Identifikasi Faktor Keberhasilan dan Kendala Implementasi Program Kang Pisman
Bibliographic record
Abstract
Abstract. The problem of waste generation in Bandung City remains a critical issue, with the majority originating from households and low levels of waste sorting. In response to this crisis, the Bandung City Government launched the Kang Pisman (Reduce, Separate, and Utilize) Program in 2018. This program aims to reduce waste at its source through a zero-waste approach and a circular economy. This study aims to identify key success factors and obstacles in implementing the Kang Pisman Program in Bandung City. The research method used was a qualitative approach with content analysis, through in-depth interviews with informants from the Environment and Sanitation Agency and program implementers. The results indicate that the program's success is determined by five main factors: household waste sorting behavior, community participation, infrastructure support, leadership factors, and strategic implementation of innovation, decentralization, and cross-sector collaboration. The main obstacles identified include low community participation, lack of detailed planning, and limited waste processing facilities. Therefore, synergy between the government and the community, along with thorough planning, are key to optimizing the program going forward. Abstrak. Permasalahan timbulan sampah di Kota Bandung masih menjadi isu kritis, dengan sebagian besar berasal dari rumah tangga dan tingkat pemilahan yang masih rendah. Sebagai respons terhadap krisis tersebut, Pemerintah Kota Bandung meluncurkan Program Kang Pisman (Kurangi, Pisahkan, dan Manfaatkan) sejak tahun 2018. Program ini bertujuan mengurangi sampah dari sumbernya melalui pendekatan zero waste dan ekonomi sirkular. Penelitian ini bertujuan mengidentifikasi faktor-faktor kunci keberhasilan dan kendala dalam implementasi Program Kang Pisman di Kota Bandung. Metode penelitian yang digunakan adalah pendekatan kualitatif dengan metode analisis konten, melalui wawancara mendalam terhadap narasumber dari Dinas Lingkungan Hidup dan Kebersihan serta tokoh pelaksana program. Hasil penelitian menunjukkan bahwa keberhasilan program ditentukan oleh lima faktor utama, yaitu perilaku pemilahan sampah rumah tangga, partisipasi masyarakat, dukungan infrastruktur, faktor kepemimpinan, dan implementasi strategi berupa inovasi, desentralisasi, serta kolaborasi lintas sektor. Kendala utama yang ditemukan meliputi rendahnya partisipasi warga, kurangnya detail perencanaan, dan keterbatasan sarana pengolahan sampah. Oleh karena itu, sinergi antara pemerintah dan masyarakat, serta perencanaan yang matang, menjadi kunci untuk optimalisasi program ke depan.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".