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Record W4376461420 · doi:10.15575/jim.v3i2.22303

PENGARUH UPAH TERHADAP TURNOVER INTENTION KARYAWAN TEXTILE INDUSTRY: STUDI KASUS PADA PT. HEGARMANAH LESTARI

2022· article· en· W4376461420 on OpenAlex
Nabiela Rizki Alifa, Versanudin Hekmatyar

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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueKomitmen Jurnal Ilmiah Manajemen · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEmployee Performance and Management
Canadian institutionsnot available
Fundersnot available
KeywordsInventory turnoverBusinessBusiness administrationQuarter (Canadian coin)Textile industryProductivityTurnoverAgricultural scienceAsset (computer security)EconomicsManagementFinanceEconomic growth

Abstract

fetched live from OpenAlex

Human capital is an important asset for the company and the presence of a high-productivity human capital plays an important role in the success of the company. Therefore, if a company has a high employee turnover rate, the company's performance can be disrupted. The Central Statistics Agency (BPS) reports that the textile industry contributed 6.56% to the non-oil and gas processing industry's Gross Domestic Product (GDP) in the second quarter of 2022. Work activity in the textile trading line has a relatively low level of turnover intention and this study is examined to validate the cause. This study aims to describe the effect of wages on employee turnover intention at PT Hegarmanah Lestari. Data was collected using a quantitative approach and presented descriptively. The results of the study show that there is a significant influence between wages on the turnover intention of PT Hegarmanah Lestari employees. In simple terms, it can be said that PT Hegarmanah Lestari has a relatively low level of turnover intention due to the implementation of wages according to established and generally accepted standards.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.267
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.036
GPT teacher head0.305
Teacher spread0.270 · 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