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Record W3125713283 · doi:10.17977/um071v25i22020p39-48

IMPLEMENTASI SISTEM MANAJEMEN K3 PADA PROYEK PEMBANGUNAN GKB UNIVERSITAS NEGERI MALANG

2020· article· id· W3125713283 on OpenAlexaff
Lenny Novitasari, Suparno Suparno, Boedi Rahardjo

Bibliographic record

VenueBANGUNAN · 2020
Typearticle
Languageid
FieldHealth Professions
TopicOccupational Health and Safety Management
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsHumanitiesBusiness administrationBusinessOperating systemComputer sciencePhilosophy

Abstract

fetched live from OpenAlex

Abstrak:Kesehatan dan keselamatan kerja (K3) sangat penting untuk mencegah dan mengurangi kecelakaan dan penyakit akibat kerja serta terciptanya tempat kerja yang aman, efisien dan produktif. Hasil penelitian menunjukkan: 1) Komitmen dan kebijakan dalam proyek dibuat langsung dengan berdasarkan standart perusahaan. 2) Perencanaan K3 dilakukan proyek konstruksi GKB UM dengan mengidentifikasi bahaya, melakukan penilaian risiko, dan menentukan pengendalian risiko. Kemudian perencanaan K3 diawali dengan membuat safety plan yang disusun berdasarkan penilaian awal dan juga berdasarkan undang-undang dan persyaratan K3 terkait. 3) Proyek konstruksi para pekerja dan karyawan baru akan diberikan safety induction dan cek kesehatan. APD disediakan secara lengkap sesuai potensi risiko dan setiap pekerja diwajibkan untuk menggunakan APD selama bekerja dilapangan, melaksanakan she talk dan toolbox meeting secara rutin sebagai bentuk komunikasi K3 antar pekerja. 4) Pemantauan dan evaluasi K3 dilakukan dengan kegiatan inspeksi secara berkala untuk memastikan bahwa setiap potensi bahaya yang dapat timbul dari kondisi tempat kerja, peralatan kerja, material serta tindakan pekerja teridentifikasi, dan juga berguna untuk mengambil tindakan perbaikan serta pencegahan yang diperlukan serta menyediakan peralatan darurat sesuai dengan peraturan tentang peralatan dan sistem tanda bahaya keadaan darurat yang disediakan, diperiksa, diuji dan dipelihara secara berkala. 5) Peninjauan dan peningkatan dilaksanakan dengan membuat statistik risiko kecelakaan maupun audit temuan yang terjadi di proyek serta melakukan perbaikan terhadap penyimpangan yang ditemukan.Kata-kata kunci: GKB, Implementasi, Sistem Manajemen K3Abstract: Occupational health and safety (K3) is very important to prevent and reduce occupational accidents and diseases as well as the creation of a safe, efficient and productive workplace. The results showed: 1) Commitments and policies in the project were made directly based on company standards. 2) OHS planning is carried out by the UM GKB construction project by identifying hazards, conducting risk assessments, and determining risk control. Then OHS planning begins with making a safety plan based on initial assessments and also based on laws and related OSH requirements. 3) Construction project workers and new employees will be given safety induction and health checks. PPE is provided in full according to potential risks and every worker is required to wear PPE while working in the field, carry out she talk and toolbox meetings regularly as a form of K3 communication between workers. 4) OHS monitoring and evaluation are carried out with periodic inspection activities to ensure that any potential hazards that may arise from workplace conditions, work equipment, materials and worker actions are identified, and are also useful for taking necessary corrective and preventive actions and providing emergency equipment. in accordance with the regulations regarding the equipment and system of emergency alerts provided, checked, tested and maintained periodically. 5) Reviews and improvements are carried out by making accident risk statistics and auditing the findings that occur in the project and making corrections to any deviations found.Keywords: GKB, Implementation, K3 Management System

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)0.003
metaresearch head score (Gemma)0.005
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: none
Teacher disagreement score0.038
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0060.004
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0380.023

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 head0.082
GPT teacher head0.371
Teacher spread0.290 · 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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Citations0
Published2020
Admission routes1
Has abstractyes

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