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Record W4415189654 · doi:10.51878/cendekia.v5i4.7155

KAJIAN PEMANFAATAN RUANG PADA KAWASAN LINDUNG DI KOTA MANADO (STUDI KASUS: KECAMATAN MAPANGET)

2025· article· en· W4415189654 on OpenAlexaff
Kindly Anugerah Imanuel Pangauw, Claudia Talita Dariwu, Fiska Chintya Ezra Pangalila

Bibliographic record

VenueCENDEKIA Jurnal Ilmu Pengetahuan · 2025
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic Growth and Fiscal Policies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPopulationHectareLand useSpatial planningSpatial analysisGovernment (linguistics)Spatial distributionPlan (archaeology)

Abstract

fetched live from OpenAlex

Mapanget District, as a new growth center in Manado City, faces significant challenges in controlling spatial utilization, particularly within its protected areas. The dynamics of rapid economic and population growth have triggered land-use changes that are often inconsistent with the Spatial Plan (RTRW), potentially leading to environmental degradation and a decline in spatial quality. This study aims to assess the level of suitability between existing spatial utilization and the spatial pattern plan for protected areas in Mapanget District. The primary focus is to identify the extent and distribution of non-compliant locations and to analyze the contributing factors to provide a basis for government recommendations. The research employed a quantitative approach with an overlay analysis method using ArcGIS 10.8 software. Spatial data from the 2023-2042 Manado City Spatial Plan were overlaid with existing land use data from 2024, updated via satellite imagery. The analysis revealed a very high level of non-compliance: of the total 233.17 hectares of protected areas analyzed, 169.80 hectares (72.8%) were found to be inconsistent with the spatial pattern plan, while only 63.37 hectares (27.2%) were compliant. The most significant non-compliance was identified in areas designated as Green Open Space (RTH), such as District Parks and Cemeteries, which are now dominated by mixed-crop plantations (150.85 hectares) and built-up areas like settlements. In conclusion, there is an urgent need for the Manado City Government to evaluate and strengthen the enforcement of spatial planning regulations through more effective supervision, law enforcement actions, and the prioritization of land acquisition programs to secure the function of protected areas from massive land-use conversion. ABSTRAKKecamatan Mapanget, sebagai pusat pertumbuhan baru di Kota Manado, menghadapi tantangan signifikan dalam pengendalian pemanfaatan ruang, khususnya di kawasan lindung. Dinamika pertumbuhan ekonomi dan penduduk yang pesat memicu alih fungsi lahan yang seringkali tidak sejalan dengan Rencana Tata Ruang Wilayah (RTRW), sehingga berpotensi merusak lingkungan dan menurunkan kualitas ruang. Penelitian ini bertujuan untuk mengkaji tingkat kesesuaian antara pemanfaatan ruang eksisting dengan rencana pola ruang pada kawasan lindung di Kecamatan Mapanget. Fokus utama adalah untuk mengidentifikasi luasan dan sebaran lokasi yang tidak sesuai serta menganalisis faktor-faktor penyebabnya sebagai dasar rekomendasi bagi pemerintah. Metode yang digunakan adalah pendekatan kuantitatif dengan analisis tumpang susun (overlay) menggunakan software ArcGIS 10.8. Data spasial rencana pola ruang RTRW Kota Manado Tahun 2023-2042 ditumpangsusunkan dengan data penggunaan lahan eksisting tahun 2024 yang diperbaharui melalui citra satelit. Hasil analisis menunjukkan tingkat ketidaksesuaian yang sangat tinggi, di mana dari total 233,17 hektar kawasan lindung yang dianalisis, sebesar 169,80 hektar (72,8%) tidak sesuai dengan rencana pola ruang, dan hanya 63,37 hektar (27,2%) yang telah sesuai. Ketidaksesuaian terbesar ditemukan pada lahan yang direncanakan sebagai Ruang Terbuka Hijau (RTH), seperti Taman Kecamatan dan Pemakaman, yang kini didominasi oleh Kebun Campuran (150,85 hektar) serta kawasan terbangun seperti permukiman. Kesimpulannya, terdapat urgensi bagi Pemerintah Kota Manado untuk mengevaluasi dan memperkuat penegakan regulasi tata ruang melalui pengawasan yang lebih efektif, penertiban, dan prioritas pada program pengadaan tanah untuk mengamankan fungsi kawasan lindung dari alih fungsi lahan yang masif.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.025
GPT teacher head0.227
Teacher spread0.203 · 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 teacher head, not a consensus.

Study designObservational
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
Published2025
Admission routes1
Has abstractyes

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