TY  - THES
N1  - Pembimbing: Dr. Agung Fatwanto, S.Si., M.Kom
ID  - digilib63762
UR  - https://digilib.uin-suka.ac.id/id/eprint/63762/
A1  - Wildan Nadiyal Ahsan, NIM.: 20206052011
Y1  - 2024/01/26/
N2  - Graph-based data analysis is a prevalent method employed across various domains. Some popularly
used graph packages such as NetworkX, igraph, NetworKit and graph-tool are examples of packages
available for the Python programming language. Each has its advantages and disadvantages. This
research aims to compare the performance (in terms of execution time) and memory usage of several
popular graph packages, namely NetworkX, Networkit, SNAP, graph-tool, igraph and rustworkX.
The research employed an experimental quantitative method. The datasets used for simulating the
network analysis by applying co-occurance network was 10.000 article titles gathered from several
journals indexed by scopus. The results shown that the mean value ± margin of error (at level of
confidence: 0.95 and number of samples/number of experiment iterations (n): 35) for the execution
time of graph-tool = 1.30291731 ± 0.268629749 second (s), networkX = 2.07304831 ± 0.672788959
(s), networkit = 1.44051549 ± 0.272388017 (s), snap = 0.92104769 ± 0.126535737 (s), igraph =
1.63668983 ± 0.621590572 (s), rustworkx = 1.33403117 ± 0.190636021 (s). Meanwhile, the mean
± margin of error for the current memory usage of graph-tool = 2.023255971 ± 0.115873399
MegaByte (MB) networkX = 5. 1896566 ± 2.431315437 (MB), networkit = 6.207405857 ±
4.225013008 (MB), snap = 3.743473629 ± 1.080429925 (MB), igraph = 4.461298114 ± 1.20858089
(MB), rustworkx = 4.267859943 ± .....(MB); and the mean ± margin of error for peak memory usage
of graph-tool = 3.402223457 ± 0.017638869 MegaByte (MB), networkX = 5.630388457 ±
2.813189597 (MB), networkit = 7.048138886 ± 4.996092409 (MB), snap = 4.120006486 ±
1.288241414 (MB), igraph = 4.825449429 ± 1.47061189 (MB), rustworkx = 4.621915486 ±
1.130673792 (MB). The results of repeated measures ANOVA and Friedman test for the execution
time, current memory usage and peak memory usage shown that there is significant difference among
these mean values. Therefore, it can be concluded that the order of the performance based on
execution time (from fastest to slowest) is: 1.snap 2.graph-tool & rustworkx 3.networkit & igraph
4.networkX. Meanwhile, the order of the efficiency based on the current memory usage and peak
memory usage (from most efficient to most inefficient) is: 1.graph-tool 2.snap 3. rustworkX 4.igraph
5.networkX 6.networkit. There was a moderate and positive correlation between execution time and
memory usage. Further, there was a very strong and positive between current memory and peak
memory usage.
PB  - UIN SUNAN KALIJAGA YOGYAKARTA
KW  - Grafik Python; Komparasi Grafik Python
M1  - masters
TI  - PERBANDINGAN WAKTU EKSEKUSI DAN PENGGUNAAN MEMORI PADA PAKET GRAFIK PYTHON UNTUK ANALISIS JARINGAN
AV  - restricted
EP  - 112
ER  -