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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
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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SISTEM INFORMASI PENGELOLAAN SERTIFIKAT TANAH PADA BADAN PERTANAHAN NASIONAL JAKARTA Priyono, Agil Hendro; -, Amrin
Jurnal Mantik Penusa Vol 3, No 2,Des (2019): Manajemen Dan Informatika
Publisher : Pelita Nusantara Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1183.729 KB)

Abstract

Nowadays the internet is needed in all fields as a source of information and telecommunications that is fast and efficient. The use of the internet has become an important requirement for the whole community. Likewise, service at the Jakarta National Land Agency (BPN) office as a means to take care of all matters relating to land. This creates difficulties for people who are far from the BPN office environment to obtain the required information. Therefore, we need an information media website that contains various information services related to land that can be accessed by all levels of society. In this study, the authors designed a web-based land certificate management information system. The method used for software development is the waterfall method. The results of this study are websites that provide information services relating to land certificates, land sales, land ownership. This website is expected to assist the Jakarta BPN office in providing information services to the public and facilitate the BPN service process. Keywords: information systems,lLand certificates, web, UML, waterfall method
Diagnosis of Tuberculosis By Artificial Neural Network Algorithm Amrin, Amrin
Sinkron : jurnal dan penelitian teknik informatika Vol. 3 No. 2 (2019): SinkrOn Volume 3 Number 2, April 2019
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (538.116 KB) | DOI: 10.33395/sinkron.v3i2.10028

Abstract

Sangat penting bagi dokter untuk melakukan diagnosa secara dini penyakit tuberculosis agar dapat mengurangi penularan penyakit tersebut kepada masyarakat luas. Pada penelitian ini, penulis akan menerapkan metode klasifikasi data mining, yaitu Algoritma Jaringan Syaraf Tiruan untuk mendiagnosa penyakit tuberculosis. Berdasarkan hasil pengukuran performa dari model tersebut dengan menggunakan metode pengujian Cross Validation, Confusion Matrix dan Kurva ROC, diketahui bahwa algoritma jaringan syaraf tiruan memiliki tingkat akurasi sebesar 89,89% dan nilai area under the curva (AUC) sebesar 0,975. Hal ini menunjukkan bahwa model yang dihasilkan termasuk katagori klasifikasi sangat baik karena memiliki nilai AUC antara 0.90-1.00.
Data Mining Model For Designing Diagnostic Applications Inflammatory Liver Disease Pahlevi, Omar; Amrin, Amrin
Sinkron : jurnal dan penelitian teknik informatika Vol. 5 No. 1 (2020): Article Research, October 2020
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v5i1.10589

Abstract

Hepatitis is an infectious disease that is a public health problem that affects morbidity, mortality, public health status, life expectancy, and other socio-economic impacts. Early diagnosis of hepatitis is very important so that it can be treated and treated quickly. In this study, the authors will apply and compare several data mining classification methods, including the C4.5 algorithm, Naïve Bayes, and k-Nearest Neighbor to diagnose hepatitis, then compare which of the three methods is the most accurate. Based on the results of measuring the performance of the three models using the Cross Validation, Confusion Matrix and ROC Curve methods, it is known that the C4.5 method is the best method with an accuracy of 70.99% and an under the curva (AUC) value of 0.950, then the k-Nearest Neighbor method with accuracy of 67.19% and the value under the curve (AUC) 0.873, then the naïve Bayes method with an accuracy rate of 66.14% and a value under the curve (AUC) of 0.742.
Implementasi Jaringan Syaraf Tiruan Dengan Multilayer Perceptron Untuk Analisa Pemberian Kredit Amrin, Amrin; Satriadi, Irawan
JURIKOM (Jurnal Riset Komputer) Vol 5, No 6 (2018): Desember 2018
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v5i6.1006

Abstract

The Problem that is often faced in giving credit is determining the decision to give credit 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 multilayer perceptron method to analyze the feasibility of giving credit. 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 multilayer perceptron has a value of  96,1% accuracy and AUC value of  0.999. This shows that the model produced, including the classification is Exellent Clasification because it has the AUC values between 0.90- 1.00.
Kajian Website Pendaftaran Peserta Pelatihan Pada Kemendag Dengan Pendekatan Technology Acceptance Model Irawan Satriadi; Amrin Amrin
Jurnal Informatika Vol 7, No 1 (2020): April 2020
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (136.497 KB) | DOI: 10.31294/ji.v7i1.7576

Abstract

Perdagangan dunia menunjukkan perkembangan dinamis terlebih dengan mulai diberlakukannya Free Trade Agreement. Hal ini perlu disikapi oleh para pelaku bisnis terutama eksportir dan calon eksportir, mengingat pasar internasional kini menuntut profesionalisme yang tinggi dan bukan sekedar transaksi. Dengan tuntutan tersebut, pelaku bisnis perlu memiliki keterampilan dan pengetahuan yang cukup untuk menangkap peluang serta memenuhi standar yang dikehendaki oleh pasar internasional. PPEI sebagai lembaga pendidikan dan pelatihan di bidang ekspor impor yang berada di lingkungan Direktorat Jenderal Pengembangan Ekspor Nasional Kementerian Perdagangan, senantiasa terlibat aktif dalam meningkatkan kemampuan sumber daya manusia para pelaku bisnis, dengan berbagai pengetahuan praktis dan keterampilan yang diperlukan untuk menjadi yang handal, berwawasan global dan berdaya saing tinggi. Penelitian ini bertujuan untuk mengevaluasi teknologi web dan mengetahui faktor-faktor yang dapat mempengaruhi penerimaan pengguna pada website pendaftaran peserta pelatihan di PPEI Kemendag. Hasil penelitian menunjukkan bahwa kemampuan  diri calon peserta berinternet berpengaruh terhadap  persepsi kemudahan calon  peserta dalam menggunakan website, tidak berpengaruh terhadap niat untuk menggunakan website, dan tidak berpengaruh terhadap perilaku penggunaan website
Model Waterfall Untuk Pengembangan Sistem Informasi Pengolahan Nilai Pada SMP Kartika XI-3 Jakarta Timur Amrin Amrin; Mita Diah Larasati; Irawan Satriadi
JURNAL TEKNIK KOMPUTER Vol 6, No 1 (2020): JTK-Periode Januari 2020
Publisher : Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (22.005 KB) | DOI: 10.31294/jtk.v6i1.6884

Abstract

- Sistem informasi berbasis web pada saat ini sudah menjadi sarana yang efektif untuk mengolah data. Selain itu juga menyediakan berbagai fasilitas yang memudahkan pemakai dalam mencari berbagai macam informasi yang dibutuhkan. SMP Kartika XI-3 Jakarta Timur membutuhkan sekali adanya sistem informasi dalam hal pengolahan data nilai siswa. Untuk itulah penulis mencoba membuat penelitian mengenai sistem pengolahan nilai rapor pada SMP Kartika XI-3 Jakarta Timur yang sampai saat ini belum terkomputerisasi. Sistem yang ada pada SMP Kartika XI-3 Jakarta Timur ini masih dilkukan secara manual, mulai dari pencataan data nilai siswa, sampai penyimpanan data-data lainnya yang berhubungan dengan proses pengolahan hingga sampai pembuatan laporan, sehingga memungkinkan pada saat proses berlangsung terjadi kesalahan dalam pencatatan, kurang akuratnya laporan yang dibuat dan keterlambatan dalam pencarian data-data yang diperlukan. Dengan menggunakan metode pengembangan perangkat lunak waterfall web ini dapat dibuat, mulai dari komunikasi, perencanaan, perancangan, pembuatan, hingga pengembangan. Sistem informasi pengolahan nilai siswa berbasis web pada SMP Kartika XI-3 Jakarta Timur yang dibuat ini dapat digunakan sebagai sarana informasi bagi siswa dan guru mengenai pelaporan data nilai siswa dengan memanfaatkan sistem komputerisasi yang diolah dengan menggunakan bahasa pemrograman web PHP serta database MySQL.
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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (670.692 KB) | DOI: 10.31294/p.v20i1.2783

Abstract

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (531.95 KB) | DOI: 10.31294/p.v20i2.3932

Abstract

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

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (761.458 KB) | DOI: 10.31294/p.v19i1.1836

Abstract

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%.
Data Mining Optimization Based on Particle Swarm Optimization For Diagnosis of Inflammatory Liver Disease Amrin Amrin; Omar Pahlevi
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 5, No 1 (2021): EDISI JULY 2021
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v5i1.5312

Abstract

Inflammation of the liver is a contagious disease that is a public health problem that affects morbidity, mortality, public health status, life expectancy, and other socio-economic impacts. Early diagnosis of this disease is very important so that it can be quickly treated and treated. In this study the researchers will apply and compare several data mining and optimization classification methods with particle swarm optimization (pso), including the C4.5 algorithm, k-Nearest Neighbor, C4.5 with PSO, and k-Nearest Neighbor with PSO to diagnose inflammatory diseases. carefully, then compare which of the several of these methods is the most accurate. Based on the results of measuring the performance of the three models using the Cross Validation, Confusion Matrix and ROC Curve methods. Based on the research results, it is known that the C4.5 method with PSO is the best method with an accuracy of 79.51% and an under the curva (AUC) value of 0.950, then the k-Nearest Neighbor method with PSO has an accuracy of 75.59% and an AUC value of 0.909, then the C4.5 method with an accuracy rate of 70.99% and an AUC value of 0.950, then the k-Nearest Neighbor method with an accuracy rate of 67.19%, and an AUC value of 0.873. This proves that particle swarm optimization can improve the performance of the classification method used.
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