Evaluasi Implementasi Modul Inventory Management Oracle di PT. X dengan Metode Fit/Gap Analysis
Why this work is in the frame
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Bibliographic record
Abstract
Penelitian ini bertujuan untuk mengevaluasi hasil implementasi modul Inventory Management di PT. X dan menganalisis gap antara As-Is Process perusahaan yang terdapat dalam modul Inventory Management dengan kebutuhan bisnis perusahaan untuk mencari solusi alternatifnya. Modul Inventory Management yang menjadi objek dalam penelitian ini merupakan bagian dari software sistem ERP yaitu Oracle. Analisis Fit/Gap dilakukan untuk menentukan bagian proses mana saja dalam sistem yang tidak sesuai dengan kebutuhan bisnis perusahaan untuk selanjutnya diberikan solusi alternatif sebagai bagian dari penyelesaian masalah. Hasil penelitian menunjukkan bahwa dari 7 (tujuh) kebutuhan bisnis perusahaan, terdapat 1 kebutuhan bisnis yang mampu dipenuhi oleh sistem (kategori: Fit ) dan terdapat 6 kebutuhan bisnis perusahaan yang belum mampu dipenuhi secara keseluruhan oleh sistem (kategori: Partial Fit ). Sebesar 86% fungsi dari sistem masih belum bisa memenuhi kebutuhan bisnis perusahaan yang bersifat spesifik. Untuk itu perlu dilakukan penyesuaian-penyesuaian terhadap modul Inventory Management Oracle yang diimplementasikan di PT. X. Hal ini juga menunjukkan bahwa utilisasi software Oracle oleh perusahaan belum optimal. Kata kunci : Evaluasi, ERP ( Enterprise Resource Planning ), Inventory Management, Oracle , Analisis Fit/Gap This research aims to evaluate the result of Inventory Management modul implementation in PT. X and then analyze the gap between As-Is Process with company’s business requirements to find the alternative solutions. Inventory Management modul which is the main object of this research is a part of ERP system software called Oracle. Fit/Gap Analysis is applied to determine which process of the system that doesn’t meet company’s business requirements and then find the alternative solutions as the part of problem solving process. Result from the research shows that from 7 business requirements, the system fully complies only to 1 business requirement (Fit) and it doesn’t fully comply to 6 business requirements (Partial Fit). By 86% of functions provided by the system still cannot meet with company’s specific business requirements. Therefore, customization needs to be done to the Oracle Inventory Management modul implemented in PT. X. This also shows that the utilization of Oracle software by the company is not optimum. Keywords : Evaluation, ERP (Enterprise Resource Planning), Inventory Management, Oracle, Fit/Gap Analysis Daftar Pustaka Addo-Tenkorang, R., & Helo, P. (2011). Enterprise Resource Planning (ERP): A Review. Proceedings of the World Congress on Engineering and Computer Science 2011 Vol II . Campbell, J. D. (1998). Maintenance, Repair and Operations Handbook. Ontario: Clifford/Elliot Publication. Fiona Fui-Hoon Nah, P. (2002). Enterprise Resource Planning Solutions and Management. USA: IRM Press. Gulati, R. (2013). Maintenance and Reliability Best Practices. New York: Industrial Press, Inc. Koyan, P. D. (n.d.). Metodologi Penelitian Kualitatif. Oracle. (n.d.). Oracle Inventory Management. Oracle Data Sheet . Pajk, D., & Kovacic, A. (2013). Fit Gap Analysis – The Role of Business Process Reference Models. In Economic and Business Review Vol. 15 (pp. 319-388). Slovenia: EBR. Pol, P., & Paturkar, M. (2011). Methods of Fit Gap Analysis in SAP ERP Projects. White Paper . Pratomo, B., Parulian, R. S., & Anggraeni, E. (2013). Evaluasi Sistem ERP Modul Sales and Distribution dengan Menggunakan Metode Fit/Gap Analysis pada PT. BFR. Umar, H. (2005). Evaluasi Kinerja Perusahaan. Jakarta: Gramedia Pustaka Utama. Wallace, T. F., & Kremzar, M. H. (2001). ERP: Making It Happen. Canada: John Wiley & Sons, Inc.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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