Abstract— Cancer is one of the deadliest diseases in the world
that needs to be handled as early as possible. One of the methods
to detect the presence of cancer cells early on is by using
microarray data. Microarray data can store human gene
expression and use it to classify cancer cells. But one of the
challenges of using microarray is its vast number of features, not
proportional to its small number of samples. To resolve that
problem, dimensionality reduction is needed to reduce the number
of features stored in microarray data. Binary Particle Swarm
Optimization (BPSO) is one of the methods to reduce
dimensionality of microarray data that can increase classification
performance. Although when combined with Backpropagation,
BPSO still shows a relatively low performance. In this research,
Modified Backpropagation with Conjugate Gradient is used to
classify data that has been reduced with BPSO. The average
accuracy result of BPSO+CGBP is 86.1%, giving it an
improvement compared to BPSO+BP which averaged to 80.8%.