PARTISIPASI MASYARAKATtTERHADAP PERENCANAAN PEMBANGUNAN INFRASTRUKTUR DI DESAaMARIOo KECAMATAN KULOoKABUPATEN SIDENRENG RAPPANG
Bibliographic record
Abstract
Reski Handayani. 43182029,pPartisipasi Masyarakattterhadap Perencanaan PembangunaniInfrastruktur di Desa Mario KecamatannKulohKabupatensSidenreng Rappang,,dibimbing oleh Hariyanti Hamid dan Saifullah.ePenelitian ini bertujuan untukmmengetahui PartisipasimMasyarakat terhadap Perencanaan PembangunaniInfrastruktur di Desa MariokKecamatan Kulo KabupatensSidenreng Rappang.pPopulasi dalam penelitian iniiadalah jumlah seluruh penduduk di DesaaMario. Teknikppengambilan sampel yangddigunakan adalahh menggunakan rumus Slovin.dengan hasil 97 orang,kdiambil berdasarkanyteknik randomnsampling.tTipe penelitianniniuadalah deskriptifkkuantitatif. Teknik pengumpulanddata yang digunakan yaituoobservasi, penelitian pustaka,dan kuisioner atau angket. Teknikaanalisis datammenggunakan analisis statistik deskriptif, uji validitas, ujirreliabilitas,,dan uji regresi linear sederhana denganmmenggunakan bantuan SPSS 28,0 dan skalalLikert..xHasil penelitianmmenunjukkan bahwaarekapitulasi variabel Partisipasi masyarakat sebesar 70% berada pada kategori sering. Rekapitulasi variabel pembangunan sebesar 72%. Berdasarkan hasiloolah data SPSSmmenggunakan rumus regresi linearrsederhana,,maka antara Partisipasi Masyarakattterhadap Perencanaan PembangunaniInfrastruktur di Desa Mario Kecamatan Kulo KabupatensSidenreng Rappang dikategorikan “signifikan/berpengaruh” dengannt hitung ≥ t tabel yaitu 4.4677˃ 1.66105 maka Ha diterima, artinya signifikan dengan persentase pengaruh .x
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 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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.010 |
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".