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Record W4400169946 · doi:10.47435/al-qalam.v16i1.2717

Metode Mengatasi Stress Kerja Di Lembaga Pendidikan Dalam Perspektif Islam

2024· article· en· W4400169946 on OpenAlexaff
Hafidah Dinatul Latifah, Imelda Fronica, Asmendri Asmendri, Milya Sari

Bibliographic record

VenueAl-Qalam Jurnal Kajian Islam dan Pendidikan · 2024
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Management
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsIslamPolitical sciencePhilosophyTheology

Abstract

fetched live from OpenAlex

This research aims to determine methods of dealing with stress in educational institutions from an Islamic perspective. Qualitative research methods are a type of research used, by searching for sources and drawing conclusions from these sources, such as books, journals and articles as well as from previous research. Based on research, it shows that in the world of work it is also known as work stress, which is a condition that affects a person's condition, there is a feeling of pressure on the mind, the influence of unstable emotions, disruption of thoughts and other conditions at that time. Factors that cause stress can arise from the individual, as well as the conditions surrounding/the individual's environment. A person must be able to control work stress on himself. In the Islamic view, work stress is a test from Allah SWT to test obedience and faith. The methods taught in Islam which are sourced from the Qur'an and hadith in dealing with stress are increasing faith and devotion to Allah SWT by increasing obligatory and sunnah worship, always being grateful to Allah, always being patient and sincere, maintaining good relations between each other/stay in touch and maintain physical health.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, 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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0050.004

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 head0.039
GPT teacher head0.410
Teacher spread0.371 · 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

Citations1
Published2024
Admission routes1
Has abstractyes

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