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FPIK Universitas Jenderal Soedirman

Laporan Analisis Multi-Ordination EcoMetrics

Rapfish · MDS Ordination · PCA · ANOSIM · Discriminant Analysis
VERIFIED RESEARCH RECORD
Ref: AREs-ECOMETRICS-2026
Rapfish (Anchored Projection)

Proyeksi multidimensi ortogonal ke garis referensi Bad-Good.

PCA + Biplot

Eigen decomposition riil dengan ekstraksi vektor beban (Loadings).

K-Means++ & Elbow Method

Inisialisasi cerdas dengan evaluasi Within-Cluster Sum of Squares.

Hierarchical Clustering (UPGMA)

Pengelompokan bertingkat (Agglomerative) berdasarkan Jarak Euclidean.

ANOSIM (Analysis of Similarities)

Uji signifikansi multivariat non-parametrik dengan 999 permutasi.

Linear Discriminant Analysis (LDA)

Mencari sumbu yang memaksimalkan separasi antar grup perlakuan.

Sitasi Perangkat Lunak (APA Style):
Wibowo, D. S. (2026). AREs: An Integrated Progressive Web Application for Aquaculture Data Management, Statistical Computing, Molecular Analytics, and Spatial Mapping (v1.0.0). Zenodo. https://doi.org/10.5281/zenodo.20729217
📐 Panduan & Referensi Ilmiah
Format Input Data (Semua Modul)

Aplikasi ini memproses data tabular mentah yang disalin (*Copy-Paste*) langsung dari Microsoft Excel atau file TSV.

Untuk modul PCA, K-Means, dan HCA, kolom pertama wajib berupa Label Identitas (misal: "Stasiun 1"), diikuti kolom numerik di sebelahnya.
Untuk ANOSIM dan LDA, kolom 1 = Label, Kolom 2 = Grup Perlakuan, Kolom 3 dst = Numerik.

Daftar Referensi Algoritma (Standar APA)

Rapfish (MDS Keberlanjutan):
Pitcher, T. J., & Preikshot, D. (2001). RAPFISH: a rapid appraisal technique to evaluate the sustainability status of fisheries. Fisheries Research, 49(3), 255-270. doi:10.1016/S0165-7836(00)00205-8

Principal Component Analysis (PCA):
Jolliffe, I. T., & Cadima, J. (2016). Principal component analysis: a review and recent developments. Philosophical Transactions of the Royal Society A, 374(2065), 20150202. doi:10.1098/rsta.2015.0202

K-Means Clustering:
Jain, A. K. (2010). Data clustering: 50 years beyond K-means. Pattern Recognition Letters, 31(8), 651-666. doi:10.1016/j.patrec.2009.09.011

Hierarchical Clustering (UPGMA):
Murtagh, F., & Contreras, P. (2012). Algorithms for hierarchical clustering: an overview. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 2(1), 86-97. doi:10.1002/widm.53

ANOSIM (Analysis of Similarities):
Clarke, K. R. (1993). Non-parametric multivariate analyses of changes in community structure. Australian Journal of Ecology, 18(1), 117-143. doi:10.1111/j.1442-9993.1993.tb00438.x

LDA (Linear Discriminant Analysis):
Izenman, I. T. (2013). Linear discriminant analysis. In Modern Multivariate Statistical Techniques (pp. 237-280). Springer. doi:10.1007/978-0-387-78189-1_8