Klasifikasi Pembelian Masker Dengan Naive Bayes Dan Random Forest = Classification of Mask Purchase with Naive Bayes and Random Forest

Septian, Hadi (2022) Klasifikasi Pembelian Masker Dengan Naive Bayes Dan Random Forest = Classification of Mask Purchase with Naive Bayes and Random Forest. Bachelor thesis, Universitas Pelita Harapan.

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Abstract

Corona virus 2019 disease (covid-19) mendorong masyarakat Indonesia untuk menjalankan pola hidup baru yang salah satunya adalah penggunaan masker untuk mengurangi risiko penularan virus. Banyaknya produk masker yang beredar di Indonesia sangat berpotensi menimbulkan persaingan antara satu masker dengan masker lainnya. Produsen masker harus lebih dahulu mengenali keadaan konsumennya sebelum membuat langkah-langkah strategis lainnya untuk bertahan ataupun memenangkan persaingan yang terjadi. Penelitian ini mengklasifikasikan pembeli masker berdasarkan usia, jenis kelamin, domisili, penghasilan, harga masker yang dibeli, lama pemakaian masker, dan warna masker yang dibeli terhadap jenis masker yang dibeli. Jenis masker pada penelitian ini dibatasi pada surgical mask, KF94, respirator KN95, dan respirator N95. Proses pengolahan data menggunakan RapidMiner Studio dengan ekstensi auto model yang dapat memproses data untuk klasifikasi pada beberapa model algoritma dan membandingkan hasil akurasinya. Akurasi yang paling tinggi pada proses tersebut berasal dari model naive Bayes dan akurasi tertinggi yang kedua berasal dari model random forest. Selain akurasi, ekstensi auto model juga menghasilkan confusion matrix yang berisikan precision dan recall dari masing-masing kelas (jenis masker). Dari data dan model yang terbentuk, penelitian ini juga menggunakan fungsi simulator pada RapidMiner Studio untuk membandingkan beberapa kemungkinan kombinasi kriteria responden terhadap kemungkinan masker yang dibeli. / Corona virus 2019 disease (covid-19) encourages Indonesian to adopt a new lifestyle (new normal), included the wear of masks to reduce the risk of virus’ transmission from one to others. There are large number of mask product circulating in Indonesian market that potentially creating competition between one to another mask. Mask manufacturers should recognize the condition of their market especially their consumers before making other strategic steps towards the competition ahead. This study classifies mask buyers based on age, gender, domicile, income, price of mask purchased, the duration of wearing a mask, color of mask purchased compared to the type of masks purchased. The types of mask in this study were limited to surgical mask, KF94, KN95 respirator, and N95 respirator. The data processing used RapidMiner Studio with auto model extension that can process the data through several model of classification. The highest accuracy on auto model came from naive Bayes model, and the second highest accuracy came from random forest model. Beside the accuracy, auto model provides confusion matrix that including precision and recall from each class of the data. This study also uses the simulator from RapidMiner Studio to compare several possible criteria combinations from respondents against the possibility of mask purchased.

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