Maximum Bipartite Matching

Referensi

1. CMSC 451: Maximum Bipartite Matching, https://www.cs.cmu.edu/~ckingsf/bioinfo-lectures/matching.pdf
2. A resource sharing (sharing platform) scheme on online taxi services, https://www.matec-conferences.org/articles/matecconf/pdf/2019/19/matecconf_concern2018_03010.pdf
3. Get started with R igraph, https://igraph.org/r/
4. Network Analysis and Visualization with R and igraph, https://kateto.net/netscix2016.html
5. Practical statistical network analysis (with R and igraph), http://statmath.wu.ac.at/research/friday/resources_WS0708_SS08/igraph.pdf
6. maxmatching: Maximum Matching for General Weighted Graph, https://rdrr.io/cran/maxmatching/
7. Hungarian Method, http://opensourc.es/blog/hungarian-method
8. The Hungarian Method, https://www-m9.ma.tum.de/graph-algorithms/matchings-hungarian-method/index_en.html
9. Optimiz(s)ation Algorithms, https://www.comp.nus.edu.sg/~stevenha/cs4234/lectures/08.Matching.pdf
10. The Munkres Assignment Algorithm (Hungarian Algorithm), https://www.youtube.com/watch?v=cQ5MsiGaDY8

GeoDa : An Introduction to Spatial Data Analysis

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Referensi

1. GeoDa is a free and open source software tool that serves as an introduction to spatial data analysis. It is designed to facilitate new insights from data analysis by exploring and modeling spatial patterns, https://geodacenter.github.io/

Manajemen Pengembangan Software dengan Gitscrum

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Referensi

1. GitScrum, Simple and Robust solution to manage your software development project, https://github.com/gitscrum-community/laravel-gitscrum