Evaluasi Kinerja Teknik Operasional Pengelolaan Persampahan Kota Tual di Kecamatan Pulau Dullah Selatan
Bibliographic record
Abstract
Abstract. South Dullah Island District, as the administrative and economic center of Tual City with 50,842 residents, generates high daily waste. However, waste management faces major issues, including lack of standard TPS, damaged communal containers, and limited transport fleets. This study evaluates operational waste management performance based on SNI 19-2454-2002 using a qualitative descriptive method across six variables. Data were collected through observation and interviews, then analyzed for conformity level. Results show an average performance of 47.5% ("Not Suitable"), with only final disposal (93.7%) nearing the standard. Strategic planning is needed for effective and sustainable island-based waste management. Abstrak. Kecamatan Pulau Dullah Selatan merupakan pusat pemerintahan dan ekonomi Kota Tual dengan jumlah penduduk 50.842 jiwa, yang menghasilkan timbulan sampah harian cukup tinggi. Namun, pengelolaan sampah menghadapi berbagai kendala seperti ketiadaan TPS standar, rusaknya wadah komunal, dan terbatasnya armada pengangkut, yang menyebabkan pencemaran lingkungan dan rendahnya efisiensi layanan. Penelitian ini bertujuan mengevaluasi kinerja teknik operasional pengelolaan sampah berdasarkan SNI 19-2454-2002 dengan metode deskriptif kualitatif dan pendekatan evaluatif pada enam variabel: pelayanan, pewadahan, pengumpulan, pengangkutan, pengolahan, dan pembuangan akhir. Data diperoleh melalui observasi dan wawancara, kemudian dianalisis secara komparatif terhadap standar untuk menentukan tingkat kesesuaian. Hasil menunjukkan bahwa kinerja operasional rata-rata hanya mencapai 47,5% dan tergolong “Tidak Sesuai”. Hanya variabel pembuangan akhir yang mendekati standar (93,7%), sementara pelayanan (6,6%) dan pengolahan (8%) sangat rendah. Diperlukan strategi pengelolaan berbasis karakteristik wilayah kepulauan agar sistem lebih efektif dan berkelanjutan.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".