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ANALISIS SPASIAL KINERJA JALAN DAN SIMPANG DI KABUPATEN KUDUS

2023· article· en· W4414917509 on OpenAlex
Nurul Fitriani, Fajar An Nashr Andika, Muhamad Wahyuseptiono, Alfath Satria Negara Syaban, Nanang Ary Wibowo

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJurnal Transportasi · 2023
Typearticle
Languageen
FieldEngineering
TopicUrban Transport Systems Analysis
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsIntersection (aeronautics)Data collectionRoad trafficData collection systemSchema crosswalk

Abstract

fetched live from OpenAlex

One of the keys to smooth traffic flow in an area is characterized by optimal road and intersection performance. Planning or evaluating roads and intersections certainly requires existing data information, so storing data digitally will make subsequent handling activities easier. As technology is easy to use, it is very helpful in storing and presenting data. Geographic Information Systems present images, check, integrate, manipulate, analyze and display data that relates to the topographic conditions of the earth. The aim of this research is to conduct a spatial analysis of road and intersection performance in the CBD of Kudus Regency using ArcGIS. The data in this research includes primary data and secondary data. Primary data includes data on traffic volume, speed, capacity, V/C ratio, degree of saturation, segment length and service level. Meanwhile, secondary data is road network data. After data analysis, road and intersection performance data were synchronized with road network data using ArcGIS. The results of this research provide an information system related to road and intersection performance, making it easier to handle roads and intersections in the CBD Area of Kudus Regency. ABSTRAK Salah satu kunci lancarnya arus lalu lintas di sebuah wilayah ditandai dengan kinerja jalan dan simpang yang optimal. Perencanaan ataupun evaluasi jalan serta simpang tentu membutuhkan informasi data eksisting, sehingga penyimpanan data secara digital akan mempermudah kegiatan penanganan selanjutnya. Seiring mudahnya penggunaan teknologi, sangat membantu dalam penyimpanan dan penyajian data. Sistem Informasi Geografis menyajikan gambar, mengecek, mengintegrasikan, memanipulasi, menganalisan dan menampilkan data yang menghubungkan kepada kondisi topografi bumi. Tujuan dari penelitian ini adalah melakukan analisis spasial kinerja jalan dan simpang di CBD Kabupaten Kudus menggunakan ArcGIS. Data pada penelitian ini meliputi data primer dan data sekunder. Data Primer antara lain data volume lalu lintas, kecepatan, kapasitas, V/C rasio, derajat kejenuhan, panjang segmen dan tingkat pelayanan. Sedangkan data sekunder yaitu data jaringan jalan. Setelah dilakukan analisis data, kemudian data kinerja jalan dan simpang disinkrongkan dengan data jaringan jalan menggunakan ArcGIS. Hasil dari penelitian ini menyajikan sistem informasi terkait kinerja jalan dan simpang, sehingga mempermudah dalam penanganan jalan dan simpang di Kawasan CBD Kabupaten Kudus.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.209
Teacher spread0.195 · 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