ANALISIS PERSISTENSI INFLASI JAWA TENGAH
Bibliographic record
Abstract
Tujuan dari penelitian ini adalah Untuk mengukur dan mengetahui tingkat persistensi inflasi umum serta menghitung dan mengetahui jangka waktu yang diperlukan untuk kembali ke tingkat alamiahnya.Variabel dalam penelitian ini yaitu inflasi umum Jawa Tengah periode tahun 2008 hingga 2013. Metode penelitian yang digunakan adalah model autoregressive. Berdasarkan penelitian diperoleh hasil olah data menggunakan Eviews 6 dapat diketahui bahwa persistensi inflasi umum di Jawa Tengah tergolong tinggi yaitu 0.85. Serta waktu yang dibutuhkan inflasi untuk kembali ke tingkat alamiahnya yaitu selama 6 bulan. Adapun saran dari penelitian ini antara lain diharapkan melalui Tim Pengendali Inflasi Daerah (TPID) terdapat semacam kebijakan yang bisa mengontrol inflasi agar efek shock dapat diantisipasi yaitu dengan membuat lalu lintas produksi dan distribusi khusus kelompok komoditas penyusun inflasi yang dihubungkan per Kabupaten Provinsi Jawa Tengah. Untuk mengantisipasi efek shock akibat cuaca ekstrem, dapat melakukan kerja sama dengan Badan Meteorologi dan Geofisika (BMKG) dalam hal monitoring dan peramalan cuaca sebagai bahan perumusan kebijakan tersebut. The aim of this research is to measure and determine the level of general inflation then calculate and determine the duration needed to diminish to the natural level. The variable in this research is general inflation in Central Java from 2008 to 2013. The method used is the model of autoregressive time series. Based on the results of the research using Eviews 6, the data showed that persistence of general inflation in Central Java is high, it is 0.85. As well as the time required to diminish the inflation back to natural level requires long time, they are 6 months. The suggestion from this study are expected through Inflation Control Team Regional (TPID) make some kind of policy that could control the inflation of foodstuffs in order to effect the shock can be anticipated that by making the traffic production and distribution of specialty food commodity linked per regency of Central Java province. To anticipate the effects of shock as a result of extreme weather may cooperate with the Meteorology and Geophysics Agency (BMKG) in monitoring and weather forecasting as an ingredient of the policy formulation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
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".