SISTEM INFORMASI MANAJEMEN ASET TETAP PADA PTMETIS TEKNOLOGI CORPORINDO
Bibliographic record
Abstract
Assets are the most important resource for an individual or an organization that has it, because the asset is a tool that supports the activities of an organization. Over time the assets in the company will go through many changes (increment and reduction) that happen very quickly and it also happened to PT Metis Teknologi Corporindo. To support operational activities, Metis still uses a semicomputerized system that is Microsoft Exce lfor the management of existing assets and inventory It is less efficient in terms of time, energy and cost. The development of technology can be utilized to overcome some of the obstacles faced today such as by creating a system that helps in the management of assets, inventory items and also lending of office inventory goods to prevent the occurrence of damage, loss or ghost items. The development of a web-based system is used with UML (Unified Modeling Language) system modeling, including use case diagrams, activity diagrams, sequence diagrams, and class diagrams. The asset management system development methodology uses prototype model, PHP programming and MYSQL database. Keywords: System, Asset, UML, Prototype Model. Aset merupakan sumber daya terpenting untuk perseorangan ataupun suatu organisasi yang memilikinya, karena aset merupakan peralatan yang menunjang kegiatan suatu organisasi. Seiring berjalannya waktu aset dalam perusahaan akan banyak mengalami perubahan (pertambahan dan pengurangan) yang berlaku sangat cepat dan itu juga terjadi pada PT Metis Teknologi Corporindo. Untuk menunjang kegiatan operasional, Metis masih menggunakan sistem semicomputerized yaitu menggunakan Microsoft Excel dalam pengelolaan aset dan barang inventaris yang ada. Hal ini kurang efisien dalam segi waktu, tenaga juga biaya. Semakin berkembangnya teknologi, dapat dimanfaatkan untuk mengatasi beberapa kendala yang dihadapi saat ini seperti dengan menciptakan suatu sistem yang membantu dalam pengelolaan aset, barang inventaris dan juga peminjaman barang inventaris kantor guna mencegah terjadinya kerusakan, kehilangan atau ghost items. Pengembangan sistem berbasis web digunakan dengan permodelan sistem yaitu UML (Unified Modeling Language), meliputi diagram use case, diagaram activity, diagram sequence, dan diagram class. Metodologi pengembangan sistem manajemen aset menggunakan prototype model, pemrograman PHP dan database MYSQL. Kata Kunci : Sistem, Aset, UML, Prototype Model.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.057 | 0.037 |
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".