AISYA IDAH TRIPUTRI PASKALITA, NIM. 162018063 (2022) IMPLEMENTASI PREDIKSI KEPUTUSAN KONSUMEN DALAM MEMBELI HIJAB PADA TOKO ISTANA HIJAB PALEMBANG DENGAN MENGGUNAKAN METODE PROBABILITY BAYES DAN DECISION TREE. Skripsi thesis, Universitas Muhammadiyah Palembang.

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Abstract

The implementation of consumer purchase decision predictions at hijab stores is usually tried manually and using tables. Until it takes a bonus time to calculate the consumer's purchase and the results are less accurate. To use the Decision Tree and Probability Bayes method to be able to help overcome this problem both in terms of predicting consumer purchasing decisions. The Decision Tree procedure is a plant structure, each point of the plant is an experimental guide, each branch is the result of the trial and the final point of the Decision Tree. And there are two interrelated models, because to build an ID3 algorithm is needed. And the Naïve Bayes algorithm is a simple probabilistic-based prediction method that is based on the implementation of Bayes' theorems or conditions, meaning that a feature exists or the information is the same. Keywords: Prediction, Decision Tree, Nave Bayes Implementasi prediksi keputusan pembelian konsumen pada toko jilbab biasanya dicoba cara manual dan tabel. Hingga dibutuhkan waktu bonus buat menghitung pembelian konsumen tersebut dan hasil yang kurang akurat. Buat digunakan tata cara Decision Tree serta Probability Bayes supaya sanggup menolong menanggulangi kasus tersebut baik dalam perihal prediksi keputusan pembelian konsumen. Tata cara Decision Tree ialah suatu struktur tumbuhan, tiap titik tumbuhan ialah petunjuk yang sudah uji coba, tiap cabang ialah hasil uji coba serta titik akhir Decision Tree. Dan ialah 2 model yang silih berhubungan, sebab buat membangun suatu dibutuhan algoritma ID3. Serta algoritma Naïve Bayes ialah metode prediksi berbasis probabilistik simpel yang bersumber pada pada pelaksanaan teorema ataupun ketentuan bayes, maksudnya merupakan suatu fitur terdapat ataupun informasi sama. Kata Kunci : Prediksi, Decision Tree, Naïve Bayes

Item Type:	Thesis (Skripsi)
Additional Information:	Pembimbing : 1. Karnadi, S.Kom, M.Kom. 2. Zulhipni Reno Saputra Elsi, S.T., M.Kom.
Uncontrolled Keywords:	Kata Kunci : Prediksi, Decision Tree, Naïve Bayes
Subjects:	Teknologi informasi > pemrograman
Divisions:	Fakultas Teknik > Teknologi Informasi (S1)
Depositing User:	Mahasiswa Fakultas Teknik
Date Deposited:	06 Oct 2022 04:42
Last Modified:	06 Oct 2022 04:42
URI:	http://repository.um-palembang.ac.id/id/eprint/22891

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