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Record W4401833341 · doi:10.33387/jpk.v3i1.8421

PENGARUH KEBIJAKAN PEMERINTAH TERHADAP HARGA PANGAN DI MALUKU UTARA

2024· article· en· W4401833341 on OpenAlexaff
Sitra Anna A Rachman, Suryati Tjokrodiningrat, Yusri Sapsuha, Nur Sjafani, Suratman Sudjud, Hamidin Rasulu

Bibliographic record

VenueJurnal Pertanian Khairun · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Security and Socioeconomic Dynamics
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsBusinessEconomicsPolitical scienceEnvironmental science

Abstract

fetched live from OpenAlex

The government implements a price control policy to protect producers and consumers while simultaneously reducing the rate of inflation by providing subsidies to companies that produce basic necessities and newly developing companies to reduce production costs so they can compete with imported products. The aim of this research is to analyze the influence of government policy on food prices in North Maluku (North Maluku Province, Ternate City and Central Halmahera Regency. Analyze the influence of government policy on food supply in North Maluku. And analyze the influence of government policy on people's purchasing power in North Maluku. The method used in this research is a descriptive method with a simple quantitative and qualitative approach. The research results which have been analyzed with Part Least Square (PLS), using the SmartPLS 4 application tool, show that Government Policy Intervention has a real or significant effect on Food Prices in the City. Ternate and Central Halmahera Regency, then (H1: accepted). So it can be explained that there is a direct influence of government policy intervention variables on food prices in Ternate City and Central Halmahera Regency. Government Policy Intervention has no real effect on Food Supply in Ternate City and Regency Central Halmahera has no real effect or (H0: rejected). And Government Policy Intervention has no real effect on People's Purchasing Power or (H0: rejected). In conclusion, government policy has a significant impact on food prices in the North Maluku region. For this reason, it needs to be optimized through subsidy policies, price regulation, distribution and logistics, agricultural support, and import management. The government also needs to make efforts to ensure the availability of sufficient food supplies at affordable prices for the community. With the right policies, local governments can help stabilize food prices and increase food security in the North Maluku region.Keywords: Government Policy, Food Prices, North Maluku

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0230.003

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 head0.013
GPT teacher head0.213
Teacher spread0.200 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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