Implikasi Perkembangan Guna Lahan Terhadap Kerusakan Jalan Soekarno-Hatta Di Kelurahan Bontang Lestari Kota Bontang
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Penelitian ini bertujuan untuk menganalisis dampak perubahan tata guna lahan dan peningkatan volume kendaraan terhadap kerusakan Jalan Soekarno-Hatta di Kelurahan Bontang Lestari, Kota Bontang, Kalimantan Timur. Metode penelitian menggunakan pendekatan deskriptif kuantitatif dengan teknik analisis data meliputi analisis kuantitatif (deskriptif statistik, indeks kerusakan jalan, dan beban lalu lintas), analisis kualitatif (kebijakan dan SWOT), serta analisis spasial berbasis citra satelit Sentinel-2 dan Sistem Informasi Geografis (GIS). Hasil penelitian menunjukkan bahwa 30% ruas jalan mengalami kerusakan berat hingga sedang, terutama disebabkan oleh peningkatan volume kendaraan berat yang melebihi kapasitas desain awal, perubahan tata guna lahan (penambahan 23,7% lahan terbangun dalam 6 tahun), dan faktor lingkungan seperti longsoran bahu jalan. Analisis SWOT mengidentifikasi kekuatan seperti potensi teknologi digital dan dukungan kebijakan, namun juga kelemahan seperti keterbatasan anggaran dan koordinasi antar instansi. Berdasarkan temuan tersebut, penelitian merekomendasikan strategi terintegrasi, termasuk pembangunan jalur alternatif untuk kendaraan berat, perbaikan sistem drainase, penegakan regulasi beban kendaraan, rehabilitasi jalan, serta pemanfaatan teknologi pemantauan real-time. Implementasi strategi ini diharapkan dapat meningkatkan kualitas infrastruktur jalan, mendukung mobilitas berkelanjutan, dan memperkuat pertumbuhan ekonomi di Bontang Lestari. This study aims to analyze the impact of land-use changes and increased vehicle volume on road degradation along Soekarno-Hatta Road in Bontang Lestari Subdistrict, Bontang City, East Kalimantan. The research employs a quantitative descriptive approach, utilizing data analysis techniques such as quantitative analysis (descriptive statistics, pavement condition index, and traffic load analysis), qualitative analysis (policy evaluation and SWOT analysis), and spatial analysis based on Sentinel-2 satellite imagery and Geographic Information Systems (GIS). The findings reveal that 30% of the road sections suffer from moderate to severe damage, primarily due to heavy vehicle traffic exceeding the road's initial design capacity, land-use changes (a 23.7% increase in built-up areas over six years), and environmental factors such as shoulder landslides. The SWOT analysis identifies strengths such as digital technology potential and policy support, alongside weaknesses like budget constraints and inter-agency coordination issues. Based on these findings, the study recommends integrated strategies, including the construction of alternative routes for heavy vehicles, drainage system improvements, stricter enforcement of vehicle load regulations, road rehabilitation, and the adoption of real-time monitoring technology. The implementation of these strategies is expected to enhance road infrastructure quality, support sustainable mobility, and strengthen economic growth in Bontang Lestari.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it