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All Journal Creative Information Technology Journal Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Riset Informatika Information System Journal (INFOS)
Bety Wulan Sari
Universitas AMIKOM Yogyakarta
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Uji Performa Algoritma Naïve Bayes untuk Prediksi Masa Studi Mahasiswa Irkham Widhi Saputro; Bety Wulan Sari
Creative Information Technology Journal Vol 6, No 1 (2019): Januari - Juni
Publisher : UNIVERSITAS AMIKOM YOGYAKARTA

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (216.226 KB) | DOI: 10.24076/citec.2019v6i1.178

Abstract

Universitas AMIKOM Yogyakarta adalah salah satu perguruan tinggi yang memiliki ribuan mahasiswa baru khususnya pada prodi Informatika. Pada tahun 2012 tercatat ada 1009 mahasiswa baru, dan pada tahun 2013 juga tercatat ada sebanyak 859 mahasiswa baru. Namun sayangnya, dari sekian banyak mahasiswa hanya sekitar 50% saja yang dapat lulus dengan tepat waktu. Data tersebut untuk membuat sistem klasifikasi menggunakan teknik data mining dengan metode Naïve Bayes. Dataset yang akan digunakan sebanyak 300 data yang bersumber dari data alumni angkatan 2012, dan 2013 dengan masing-masing data sebanyak 150. Data yang diperoleh memiliki 144 mahasiswa dengan keterangan lulus tepat waktu, dan 156 mahasiswa dengan keterangan lulus tidak tepat waktu. Proses pengujian akan dilakukan menggunakan metode 10-Fold Cross Validation, dan Confusion Matrix. Hasil pengujian menunjukkan bahwa rata-rata performa dari model Naïve Bayes mempunyai nilai akurasi sebesar 68%, nilai precision sebesar 61.3%, nilai recall sebesar 65.3%, dan nilai f1-score sebesar 61%. Nilai performa dari model dapat dipengaruhi oleh dataset yang digunakan untuk pembuatan model.Kata Kunci — data mining, Naïve Bayes, K-Fold Cross Validation, Confusion MatrixAMIKOM Yogyakarta University is one of the colleges that has thousands of new students, especially in the Informatics study program. In 2012 there were 1009 new students, and in 2013 there were 859 new students. But unfortunately, of the many students only around 50% can graduate on time. The data is to make the classification system using data mining techniques with the Naïve Bayes method. The dataset will be used as much as 300 data sourced from alumni data of 2012, and 2013 with each data as much as 150. The data obtained has 144 students with information passed on time, and 156 students with graduation information not on time. The testing process will be carried out using the 10-Fold Cross Validation, and Confusion Matrix method. The test results show that the average performance of the Naïve Bayes model has an accuracy value of 68%, precision value is 61.3%, recall value is 65.3%, and f1-score is 61%. The performance value of the model can be influenced by the dataset used for modeling.Keywords — data mining, classification, Naïve Bayes, graduation time
PREDIKSI PEMBERIAN KELAYAKAN PINJAMAN DENGAN METODE FUZZY TSUKAMOTO Nurul Ajeng; Bety Wulan Sari; Donni Prabowo
Information System Journal Vol. 3 No. 1 (2020): Information System Journal (INFOS)
Publisher : Universitas Amikom Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24076/infosjournal.2020v3i1.215

Abstract

Sentra Gadai is a place to borrow in Yogyakarta. Every day giving loans to customers. In granting a loan the Senta Gadai has a condition that is a loan size of 50% of the collateral price. If the loan is more than 50%, the Sentra Gadai sometimes still hesitate to provide the loan. The Loan Eligibility Prediction System is used to help the Sentra Gadai in making decisions by providing alternative estimates in determining the feasibility of borrowing by the customer. This prediction system uses Tsukamoto's fuzzy method in estimating the feasibility of loans to customers by having several criteria such as the duration of the loan, the price of the guarantee and the condition of the goods. This prediction system is based on desktop because it is only used by the Sentra Gadai and not to the public with the Java programming language and database using phpMyAdmin. Keywords : Prediction System, Loan,Fuzzy Tsukamoto
NAIVE BAYES ALGORITHM IMPLEMENTATION TO DETECT HUMAN PERSONALITY DISORDERS Yoga Aditama Ika Nanda; Bety Wulan Sari
Jurnal Techno Nusa Mandiri Vol 17 No 1 (2020): Techno Nusa Mandiri : Journal of Computing and Information Technology Period of
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (991.672 KB) | DOI: 10.33480/techno.v17i1.1239

Abstract

We live in a society that still sees problems regarding one's soul and personality as taboo, even though mental health is as important as physical health. A personality disorder itself is a disorder that can be seen from behavior, mindset, and attitude, which brings difficulties to life. Based on this problem, this study applies the method of Naive Bayes classifier as early detection of human personality disorders. Using a data set of 130 correspondences from the AMIKOM university scope with the age limit of 18-25 years and identified personality disorders is a borderline type disorder. The data obtained was 94 with undiagnosed classes and 36 with undiagnosed classes, with the research variables in the form of questionnaire questions as many as 13 questions. The testing process is done with 10 fold and 5 fold cross-validation, and confusion matrix with the results in the form of accurate 10 folds superior with a value of 88.8% compared to 5 folds that is 88.2%, for precision 10 folds superior with 88.7%, but for 5 fold recall superior with 88.3%, while the final results of these two performances in F1-Score, produce the same value, which is 86.1%.
User Experience Using the Planes Method on the BUKUERP Application Bety Wulan Sari; Donni Prabowo
Jurnal Riset Informatika Vol. 6 No. 3 (2024): June 2024
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34288/jri.v6i3.291

Abstract

This study applies the five planes method to comprehensively investigate a particular enterprise resource planning (ERP) application. To improve overall usability and user satisfaction, the organizational requirements component is the specific focus of this study. This research utilizes the five planes method, which consists of five UX design elements: strategy, scope, structure, skeleton, and surface. A review of the methodology, processes, and frameworks of similar research within user experience and user experience analysis is conducted. Each component makes The addressed problems more definite, understandable, and explicit. The System Usability Scale (SUS) is used in this study to examine and assess the procedure for raising user satisfaction. This study explains the significance of a structured approach emphasizing users in the application development, particularly in digitizing an organization's business.
Co-Authors Donni Prabowo Donni Prabowo Irkham Widhi Saputro Nurul Ajeng Yoga Aditama Ika Nanda