The Concept for the Development of Biogas as Renewable Energy in Rural Indonesia
Bibliographic record
Abstract
Indonesia policy in Presidential Regulation No. 5 of 2006 on National Energy Management 2006-2025 states that one of its tasks is the ethical and sustainable management of energy, including the maintenance of environmental functions and increasing the role of new and renewable energy to 5% by 2025. In response to this problem, an effort is needed to meet the Indonesian people's energy needs. One of the programs of the Indonesian government is the implementation of an energy-independent village program. Jimbaran Village is one of the villages that have the potential to develop into an Energy Independent Village. The majority of Jimbaran Village residents work as cattle breeders, i.e., 1,663 families. The average farmer in Jimbaran Village has 3-4 cows/family heads with a total of 5,976 dairy cows. However, of the many existing breeders, no one has processed cow waste into biogas, which is a source of renewable energy. Animal waste may also be used to develop the clove and coffee plantation sector when processed into compost. Livestock waste is only dumped into sewers or human yards, so the environment is very polluting. It is, therefore, necessary to process livestock waste into biogas or compost. The analysis technique used in calculating the plan for the production of communal biogas is the analysis of supply, demand, and energy performance. Based on the calculation of the energy performance, it can be seen that the energy performance is more than 100 percent, which means that there is an excess of energy generated by existing biogas. Excessive energy can be allocated to other energy needs, such as electricity so that people can convert their current source of electrical energy from PLN to biogas.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".