PERAN STRATEGI PEMASARAN DAN KUALITAS PRODUK TERHADAP KEBERHASILAN USAHA TANI PAPAYA CALIFORNIA (Carica Papaya L.) (Suatu Kasus Terhadap Petani Papaya California di Kecamatan Cibeber, Cianjur, Jawa Barat)
Bibliographic record
Abstract
Tujuan dari penelitian ini adalah untuk mengetahui dan membuktikan peran strategi pemasaran dan kualitas produk dalam keberhasilan usahatani pepaya California. Teknik penentuan responden dilakukan dengan menggunakan teknik sensus dan diperoleh 75 orang. Teknik analisis yang digunakan adalah analisis jalur. Hasil penelitian menunjukkan bahwa Kinerja Usaha Tani Pepaya California dicirikan oleh: rata-rata penggunaan lahan seluas 0,54 ha. Harga jual yang diterima petani tergantung kualitas A. Rp. 3.500/kg dan kualitas B. Rp. 3.000/kg. Dari aspek usaha tani diperoleh efisiensi usaha tani R/C = 2,17. Kinerja Strategi Pemasaran terkait kegiatan budidaya di tingkat petani meliputi: kemitraan; bekerja sama dengan influencer; melibatkan karyawan; dan merawat pelanggan memperoleh tingkat pencapaian 80,21% kriteria Baik. Kinerja Kualitas Produk meliputi aspek; estetika produk; manfaat produk; daya tahan; dan Kesesuaian harga diperoleh pencapaian 79,23% kriteria Baik. Kebun pepaya California menunjukkan keberhasilan yang terdiri dari: Harga Jual; Produktifitas; dan tingkat pencapaian efisiensi usahatani diperoleh 66,78%, terdapat koefisien sebesar 0,875. kriteria yang baik dan semakin baik pula strategi pemasarannya. Lebih baik kualitas produk dan sebaliknya. Strategi pemasaran dan kualitas produk terhadap keberhasilan budidaya pepaya california berpengaruh positif. Pengaruh kedua variabel secara total masing-masing 45,04%, dan 30,88%. Semakin tinggi/baik strategi pemasaran, semakin tinggi pula keberhasilan usaha tani. Kata Kunci: Pemasaran, Kualitas, Kesuksesan
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".