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Record W6894134061 · doi:10.5281/zenodo.8008498

Talent Readiness of PT KAI to Face the Era of Change

2023· article· en· W6894134061 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2023
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHuman Resource and Talent Management
Canadian institutionsnot available
Fundersnot available
KeywordsGeneral partnershipData collectionSubsidiaryIndonesianQuarter (Canadian coin)PoolingFace (sociological concept)

Abstract

fetched live from OpenAlex

<strong>ABSTRACT: </strong>PT KAI is the only rail-based transportation company in Indonesia managed by SOEs. The main services offered by PT KAI are transportation for passengers and products, while its non-core business is real estate, and its subsidiaries include six companies offering a wide range of services. PT KAI is currently undergoing changes that can be seen with the change in partnership PT KAI is moving towards Global Partnership. This can be seen by the cooperation carried out by PT KAI with other countries in carrying out the Indonesian Fast Train project. One of PT KAI's missions is to become digital-based railway transportation. This mission is a business response to changes moving into the digital era. This research was conducted using quantitative methods. Data collection was carried out by researchers by visiting PT KAI Head Office located on Jl. Perintis Kemerdekaan No.1, Babakan Ciamis, Kec. Sumur Bandung, Bandung City, West Java, and PT KAI Training Center located in two locations, namely Jl. Kacapiring, Batununggal District, Bandung City, West Java, Indonesia, and Jl. Ir. H. Juanda No.215, Dago, Coblong District, Bandung City, West Java, Indonesian. The respondents of this study were active employees of PT KAI totaling 168 respondents. The method of data collection is carried out by du event, namely Quick Count or Pooling Priority, and also through Questionnaires. The data processed then was from 140 respondents. The data reduction was carried out because it was found that there were outliers of 28 respondents or 16.67% obtained through examination with the SPSS 26 tool with the Casewise Diagnostic method. Researchers also provide solutions to change issues so that PT KAI is better prepared to face the era of change in the future, consist of PT KAI Goes International through English Habits, and Work Abroad Opportunities for PT KAI's Top Talent, Transforming Service Quality and Security by maximizing the use of AI and Renewable Technology in all Business processes, Creating Synergies (Including SOEs) through harmonious and collaborative strategic alliances with other state-owned companies, Global Partnership as the best transportation ecosystem solution for Indonesia by opening up to the existence of a Global partnership business scheme.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.288
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.009

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 head0.088
GPT teacher head0.256
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; 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

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