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Sistem Pendeteksian Manusia untuk Keamanan Ruangan menggunakan Viola – Jones Sianturi, Jonatan; Rahmat, Romi Fadillah; Nababan, Erna Budhiarti
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 1, No 2 (2018): Edisi Januari
Publisher : Universitas Medan Area

Aspek keamanan sangat dibutuhkan dalam berbagai kehidupan saat ini seperti keamanan rumah, gedung, atau ruangan yang memiliki nilai penting bagi pemilik. Keamanan dapat dikerjakan oleh tenaga manusia tetapi cara ini kurang efisien karena menghabiskan banyak resources seperti uang, waktu, tenaga dan juga sangat rentan terhadap kelalaian manusia (human error). Oleh karena itu diperlukan suatu pendetekatan untuk dapat melakukan keamanan tersebut.Salah satu pendekatan yang dapat dilakukan adalah dengan melakukan pendeteksian objek manusia melalui kamera yang terhubung dengan komputer.Dalam penelitian ini digunakan Viola-Jones untuk mendeteksi objek manusia dalam citra berdasarkan fitur. Citra yang diinput dari webcam dengan fungsi capture dalam library OpenCV diubah menjadi citra abu-abu setelah mengalami proses scaling, dilanjutkan ekualisasi histogram, perhitungan fitur dengan citra integral, dan pendeteksian objek dengan cascade of classifier. Pada penelitian ini ditunjukkan bahwa metode yang diajukan mampu melakukan pendeteksian objek dengan hasil akurasi mencapai 86,88% . Kata Kunci : viola-jones, pendeteksian manusia, keamanan ruangan, cascade of classifier, opencv.

Financial management efficiency of islamic boarding school based on information technology Arisandi, Dedy; Romi Fadillah Rahmat; Seniman; Sawaluddin
ABDIMAS TALENTA: Jurnal Pengabdian Kepada Masyarakat Vol. 6 No. 1 (2021): ABDIMAS TALENTA : Jurnal Pengabdian Kepada Masyarakat
Publisher : Talenta Publisher

Utilization of information technology is a very important requirement for every component of society. Easy, fast and accurate data and information access can optimize routine daily work. Mawaridussalam Islamic boarding school Batang Kuis as an Islamic education institution that plays a role in shaping the character and personality of the next generation of the nation is expected to be able to optimally manage finances and provide good service to the academics of the Islamic boarding school. Until now, financial management is still done manually using bookkeeping, there is no specific financial application used in Islamic boarding school financial management, so it is difficult and slow in recording, processing, controlling and reporting financial activities. Based on these problems, an application is needed that can be used by the treasurer and board of boarding school leaders for financial management systematically. The method applied is the User Centered Design approach and the target that was successfully achieved is the availability of web-based financial management applications that are used properly to increase the efficiency and effectiveness of financial management in Islamic boarding schools.

Information technology based smart farming model development in agriculture land Al-Khowarizmi Al-Khowarizmi; Arif Ridho Lubis; Muharman Lubis; Romi Fadillah Rahmat
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i2.pp564-571

Smart farming in various worlds is not just about applying technology in terms of storing data on agricultural land. However, having a concept of measurable data based on available computational techniques trained and then generating knowledge. As an application, the agri drone sprayer can be used for the process of applying pesticides and liquid fertilizers on each side. In addition, drone surveillance is also useful in implementing smart farming such as mapping land so that farmers will know the condition of their agricultural land. However, the soil and weather sensor will also help the farmers to monitor the farmland as well. Devices with sensors can only obtain data in the form of air and soil humidity, temperature, soil pH, water content and forecasting the harvest period. So that the smart farming model can help farmers to get recommendations, in preventing the predicted damage to their land and crops. However, according to its geographical location, the application of smart farming can be a smart solution to agricultural problems in Indonesia and make the future of Indonesian Agriculture a technology-based smart agriculture.

Advertisement billboard detection and geotagging system with inductive transfer learning in deep convolutional neural network Romi Fadillah Rahmat; Dennis Dennis; Opim Salim Sitompul; Sarah Purnamawati; Rahmat Budiarto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 5: October 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i5.11276

In this paper, we propose an approach to detect and geotag advertisement billboard in real-time condition. Our approach is using AlexNet’s Deep Convolutional Neural Network (DCNN) as a pre-trained neural network with 1000 categories for image classification. To improve the performance of the pre-trained neural network, we retrain the network by adding more advertisement billboard images using inductive transfer learning approach. Then, we fine-tuned the output layer into advertisement billboard related categories. Furthermore, the detected advertisement billboard images will be geotagged by inserting Exif metadata into the image file. Experimental results show that the approach achieves 92.7% training accuracy for advertisement billboard detection, while for overall testing results it will give 71,86% testing accuracy.

File Reconstruction in Digital Forensic Opim Salim Sitompul; Andrew Handoko; Romi Fadillah Rahmat
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 2: April 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i2.8230

File recovery is one of the stages in computer forensic investigative process to identify an acquired file to be used as digital evident. The recovery is performed on files that have been deleted from a file system. However, in order to recover a deleted file, some considerations should be taken. A deleted file is potentially modified from its original condition because another file might either partly or entirely overriding the file content. A typical approach in recovering deleted file is to apply Boyer-Moore algorithm that has rather high time complexity in terms of string searching. Therefore, a better string matching approach for recovering deleted file is required. We propose Aho-Corasick parsing technique to read file attributes from the master file table (MFT) in order to examine the file condition. If the file was deleted, then the parser search the file content in order to reconstruct the file. Experiments were conducted using several file modifications, such as 0% (unmodified), 18.98%, 32.21% and 9.77%. From the experimental results we found that the file reconstruction process on the file system was performed successfully. The average successful rate for the file recovery from four experiments on each modification was 87.50% and for the string matching process average time on searching file names was 0.32 second.

Sistem Pendeteksian Manusia untuk Keamanan Ruangan menggunakan Viola – Jones Jonatan Sianturi; Romi Fadillah Rahmat; Erna Budhiarti Nababan
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol 1, No 2 (2018): Edisi Januari
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v1i2.1424

Aspek keamanan sangat dibutuhkan dalam berbagai kehidupan saat ini seperti keamanan rumah, gedung, atau ruangan yang memiliki nilai penting bagi pemilik. Keamanan dapat dikerjakan oleh tenaga manusia tetapi cara ini kurang efisien karena menghabiskan banyak resources seperti uang, waktu, tenaga dan juga sangat rentan terhadap kelalaian manusia (human error). Oleh karena itu diperlukan suatu pendetekatan untuk dapat melakukan keamanan tersebut.Salah satu pendekatan yang dapat dilakukan adalah dengan melakukan pendeteksian objek manusia melalui kamera yang terhubung dengan komputer.Dalam penelitian ini digunakan Viola-Jones untuk mendeteksi objek manusia dalam citra berdasarkan fitur. Citra yang diinput dari webcam dengan fungsi capture dalam library OpenCV diubah menjadi citra abu-abu setelah mengalami proses scaling, dilanjutkan ekualisasi histogram, perhitungan fitur dengan citra integral, dan pendeteksian objek dengan cascade of classifier. Pada penelitian ini ditunjukkan bahwa metode yang diajukan mampu melakukan pendeteksian objek dengan hasil akurasi mencapai 86,88% . Kata Kunci : viola-jones, pendeteksian manusia, keamanan ruangan, cascade of classifier, opencv.

Acute Coronary Syndrome Disorders Classification Based On ECG Images Using Adaptive Neuro-Fuzzy Inference System (ANFIS) Sharfina Faza; Meryatul Husna; Janferson Panggabean; Romi Fadillah Rahmat; Dani Gunawan
Indonesian Journal of Education, Social Sciences and Research (IJESSR) Vol 2, No 1 (2021)
Publisher : Indonesian Journal of Education, Social Sciences and Research (IJESSR)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/ijessr.v2i2.7148

The heart is one of the most vital human organs that acts as a blood-pumping tool to supply oxygen and essential nutrients throughout the human body. Abnormalities in the heart greatly affect the work of the heart which results in the heart not being able to carry out its duties properly. Heart defect is one of the most common causes of death in many countries, including Indonesia. Electrocardiogram (ECG) is one of the most important examination models used to diagnose various abnormal heart rhythms. An ECG records the electrical activity of the heart by showing waveforms on a monitor or printing them on paper to classify cardiac abnormalities from the electrocardiogram image using image processing and artificial neural networks. The method used for the classification is the Adaptive Neuro-Fuzzy Inference System (ANFIS) and using the Chain code to take the value of the ECG feature. There were 92 ECG images to be used which were partitioned to 70 images for training data 22 images for test data with 3 types of abnormalities, namely coronary heart disease, angina, and myocardial infarction. The test was carried out using 4 choices of ANFIS functions. The parameters used to classify coronary heart disease, angina pectoris, and myocardial infarction reached 95.23% (DR), and 29.41% (DER), using the GBell function with the number of MFs (3) and epoch (100).

Astrocytoma, ependymoma, and oligodendroglioma classification with deep convolutional neural network Romi Fadillah Rahmat; Mhd Faris Pratama; Sarah Purnamawati; Sharfina Faza; Arif Ridho Lubis; Al-Khowarizmi Al-Khowarizmi; Muharman Lubis
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 11, No 4: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v11.i4.pp%p

Glioma as one of the most common types of brain tumor in the world has three different classes based on its cell types. They are astrocytoma, ependymoma, oligodendroglioma, each has different characteristics depending on the location and malignance level. Radiological examination by medical personnel is still carried out manually using magnetic resonance imaging (MRI) medical imaging. Brain structure, size, and various forms of tumors increase the level of difficulty in classifying gliomas. It is advisable to apply a method that can conduct gliomas classification through medical images. The proposed methods were proposed for this study using deep convolutional neural network (DCNN) for classification with k-means segmentation and contrast enhancement. The results show the effectiveness of the proposed methods with an accuracy of 95.5%.

Android-based automatic detection and measurement system of highway billboard for tax calculation in indonesia Romi Fadillah Rahmat; Sarah Purnamawati; Handra Saito; Muhammad Fariz Ichwan; Tri Murti Lubis
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 2: May 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i2.pp877-886

Billboards are objects, tools or actions, which based on the characteristics serve its own purpose to earn profits, advertise certain people or service, and to draw public’s attention by placing it in a very strategic place. It has led the government to charge tax on billboards based on its location, dimensions, and viewpoints. Therefore, authorized parties have to be able to ensure the data authenticity of the proposed billboards. One of the obstacles in data verification is the time of billboards measurement process due to its size and height from the ground, based on this problem, and we developed a system which can measure the dimensions of billboards without physically touching it by implementing image processing methods to identify the billboards. The implementation is by measuring the dimensions of the billboards using perspective concept, then calculates the distance between the camera and the object using two-point distance calculation GPS coordinates. The results showed that the distance calculation using the GPS method generated inaccurate values, whereas the systematic distance method generated a result of errors’ range from 0.5 to 25 cm if the image acquisition is performed nearly perpendicular to the object.

Vacant parking space identification using probabilistic neural network Romi Fadillah Rahmat; Sarah Purnamawati; Joko Kurnianto; Sharfina Faza; Muhammad Fermi Pasha
Indonesian Journal of Electrical Engineering and Computer Science Vol 14, No 2: May 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v14.i2.pp887-894

The need for public parking space is increasing nowadays due to the high number of cars available. Users of car parking services, in general, are still looking for vacant parking locations to park their vehicle manually. With the current technological developments, especially in image processing field, it is expected to solve the parking space problem. Therefore, this research implements image processing to determine the location of vacant parking space or occupied ones that run in real-time. In this study, the proposed method is divided into five stages. The first stage is image acquisition to capture the image of parking location. Then it continues to pre-processing stage which consists of the process of saturation, grayscale and thresholding. The third stage is image segmentation to cut the image into five parts. The next stage is feature extraction using invariant moment, and the last stage would be identification process to determine the location of vacant parking spaces or occupied ones. The results of this research using 100 test images generates an accuracy, recall, and precision of 94%.

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