Analisis Tingkat Bahaya Tempat Pemrosesan Akhir (TPA) Sembung Gede di Desa Sembung Gede, Kecamatan Kerambitan, Kabupaten Tabanan, Provinsi Bali
Bibliographic record
Abstract
TPA Sembung Gede telah beroperasi sejak tahun 1995. Sistem Controlled Landfill yang semula direncanakankini tergantikan dengan sistem penimbunan terbuka. Disamping itu, keterbatasan lahan dan infrastrukturmembuat TPA Sembung Gede berisiko membahayakan lingkungan seiring dengan kompleksnya permasalahanyang timbul, seperti produksi lindi, bau, hingga kebakaran. Penelitian ini ditujukan untuk menganalisis tingkatbahaya dari kegiatan operasional TPA Sembung Gede guna mengetahui arahan pengelolaan yang dibutuhkan.Penelitian dilakukan dengan metode survey dan pemetaan, wawancara, uji laboratorium, serta pembobotanberdasarkan penilaian indeks risiko lingkungan, mengacu pada Peraturan Menteri Pekerjaan Umum RepublikIndonesia Nomor 3 Tahun 2013. Terdapat 3 kategori dengan 27 parameter penilaian, diantaranya adalah kriterialokasi TPA Sampah (20 parameter), karakteristik sampah (4 parameter) dan karakteristik lindi (3 parameter).Hasil penelitian menunjukkan bahwa, TPA Sembung Gede memiliki tingkat bahaya sedang dengan nilai indeksrisiko lingkungan sebesar 510,4. Berdasarkan nilai tersebut, operasional TPA masih dapat diteruskan dandirehabilitasi menjadi lahan urug terkendali secara bertahap. Adapun 5 dari keseluruhan parameter teridentifikasimemiliki nilai indeks sensitivitas 1, sehingga perlu menjadi perhatian lebih untuk ditangani agar tingkat bahayaTPA tidak semakin bertambah.Kata Kunci: Indeks Risiko Lingkungan; Rehabilitasi TPA; Sampah; Tempat Pemrosesan Akhir; Tingkat BahayaTPA
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".