entry programs, a BPS staff spent several weeks at ORC Macro offices in Calverton, Maryland. Data entry and editing activities, which began in September, 2007 were completed in March 2008.

Response rate

In general, the response rates for both the household and individual interviews in the 2007 IDHS are high. A total of 42,341 households were selected in the sample, of which 41,131 were occupied. Of these households, 40,701 were successfully interviewed, yielding a household response rate of 99 percent.

In the interviewed households, 34,227 women were identified for individual interview and of these completed interviews were conducted with 32,895 women, yielding a response rate of 96 percent. In a third of the households, 9,716 eligible men were identified, of which 8,758 were successfully interviewed, yielding a response rate of 90 percent. The lower response rate for men was due to the more frequent and longer absence of men from the household.

Note: See summarized response rates by place of residence in Table 1.2 of the survey report.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2007 Indonesia Demographic and Health Survey (IDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2007 IDHS is only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall.

Konsep
Penduduk versi BPS Kab Bandung

Definisi / Detail
Penduduk adalah semua orang yang berdomisili di wilayah geografis Republik Indonesia selama 6 bulan atau lebih dan atau mereka yang berdomisili kurang dari 6 bulan tetapi bertujuan untuk menetap.

Klasifikasi
Data bersifat Tahunan

Ukuran
Jumlah

Satuan
Jiwa

Kegiatan Statistik Penghasil Data
Kompilasi Produk Administrasi

Keterangan
Sumber Data BPS Kabupaten Bandung

Context

The COVID-19 dataset in Indonesia was created to find out various factors that could be taken into consideration in decision making related to the level of stringency in each province in Indonesia.

Content

Data compiled based on time series, both on a country level (Indonesia), and on a province level. If needed in certain provinces, it might also be provided at the city / regency level.

Demographic data is also available, as well as calculations between demographic data and COVID-19 pandemic data.

Acknowledgements

Thank you to those who have provided data openly so that we can compile it into a dataset here, which is as follows: covid19.go.id, kemendagri.go.id, bps.go.id, and bnpb-inacovid19.hub.arcgis.com

Acknowledgements

This dataset is a result of joining the GPS data from Indo-GeoJSON and the population data from BPS.

Dataset ini berisi data laju pertumbuhan penduduk berdasarkan kabupaten/kota di Provinsi Jawa Barat dari tahun 2017 s.d. 2023.

Dataset terkait topik Kependudukan ini dihasilkan oleh Badan Pusat Statistik yang dikeluarkan dalam periode 1 tahun sekali.

Penjelasan mengenai variabel di dalam dataset ini:

• kode_provinsi: menyatakan kode Provinsi Jawa Barat sesuai ketentuan BPS merujuk pada aturan Peraturan Badan Pusat Statistik Nomor 3 Tahun 2019 dengan tipe data numerik.
• nama_provinsi: menyatakan lingkup data berasal dari wilayah Provinsi Jawa Barat sesuai ketentuan BPS merujuk pada aturan Peraturan Badan Pusat Statistik Nomor 3 Tahun 2019 dengan tipe data teks.
• laju_pertumbuhan_penduduk: menyatakan nilai laju pertumbuhan penduduk per tahun dengan tipe data numerik.
• satuan: menyatakan satuan dari pengukuran laju pertumbuhan penduduk dalam persen dengan tipe data teks.
• tahun: menyatakan tahun produksi data dengan tipe data numerik.

This dataset contains the percentage of population living below the poverty line at province and district level, 2007-2018. The poverty line was defined as the Indonesian rupiah value of the monthly per capita expenditure required to provide a minimum level of food and non-food basic consumption. This data, derived from the National Socio-Economic Survey (SUSENAS) data published by BPS every six months (March and September). The data is available in MS. Excel (XLS) format: https://www.bps.go.id/dynamictable/2016/08/18/1219/persentase-penduduk-miskin-menurut-provinsi-2007---2018.html (province level); https://www.bps.go.id/dynamictable/2017/08/03/1261/persentase-penduduk-miskin-menurut-kabupaten-kota-2015---2017.html (district level).

Dataset ini berisi informasi mengenai jumlah petani berdasarkan subsektor dan jenis kelamin petani pada tahun Sensus Tani

Penjelasan mengenai Variabel pada Dataset ini:

1. subsektor: Subsektor
2. jenis_kelamin: Jenis Kelamin
3. jumlah_petani: Jumlah Petani dari Jenis Kelamin tersebut
4. persen_petani: Persentase Petani dari Jenis Kelamin tersebut

Geographic coverage

National coverage

Analysis unit

households/individuals

Kind of data

survey

Frequency of data collection

Twice a year: February and August

Sampling procedure

Sample size:

Dataset ini berisi data mengenai berat dan nilai impor Indonesia berdasarkan klasifikasi HS (Harmonized System) Code. Keterangan lebih lanjut mengenai HS Code ini bisa dirujuk di: http://sirusa.bps.go.id/index.php?r=istilah/view&id=256 Penjelasan mengenai Variabel pada Dataset ini: 1. tahun: Tahun 2. bulan: Bulan 3. kode_hs: Kode Harmonized System (HS) 4. deskripsi_hs: Deskripsi dari Harmonized System (HS) 5. nilai: Nilai (dalam US Dollar) 6. berat: Berat (dalam Kilogram)

Penjelasan mengenai Variabel pada Dataset ini: 1. indikator: Garis kemiskinan 2. tahun: Tahun 3. nilai: Nilai dari Indikator terkait

Abstract

Agriculture significantly contributes to Indonesia’s economy. Up to 2013, this sector is the second largest contribution behind manufacturing industry sector, even though the value of the contribution keeps declining from time to time. However, the interesting fact is that approximately a third of total labor force depends on this sector (National Labor Force Survey, August 2013). To develop agriculture sector requires detailed and accurate data on various characteristics of agricultural holdings. Therefore, to meet the requirement for the data, BPS (Statistics Indonesia) as the national statistical office has conducted not only surveys but also census on agriculture. Since independence, Indonesia has carried out national agricultural census six times. The first was the 1963 Agricultural Census that might hardly be successful in practice but served as a reference to the next censuses refinement.

Objectives of Agricultural Census 2013:

The data obtained from the census has distinct characteristics compared to the data from annual agricultural surveys. The main purposes of the 2013 Census are as follows:

a. Collecting accurate and comprehensive data that delineate agriculture condition in Indonesia.

b. Building sampling frame to be used for agricultural surveys.

c. Collecting information on agricultural population, peasants or farmers with = 0.5 hectare of farmland), crops and livestock, landowning and cultivation, etc. The result of the 2013 Census will be used as benchmarks for various agricultural surveys.

Geographic coverage

National coverage

Analysis unit

Households

Universe

The statistical unit was the agricultural holding, defined as an activity producing agricultural products with the aim of partially or completely selling or exchanging the products, except when food crops were exclusively for self-consumption. In general, two types of holdings were covered in the household sector: agricultural production households ("household agricultural holding") and other households ("non-agricultural households").

Kind of data

Census/enumeration data [cen]

Sampling procedure

(a) Complete Enumeration The 2013 Agricultural Census applied complete enumeration of agricultural households. It was meant to collect data and information on population of agricultural holdings, number of crops and livestock, and farmland area distribution. The result of the census will be used as sampling frame and benchmark for further agricultural surveys.The agricultural census activities also included the surveys that provide supporting data for the census itself. The beginning activity in the implementation stage was updating households and buildings, conducted in May 2013, in order to discover current information on agricultural households in every census block. The result will be in the form of lists that distinguish between agricultural and non-agricultural households. In operation, the census was supported by 246,412 enumerators and team coordinators.

(b) Strategy There were two methods of enumeration, door to door and snowball. Door to door was conducting visit to all households both listed and unlisted in the block census. Area coverage of this method was rural villages and urban villages with the majority of agricultural business (in district) and the areas with the majority of agricultural business (in municipality). Meanwhile, the snowball method was carried out in urban villages with the majority of agricultural business (in district) and urban areas with the majority of nonagricultural business (in municipality). Through the enumeration, it was founded there are 26,135,469 agricultural households.

Mode of data collection

Face-to-face [f2f]

Research instrument

1. The listing of households engaged in the agricultural sector was conducted using the ST2013-P form ("door-to-door" and "snowball").

2. The census questionnaire used the ST2013-L form.

3. Other specific questionnaires were used for collecting information in subsequent surveys as part of the CA 2013 programme:

(i) the Agricultural Household Income Survey, in 2013 (ST2013-SPP.S form) (ii) the Agricultural Households Sub-sector Survey, in 2014 (iii) the Survey of Forestry Households in 2014 (ST2013-SKH form)

The CA 2013 questionnaire covered all 16 core items recommended for the WCA 2010 round, namely;

0001 Identification and location of agricultural holding 0002+ Legal status of agricultural holder 0003 Sex of agricultural holder 0004 Age of agricultural holder 0005 Household size 0006 Main purpose of production of the holding 0007 Area of holding according to land use types 0008 Total area of holding 0009 Land tenure types on the holding 0010 Presence of irrigation on the holding 0011 Types of temporary crops on the holding 0012 Types of permanent crops on the holding and whether in compact plantation 0013 Number of animals on the holding for each livestock type 0014 Presence of aquaculture on the holding 0015+ Presence of forest and other wooded land on the holding 0016 Other economic production activities of the holding's enterprise

See questionnaire in external materials tab

Cleaning operations

(a) Data Processing Data processing of The 2013 Agricultural Census is a follow-up activity after the enumeration. This activity will produce the intended data in accurate and timely manner. It doing the data processing, it was supported by data capture technologies by scanner machine in all provinces and district/municipalities from June to December 2013. The stages of the data processing were as follows:

1. Pre-computer processing:
2. Document receiving
3. Document batching

4. Editing and coding

5. Computer processing:

6. Data scanning

7. Data tabulation

All data processing used a particular network system in processing center. This network system was made for the census data processing purposes only. It was separated from local and other networking, so it can prevent the large data traffic that could slow down the data processing.

Sampling error estimates

(nonsampling error). Errors made by the enumerators might be in the forms of coverage error (either under-coverage or over-coverage), and content error. Error in completing the questionnaire were mostly derived from the respondents which was called response error.

Data appraisal

PES was conducted immediately after the completion of the data collection process and independently from the census enumeration. This survey sought to determine the level of coverage accuracy, the level of content accuracy in the implementation of the CA 2013, and to facilitate the use of census data by giving deeper insights on the quality and limitations of census data

Jumlah Penduduk Menurut Jenis Kelamin Tahun 2019-2021

Dataset ini berisi data persentase pemuda yang mengalami keluhan kesehatan selama sebulan terakhir dan mengobati sendiri menurut kabupaten/kota di Provinsi Jawa Barat tahun 2023.

Dataset terkait topik kesehatan ini dihasilkan oleh Badan Pusat Statistik yang dikeluarkan dalam periode 1 tahun sekali.

Penjelasan mengenai variabel di dalam dataset ini:

• kode_provinsi: menyatakan kode Provinsi Jawa Barat sesuai ketentuan BPS merujuk pada aturan Keputusan Kepala Badan Pusat Statistik Nomor 649 tahun 2023 dengan tipe data numerik.
• nama_provinsi: menyatakan lingkup data berasal dari wilayah Provinsi Jawa Barat sesuai ketentuan BPS merujuk pada aturan Keputusan Kepala Badan Pusat Statistik Nomor 649 tahun 2023 dengan tipe data teks.
• kode_kabupaten_kota: menyatakan kode dari setiap kabupaten dan kota di Provinsi Jawa Barat sesuai ketentuan BPS merujuk pada aturan Keputusan Kepala Badan Pusat Statistik Nomor 649 tahun 2023 dengan tipe data numerik.
• nama_kabupaten_kota: menyatakan lingkup data berasal dari setiap kabupaten dan kota di Provinsi Jawa Barat sesuai penamaan BPS merujuk pada aturan Keputusan Kepala Badan Pusat Statistik Nomor 649 tahun 2023 dengan tipe data teks.
• mengobati_sendiri: menyatakan upaya pengobatan yang dilakukan tanpa menggunakan resep/saran dari tenaga kesehatan yaitu ya dan tidak dengan tipe data teks.
• persentase_pemuda: menyatakan nilai persentase pemuda dengan tipe data numerik.
• satuan: menyatakan satuan dari persentase pemuda dalam persen dengan tipe data teks.
• tahun: menyatakan tahun produksi data dengan tipe data teks.