Diversitas Penggunaan Lahan pada Kawasan Komersial Jalan Cihampelas dan Sekitarnya
Bibliographic record
Abstract
Abstract. Land use diversity is one of the supporting aspects in the movement of urban communities. Bandung City has several City Strategic Areas (KSK) for economic growth, one of which is the KSK jeans and fashion center Cihampelas. As a linear trade, the commercial area of Jalan Cihampelas and its surroundings is a dense and crowded area with visitors. The diversity of land use in the commercial area of Jalan Cihampelas and its surroundings allows visitors there to get different goals or activities within a small area, thus increasing the integration of movement. The approach method used in this study is a quantitative approach with data collection techniques through observation, literature studies, and satellite imagery. The observational data obtained will go through an image accuracy test to measure the level of data confidence before being analyzed. Meanwhile, the research method used is entropy index analysis which can show the heterogeneity of land use from each predetermined analysis grid. The results found that the grid with the highest entropy index in the research area is in grid 3 (three). Abstrak. Diversitas penggunaan lahan merupakan salah satu aspek pendukung dalam pergerakan masyarakat kota. Kota Bandung memiliki beberapa Kawasan Strategis Kota (KSK) pertumbuhan ekonomi, salah satunya adalah KSK sentra jeans dan fashion Cihampelas. Sebagai perdagangan linier, kawasan komersial Jalan Cihampelas dan sekitarnya menjadi area yang padat dan ramai pengunjung. Keragaman penggunaan lahan pada kawasan komersial Jalan Cihampelas dan sekitarnya memungkinkan pengunjung yang berada di sana mendapatkan tujuan atau kegiatan yeng berbeda-beda dalam satu lingkup wilayah yang kecil, sehingga dapat meningkatkan integrasi pergerakan. Metode pendekatan yang dilakukan pada penelitian ini adalah pendekatan kuantitatif dengan teknik pengumpulan data melalui observasi, studi literatur, dan citra satelit. Data hasil observasi yang didapatkan akan melalui uji akurasi citra untuk mengukur tingkat kepercayaan data sebelum dianalisis Sedangkan metode penelitian yang digunakan adalah analisis entropy index yang dapat menunjukan heterogenitas penggunaan lahan dari tiap-tiap grid analisis yang telah ditentukan. Hasilnya, ditemukan bahwa grid dengan entropy index tertinggi wilayah penelitian terdapat pada grid 3 (tiga).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".