PENGARUH KEBUTUHAN AIR BERSIH TERHADAP JUMLAH PENDUDUK PULAU KARIMUN BESAR (STUDI: PDAM TIRTA KARIMUN)
Bibliographic record
Abstract
Masalah penyediaan air bersih saat ini menjadi permasalahan yang sangat serius di pulau Karimun besar. Kebutuhan air bersih tiap tahun mengalami peningkatan sedangkan ketersediaan air bersih semakin terbatas, dikarenakan semakin sempitnya daerah serapan, eksploitasi sumber air baku yang tidak memperhatikan kelestarian sumber air dan jumlah debit air waduk yang dipengaruhi oleh iklim. PDAM Tirta Karimun merupakan institusi yang bertanggung jawab dalam penyediaan air bersih. Tujuan penelitian ini adalah untuk menganalisis pengaruh kebutuhan air bersih terhadap jumlah penduduk dan kawasan penampungan air waduk sei bati sudah sesuai dengan perencanaan Tata Ruang Wilayah Kabupaten Karimun. Metode penelitian ini menggunakan metode kuantitatif yaitu dalam penelitian kuantitatif digunakan uji static dengan bantuan software SPSS. Dan hasil penelitian menunjukan adanya pengaruh yang signifikan kebutuhan air bersih terhadap jumlah penduduk di Pulau Karimun Besar. Hal ini terlihat dari uji F dan uji T, dimana hasil analisis uji statistic didapati F hitung > F table (34,309 > 3,416), untuk uji T, hasil analisis data didapati T hitung > T table (5,857 > 3,195)
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".