Identifikasi Pelayanan Puskesmas Berdasarkan Network Analysis di Kabupaten Bandung
Bibliographic record
Abstract
Abstract. Health is one of the most important things for humans. A sign of poor health is that humans will have difficulty carrying out their daily activities. The government is obliged to build health facilities to support the health of its people. Puskesmas is a health facility provided by the government for community health services. The health center service standard from SNI 13-1733-2004 has a radius of 3000 meters. Bandung Regency has a population in 2022 of 3,718,660 residents with population growth of 1.3% per year. This is because Bandung Regency is the hinterland area of Bandung City. Based on this phenomenon, the problem of this research is "Have all areas in Bandung Regency been identified as being included in the community health center service area?". Researchers use quantitative methods supported by geospatial information systems (GIS). Data collection in this research was agency and literature study. The monetary data used are the coordinates of the location of the health center, road network shapefiles, and average vehicle speed. The analysis method used is network analysis with the service area method. The results of this research show that the service coverage area in Bandung Regency is still not covered throughout the region. The total area of puskesmas service coverage based on distance is 193,211,573 hectares and the total area of puskesmas service coverage based on travel time is 2,281,709,838 hectares. Abstrak. Kesehatan merupakan salah satu hal terpenting bagi manusia. Tanda apadanya kesehatan, manusia akan kesulitan dalam menjalani aktivitas kesehariannya. Pemerintah wajib membangun sarana kesehatan untuk menunjang kesehatan masyarakatnya. Puskesmas merupakan sarana kesehatan yang disediakan pemerintah untuk pelayanan kesehatan masyarakat. Standar pelayanan puskesmas dari SNI 13-1733-2004 memiliki jangkauan radius seluas 3000 meter. Kabupaten Bandung memiliki jumlah penduduk di tahun 2022 sebanyak 3.718.660 penduduk dengan jumlah pertumbuhan penduduk sebesar 1,3% pertahun. Hal ini dikarenakan Kabupaten Bandung merupakan wilayah hinterland nya Kota Bandung. Berdasarkan fenomena tersebut, maka permasalahan penelitian ini yaitu "Apakah semua wilayah di Kabupaten Bandung sudah teridentifikasi masuk kedalam area pelayanan puskesmas?". Peneliti menggunakan metode kuantitatif yang didukung dengan sistem informasi geospasial (SIG). Pengumpulan data dalam penelitian ini yaitu instansi dan studi pustaka. Data-data uang digunakan yaitu titik koordinat lokasi puskesmas, shapefile jaringan jalan, dan rata-rata kecepatan kendaraan. Metode analisis yang digunakan yaitu network analysis dengan metode service area. Hasil dari penelitian ini bahwa area cakupan pelayanan di Kabupaten Bandung masih belum tercakup ke seluruh wilayah. Total luas cakupan pelayanan puskesmas berdasarkan jarak seluas 193.211,573 hektar dan total luas cakupan wilayah pelayanan puskesmas berdasarkan waktu tempuh seluas 2.281.709,838 hektar.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".