PENDAMPINGAN PENGINPUTAN DATA KLHS KE DALAM INTEGRASI RPJMD KABUPATEN SBB TAHUN 2025-2029
Bibliographic record
Abstract
ABSTRACT This community service program was conducted to strengthen the capacity of the Government of West Seram Regency in integrating the Strategic Environmental Assessment (SEA/KLHS) into the Regional Medium-Term Development Plan (RPJMD) for the 2025–2029 period. The activity was initiated in response to the limited quality of sectoral data and weak coordination among Regional Apparatus Organizations (OPDs), which have hindered the implementation of sustainable development principles in regional planning documents. A participatory and collaborative approach was applied by involving experts in urban and regional planning, environmental studies, social development, and Geographic Information Systems (GIS). The main stages included the collection and verification of Sustainable Development Goals (SDG) achievement data, the analysis of environmental carrying and assimilative capacities, and the validation of results through public consultation forums engaging various stakeholders. The mentoring process resulted in an increase in SDG data availability up to 75%, the preparation of regional and environmental baseline data, and the identification of six strategic sustainable development issues integrated into the Policies, Plans, and Programs (KRP) of the RPJMD. Overall, this activity significantly improved data governance and evidence-based decision-making, while also opening opportunities for developing a GIS-based digital assistance system to support sustainable and adaptive regional development planning. ABSTRAK Kegiatan pengabdian kepada masyarakat ini dilaksanakan untuk memperkuat kemampuan Pemerintah Kabupaten Seram Bagian Barat dalam mengintegrasikan Kajian Lingkungan Hidup Strategis (KLHS) ke dalam Rencana Pembangunan Jangka Menengah Daerah (RPJMD) periode 2025–2029. Kegiatan ini berangkat dari kondisi lemahnya kualitas data sektoral serta kurangnya koordinasi lintas Organisasi Perangkat Daerah (OPD), yang berdampak pada rendahnya penerapan prinsip pembangunan berkelanjutan di dokumen perencanaan daerah. Pendekatan yang digunakan bersifat partisipatif dan kolaboratif, dengan melibatkan para ahli di bidang perencanaan wilayah dan kota, lingkungan, sosial, dan sistem informasi geografis (GIS). Rangkaian kegiatan meliputi pengumpulan dan verifikasi data capaian Tujuan Pembangunan Berkelanjutan (TPB), analisis terhadap daya dukung dan daya tampung lingkungan, serta validasi hasil melalui forum konsultasi publik yang melibatkan berbagai pemangku kepentingan. Hasil pendampingan menunjukkan adanya peningkatan ketersediaan data TPB hingga mencapai 75%, tersusunnya data kondisi umum daerah dan lingkungan hidup, serta identifikasi enam isu strategis pembangunan berkelanjutan yang kemudian diintegrasikan ke dalam Kebijakan, Rencana, dan Program (KRP) RPJMD. Secara keseluruhan, kegiatan ini memberikan kontribusi nyata terhadap peningkatan kualitas tata kelola data, pengambilan keputusan berbasis bukti, serta membuka peluang pengembangan sistem pendampingan digital berbasis GIS guna memperkuat perencanaan pembangunan daerah yang berkelanjutan dan adaptif terhadap perubahan.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.062 | 0.008 |
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".