Efforts to Resolve Juvenile Delinquency in Serang (A Case study in SMKN 5, SMK PGRI I, and SMK PGRI 3, Serang)
Bibliographic record
Abstract
The purpose of the research is to discover and to analyze the cause of juvenile delinquency, school’s role in order to overcome the issue, and the efforts performed to resolve the issue in three vocational high schools in Serang. Qualitative method is used in order to comprehend the regular state of the objects through placing the researcher as the key instrument. The data collection is done through purposive and snowball technique, a technique done through triangulating, where the data analysis is inductive, and the findings are emphasized on significance rather than generalization. The findings show that the cause of juvenile delinquency in Serang involves internal and external factors. The internal factor revolves around personality, status and the students’ role in the society. Meanwhile, the external factors are family where the issues lies on the parent’s inability in disciplining their children, the lack of spiritual knowledge, especially Islamic value, and the poor control from the society which is often oblivious of student’s characteristic. The method to resolve juvenile delinquency in Serang concentrates on the curative and preventive precautions as following: reciting the Quran 15 minutes before the first subject of each day begins, conducting a routine group dhikr every Friday night, conducting a religious seminar every month which involves every party, conducting a routine brief lecture after Zuhr pray, whether it is delivered by teacher of the students, as well as da’wah training for students given by the teachers.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".