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Record W4386547729 · doi:10.29313/bcsurp.v3i2.9573

Penentuan Lokasi Tempat Pemakaman Umum (TPU) di SWK Ujung Berung Kota Bandung

2023· article· en· W4386547729 on OpenAlexaff
Adam Pramudya Jourdan, Verry Damayanti

Bibliographic record

VenueBandung Conference Series Urban & Regional Planning · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicCoastal Management and Development
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsAnalytic hierarchy processGeographyPopulationHectareData collectionSocioeconomicsEnvironmental planningArchaeologyOperations researchSociologyEngineeringDemographySocial scienceAgriculture

Abstract

fetched live from OpenAlex

Abstract. Planning is something that is needed in determining an activity for the future so that it can run well. One of them is planning regarding land for burial. The city as a place for various activities of the citizens of the city. A city will have a large burden in meeting the needs of its citizens. Population growth due to births and migration will lead to an increase in the need for land as a means of breeding and carrying out daily activities. On the other hand, population withdrawal in an area caused by death will require land designated for burial areas. Therefore the purpose of this study was to identify the optimal location for a Public Cemetery which is useful for serving the needs of the community for burial grounds in the Ujung Berung area, City of Bandung. The approach method used in this research is descriptive quantitative and the analytical method used in this research is ownership analysis, land use analysis, process hierarchy analysis (AHP), and spatial analysis. For data collection methods using secondary and primary data. The results of the analysis that has been carried out are 3 optimal locations based on the area, namely location 1 with an area of 31.7 Ha, location 2 with an area of 14.4 Ha and location 3 with an area of 8.2 Ha. With a land requirement of 5 hectares for the next 20 years, location 2 is the optimal and effective location for a public cemetery in the Ujung Berung area that can serve the needs of local community facilities. Abstrak. Perencanaan merupakan suatu hal yang sangat dibutuhkan didalam menentukan suatu kegiatan untuk kedepannya agar dapat berjalan dengan baik. Salah satu nya adalah perencanan mengenai lahan untuk pemakaman. Kota sebagai tempat berbagai aktifitas warga kotanya. Suatu kota akan memiliki beban yang besar dalam memenuhi kebutuhan warganya. Pertambahan penduduk akibat dari adanya kelahiran serta migrasi akan menyebabkan peningkatan kebutuhan lahan sebagai sarana untuk berkembang biak dan melakukan aktivitas sehari-hari. Disisi lain pengurangan penduduk pada suatu wilayah yang diakibatkan oleh faktor kematian akan membutuhkan lahan yang diperuntukan untuk area pemakaman. Maka dari itu tujuan dari penelitian ini adalah untuk mengidentifikasi lokasi yang optimal untuk Tempat Pemakaman Umum (TPU) yang berguna untuk melayani kebutuhan masyarakat akan lahan pemakaman di wilayah SWK Ujung Berung Kota Bandung. Metode pendekatan yang digunakan dalam penelitian ini adalah kuantitatif deskriptif dan metode analisis yang digunakan dalam penelitian ini adalah analisis kependudukan, analisis penggunaan lahan, analisis hirarki proses (AHP), dan analisis spasial. Untuk metode pengumpulan data menggunakan data sekunder dan primer. Hasil dari analisis yang telah dilakukan terdapat 3 lokasi yang optimal berdasarkan luasan wilayah nya, yaitu lokasi 1 dengan luas 31,7 Ha, lokasi 2 dengan luas 14,4 Ha dan lokasi 3 dengan luas 8,2 Ha. Dengan kebutuhan lahan untuk 20 tahun yang akan datang sebesar 5 Ha maka lokasi 2 merupakan lokasi yang optimal dan efektif untuk sebuah lahan pemakaman umum di wilayah SWK Ujung Berung yang dapat melayani kebutuhan sarana masyarakat setempat.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score0.213

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0640.006

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.

Opus teacher head0.040
GPT teacher head0.246
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations1
Published2023
Admission routes1
Has abstractyes

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