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All Journal International Journal of Electrical and Computer Engineering International Journal of Power Electronics and Drive Systems (IJPEDS) IAES International Journal of Artificial Intelligence (IJ-AI) MEDIA ELEKTRIKA Elkom: Jurnal Elektronika dan Komputer Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik PROSIDING CSGTEIS 2013 Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Journal of Telematics and Informatics Setrum : Sistem Kendali-Tenaga-elektronika-telekomunikasi-komputer JUITA : Jurnal Informatika Majalah Ilmiah MOMENTUM JURNAL NASIONAL TEKNIK ELEKTRO Proceeding of the Electrical Engineering Computer Science and Informatics TRANSISTOR Elektro dan Informatika E-Dimas: Jurnal Pengabdian kepada Masyarakat Journal of Electrical Technology UMY RADIAL: JuRnal PerADaban SaIns RekAyasan dan TeknoLogi Aviation Electronics, Information Technology, Telecommunications, Electricals, Controls (AVITEC) Jurnal Rekayasa elektrika International Journal of Information Engineering and Science International Journal of Electrical Engineering, Mathematics and Computer Science International Journal of Mechanical, Electrical and Civil Engineering Green Engineering: Journal of Engineering and Applied Science RADIAL: Jurnal Peradaban Sains, Rekayasa dan Teknologi
Sri Arttini Dwi Prasetyawati
Universitas Islam Sulta Agung
Aerospace Engineering Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Environmental Science Library & Information Science Mathematics Mechanical Engineering Social Sciences

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Journal : Journal of Telematics and Informatics

 1 
Cosine Similarity Measurement for Indonesian Publication Recommender System Darso D; Imam Much Ibnu Subroto; Prasetyowati Sri Arttini Dwi
Journal of Telematics and Informatics Vol 5, No 2: September 2017
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (604.037 KB) | DOI: 10.12928/jti.v5i2.

Abstract

So many publications are increasing every year and it causes an overflow of data and it makes the information function on the site cannot be delivered entirely to the visitors. As a scientific publication site, the IPI garuda portal (Index of Indonesian publications) has more than 4000 Indonesian journals in the database. Therefore it will be designed a system that can provide information and knowledge for the user. The system can also provide recommendations related articles and relevant for users. Recommendations are made by calculating similarities between related documents. The similarity calculation method used in this research was cosine similarity. The steps taken were pre-processed, weight calculation, vector length and then they were calculated using cosine similarity so that the value would be achieved that ranged from 0 to 1. Performance testing of recommendation system used precision and recall. Performance system with average precision value about 0.664 meant that the document had good system accuracy, and then the average recall point with value about 0.962 meant that documents were successfully returned by the system.
Forward and Inverse Kinematic on Wheeled Soccer Robot La Ode Muhamad Idris; Sri Arttini Dwi Prasetyowati; Imam Much Ibnu Subroto
Journal of Telematics and Informatics Vol 6, No 4: December 2018
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jti.v6i4.

Abstract

In this research rotary encoder sensor and gyroscope sensor are used as main sensor for moving wheeled soccer robot. Rotary encoder is used to measure the speed and distance of each robot wheel and the gyroscope is used to measure the orientation of the robot, then both of them expressed in cartesian diagrams (x, y, θ). A rotary encoder type magnetic incremental encoder is used in this research and it mounted on each wheel. Inverse kinematic and forward kinematic are used to control the movement of the robot when positioning in the field or making decision when kicking the ball towards the opponent’s side and the other decision. From the test results, robot can move to any direction from the starting position to the end position with a different robot orientation and robot can measure the coordinates of the robot with average error of x = 5.37%, y = 5.2%, and Theta = 0.26%. The robot is also able to move in the direction of the coordinates given with a traveling time of 3-4 seconds.
Analysis of Bone Fracture Detection Based on Harris Corner Detector Method Bahrun Niam; Imam Much Ibnu Subroto; Sri Arttini Dwi Prasetyowati
Journal of Telematics and Informatics Vol 6, No 2: June 2018
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jti.v6i1.

Abstract

Bone is part of the human body to sustain other parts of the body. One of the bones is leg bone. Leg bones have often cracks or fractures caused by collision. Leg bone fractures can be identified by using x-ray manually. Eye train can cause less accurate in identifying the result of roentgen so that it needs a method to make radiologist easier in determining leg bone fractures. The recommended method in this research was Harris corner detector method. Before identified, the object was firstly in pre-processing such collecting data, grayscale and cropping image. The research result was Harris corner detector method could identify leg bone fractures with 70% accuracy. Bone is part of the human body to sustain other parts of the body. One of the bones is leg bone. Leg bones have often cracks or fractures caused by collision. Leg bone fractures can be identified by using x-ray manually. Eye train can cause less accurate in identifying the result of roentgen so that it needs a method to make radiologist easier in determining leg bone fractures. The recommended method in this research was Harris corner detector method. Before identified, the object was firstly in pre-processing such collecting data, grayscale and cropping image. The research result was Harris corner detector method could identify leg bone fractures with 70% accuracy.
EMG Signal Recognition of Gait Pattern Using Back Propagation Neural Network for Stroke Disease Rehabilitation Diah Arie WK; Sri Arttini Dwi Prasetyowati; Arief Marwanto
Journal of Telematics and Informatics Vol 6, No 2: June 2018
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jti.v6i2.

Abstract

Electromyography (EMG) is the electrical activity obtained from muscles activity. Gait pattern of leg muscles will be measured and recognized by EMG signals. The EMG signal on the leg muscles is measured by six electrodes which are filtered with 0.33Hz high pass filter (HPF) and a low pass filter (LPF) for anti aliasing. Maximum frequency of EMG is 600 Hz, that sampled perfectly by Analog to Digital Converter (ADC) using 2 KHz. Artificial Neural Networks (ANN) algorithm is applied to obtain the accuracy and optimization of EMG signal. The performance of the results are investigates based on two type of human condition, first is healthy person and second is severe person. The combination of EMG measurements with ANN has gives better results compares than without an ANN model. The results showed that the measurement for healthy individuals during normal walking conditions was 4.56 volts with a frequency of 0,00582Hz; the measurement of stroke patients which walking at normal speed is 8.80 volts and the frequency is 1,231Hz. Therefore, proposed prototype that combined using ANN algorithm has increased capability of  measurement of EMG signal for normal and severe humans models. Keywords : EMG, ANN, Gait
Optimizing Group Discussion Generation Using K-Means Clustering And Fair Distribution Alfano Endra Wardhana; Imam Much Ibnu Subroto; Sri Arttini Dwi Prasetyowati
Journal of Telematics and Informatics Vol 6, No 2: June 2018
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jti.v6i2.

Abstract

The development of computer-based learning system today can provide a different learning process in a teaching and learning process, but the problems faced by a teacher is the difficulty in grouping discussion group that has a different value of knowledge and skills, because usually this selection of discussion groups in e-learning is done based on the wishes of each student or randomly regardless of the data of knowledge and skills. This research was conducted with the aim of grouping the discussion groups based on the indicators of knowledge and skill by using k-means clustering analysis at SMK Sore Tulungagung. The knowledge and skills scores of class X students in Pekerjaan Dasar Elektromekanik subjects, The Competence of Electricity Installation Engineering will be used as the basic scores. Then, the students of class X were divided into 2 groups, namely the k-means based group and the random based group for further research. The mean score of knowledge and skills are before the learning process and after the results of the evaluation of the discussion group on the k-means based and the random based group. The k-means based class score increases 4,083 from the average. Before the learning, it was 83.292 and it becomes 87.375 after the evaluation, while the random based class only experienced an increase 0,083 from the average. Before the learning it was 81,250 and it becomes 81,333 after the learning evaluation. Based on the result, grouping the discussion group in a fair way in e-learning on the indicators of knowledge and skills using k-means clustering method shows more visible improvement, so k-means clustering is a more optimal method.
THE PREDICTION OF NATIONAL EXAM SCORES OF JUNIOR HIGH SCHOOL STUDENTS USING K-NEAREST NEIGHBOR (k-NN) ALGORITHM Pranoto Wibowo; Sri Arttini Dwi Prasetyowati; Imam Much Ibnu Subroto
Journal of Telematics and Informatics Vol 7, No 1: MARCH 2019
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jti.v7i1.

Abstract

The prediction of the acquisition of national exam scores for Junior High School (JHS) students is intended to know the results of the student’s national exam early when students take the national examination. Knowledge gained from the results of this prediction will be important information for the school to take appropriate steps so that the acquisition of student national exam scores can be improved even better. The acquisition of student national  exam scores is low and there is no prediction model that is used to predict the achievement of student national exam scores is a problem that needs to be addressed. This paper propose a predicting student’s national exam scores for four national exam subjects (INDONESIAN, ENGLISH, MATHEMATICS and SCIENCE) using K-Nearest Neighbor (k-NN) as a prediction method and compare it with Decission Tree method. The results of the study showed that the prediction k-NN model had better performance than the prediction model of Decission Tree. Performance results obtained by evaluating using derivatives of the confussion matrix terminology to determine the value of accuracy, sensitivity (recall), and precission each subjects. To measure the performance of predictive methods used the value of accuracy in each method and each subject. The greater the accuracy value ( max 1 ), then the better performance of the prediction model used. Performance of k-NN in average accuracy=0.85, precision=0.87, recall=0.91 is better than Decission Tree method performance with accuracy=0.82, precision=0.85, and recall=0.89.  
HUMAN WEIGHT MEASUREMENT PREDICTION WITH VISUAL IMAGES WITH ARTIFICIAL NEURAL NETWORK ALGORITHM Abdul Basit; Imam Much Ibnu Subroto; Sri Arttini Dwi Prasetyowati
Journal of Telematics and Informatics Vol 8, No 1 (2020)
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jti.v8i1.

Abstract

Measuring instrument becomes very important to be able to know how much human weight is. Weight information is generally obtained from measurements by body scale. One of other methods to find out a person's weight is by image processing. This study aims to calculate body weight by image processing with the Artificial Neural Network algorithm using back propagation method to detect body weight. The results of testing, analysis, and system accuracy of 97% indicate that the method of calculating body weight is very possible through image processing with various provisions and restrictions.   Key words: Weight, Computer Vision, Artificial Neural Network
IMAGE PROCESSING FOR PERCENTAGE ANALYSIS OF VESSELS FOR VESSELS IN CORONARY HEART DISEASE PATIENTS Agung Satrio Nugroho; Sri Arttini Dwi Prasetyowati; Arief Marwanto
Journal of Telematics and Informatics Vol 8, No 2 (2020)
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jti.v8i2.

Abstract

Cardiovascular disease is the highest cause of death worldwide, for this reason early detection is important to reduce mortality due to heart disease and blood vessels, so that a program is needed to calculate the narrowing that occurs in blood vessels experienced in patients affected by coronary heart disease, so can make it easier for a doctor to analyze and give a medical decision whether to do the ring installation or just administering drugs for blood thinning. This research uses the development of image processing technology from angiographic results by utilizing cropping to determine the area to be analyzed and image segmentation, where image segmentation is in the form of a denoise as a mean filter and increases the transmission of the image to be analyzed and thresholding which is a way of emphasizing the image by changing the image to black and white. Where the narrowing area is obtained from counting the number of logical pixels 1 of the image area that has been blocked and has been reconstructed while the normal area is calculated from the number of pixels having logic 1 plus the pixel area having logic 1, logic pixel 0 is an area of the vessel that is not narrowed. The results showed that the narrowing of the vessels in patients experienced by patients affected by coronary heart can be measured how narrowing is experienced. Of the 11 patient data measured, there were 4 patient data that were compared with the measurement results of the angiography instrument with the highest obtained error value of 3.9% and the lowest error value of 0.1% with an average value of error 1.8% where the error value is still within the tolerance value. Keywords: image processing, vessels for vessels, coronary heart disease
Co-Authors ., Gunawan Abdul Basit Achmad Sulchan Adhi Susanto Adhi Susanto Agung Satrio Nugroho Agus Adhi Nugroho Agus Adhi Nugroho Akhmad Syakhroni Alfano Endra Wardhana Ari Wibowo Arief Marwanto Aries Budiyono Ary Sulistyo Utomo Aulia, Muhammad Rifky Badieah Assegaf Bahrun Niam Bhakti Yudho Suprapto Bima Sekti Wibawanto Budiyono, Aries Bustanul Arifin Bustanul Arifin BUSTANUL ARIFIN Darso D Deris Stiawan Diah Arie WK Eka Nuryanto Budi Susila Erwanto, Danang Fajar Yumono Floris Boogaard Gunawan . Hapsari, Jenny Putri Ida Widihastuti Ilham M Rusdiyanto Imam Much Ibnu Subroto Imam Rachmat Widodo Indra Ava Dianta Iqbal Sobri Bagasghani Ismail, Munaf Jati, Budi Pramono Jenny Putri Hapsari La Ode Muhamad Idris Luh Putu Ratna Sundari Luqman Assaffat Mohammad Ilham Adi Saputra Muhamad Haddin Muhammad Kevin Hardiansyah Muhammad Khoirun Faza Muhammad Khosyi'in Muhammad Khosyi’in Muhammad Rifky Aulia Munaf Ismail Munaf Ismail Munawar A Riyadi Pranoto Wibowo Raditya Rahmat Wijaya Rieska Ernawati Riyadi, Munawar A Sauqie Fairoozy Firdaus Slamet Imam Wahyudi Sobri Bagasghani, Iqbal Suhartono Suhartono Suryani Alifah Syakhroni, Akhmad Tole Sutikno Widihastuti, Ida Zainuddin Nawawi