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Record W3128478802 · doi:10.59697/jsik.v5i1.714

SISTEM PENDUKUNG KEPUTUSAN PEMBERIAN BANTUAN PROGRAM KELUARGA HARAPAN (PKH) DENGAN METODE ELECTRE (ELIMINATION ET CHOIX TRADUISTANT LA REALITE) STUDI KASUS: KECAMATAN SELESAI

2021· article· en· W3128478802 on OpenAlexaff
Khairunnisa Harahap, Akim M. H. Pardede, Tio Ria Pasaribu

Bibliographic record

VenueJurnal Sistem Informasi Kaputama (JSIK) · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicPublic Administration in Developing Nations
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsELECTREMathematicsOperations researchMultiple-criteria decision analysis

Abstract

fetched live from OpenAlex

Program Keluarga Harapan (PKH) is an intense social protection program on providing cash assistance to households that meet the criteria of the Program Keluarga Harapan (PKH). The goal of Program Keluarga Harapan (PKH) in the short term is to reduce the burden of KSM (Very Poor Families) while in the long term it is expected to break the poverty chain between generations, so that the next generation can get out of poverty and be more prosperous. Based on the results of this study proposed a decision support system with the METHOD ELECTRE (Elimination Et Choix Traduisant La Realite) which is one of the multi-criterion decision making methods based on the concept of outranking by using a paired comparison of alternatives based on each appropriate criteria. From the ELECTRE method, there is an alternative result that is less favourable, namely A1 with the result of 0, A2 with the result of 0, A3 with the result of 2, A2 with the result of 1 and A5 with the result of 4. Thus the A5 becomes the alternative with the highest value.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.031
GPT teacher head0.378
Teacher spread0.347 · 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 designSimulation or modeling
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
Published2021
Admission routes1
Has abstractyes

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