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All Journal Jurnal Online Mahasiswa (JOM) Bidang Ilmu Sosial dan Ilmu Politik Jurnal Pseudocode Jurnal Informatika dan Teknik Elektro Terapan Jurnal Sistem Informasi dan Bisnis Cerdas SPEKTRA: Jurnal Kajian Pendidikan Sains Jurnal Eksplora Informatika Jurnal Nasional Komputasi dan Teknologi Informasi Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Technologia: Jurnal Ilmiah Jurnal Teknologi Dan Sistem Informasi Bisnis Jurnal Informatika dan Rekayasa Perangkat Lunak Jurnal Pengabdian Masyarakat Indonesia Jurnal Ilmiah Teknologi Informasi dan Robotika Jurnal Abdi Masyarakat Indonesia International Journal Of Computer, Network Security and Information System (IJCONSIST) Jurnal Pengabdian Mitra Masyarakat (JPMM) Journal Research of Social Science, Economics, and Management TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi
Irfan Pratama
Universitas Mercu Buana Yogyakarta
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Medicine & Pharmacology Neuroscience Physics Public Health Social Sciences Transportation Other

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IMPLEMENTASI METODE CENTROID DECOMPOSITION UNTUK PERAMALAN PADA DATA CUACA Irfan Pratama
Jurnal Ilmiah Teknologi Informasi dan Robotika Vol. 1 No. 1 (2019): Jurnal Ilmiah Teknologi Informasi dan Robotika
Publisher : Universitas Pembangunan Nasional Veteran Jawa Timur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/jifti.v1i1.7

Abstract

Data mining adalah sebuah fase pencarian pengetahuan pada kumpulan suatu data. Data mining juga adalah sebuah proses ekstraksi dari informasi-informasi dan pengetahuan-pengetahuan yang berguna yang didapat dari kumpulan data yang besar, tidak lengkap, acak, dan ambigu. Berdasarkan pengetahuan tersebut, penelitian ini dilakukan untuk mengetahui apakah metode yang diterapkan oleh peneliti sebelumnya pada penanganan missing values dapat diterapkan pada proses prediksi dengan beberapa penyesuaian. Seiring bertambahnya titik prediksi, hasil dari metode Ekstrapolasi Linear semakin buruk. Dengan kata lain tidak cocok untuk melakukan prediksi jangka menengah hingga panjang, namun dapat dilakukan menggunakan metode Centroid Decomposition.
Implementasi Metode Certainty Factor dan Bayesian dalam Sistem Pakar Diagnosa Inkontinensia Urine Lansia Putri Taqwa Prasetyaningrum; Mutaqin Akbar; Agus Sidiq Purnomo; Irfan Pratama; Imam Suharjo
TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akuntansi Vol 4 No 2(SEMNASTIK) (2024): TAMIKA: Jurnal Tugas Akhir Manajemen Informatika & Komputerisasi Akunt
Publisher : Universitas Methodist Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46880/tamika.Vol4No2(SEMNASTIK).pp191-199

Abstract

Urinary incontinence is a medical condition commonly experienced by the elderly, requiring prompt and accurate diagnosis for effective treatment. This study aims to develop and compare the performance of two methods in expert systems for diagnosing urinary incontinence in the elderly: Certainty Factor and Bayesian. The developed expert system is web-based and utilizes a symptom dataset collected from the Santa Monika Boro Nursing Home. The findings reveal that the Certainty Factor method excels in diagnostic processing speed, while the Bayesian method offers higher accuracy in diagnostic predictions. This comparison provides valuable insights into selecting appropriate approaches for expert system applications in medical settings.
COMPARISON OF SUPPORT VECTOR MACHINE RADIAL BASE AND LINEAR KERNEL FUNCTIONS FOR MOBILE BANKING CUSTOMER SATISFACTION ANALYSIS Putri Taqwa Prasetyaningrum; Nurul Tiara Kadir; Albert Yakobus Chandra; Irfan Pratama
IJCONSIST JOURNALS Vol 4 No 1 (2022): September
Publisher : International Journal of Computer, Network Security and Information System

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/ijconsist.v4i1.75

Abstract

Banking services using mobile banking applications, including Indonesian state bank (called BRI). A study on feedback regarding BRI services based on mobile applications was done. In order to compete with other banks, that is used to enhance and modernize the quality of BRI services provided to clients. Based on phenomena that occur in these situations. This study aims to classify comments from users of the BRI Mobile Banking Application on Google Play services into positive and negative comment sentiments. In this study, the Support Vector Machine (SVM) technique is utilized to determine between positive or negative reviews. The sentiment analysis of BRI google play data was carried out by comparing the Radial Basis Function (RBF) kernel function and the Linear kernel. As well as the experiment of adding feature selection, parameters, and n-grams for a period of two years, from January 1st,, 2017 to December 31st, 2018. The results of the study using the k-fold cross-validation test, the precision value of the SVM kernel linear is 90.80 percent and the SVM kernel RBF is 90.15 percent. In the RBF kernel, there are 1,816 positive classes and 1,455 negative classes. While the Linear kernel obtained a positive class of 1,734 and a negative class of 1,637.
Co-Authors Adi Indhito, Tatak Guritno Ahmad Iwan Fadli ahmad subadri Albert Yakobus Chandra Albert Yakobus Chandra Ardhi Choiruddin Eko Suyanto George Recksy Sandy Pratama I Dewa Putu Nyeneng Kukuh Truna Wijaya Mutaqin Akbar Nugraha, Anggit Ferdita Nurul Tiara Kadir Nurul Tiara Kadir Ozzi Suria Prasetyaningrum, Putri Taqwa Sidiq Purnomo, Agus Suharjo, Imam Wahyu Ajitomo Welly Wirman Yoga Pristyanto