Article Per Year (5 Year)
p-Index From 2021 - 2026
6.398
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Advances in Applied Sciences Transmisi: Jurnal Ilmiah Teknik Elektro TELKOMNIKA (Telecommunication Computing Electronics and Control) Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Journal of Telematics and Informatics Proceeding of the Electrical Engineering Computer Science and Informatics TRANSISTOR Elektro dan Informatika Jurnal Manajemen Keuangan Publik AKSIOLOGIYA : Jurnal Pengabdian Kepada Masyarakat Jurnal Kesehatan Global PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Indonesian Journal of Electrical Engineering and Computer Science Jurnal Bumigora Information Technology (BITe) Pengmasku Prosiding Seminar Riset Mahasiswa Jurnal Nusantara Mengabdi Jurnal Rekayasa Sistem Informasi dan Teknologi Jurnal Bakti Masyarakat Manajemen
Imam Much Ibnu Subroto
Department Of Informatics, Universitas Islam Sultan Agung
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Physics Public Health Social Sciences Other

Published : 96 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 96 Documents
Search

 2   3   4   5   6 
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.
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.  
Automatic Irrigation System Based on Fuzzy Logic Qirom Qirom; Arief Marwanto; Imam Much Ibnu Subroto
Journal of Telematics and Informatics Vol 7, No 2: JUNE 2019
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jti.v7i2.

Abstract

Rice plant which is a source of food for the people, it needs enough temperature, air humidity and high water for maximum growth. The irrigation system is a major requirement in the field of agriculture, especially for rice plant. Some constraints in conventional irrigation, so they need irrigation system automatically. Some previous studies about automatic irrigation were only used one or two parameters and only used fuzzy or IoT. The method offered in this study uses fuzzy logic using 3 inputs and combines the monitoring system in real time based on IoT. The purpose of this study is to determine the effectiveness of fuzzy logic using three inputs to control the automatic irrigation system byreal time monitoring usingIoT. Data obtained by testing in themorning, afternoon, evening, night and using heat and rain treatment then compared using Matlab calculation. From the tool testing, the average precision of the tool comparison using the calculation is 77.13%.
SIMBOX Identification Using K-Nearest Neighbor Based On Spectrum Analyzer Agung Suryowibowo; Imam Much Ibnu Subroto; Eka Nuryanto Budi Susila
Journal of Telematics and Informatics Vol 7, No 3: SEPTEMBER 2019
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jti.v7i3.

Abstract

Telecommunication Service Provider should deal with illegal players (grey operators) who do not have permission to conduct international voice service. These illegal players perform their activities by passing international incoming traffic using Simbox devices. To identify visual simbox usage is very difficult and less reliable, therefore by using spectrum analyzer and K-Nearest Neighbor (K-NN) method is one way to identify simbox usage. The attributes used in the identification process are Location / Document, Strong Frequency Signal, and by applying K-NN algorithm based on proximity of training data with data testing. The determination of this attribute is based on GSM DCS 1800 MHz uplink frequency measurement in Cilacap and Banyumas area. The identification process was conducted on six frequencies points on 18 data with the largest signal strength as training data. Moreover, the signal strength data testing  by using 32 data gives result 81.25% accuracy. The results of K-NN algorithm calculations can be implemented to identify the use of simbox, hence it can be used as a reference for mobile operators to identify simbox usage in other areas.Telecommunication Service Provider should deal with illegal players (grey operators) who do not have permission to conduct international voice service. These illegal players perform their activities by passing international incoming traffic using Simbox devices. To identify visual simbox usage is very difficult and less reliable, therefore by using spectrum analyzer and K-Nearest Neighbor (K-NN) method is one way to identify simbox usage. The attributes used in the identification process are Location / Document, Strong Frequency Signal, and by applying K-NN algorithm based on proximity of training data with data testing. The determination of this attribute is based on GSM DCS 1800 MHz uplink frequency measurement in Cilacap and Banyumas area. The identification process was conducted on six frequencies points on 18 data with the largest signal strength as training data. Moreover, the signal strength data testing  by using 32 data gives result 81.25% accuracy. The results of K-NN algorithm calculations can be implemented to identify the use of simbox, hence it can be used as a reference for mobile operators to identify simbox usage in other areas.
Classification of Muslim Woman Student Using Artificial neural network Ulil Albab; Imam Much Ibnu Subroto; Muhammad Haddin
Journal of Telematics and Informatics Vol 7, No 3: SEPTEMBER 2019
Publisher : Universitas Islam Sultan Agung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/jti.v7i3.

Abstract

Hijab is a female genital covering commonly used by adult women. The number of hijab wearing fashion modes is developing, this makes one of the factors lack of understanding about using the correct hijab. By utilizing image processing using classification techniques can be distinguished between veiled women and not veiled. Artificial Neural Network (ANN) is an artificial intelligence that presents like a human brain by means of learning. ANN can be embedded into a computer program for the calculation process. One of the uses of ANN is to process the image to be classified. Image processing stages are data acquisition, preprocessing, edge detection, training, testing and classification. Based on the tests that have been carried out as many as 20 experiments, the results of image classification using Artificial Neural Network algorithm and backpropagation learning methods show a good level of accuracy.
A Prediction Method Of Rice Harvesting Using Artificial Neural Network Fitri Anindyahadi; Imam Much Ibnu Subroto; Arief Marwanto
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

Crops rice is a thing he could never expected for sure, but could have predicted data in of existing. The availability of data about the outcome of rice harvesting is very substantial for use as yardstick in estimate and predicts crops rice as a gesture to fix the next planting. Artificial neural network method backpropagation often used to settle trouble complex relating to identification, predictions, pattern recognition and so on. In this study, backpropagation processing the data affecting rice crops from 2014 until 2016 to predict crop Pengkok, Kedawung, Sragen the future. After through process of training and testing and experiment some pattern architecture network, in the network get architecture best in a prediction.
HAPPINESS ANALYSIS OF LIBYANS PEOPLE BASED ON TWITTER DATA USING ARTIFICAL NEURAL NETWORK khaled jemah basher; Imam Much Ibnu Subroto; Arief Marwanto; Muhammad Qomaruddin
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.v8i4.

Abstract

Information technology is always developing and has very rapid growth. The internet has become a very important online communication tool for many people today. Nowadays people tend to prefer anything that is practical, faster, and flexible. Social networking services have become a simple and universal concept in the internet environment. Purpose of this study are: To analyse happiness of Libyans people based on Twitter data using artificial neural network. This study is an analytical study of secondary data processing obtained without direct field experiments. MTE (Magister program of Electrical Engineering) UNISSULA must have experiment. This study is an analytical study of data based on social media specifically using twitter data. The result of this study is Libyan feel they write down their feelings when happy rather than unhappy. Social media has become an important part of modern life, and Twitter is again a center of focus in recent events. Whatever your opinion of social media these days, there is no denying it is now an integral part of our digital life. Twitter is a good starting point for social media analysis because people openly share their opinions to general public. This is very different from Facebook where social interactions are often private. In this paper, we propose a ANN model for Twitter opinion mining prediction and classification approach. Also, we used the ANN model for Twitter Opinion abstraction and visualization scheme. The main contribution of this work is to propose such a new visualization model for Twitter mood prediction based on ANN  approach
A STEGANOGRAPHY LEAST SIGNIFICATION BITS (LSB) TECHNIQUE FOR HIDE TEXT DATA ENCRYPTION WITHIN IMAGE Riyadh Alnajih Alsayih; Muhamad Qomaruddin; Imam Much Ibnu Subroto; Suryani Alifah
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.v8i4.

Abstract

With the development of means of communication and the exchange of information over the Internet, and with the development of hacking operations, intruders became able to view, and change information, so the need to find means to preserve privacy and information exchange arose. Cryptography and steganography had a prominent role in this field Encryption distorts the message and steganography hides the message's presence. In this paper, the proposed system uses both steganography and cryptography to provide a double layer of security. In cryptography, we use both a substitution and RSA algorithm to encrypt the message. In steganography, we used LSB technology with a stego key to embed data in the image, all of this to improve data security. A scale of Mean Square Error (MSE) and a scale of peak signal-to-noise ratio (PSNR) assessed system performance. The results showed that the image quality is good, and it is difficult to notice any difference between it and the original image. The results of both MSE and PSNR were good, as the PSNR value was more than 56.
Forming Heterogeneous Group in Cooperative Learning Process using Partitioning Around Medoids (PAM) and Equitable Distribution Imam Much Ibnu Subrotto; Badieah Badieah; Wardianto Eko Saputra
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 4: EECSI 2017
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (304.391 KB) | DOI: 10.11591/eecsi.v4.1097

Abstract

Selection of methods will greatly impact in learning process. One of the methods commonly applied are Cooperative learning. Cooperative learning is one of many learning techniques to improve the performance of students in the academic literature. Moreover, the heterogeneity in study group’s academics can improve performance, but only partially implementing cooperative learning in a group of heterogeneous formations. The problem faced in this type is the process of forming group of students into a heterogeneous group and inter-group quality is relatively equal or balanced. In this study, the authors aimed to provide intelligent solutions in the distribution group based on the value (The value of achievement on related subjects) and personality traits of each student in the determination of the performance of students are using the algorithm clustering Partitioning Around Medoids (PAM) in consideration of the value of measurement Euclidean Distance (ED) and the equitable distribution to form heterogeneous groups based on their level of heterogeneity in Measured with Goodness of Heterogeneity in Group (GH) and the rate of coefficient variation (CV) in same group or between groups with groups and equitable distributions on college campuses.
Co-Authors A Azidny A. A. Uliansyah, Beta Abdelhadi Husein Aburawis Abdul Rohman Soleh Achmad Chaidir Adi Ariyo Munandar Adib Ulil Anwar Agung Suryowibowo Ahmad Syarif Hidayatullah Akhmad Priharjanto, Akhmad Akhmad Solikin Akhsinatul Laeliyah Alfano Endra Wardhana Alfiah Nurul Fatimah Intan Pertiwi Ali Selamat Ali Selamat Andhika Bayu Pratama Andi Riansyah Arief Marwanto Arifin, Bustanul Arifin, Zaenal Arigama, Rizki Artini DP, Sri Aser Anou Ashar, Firbaya Mutiara Asih Widi Harini Ayunda Miftakhul Laili Azmia, Hisnan Faudan Badieah Assegaf Badie’ah, Badie’ah Badie’ah, Badie’ah Bahrun Niam Bahtiar, Thoriq Basit, Abdul Budi Cahyo Wibowo Bustanul Arifin Bustanul Arifin Chaerul Haviana, Sam F. Chanif, Muhammad Nur Daniyah, Daniyah Darso D Dedy Kurniadi Deris Stiawan Deshinta Arrova Dewi Dwi Zunia Arianto Eka Nuryanto Budi Susila Eko Saputra, Wardianto F Feriawan Fadhilah, Achmad Naufal Fahmi Arif Dewoputro Fahrizal, Fery Fajar Yumono Fajarini, Intan Putri Nur Febrian Rio Hartono Fitri Anindyahadi Goli Arji Hardjana, Irawan Pudja Hud Munawar Ilhamsyah, Muhamad Reynaldi Imam Hendi Susanto Irfan Fadhil Irwan Sukendar Irwan Sukendar Iska Yanuartanti khaled jemah basher Kharis Abdullah La Ode Muhamad Idris Laksamana Rajendra Haidar Lestari Kurniawati, Lestari Lina Handayani Mahfud Ade Purwanto Maryuliana Maryuliana Maulida, Aina Nurul Mekacahyani, Rakhimatulfitria Milasanti, Denina Moch Taufik Moloud Abdar Muhamad Haddin Muhamad Qomaruddin Muhammad Fadelillah Muhammad Khosyiin Muhammad Nur Gofinda Muhammad Qomaruddin Muhammad Rahman Hakim Munawar Agus Riyadi Mustafa, Mustafa Najmah, Najmah Nova Catur Anggi Cahyo Nur Ramadhanif Nur'aini, Intan Nurhidayah, Eva Nurhidayati Nurhidayati Nurnasikha, Kusuma Nuzulia Khoiriyah Poetro, Bagus Satrio Waluyo Pranoto Wibowo Prasetyo, Muhammad Krisna Heri Putra, Allief Suryatama Jaya Putra, Yustian Dikma Eka Putri, Sarah Dwi Qirom Qirom Rachmad Gabels Raden Abdul Rahman Ratna Supradewi Riansyah, Andi Ridwan Putri, Sandhyakalaning Jiwatami Riky Maulana Firdaus Rini Oktarina Riyadh Alnajih Alsayih Riyani, Dita Rizki Arigama Rohman, Andhi Rony, Zahara Tussoleha Rusmal Firmansyah S Suprayogi Saadah, Farikhatus Sam F. Chaerul Haviana Sam Farisa Chaerul Haviana Sapto Utomo Sharareh R. Niakan Kalhori Sigit Ardianto Sofia Murtiani Sri Artini DP Sri Arttini Dwi Prasetyawati Sri Mulyono Suharyo Herwasto Sukendar, Irwan Supriyanto S Suryani Alifah Suyanto Suyanto Tole Sutikno Tri Basuki Kurniawan Trisnawarman, Trisnawarman Ulil Albab Ushuludin, Mohammad Wardianto Eko Saputra Wicaksono, Yusuf Arief Wiwiek Fatmawati Yahya Hidayatullah Yasni, Loura Yusuf Arief Wicaksono Zaenal Arifin