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Record W4396632982 · doi:10.31292/jta.v7i2.312

Instrumen Pelaporan dalam Rangka Pengendalian Alih Fungsi Lahan Pertanian Berbasis Partisipasi Masyarakat

2024· article· en· W4396632982 on OpenAlexaff
Trisnanti Widi Rineksi, Reza Nur Amrin, Sari Sekar Ayu, Dhatu Mukti Kuncoro, Dian Fitriliyani Anggorowati, Luluk Qoniah Khoirunisa, Ricco Prasetya Bhagaskara

Bibliographic record

VenueTunas Agraria · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural Development and Management
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsBusiness

Abstract

fetched live from OpenAlex

As the population grows and develops, agricultural land conversion becomes an inevitable activity. In the Special Region of Yogyakarta, Sleman Regency has the most agricultural land conversion problems. A comprehensive strategy with community involvement is needed to resolve this problem. Reporting is one way for community involvement in controlling agricultural land conversion. The aim of this study is to develop a community-supported information system and reporting instrument for monitoring agricultural land conversion. Using a participatory qualitative approach, the research method adapts the waterfall method to prepare a reporting application system. Spatial analysis was carried out to understand the characteristics of land use changes at the research location. The results of the research are a reporting application and a reporting dashboard in the form of a webGIS that provides initial information as input for the regional government in implementing monitoring, evaluating, and controlling space utilization. A web-based reporting application allows the community to report agricultural land conversions suspected of violating spatial planning. The community can also find out the direction of spatial planning in their area from the spatial planning map, which is the application's base map The reporting dashboard is a webGIS interface designed to be operated by authorized agencies and contains the results of public reporting. Access is limited and may not be released until the validation procedure is complete. Seiring bertambahnya dan berkembangnya jumlah penduduk, alih fungsi lahan pertanian merupakan suatu kegiatan yang tidak bisa dihindari. Di Daerah Istimewa Yogyakarta, Kabupaten Sleman mempunyai permasalahan konversi lahan pertanian yang paling banyak. Dibutuhkan strategi menyeluruh dengan keterlibatan masyarakat untuk menyelesaikan masalah ini. Salah satu bentuk keterlibatan masyarakat dalam mengendalikan alih fungsi lahan pertanian adalah dalam bentuk pelaporan. Tujuan studi ini adalah untuk mengembangkan sistem informasi dan instrumen pelaporan yang didukung masyarakat untuk pemantauan konversi lahan pertanian. Metode penelitian mengadaptasi metode waterfall dalam rangka penyusunan sistem aplikasi pelaporan dengan menggunakan pendekatan kualitatif partisipatif. Analisis spasial dilakukan untuk memahami karakteristik perubahan penggunaan tanah di lokasi penelitian. Hasil dari penelitian adalah aplikasi pelaporan dan dashboard pelaporan berbentuk webGIS yang memberikan informasi awal sebagai masukan bagi Pemerintah Daerah dalam pelaksanaan pemantauan serta evaluasi pemanfaatan ruang dan pengendalian pemanfaatan ruang. Masyarakat dapat melaporkan konversi lahan pertanian yang diduga melanggar tata ruang melalui aplikasi pelaporan berbasis web. Masyarakat juga dapat mengetahui arah penataan ruang di wilayahnya dari peta rencana tata ruang yang menjadi peta dasar aplikasi. Dashboard pelaporan merupakan webGIS yang dirancang untuk dapat operasikan oleh instansi yang berwenang, dan memuat hasil dari pelaporan masyarakat yang aksesnya dibatasi dan tidak boleh dirilis hingga prosedur validasi selesai.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.033
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0330.007

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.

Opus teacher head0.009
GPT teacher head0.180
Teacher spread0.171 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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