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All Journal Dinamik Bulletin of Electrical Engineering and Informatics Sinkron : Jurnal dan Penelitian Teknik Informatika Journal of Computer Networks, Architecture and High Performance Computing Data Sciences Indonesia (DSI)

Amir Mahmud Husein, Amir Mahmud

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Author-ID : 621429

Computer Science & IT Education Electrical & Electronics Engineering Physics

Published : 26 Documents Claim Missing Document

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Articles

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Enhancing the Quality of Cellular Camera Video With Convolutional Neural Network Tampubolon, Hotman Parsaoran; Sinurat, Watas; Gulo, Steven Eduard; Gulo, Befi Juniman; Husein, Amir Mahmud
Sinkron : jurnal dan penelitian teknik informatika Vol. 4 No. 1 (2019): SinkrOn Volume 4 Number 1, October 2019
Publisher : Politeknik Ganesha Medan

Abstrak— At present technological developments, especially in the field of computer vision, are showing significant performance such as the application of convolutional neural networks that have a very high degree of accuracy, for example improving video quality which recently has image restoration such as super resolution (VSR) thanks to deep learning with the aim of helping produce better visual videos. The use of video cameras for mobile devices is now increasingly highly developed. Nowadays mobile devices are experiencing a rapid increase in quality especially in cameras. However, physical limitations such as the small sensor size, compact lens and the lack of supporting hardware can prevent cellular devices from achieving good video camera quality results. For that many method approaches are applied, one of which is the CNN (Convolutional Neural Network) method. This method can improve the image of video recordings that have poor quality. Keywords—Convolutional neural network, computer vision, Improved video quality ;

Comparison Of Cellular Video Quality For Object Detection Using Neural Network Convolution Kevin, Kevin; Gunawan, Nico; Zagoto, Mariana Erfan Kristiani; Laurentius, Laurentius; Husein, Amir Mahmud
Sinkron : jurnal dan penelitian teknik informatika Vol. 4 No. 1 (2019): SinkrOn Volume 4 Number 1, October 2019
Publisher : Politeknik Ganesha Medan

Abstract— The purpose of this study is to compare the video quality between the Samsung HP camera and the Xiaomi HP camera. The object of study was UNPRI students who walked through the front yard of the UNPRI SEKIP campus. Here we test how accurate the camera's HP capture capacity is used to take the video. The method used to test this research is the Convolution Neural Network method. Object detection and recognition aim to detect and classify objects that can be applied to various fields such as face, human, pedestrian, vehicle detection (Pedoeem & Huang, 2018), besides the ability to find, identify, track and stabilize objects in various poses and important backgrounds in many real-time video applications. Object detection, tracking, alignment and stabilization have become very interesting fields of research in the vision and recognition of computer patterns due to the challenging nature of several slightly different objects such as object detection, where the algorithm must be precise enough to identify, track and center an object from the others

Penerapan Metode Distance Transform Pada Kernel Discriminant Analysis Untuk Pengenalan Pola Tulisan Tangan Angka Berbasis Principal Component Analysis: Penerapan Metode Distance Transform Pada Kernel Discriminant Analysis Untuk Pengenalan Pola Tulisan Tangan Angka Berbasis Principal Component Analysis Husein, Amir Mahmud; Harahap, Mawaddah
Sinkron : jurnal dan penelitian teknik informatika Vol. 2 No. 1 (2017): SinkrOn Volume 2 Nomor 1 Oktober 2017
Publisher : Politeknik Ganesha Medan

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Pengenalan pola merupakan salah satu bidang penelitian yang cukup popular Karena dapat digunakan untuk berbagai keperluan. Penelitian ini bertujuan membangun sebuah aplikasi untuk dapat mengenali sebuah objek tulisan tangan angka secara langsung dengan penerapan metode Distance Transform (DT) Pada Algoritma Kernel Discriminant Analysis (KDA) Berbasis Principal Component Analysis (PCA). Penerapan PCA untuk proses segementasi sedangkan KDA untuk ekstrasi fitur pola tulisan tangan angka, DTdiusulkan untuk memperbaiki performa KDA terhadap waktu komputasi dengan PCA untuk ekstraksi. Kerangkan analisis yang diusulkan menggunakan dua pendekatan, pendekatan pertama analisa kinerja PCA+KDA, kemudian PCA+KDA dengan DT, kedua hasil pendekatan akan dibandingkan untuk mengetahui dampak DT terhadap KDA berbasis PCA pada pengenalan pola tulisan tangan angka secara langsung.Berdasarkan hasil pengujian metode DT yang diusulkantidak berpengaruh secara signifikan untukmemperbaiki kelemahan KDA pada optimasi waktu, namun untuk ekstraksi pada kernelyang berbeda dengan tingkat akurasi pengenalantulisan tangan angka secara langsung 95,5% dibandingkan kombinasi KDA berbasis PCA sebesar 87,98%

Application of Data Mining for Optimal Drug Inventory in a Hospital Siringo-Ringo, Dewi Sahputri; Tambunan, Razana Baringin Daud; Yulizar, Dian; Daulay, Tri Agustina; Husein, Amir Mahmud
Sinkron : jurnal dan penelitian teknik informatika Vol. 4 No. 1 (2019): SinkrOn Volume 4 Number 1, October 2019
Publisher : Politeknik Ganesha Medan

The Hospital is a health care institution that conducts complete individual health services that provide inpatient, outpatient and emergency services. Drug inventory management is one thing that is very important for the survival of hospitals, management of the supply of medical equipment that is not optimal including medicines will have an impact on medical services as well as economically, because 70% of hospital revenue comes from drugs. In this study we propose data mining with a focus on contributions to the comparison of the K-Means and K-Nearest Neighbor (KNN) algorithms for disease classification, then the classification results are carried out mapping the correlation of diseases with drugs using Apriori, based on the results of testing the K-Means algorithm more accurately compared KNN in the Apriori method to find the relationship of disease with drugs based on the value of support, trust, support value, trust is expected to be a reference for drug purchase recommendations so that there is no excess or emptiness of the drug.

Digital Signs Security System using AES-Blowfish-RSA Hybrid Cryptography Approach HS, Christnatalis; Husein, Amir Mahmud
Sinkron : jurnal dan penelitian teknik informatika Vol. 4 No. 1 (2019): SinkrOn Volume 4 Number 1, October 2019
Publisher : Politeknik Ganesha Medan

Increasing application of digital signatures in legitimate authentication of administrative documents in both public and private environments is one of the points of concern, especially the issue of security and integrity of ownership of signatures. Digital signature is a mathematical scheme, which a unit to identify and prove the authenticity of the owner of the message or document. The study aims to analyze security patterns and identification of digital signatures on documents using the RSA-AES-Blowfish hybrid cryptographic method approach for securing digital signatures, while the Kohonen SOM method is applied to identify ownership recognition of signature images. The analysis framework used in this study is each signature will be stored in the form of a digital image file that has been encrypted using hybrid method of AES-Blowfish with the SHA 256 hash function. Process of forming private keys and public keys in the signature image using the RSA algorithm. Authentic verification of the use of digital signatures on the document has 2 (two) stages, the first stage is signature will be valid used on the document if the result of hashing the selected signature image is the same based on the private key and public key entered by the user, while the second stage identification is done using the Kohonen SOM method to validate the similarity of the chosen signature with the ownership of the signature.

Drug Demand Prediction Model Using Adaptive Neuro Fuzzy Inference System (ANFIS) Husein, Amir Mahmud; Simarmata, Allwin M
Sinkron : jurnal dan penelitian teknik informatika Vol. 4 No. 1 (2019): SinkrOn Volume 4 Number 1, October 2019
Publisher : Politeknik Ganesha Medan

Drug planning is the process of activities in the selection of types, quantities, and prices in accordance with the needs and budget for the coming procurement period in order to avoid the occurrence of excess or emptiness of drug supplies when needed by patients. Management of planning that is not optimal drug needs will have a negative impact on hospitals, both medically and economically, because 50-60% of the total budget used for treatment and medical equipment, uncertainty of drug needs due to disease population and the number of patients can change according to conditions the volume of patient diagnostic data, thus requiring an automatic way to select drug needs according to disease progression. This study aims to create a prediction model for drug needs with the ANFIS method, the data analysis framework used is sourced from drug usage / sales data at the Royal Prima Hospital 2016-2017 by building a software that implements the ANFIS method. Stages of application testing are carried out by applying the previous year's data to predict the current year, namely the 2016 data for 2017 predictions, while the 2017 data for 2018 predictions. The data source will be used to analyze the ANFIS membership function that generates parameters for the ANFIS method in training and testing data. The results of the analysis of the ANFIS parameters will be updated to produce a small error value (close to 0), based on the value of Root Mean Square Error (RMSE), then an evaluation is carried out with a quantitative and qualitative analysis of the predicted results with the existing system.

Message Insertion Using the Convolutional Neural Network Model Approach Ambarwati, Lita; Sirait, Agrifa Darwanto; Tambun, Bella Siska; Purwanto, Eko Paskah Jeremia; Husein, Amir Mahmud
Sinkron : jurnal dan penelitian teknik informatika Vol. 4 No. 1 (2019): SinkrOn Volume 4 Number 1, October 2019
Publisher : Politeknik Ganesha Medan

One problem in computer vision that has long been sought for a solution is the classification of objects in the image in general. How to duplicate the ability of humans to understand image information, so that computers can recognize objects in the image as humans do. The feature engineering process used is generally very limited where it can only apply to certain datasets without the ability to generalize to any type of image. That is because various differences between images include differences in perspective, differences in scale, differences in lighting conditions, deformation of objects, and so on. Academics who have long struggled with this issue. The application of the Convolutional Neural Network (CNN) method for the insertion of messages in an image with the aim of securing the proposed message produces good security, from the test results, it can be concluded as follows The Convolutional Neural Network (CNN) method requires computing time to insert messages in a secret image. The model framework uses 2 (two) images with the aim of the cover image as input and the secret image where the secret image has been inserted a message so that the secret is not visible. The cover image that has been inserted a secret picture that contains the message looks not much different, but the file size of the secret picture has increased by 66%.

Generative Adversarial Networks Time Series Models to Forecast Medicine Daily Sales in Hospital Husein, Amir Mahmud; Arsyal, Muhammad; Sinaga, Sutrisno; Syahputa, Hendra
Sinkron : jurnal dan penelitian teknik informatika Vol. 3 No. 2 (2019): SinkrOn Volume 3 Number 2, April 2019
Publisher : Politeknik Ganesha Medan

The success of the work of Generative Adversarial Networks (GAN) has recently achieved great success in many fields, such as stock market prediction, portfolio optimization, financial information processing and trading execution strategies, because the GAN model generates seemingly realistic data with models generator and discriminator .Planning for drug needs that are not optimal will have an impact on hospital services and economics, so it requires a reliable and accurate prediction model with the aim of minimizing the occurrence of shortages and excess stock, In this paper, we propose the GAN architecture to estimate the amount of drug sales in the next one week by using the drug usage data for the last four years (2015-2018) for training, while testing using data running in 2019 year , the classification results will be evaluated by Actual data uses indicators of Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). From the results of the experiment, seen from the value of MAE, RMSE and MAPE, the proposed model has promising performance, but it still needs to be developed to explore ways to extract factors that are more valuable and influential in the trend disease progression, thus helping in the selection of optimal drugs

Deep Neural Networks Approach for Monitoring Vehicles on the Highway Husein, Amir Mahmud; Christopher, Christopher; Gracia, Andy; Brandlee, Rio; Hasibuan, Muhammad Haris
Sinkron : Jurnal dan Penelitian Teknik Informatika Vol 4 No 2 (2020): SinkrOn Volume 4 Number 2, April 2020
Publisher : Politeknik Ganesha Medan

Vehicle classification and detection aims to extract certain types of vehicle information from images or videos containing vehicles and is one of the important things in a smart transportation system. However, due to the different size of the vehicle, it became a challenge that directly and interested many researchers . In this paper, we compare YOLOv3's one-stage detection method with MobileNet-SSD for direct vehicle detection on a highway vehicle video dataset specifically recorded using two cellular devices on highway activities in Medan City, producing 42 videos, both methods evaluated based on Mean Average Precision (mAP) where YOLOv3 produces better accuracy of 81.9% compared to MobileNet-SSD at 67.9%, but the size of the resulting video file detection is greater. Mobilenet-SSD performs faster with smaller video output sizes, but it is difficult to detect small objects.

Application for Employee Performance Assessment Using Profile Matching Method Aisyah, Siti; Purba, Windania; Harahap, Mawaddah; Husein, Amir Mahmud
Sinkron : jurnal dan penelitian teknik informatika Vol. 4 No. 1 (2019): SinkrOn Volume 4 Number 1, October 2019
Publisher : Politeknik Ganesha Medan

Human resources an important role for the agency. Good employee performance can provide a good image for the company. Many companies give rewards or rewards to their employees for their work performance. The assessment is done in addition to giving or appreciation as well as motivation for employees to work better. Problems that often occur in the employee appraisal process are the large number of employees and the criteria assessed and data processing are still in conventional process so that takes a long time and the results of the assessment are still not objective. To overcome, application was built could simplify the employee performance appraisal process. The method used is Profile Matching to assess and determine employees who excel. Factors or criteria used in the form of performance, discipline, honesty, years of service, cooperation. Profile matching is broadly the process of comparing the actual data value of a profile to be assessed with the expected profile value. Application is built based on web with PHP programming and MYSQL. To help the process of employee performance appraisal at Universitas Prima Indonesia. Collecting data in research using literature studies, observations, interviews, and sampling. Result the research is Profile Matching Method can be use for Decision Support System in determining employee achievement, with the highest calculation results in the sample data obtained by A3 and the lowest position obtained by A1. In academic, research can be an enrichment of teaching materials especially in subject of Decision Support Systems and information systems in general.

Co-Authors Ambarwati, Lita Andika Andika Andika Rahmad Kolose Sumangunsong Andreas Simatupang Anugrah Putri, Gustie Vaniest Astasachindra, Rishi Banjarnahor, Prayoga Br Sihotang, Nurseve Lina Brandlee, Rio Christopher Christopher Damanik, Melky Eka Putra Dashuah, Ramonda Daulay, Tri Agustina Dodi Setiawan Fauza, Ra'uf Harris Feri Imanuel Fernandito, Peter Ginting, Deskianta Gracia, Andy Gulo, Befi Juniman Gulo, Steven Eduard Gultom, Atap Gunawan, Nico Hasibuan, Muhammad Haris Hendiko, Kennyzio HS, Christnatalis Hutauruk, Eben Kevin kevin Kevry Kosasi, Tommy Kwok, Shane Christian Larosa, Tri Putra Laurentius, Laurentius Leonardi, Jocelyn Linardy, Alvin Livando, Nicholas Lovely, Veryl Lubis, Fachrul Rozi Manik, David Hamonangan D. Mawaddah Harahap, Mawaddah Muhammad Arsyal, Muhammad Muhammad Khoiruddin Harahap Nainggolan, Yandi Tumbur Noflianhar Lubis, Kevi Ong, Derrick Kenji Phan, Gary Pratama, Panji Dika PUJI LESTARI Purba, Windania Purwanto, Eko Paskah Jeremia Salim Sidabutar, Daniel Shela Aura Yasmin Sihombing, Zein Adian Laban Silitonga, Benny Art Simanggungsong, Antonius Moses Simanjuntak, Andre Juan Simarmata, Allwin M Simarmata, Harry Binur Pratama Sinaga, Candra Julius Sinaga, Sutrisno Sinurat, Watas Sipahutar, Berninto Sirait, Agrifa Darwanto Siringo-Ringo, Dewi Sahputri Siti Aisyah Situmorang, Priskila Natalia C. Sormin, Pedro Samuel Syahputa, Hendra Tambun, Bella Siska Tambunan, Razana Baringin Daud Tampubolon, Hotman Parsaoran Tampubolon, Mei Monica Telaumbanua, Agustritus Pasrah Hati Tommy, Tommy Waren, Ashwini Waruwu, Seven Kriston William Chandra Willim, Alfredy Wizley, Vincent Yuanda, Yansan Yulizar, Dian Zagoto, Mariana Erfan Kristiani

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