Pemetaan Proses Bisnis dengan Pendekatan Klasifikasi Proses CIMOSA: Studi Kasus Perusahaan Pengelola Kawasan Industri
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
A business process map is said to be an effective tool to manage a firm value chain. Yet, the absence of business maps in the firms was frequently found. Some of the reasons behind this absence include an overwhelming large number of available languages with their complexity and the large amount of prcess-related data to construct the map while business practitioners have already been burdened by job routines. Offering a simple approach, this paper aims to map business processes using CIMOSA process classification framework. The mapping employed process reasoning and expert judgement from the observed company. An extensive use of the company internal data, interview, and FGD with stakeholders dominated the process mapping. Through iterative verification and validation, a complete business process map has been resulted for the case study. Relationships between process groups within CIMOSA process classification were also proposed. The result suggested CIMOSA process classification was proven to be applicable for nonmanufacturing based company, yet it is very practical for business process mapping at a certain level of detail.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it