KAJIAN TEKNOLOGI PEMANFAATAN BIOGAS POME (PALM OIL MILL EFFLUENT) KE BOILER
Bibliographic record
Abstract

 In collaboration with BPPT, PTPN V management starting in 2018 took place at the Sei Pagar Mill PTPN V in Riau Province, planning the implementation of Biogas to Boiler technology to maximize the use of Biogas. The study aims to substitute shells for steam boilers / kettle through the scheme of using biomass POME to boilers at palm oil mills. The Utilization Model is a simple representation of a complex process in reality. To produce the scheme the model was preceded by conducting technical studies and economic studies and comparative studies on several Mill s in Sumatra and Kalimantan. From some of the findings from the studies that were compiled, one of the most suitable models will be made that will be applied in the Sei Pagar Mill. Furthermore, from the model, still through the RISTEKDIKTI Flagship Insinas Program, it will be developed to produce Prototypes and Construction / modifications to the Existing Boiler that is applied to the Sei Pagar Mill . Utilization Model Scheme. Biogas POME to Boilers at Palm Oil Mill by applying Biogas to Boiler technology includes several components of equipment, such as: Blower, Piping System, Valve Train, Gas Burner (Single Burner), Forced Draft Fan, and Control Panel (PHB). Utilization Model. Biogas POME to Boilers at Palm Oil Mill can later be developed and implemented to support the application of Biogas to Boiler technology at Palm Oil Mills in Indonesia.
 Keywords: Steam Boiler / Boiler, Blower, Piping System, Valve Train, Gas Burner (Single Burner), Forced Draft Fan, and Control Panel (PHB)
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.009 |
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; both teacher heads agree on what is shown here.
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".