Penerapan Enterprise Resource Planning Berbasis Odoo pada Modul CRM (Studi Kasus UMKM Credeva)
Bibliographic record
Abstract
UMKM Credeva is one of the UMKM website design and programming services located in the Duduk Sampeyan area, Gresik City. Enterprise Resource Planning (ERP) software is a system that integrates all business processes, from inventory, accounting and finance, resource management, and so on. By using ERP software, companies get several benefits, including: increased efficiency & productivity, planning & information management, process standardization, and of course better business integration & data accuracy. The accuracy of this data is very important to see the amount of data that is in the business processes of a company, especially medium and large companies. The Odoo UMKM Credeva implementation project was carried out because it saw problems in its business processes. The problem is in Relationship Management between customers because it is still not optimal when there are many overloads on incoming orders because they are still using manual recording. Then the problem that often occurs is the negligence of not recording the order deadline to the customer. As well as other problems, lack of understanding of the use of customer management where employees are still minimal. This results in a gap between reports and delays in accessing information to customer requests. So that Odoo is very much needed in carrying out business processes going forward. In this plan, will provide a module on CRM (customer relationship management)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".