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Record W3184985965 · doi:10.31004/abdidas.v2i4.357

Pelatihan Pemanfaatan Sistem Informasi Pelaporan Retribusi Sampah

2021· article· id· W3184985965 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJurnal Abdidas · 2021
Typearticle
Languageid
FieldComputer Science
TopicEdcuational Technology Systems
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsPhysics

Abstract

fetched live from OpenAlex

Sistem pelaporan retribusi sampah yang ada saat ini di Kecamatan Manggala Kota Makassar, masih menggunakan sistem pelaporan retribusi sampah secara manual, yaitu pada saat pelaporan retribusi sampah dilaporkan pada petugas penagih retribusi sampah, dan harus melakukan pelaporan langsung ke kepala seksi kebersihan dengan membawa catatan hasil laporan tagihan retribusi sampah yang ditulis secara manual. Hal ini akan mempersulit proses pelaporan terhadap penagih yang dilakukan setiap bulan, karena data tidak sesuai hasil dari tagihan yang dicatat dilapangan karena sering terjadi kehilangan data. Oleh karena itu perlu adanya sistem untuk memudahkan penagih retribusi sampah dan mengefisienkan waktu dan biaya, sehingga proses pelaporan retribusi sampah lebih efiseian dibandingkan dengan pelaporan secara manual. Metode yang digunakan dalam kegiatan ini adalah metode ceramah dan metode tutorial. Hasil dari pengabdian masyarakat ini yaitu para pegawai kebersihan & pertanaman sangat merespon dengan adanya sistem informasi pelaporan retribusi sampah yaitu mereka langsung mengimplementasikan di Kantor Kelurahan Manggala untuk pelaporan retribusi sampah.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.709
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.023
GPT teacher head0.256
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it