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All Journal METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi
Tundo Tundo
Sekolah Tinggi Ilmu Komputer Cipta Karya Informatika
Computer Science & IT Economics, Econometrics & Finance

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Analisis Tingkat Kepuasan Mahasiswa dalam Kegiatan UKM di Stikom CKI Menggunakan Algoritma Naive Bayes Ramdani Arvianto; Tundo Tundo; Eflin Tresia; Firly Januarsyah
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 2 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No2.pp206-214

Abstract

The main problem in increasing the level of student satisfaction in UKM activities at STIKOM CKI is caused by various factors, including the rare frequency of meetings and the multiplication of material without significant development. This dissatisfaction can reduce students' interest in actively participating in UKM activities, which should be a source of positive experiences and skills development. Well-managed SME activities can be an important means of developing soft skills such as leadership, team collaboration and communication skills. However, when these activities are not managed well, the results can be counterproductive, causing frustration and dissatisfaction among students. Based on these problems, an application of the Naive Bayes algorithm will be carried out to determine the satisfaction level of STIKOM CKI students with 80 training data and 6 test data. After calculating, an accuracy rate of 83.33%, recall of 33.33%, and precision are obtained. 100%. Therefore, it is important to manage student satisfaction levels to avoid being counterproductive. One of the appropriate data mining algorithms to solve the case above is to use the Naive Bayes algorithm.
Penerapan Data Mining Menggunakan Algoritma Apriori pada Brand Milenials Cafe Hadi Gunawan; Tundo Tundo; Devika Azahra Ramadhani; Farhan Adriansyah Waloeya
METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Vol. 8 No. 2 (2024): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/jmika.Vol8No2.pp215-221

Abstract

Millennials Café is a cafe that just opened in March 2024, in an effort to stay relevant and competitive in this field, Millennials Café needs to continue to innovate and adjust to customer preferences. One way is to utilize data mining technology. The Apriori algorithm is one of the data mining technologies that can be used. The application of the apriori algorithm to the Milenials Café transaction data aims to find association rules to be able to generate frequencies and relationships between one or more items in the transaction data in the Milenials Café. This research produces 33 association rules that can help the sales strategy at Milenials Café. The following are the association rules with the highest confidence value, namely the Thai Tea menu, Milo Dinasourus, 100% Millennials Pizza, Hezelnut Chocolate, Oreo Cookies and Cream Shake 97%. Millennials Pizza, Fried Potatoes 96%. The 33 rules that already exist can be used as a reference for the owner of Millennials Café to create a sales strategy that can increase cafe revenue.
Co-Authors Devika Azahra Ramadhani Eflin Tresia Farhan Adriansyah Waloeya Firly Januarsyah Hadi Gunawan Ramdani Arvianto