IMPLEMENTASI ALGORITMA APRIORI SEBAGAI ALTERNATIF STRATEGI PROMOSI UNIVERSITAS PGRI MAHADEWA INDONESIA

UPMI Bali is a new campus, so campus promotion is still very much needed to increase prospective new students at UPMI Bali. By utilizing available data, the campus can determine effective campus promotion strategies using data mining. The data system will be built using the Association Rules technique. Association Rules is a data mining method to find frequently occurring association patterns in data. This method is popular because it is often used to analyze shopping carts. The rules formed will be in the form of "If-Then" in a transaction. Using the apriori algorithm generally involves finding frequent itemsets from a sales transaction database through several iteration stages. The association patterns formed with a minimum support value of 10% and confidence of 50% produced 18 association rules, with the strong rule obtained being Lecturer and Denpasar with a support value of 22% and confidence of 50%. Thus, if students know about the UPMI campus reference from a Lecturer, then these students are from Denpasar.

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Publication Details

Journal
Jurnal Manajemen dan Teknologi Informasi
Published
2025-04-30
DOI
https://doi.org/10.59819/jmti.v15i1.4643
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

IMPLEMENTASI ALGORITMA APRIORI SEBAGAI ALTERNATIF STRATEGI PROMOSI UNIVERSITAS PGRI MAHADEWA INDONESIA

Bindu Gupta, I Kadek Juni Arta, I Wayan Dika, Ida Ayu Putu Febri Imawati
Jurnal Manajemen dan Teknologi Informasi
Data Mining and Machine Learning Applications
article

IMPLEMENTASI ALGORITMA APRIORI SEBAGAI ALTERNATIF STRATEGI PROMOSI UNIVERSITAS PGRI MAHADEWA INDONESIA

Bindu Gupta, I Kadek Juni Arta, I Wayan Dika, Ida Ayu Putu Febri Imawati
article en

Abstract

UPMI Bali is a new campus, so campus promotion is still very much needed to increase prospective new students at UPMI Bali. By utilizing available data, the campus can determine effective campus promotion strategies using data mining. The data system will be built using the Association Rules technique. Association Rules is a data mining method to find frequently occurring association patterns in data. This method is popular because it is often used to analyze shopping carts. The rules formed will be in the form of "If-Then" in a transaction. Using the apriori algorithm generally involves finding frequent itemsets from a sales transaction database through several iteration stages. The association patterns formed with a minimum support value of 10% and confidence of 50% produced 18 association rules, with the strong rule obtained being Lecturer and Denpasar with a support value of 22% and confidence of 50%. Thus, if students know about the UPMI campus reference from a Lecturer, then these students are from Denpasar.

Jurnal Manajemen dan Teknologi InformasiVol. 15(1)
Universitas Pendidikan Ganesha (ID), Universitas PGRI Mahadewa Indonesia (ID)
Openalex Percentile: Top 88%
Data Mining and Machine Learning Applications
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