Pembangunan Sistem Pemantauan Populariti ahli Politik (SPPP)
DOI:
https://doi.org/10.64382/mjii.v4i2.87Keywords:
pembelajaran mesin, media sosial, analisis sentimen, politik, Naive BayesAbstract
Kajian ini membentangkan pembangunan Sistem Pemantauan Populariti ahli Politik (SPPP) menggunakan algoritma yang Naïve Bayes yang membolehkan pengguna memantau populariti ahli politik berdasarkan akaun peribadi di aplikasi X. Dalam kajian ini, aplikasi X digunakan sebagai sumber utama sistem ini untuk pengekstrakan data (tweet). Kuantiti tweet yang besar ini menawarkan pola atau maklumat yang berharga kepada organisasi atau individu dalam membuat keputusan yang berkesan. Matlamat kajian ini adalah untuk membangunkan sistem antara muka mesra pengguna bagi menganalisis status populariti ahli politik secara masa nyata dan seterusnya memvisualisasikan keputusan dalam bentuk grafik seperti carta bar, carta donat dan word cloud. Sistem ini menggunakan analisis sentimen dan teknik pembelajaran mesin Naïve Bayes. Teknik pengelasan Naïve Bayes digunakan untuk membina model pengelas yang boleh mengklasifikasikan tweet yang dikumpul sebagai sentimen positif, neutral dan negatif.
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