MétaCan
Menu
Back to cohort
Record W4386744057 · doi:10.38194/jurkom.v6i2.676

Model Perencanaan Program Komunikasi Humas Badan Pengelola Transportasi Jabodetabek Kementerian Perhubungan

2023· article· id· W4386744057 on OpenAlexaff
Asep Rahman Umbara, Aminah Swarnawati

Bibliographic record

VenueJurnal Riset Komunikasi · 2023
Typearticle
Languageid
FieldSocial Sciences
TopicSMEs Development and Digital Marketing
Canadian institutionsEncana (Canada)WiLAN (Canada)
Fundersnot available
KeywordsHumanitiesPolitical scienceSociologyPhilosophy

Abstract

fetched live from OpenAlex

Perencanaan komunikasi adalah hal sangat penting bagi sebuah organisasi publik seperti BPTJ. Dalam menjalankan tugas dan perannya, Humas BPTJ dituntut dapat menyusun perencanaan komunikasi yang tepat berdasarkan tahapan-tahapan yang dijalankan untuk mencapai tujuan utama dari program komunikasi humas itu sendiri yaitu membangun opini dan perubahan perilaku. Tujuan penelitian ini untuk mengetahui dan menganalisis tahapan-tahapan perencanaan program komunikasi Humas BPTJ, mengambarkan model yang dijalankan oleh Humas BPTJ serta tantangan dan hambatan dalam menjalankan perencanaan program komunikasi. Teori yang digunakan adalah model perencanaan komunikasi Assifi dan French. Penelitian ini menggunakan pendekatan kualitatif metode deskriptif dengan teknik pengumpulan data melalui wawancara mendalam dan studi pustaka. Berdasarkan hasil penelitian dapat disimpulkan bahwa Humas BPTJ telah menjalankan tahapan perencanaan komunikasi dari mulai analisis masalah sampai dengan evaluasi. Model Assifi dan French telah dijalankan oleh Humas BPTJ serta memiliki tantangan dan hambatan baik dari internal maupun eksternal organisasi. Rekomendasinya penelitian ini, Humas BPTJ harus memiliki konsep baku sebuah perencanaan komunikasi, konsisten dalam perihal tampilan visual di media sosial seperi corporate colour dan lebih mengoptimalkan publik sebagai komunikator.

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 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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.793
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.054
GPT teacher head0.318
Teacher spread0.264 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJurnal Riset KomunikasiSame topicSMEs Development and Digital MarketingFrench-language works237,207