Analisis Variabel yang Berpengaruh terhadap Konsolidasi Lahan di Permukiman Kumuh Kawasan Perkotaan Kelurahan Ciumbuleuit, Kota Bandung
Bibliographic record
Abstract
Abstract. The fulfillment of land needs is one step towards achieving social welfare for all Indonesian people, which is part of the government's responsibility. The difference between communities with adequate housing and those living in slums highlights a social gap that should not exist in a country aiming for prosperous citizens. Efforts to improve housing and settlement environments, including slums, have been many but are less effective in eradicating slum housing. To address this issue, the MICMAC Analysis method and descriptive analysis method are used to identify variables that play a role in consolidating slum land in urban areas. The study found two highly influential variables: Community Willingness to Accept Land Consolidation Programs (KMKL) and Funding Sources (SPBY), and two variables with low influence and dependency: Administration and Documentation in Land Consolidation Implementation (ADPKL) and Benefits of Land Consolidation Implementation (KMPKL). A key variable for the next 20 years is the Social & Economic Conditions of the Community (KSEM). The planned land consolidation in Ciumbuleuit focuses on infrastructure improvement and procurement, and further slum housing arrangements must consider land area, community willingness, budget, and other variables. This study is expected to provide insights for planning and implementing land consolidation and could offer new ideas to improve the success of land consolidation planning for slum settlements in urban areas. Abstrak. Pemenuhan kebutuhan akan lahan menjadi salah satu langkah untuk mencapai kesejahteraan sosial bagi seluruh rakyat Indonesia yang merupakan bagian dari tanggung jawab pemerintah. Perbedaan antara masyarakat yang kebutuhan perumahannya terpenuhi dan masyarakat yang tinggal di daerah kumuh menjelaskan adanya kesenjangan sosial yang seharusnya tidak boleh terjadi sebagai sebuah negara yang bertujuan untuk menjadi rakyat yang sejahtera. Upaya yang dilakukan dalam perbaikan lingkungan perumahan dan pemukiman yang termasuk kumuh sudah banyak dilakukan, namun kurang efektif dalam pemberantasan perumahan kumuh. Untuk memecahkan masalah tersebut maka digunakan metode Analisis MICMAC dan metode analisis deskriptif untuk mengetahui variabel yang berperan dalam konsolidasi lahan perumahan kumuh di kawasan perkotaan. Hasil dari penelitian ini adalah terdapat 2 variabel yang paling berpengaruh, diantaranya Kesediaan Masyarakat Menerima Program Konsolidasi Lahan (KMKL) dan Sumber Pembiayaan (SPBY), dan 2 variabel yang memiliki pengaruh dan ketergantungan yang rendah, yaitu Administrasi dan Dokumentasi Dalam Pelaksanaan Konsolidasi Lahan (ADPKL) dan Keuntungan/Manfaat Pelaksanaan Konsolidasi Lahan (KMPKL), variabel yang berpengaruh untuk 20 tahun kedepan, yaitu Kondisi Sosial & Ekonomi Masyarakat (KSEM). Konsolidasi lahan yang direncanakan di Kelurahan Ciumbuleuit difokuskan untuk pembenahan dan pengadaan infrastruktur, begitu pula untuk penataan perumahan kumuh lebih lanjut harus mempertimbangkan luas lahan, kesediaan masyarakat, anggaran dan variabel lainnya. Diharapkan kajian ini dapat menjadi bahan refleksi perencanaan dan pelaksanaan konsolidasi lahan dan dapat menjadi pokok pemikiran baru untuk meningkatkan keberhasilan perencanaan konsolidasi lahan untuk penangan permukiman kumuh di kawasan perkotaan.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| 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".