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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Informatika Jurnal Teknik Komputer AMIK BSI Jurnal Khatulistiwa Informatika Paradigma JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Techno Nusa Mandiri : Journal of Computing and Information Technology Jurnal Mantik Penusa JURIKOM (Jurnal Riset Komputer) Jurnal Informasi dan Teknologi Jurnal Infortech RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI Computer Science (CO-SCIENCE) INSANtek – Jurnal Inovasi dan Sains Teknik Elektro IMTechno: Journal of Industrial Management and Technology

Amrin Amrin

Universitas Bina Sarana Informatika

Author-ID : 2543071

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Library & Information Science

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Title

Perbandingan Metode Neural Network Model Radial Basis Function Dan Multilayer Perceptron Untuk Analisa Risiko Kredit Mobil Amrin Amrin
Paradigma Vol 20, No 1 (2018): Periode Maret 2018
Publisher : LPPM Universitas Bina Sarana Informatika

Problems are often encountered in the provision of credit is to determine lending decisions to someone, while other issues are not all credit payments can run well. Among the causes are errors of judgment in making credit decisions. In this study will be used neural network with radial basis function method and neural network with multilayer perceptron method to analyze the risk of car credit, then compare which method is the better. From the test results to measure the performance of the method is to use testing methods confusion matrix and ROC curve, it is known that the method of neural network with multilayer perceptron is better than method of neural network with radial basis function where has a value of accuracy is 96,1% and value of AUC is 0.999. This shows that the model produced, including the classification is Exellent Clasification because it has the value of AUC between 0.90- 1.00.

Aplikasi Diagnosa Penyakit Tuberculosis Menggunakan Algoritma Data Mining Amrin Amrin; Hafdiarsya Saiyar
Paradigma Vol 20, No 2 (2018): Periode September 2018
Publisher : LPPM Universitas Bina Sarana Informatika

It is important for doctors to make an early diagnosis of tuberculosis in order to reduce the transmission of the disease to the wider community. In this study, the authors will apply and compare several methods of data mining classification, including AlgoritmaC4.5, Naïve Bayes, and Neural Network to diagnose tuberculosis disease, then compare which of the three methods are the most accurate. Based on the performance measurement results of the three models using Cross Validation, Confusion Matrix and ROC Curve methods, it is known that Naïve Bayes method is the best method with accuracy of 94.18% and under the curva (AUC) value of 0.977 , then neural network method with accuracy 89,89% and under the curva value (AUC) 0,975, and then C4.5 method with accuracy level equal to 84,56% and under the curva value (AUC) equal to 0,938. This shows that the three models that are produced including the category of classification is very good because it has an AUC value between 0.90-1.00.

DATA MINING DENGAN ALGORITMA APRIORI UNTUK PENENTUAN ATURAN ASOSIASI POLA PEMBELIAN PUPUK Amrin Amrin
Paradigma Vol 19, No 1 (2017): Periode Maret
Publisher : LPPM Universitas Bina Sarana Informatika

In order to find out what fertilizer purchased by consumers, can be done with analytical techniques that is the analysis of consumer buying habits. Detection of fertilizers often purchased simultaneously is done using association rules. In this research will be used a priori algorithm for determining the rules of association of fertilizer purchases. From the results of the discussion and analysis of data can be concluded that with the application of a priori algorithm in determining the combination between itemsets with minimum support of 20% and minimum confidence 75% found 6 association rules, which has the highest value of support and confidence is if the consumer made a purchase transaction of fertilizer Organic and urea fertilizers simultaneously with the value of 60% support and 86% confidence value. Thus, if there are consumers buying organic fertilizers, then the possibility of consumers buying urea fertilizer is 86%.

Analisa Kelayakan Pemberian Kredit Mobil Dengan Menggunakan Metode Neural Network Model Radial Basis Function Amrin Amrin
Paradigma Vol 19, No 2 (2017): Periode September 2017
Publisher : LPPM Universitas Bina Sarana Informatika

Problems are often encountered in the provision of credit is to determine lending decisions to someone, while other issues are not all credit payments can run well. Among the causes are errors of judgment in making credit decisions. In this study will be used neural network with radial basis function method to analyze the feasibility of providing car loans. From the test results to measure the performance of the method is to use testing methods confusion matrix and ROC curve, it is known that the method of back neural network radial basis function has a value of 89,2% accuracy and AUC value of 0.9471. This shows that the model produced, including the classification is Exellent Clasification because it has the AUC values between 0.90- 1.00.

PENGARUH PEMBELAJARAN SISTEM MODUL TERHADAP HASIL BELAJAR MATEMATIKA SISWA SD Amrin Amrin
Paradigma Vol 12, No 1 (2010): Vol. 12 Nomor 1, Maret 2010
Publisher : LPPM Universitas Bina Sarana Informatika

The learning of module system is a model of learning that is designed and arranged in a systematically planned way and aimed to help students and teachers reach for learning goals. This research aims to know and to describe whether the learning of mathematics by using the module can show the students learning progress and whether it’s better than conventional models. This research uses a quantitative experimental approach. The population of this research is sixth level students from elementary school named Daar el Salam in Gunung Putri, Bogor. Then sampling taken in this research is 30 students by using purposive sampling method. Instruments used to collect data are: Test and Questionnaire. The data collected will be analyzed by descriptive statistical analysis and inferential statistical analysis. From the results of descriptive statistical analysis,it can be known that the interest of students in learning mathematics by using module is very good Then by inferential statistical analysis, it can be found that t count = -20.80 and t table = 2.00. By using the two-tailed test,it can be seen that the value of t count is outside the tolerance of acceptance Ho: -2 <t count <2, so that Ho is rejected and H1 is accepted. The conclusion can be taken that the learning of mathematics with the module system has a very significant impact . Or in the other words, the learning mathematics with the module system is better than the conventional method. Key Word : Impact, Learning of Mathematic, Module

Co-Authors Andi Nana Mariana Budiarto, Balla Wahyu David Ridwan Savero Donny Dharmawan Eni Irfiani Frans Sudirjo Hafdiarsya Saiyar Harsih Rianto Irawan Satriadi Irawan Satriadi Luh Komang Candra Dewi Mita Diah Larasati Muhammad Alawi Muhammad Reza Aldiansyah Oki Rosanto Omar Pahlevi Priyono, Agil Hendro Rudianto Rudianto Satriadi, Irawan Sismadi , Sismadi Yopi Handrianto, Yopi

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