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Record W2796635758 · doi:10.35585/inspir.v7i2.2449

Sistem Kendali Penyiram Tanaman Menggunakan Propeller Berbasis Internet Of Things

2017· article· id· W2796635758 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

VenueInspiration Jurnal Teknologi Informasi dan Komunikasi · 2017
Typearticle
Languageid
FieldComputer Science
TopicIoT-based Control Systems
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsPhysicsOperating systemHorticultureComputer scienceBiology

Abstract

fetched live from OpenAlex

Penyiraman tanaman yang masih manual menjadikan tanaman tidak terawat dengan baik karena waktu aktifitas yang padat, atau jenis tanaman yang dimiliki memiliki perhatian khusus baik secara tempat yang harus sejuk dan kebutuhan air yang harus tetap terpenuhi.Jika penyiraman tanaman ini bisa dilakukan secara otomatis oleh bantuan alat maka akan sangat bermanfaat dan lebih mempermudah dalam proses perawatan tanaman. Penelitian ini bertujuan untuk merancang sebuah alat penyiram tanaman otomatis dengan menggunakan propellerdan sensor moinsture sebagai alat untuk mendeteksi kadar kelembaban tanah. Data diperoleh melalui (1) Penelitian Lapangan (2) Penelitian Pustaka (3) Wawancara. Hasil penelitian ini menunjukkan bahwa prototype penyiram tanaman menggunakan propeller berbasis internet of things dapat mempermudah dan menghemat waktu.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.797
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0030.008
Open science0.0070.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.258
Teacher spread0.228 · 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