An Assessment of Entrepreneurship Programme towards Modern Agri-Technology Usage in Serdang, Selangor, Malaysia
Bibliographic record
Abstract
Problem Statement: Malaysia is generally driven by a service oriented industry whereby agriculture was placed at the third ranks of government economic priority. In the agriculture sector, the human capital empowerment has contributed towards agriculture productivity and production success which relates to those people involve in farming as farmers. Recent insight reviled that farmers with quality of an entrepreneur will largely to succeed in agriculture based business. Hence, a lot of agriculture based business depends on agriculture entrepreneur in Malaysia. Thus, an assessment study was done for one of entrepreneurship programme held in Serdang and its relation to entrepreneurship development in Malaysia. Methodology: The research design of this study employs qualitative research method. Data were gathered using social inquiry and in-depth interview techniques. It was used to develop a better understanding of the programme particularly in aspects of course content, their individual perception, and personal experience towards the programme. Sampling method was done via a purposive sampling. Five respondents were chosen and interviewed. Findings and discussions: The interviews of respondents indicated most of farmers or agri-entrepreneur was male, ranging age from 20 to 50 years old and majority mean of agriculture field experience is three years. They became an entrepreneur by inner intuition, learn farming from their parents, and one of them had influenced by his surrounding environments. They were highly specialized in their field, business minded, and very committed to their business venture. All respondents know how to use the technological application of fertigation planting system in growing crops. Finding also shows early acceptance of mediated change to entrepreneurs whereby improving their knowledge, attitude and skill. Thus, entrepreneurship values showed in them are; 1) must have planning and aim, 2) past farming experience, 3) believed in their self, and 4) continue and eager to improve the farming business. This study shows one can succeed in doing business venture through the will power, able to control focus on aims and later will generate profit thereafter. As to succeed in life, they only have to continue pushing the limits and sustainability of their business.Conclusions: The entire respondent shows improvement after the incubation programme and after finish the programme they become a successful entrepreneur where the evidence by their actions for at past, present experience, and in their future aims. This programme is a good programme meant to be as intermediary programme where improving the life of farmers and nurtured them becoming an experience agri-technology entrepreneur.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".