Implementasi Design Thinking dalam Perancangan UI/UX Aplikasi Parkir Online pada Soto Ayam Lamongan CH
Bibliographic record
Abstract
Soto Ayam Lamongan CH merupakan tempat kuliner populer yang berada di wilayah Surabaya. Sehingga tempatnya tidak pernah sepi dari pembeli. Namun Soto Ayam Lamongan CH mempunyai kapasitas lahan parkir terbatas menampung kendaraan para pembeli. Tidak jarang terjadi overload terutama saat memasuki jam makan siang dan hari libur. Dalam penelitian ini dilakukan menggunakan metode design thinking bertujuan untuk perancangan UI/UX aplikasi parkir online. Serangkaian proses metode design thinking diantaranya adalah emphatize, define, ideate, prototype dan test. Sehingga awal dari penelitian ini penulis mencari permasalahan parkir dari Soto Ayam Lamongan CH, selanjutnya penentuan topik permasalahan hingga menjadi solusi merancang sebuah aplikasi parkir serta diakhir perancangan dilakukan uji coba aplikasi menggunakan system usability scale (SUS). Dari hasil SUS diketahui hasil akhir dari perancangan UI/UX Aplikasi Parkir Online menggunakan design thinking yaitu 78,18 dengan demikian pengujian hasil prototype terbilang berhasil, tetapi masih perlu adanya perbaikan pada penelitian selanjutnya yang berfokus pada pengembangan aplikasi parkir online.
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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 | 0.012 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 0.006 |
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".