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All Journal Creative Information Technology Journal Jurnal Pilar Nusa Mandiri Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Riset Informatika Information System Journal (INFOS)

Bety Wulan Sari

Universitas AMIKOM Yogyakarta

Author-ID : 2483696

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Articles

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

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

IMPLEMENTASI SUPPORT VECTOR MACHINE UNTUK ANALISIS SENTIMEN PENGGUNA TWITTER TERHADAP PELAYANAN TELKOM DAN BIZNET Bety Wulan Sari; Fadholi Fat Haranto
Jurnal Pilar Nusa Mandiri Vol 15 No 2 (2019): PILAR Periode September 2019
Publisher : LPPM Universitas Nusa Mandiri

Sosial media merupakan suatu media yang dapat digunakan untuk berekspresi oleh penggunanya. Twitter cukup populer dan sering digunakan di Indonesia, pengguna twitter dapat berekspresi dan beraspirasi tanpa adanya batasan. Tweet yang berupa ekspresi dan aspirasi yang ditulis oleh pengguna twitter dapat digunakan untuk ulasan sebuah produk atau layanan. Pada penelitian ini, peneliti menggunakan teknik text mining dengan menerapkan algoritma Support Vector Machine yang dipergunakan untuk analisis sentimen pengguna twitter terhadap pelayanan Telkom dan Biznet. Data pada pelayanan Telkom dan Biznet akan dilakukan perhitungan pada penelitian ini dengan jumlah dataset sebanyak 500 tweet yang berasal dari crawling data twitter, terdapat 250 tweet yang dijadikan dataset pada masing-masing objek. Sejumlah data tersebut akan dipergunakan untuk data training serta data testing dalam proses pembuatan model menggunakan algoritma Support Vector Machine. Metode yang digunakan untuk pengujian model adalah Confusion Matrix sedangkan K-Fold Cross Validation ditujukan untuk untuk membagi data training dan data testing sesuai lipatan yang digunakan. Hasil pengujian yang diperoleh menggunakan metode K-Fold Cross Validation dan Confusion Matrix pada model yang dibuat menggunakan algoritma Support Vector Machine yang memberikan hasil nilai accuracy 79,6%, precision 76,5%, recall 72,8% , dan F1-score 74,6% untuk Telkom, serta accuracy 83,2%, precision 78,8%, recall 71,6%, dan F1-score 75% untuk Biznet.

IMPLEMENTATION OF MOORA METHOD FOR DECISION SUPPORT SYSTEM SCHOLARSHIP SELECTION IN SMK MUHAMMADIYAH PRAMBANAN Dinar Abdi Perdana; Donni Prabowo; Bety Wulan Sari
Jurnal Pilar Nusa Mandiri Vol 18 No 1 (2022): Publishing Period for March 2022
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v18i1.2261

Decision Support System for Scholarship Selection at SMK Muhammadiyah Prambanan Using the MOORA Method aims to implement the Multi-Objective Optimization method on the basis of Ration Analysis. In determining scholarship recipients based on predetermined criteria and building a system in the form of a website to help provide alternative decisions in determining the acceptance of scholarships at SMK Muhammadiyah Prambanan. Based on the source of the data obtained, using primary data including interview and observation methods supported by secondary data obtained by literature studies that are relevant to the problem. Scholarship data is calculated and then ranked based on the final value generated from the MOORA calculation. The process of scholarships selection is based on criteria including report card grades, dependents of parents, the income of parents, percentage of attendance, and the number of siblings. The results of this study are the Scholarship Selection Decision Support System Using the MOORA Method, where the final value in the form of an alternative that has the greatest preference value will be placed at the top rank. The alternative will be a recommendation to receive a scholarship.

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

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
Techno Nusa Mandiri: Journal of Computing and Information Technology Vol 17 No 1 (2020): TECHNO Period of March 2020
Publisher : Lembaga Penelitian dan Pengabdian Pada Masyarakat

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%.

Implementation of Smarter Method for Prospective Student Council Selection System SMK Negeri 1 Rembang Bety Wulan Sari; Donni Prabowo; Wahyu Puji Lestari
Jurnal Pilar Nusa Mandiri Vol 19 No 2 (2023): Publishing Period for September 2023
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v19i2.4591

One of the schools that has attempted to make the student council active and the primary platform for student development to encourage student activities at school is SMK Negeri 1 Rembang. OSIS administrators can execute numerous labor programs in both academic and non-academic domains. Participants must pass several selection processes to join the SMK Negeri 1 Rembang OSIS board. This student council board's election procedure still employs manual methods. The selection procedure may take longer and allow for subjective evaluations depending on the number of candidates and the criteria used. As a result, it is essential to develop a decision support system (SPK) that uses Rank Order Centroid (ROC) weighting and the Simple Multi-Attribute Rating Technique Exploiting Rank (SMARTER) method to help choose student council administrators. The SMARTER technique addressed disproportionality because the weights assigned do not provide a hierarchy or order of importance between the current criteria and their sub-criteria. Based on the computation of the final value of the standards and sub-criteria on each alternative, the system produces results in the form of the biggest to most minor order. Blackbox testing of this program demonstrates that it can operate and be used at SMK N 1 Rembang both in terms of functionality and outcomes from the system.

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

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 Dinar Abdi Perdana Donni Prabowo Donni Prabowo Fadholi Fat Haranto Irkham Widhi Saputro Nurul Ajeng Wahyu Puji Lestari Yoga Aditama Ika Nanda

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