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| Kajian Skoping Patuh PRISMA× | Tinjauan Literatur Sistematik× | |
|---|---|---|
| Bidang | Saintometrik | Saintometrik |
| Keluarga | Process / pipeline | Process / pipeline |
| Tahun asal≠ | 2018 (PRISMA-ScR extension); 2005 (scoping review framework) | 1993 (Cochrane Collaboration); 2004 (Kitchenham SLR guidelines) |
| Pengasas≠ | Tricco et al. (PRISMA-ScR); Arksey & O'Malley (scoping review framework) | Archie Cochrane (conceptual foundation); formalized by the Cochrane Collaboration (1993) and Barbara Kitchenham in software engineering (2004) |
| Jenis≠ | Evidence synthesis — scoping review with standardized reporting | Evidence synthesis methodology |
| Sumber perintis≠ | Tricco, A. C., Lillie, E., Zarin, W., O'Brien, K. K., Colquhoun, H., Levac, D., ... & Straus, S. E. (2018). PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation. Annals of Internal Medicine, 169(7), 467–473. DOI ↗ | Kitchenham, B. (2004). Procedures for Performing Systematic Reviews. Keele University Technical Report TR/SE-0401. link ↗ |
| Alias | PRISMA-ScR scoping review, scoping review with PRISMA-ScR, PRISMA scoping review, transparent scoping review | SLR, systematic review, evidence synthesis review, structured literature review |
| Berkaitan≠ | 6 | 5 |
| Ringkasan≠ | A PRISMA-compliant scoping review is a scoping review conducted and reported according to the PRISMA for Scoping Reviews (PRISMA-ScR) extension, a 20-item checklist plus explanation published by Tricco et al. in 2018. Scoping reviews map the breadth and volume of evidence on a topic without synthesizing effect sizes; the PRISMA-ScR overlay adds transparency, reproducibility, and reporting completeness standards analogous to those PRISMA provides for systematic reviews and meta-analyses. | A systematic literature review (SLR) is a structured, reproducible method for identifying, appraising, and synthesizing all relevant studies on a research question. Unlike a narrative review, it follows an explicit, pre-specified protocol — from database search strings through inclusion criteria to data extraction — so that the process is transparent, auditable, and replicable by other researchers. It is widely used in medicine, education, software engineering, and the social sciences to produce the most comprehensive possible evidence base on a topic. |
| ScholarGateSet data ↗ |
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