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KINERJA MANAJEMEN LALU LINTAS BARU DI KAWASAN LOSARI KOTA MAKASSAR

2020· article· en· W3023175918 on OpenAlexaff
Qadriathi Dg Bau, Ichsan Ali, Nurul Tri Ayu Reski

Bibliographic record

VenueJurnal Transportasi · 2020
Typearticle
Languageen
FieldEngineering
TopicUrban Transport Systems Analysis
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsTransport engineeringTraffic congestionBusinessEngineering

Abstract

fetched live from OpenAlex

Abstract The problem of urban traffic congestion is the main thing that always gets attention because congestion has a negative impact on the economy, the environment, and vehicle drivers. Makassar City is one of the cities experiencing traffic congestion on several existing roads, including roads in the Losari Area. Various efforts have been made by the government to reduce traffic congestion in the area, but optimum results have not been obtained. In 2019, a change in the direction of traffic movement in the Losari area was done by implementing a traffic management called the New Traffic Management. Through this new scheme, changes are made in the direction of movement of traffic on Jalan Penghibur, Jalan Haji Bau, and Jalan Lamadukelleng. This study aims to analyze the performance of the New Traffic Management towards improving traffic conditions in the Losari Area. The results of this study indicate that the application of New Traffic Management in the Losari Area has succeeded in improving traffic conditions in the area. Through this new traffic management scheme, the three road sections observed have service level A. Keywords: traffic congestion, traffic management, service level Abstrak Masalah kemacetan lalu lintas di perkotaan merupakan hal utama yang selalu mendapat perhatian karena kemacetan menimbulkan dampak negatif terhadap ekonomi, lingkungan, dan pengemudi kendaraan. Kota Makassar merupakan salah satu kota yang mengalami kemacetan lalu lintas di beberapa ruas jalan yang ada, termasuk jalan-jalan di kawasan Losari. Berbagai upaya telah dilakukan oleh pemerintah untuk mengurangi kemacetan lalu lintas di kawasan tersebut, tetapi belum diperoleh hasil yang optimum. Pada tahun 2019, dilakukan perubahan arah pergerakan lalu lintas di kawasan Losari dengan menerapkan suatu manajemen lalu lintas yang dinamakan Manajemen Lalu Lintas Baru atau New Traffic Management. Melalui skema yang baru ini dilakukan perubahan arah pergerakan lalu lintas di Jalan Penghibur, Jalan Haji Bau, dan Jalan Lamadu-kelleng. Penelitian ini bertujuan menganalisis kinerja Manajemen Lalu Lintas Baru ini terhadap perbaikan kondisi lalu lintas di kawasan Losari. Hasil studi ini menunjukkan bahwa penerapan Manajemen Lalu Lintas Baru di kawasan Losari berhasil memperbaiki kondisi lalu lintas di kawasan tersebut. Melalui skema manajemen lalu lintas yang baru ini, ketiga ruas jalan yang diamati mempunyai tingkat pelayanan A. Kata-kata kunci: kemacetan lalu lintas, manajemen lalu lintas, tingkat pelayanan

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)0.001
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 score0.020
Threshold uncertainty score0.067

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0200.003

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 head0.016
GPT teacher head0.184
Teacher spread0.168 · 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".

Quick stats

Citations4
Published2020
Admission routes1
Has abstractyes

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