ANALISA SENTIMEN UNTUK MENGIDENTIFIKASI KECENDERUNGAN RADIKALISME DENGAN NAÏVE BAYES
Abstract
ABSTRACT
Radicalism in Indonesia is still an issue that is often discussed considering that there are still many acts of radicalism in Indonesia. The relatively rapid spread of radicalism requires special handling to stop the spread. This study aims to identify radicalism by grouping it into 3 (three) groups or levels which are later expected to facilitate the search for solutions to stop the spread of radicalism. The analysis system will use sentiment analysis using the method of machine learning, namely Naive Bayes. The data used were collected through surveys to students and religious leaders. The Naive Bayes method will later serve to determine the survey results of each individual based on his group. The total data collected for this study amounted to 250 respondents who have filled out survey questions, the data will be divided into 2 types, there are 165 data used for the training phase and 85 data for testing. After processing the data, the results were obtained using classification report calculations and obtained an accuracy of 85% from 3 radical groups.
Keywords: sentiment analysis; machine learning; naïve Bayes; radicalism
ABSTRAK
Radikalisme di Indonesia, hingga saat ini masih menjadi suatu isu yang diperbincangkan mengingat masih banyaknya aksi-aksi radikalisme di Indonesia. Penyebaran paham radikalisme yang relative cepat memerlukan adanya penanganan khusus untuk menghentikan penyebaran tersebut. Penelitian ini bertujuan untuk mengidentifikasi radikalisme dengan mengelompokannya menjadi 3 (tiga) kelompok atau tingkatan yang nantinya diharapkan dapat memudahkan pencarian solusi penghentian penyebaran paham radikalisme tersebut. Sistem analisis akan menggunakan analisis sentiment dengan menggunakan metode dari machine learning yaitu naive bayes. Data yang digunakan sendiri dikumpulkan melalui survey kepada santri dan pemuka agama. Metode naive bayes nantinya akan berfungsi untuk menentukan hasil survey tiap individu tersebut berdasarkan kelompoknya. Total data yang terkumpul untuk penelitian ini berjumlah 250 responden yang sudah mengisi pertanyaan survey, data tersebut nantinya akan dibagi 2 jenis, terdapat 165 data digunakan untuk tahap training dan 85 data untuk testing. Setelah melakukan proses olah data hasil yang didapat menggunakan perhitungan classification report dan didapat akurasi sebesar 85% dari 3 kelompok radikal.
Kata Kunci: sentiment analysis; machine learning; naïve bayes; radikalisme
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References
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