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All Journal Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Proceeding of the Electrical Engineering Computer Science and Informatics Indonesian Journal on Software Engineering (IJSE) Faktor Exacta INOVTEK Polbeng - Seri Informatika Jurnal Sisfokom (Sistem Informasi dan Komputer) Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Jurnal ICT : Information Communication & Technology SENSITEK Respati SKANIKA: Sistem Komputer dan Teknik Informatika Jurnal Abdimas Sangkabira Kresna: Jurnal Riset dan Pengabdian Masyarakat Bit (Fakultas Teknologi Informasi Universitas Budi Luhur) International Journal on Advanced Technology, Engineering, and Information System (IJATEIS) Eduvest - Journal of Universal Studies Telematika MKOM Jurnal Pengabdian Masyarakat Nasional Artinara Jurnal Ticom: Technology of Information and Communication INOVTEK Polbeng - Seri Informatika
Mohammad Syafrullah
Universitas Budi Luhur
Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Neuroscience Social Sciences Other

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Privacy Control In Social Networks By Trust Aware Link Prediction Syam Prasad Dhannuri; Sanjay Kumar Sonbhadra; Sonali Agarwal; P. Nagabhushan; M. Syafrullah; Krisna Adiyarta
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1972

Abstract

Social networks are exceedingly common in today’s society. A social network site is an online platform where people build social relations with others and share information. For the last two decades, rapid growth in the number of users and applications with these social networking sites, make the security as the most challenging issue. In this virtual environment, some greedy people intentionally perform illegal activities by accessing others’ private information. This paper proposes a novel approach to detect the illegal access of a particular’s information by using trustaware link prediction. The facebook dataset is used for experiments and the results justify the robustness andtrustworthiness of the proposed model.
Gesture recognition by learning local motion signatures using smartphones Prachi Agarwal; Sanjay Kumar Sonbhadra; Sonali Agarwal; P. Nagabhushan; Muhammad Syafrullah; Krisna Adiyarta
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1982

Abstract

In recent years, gesture or activity recognition is an important area of research for the modern health care system. An activity is recognized by learning from human body postures and signatures. Presently all smartphones are equipped with accelerometer and gyroscopes sensors, and the reading of these sensors can be utilized as an input to a classifier to predict the human activity. Although the human activity recognition gained a notable scientific interest in recent years, still accuracy, scalability and robustness need significant improvement to cater as a solution of most of the real world problems. This paper aims to fill the identified research gap and proposes Grid Search based Logistic Regression and Gradient Boosting Decision Tree multistage prediction model. UCI-HAR dataset has been used to perform Gesture recognition by learning local motion signatures. The proposed approach exhibits improved accuracy over preexisting techniques concerning to human activity recognition.
Client Side Channel State Information Estimation for MIMO Communication Sambhavi Tiwari; Abhishek Abhishek; Shkehar Verma; K Singh; M Syafrullah; Krisna Adiyarta
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1993

Abstract

Multiple-input multiple-output (MIMO) system relies on a feedback signal which holds channel state information (CSI) from receiver to the transmitter to do pre-coding for achieving better performance. However, sending CSI feedback at each time stamp for long duration is an overhead in the communication system. We introduce a deep reinforcement learning based channel estimation at receiver end for single user MIMO communication without CSI feedback. In this paper we propose to train the receiver with known pilot signals to analyse the stochastic behaviour of the wireless channel. The simulation on MIMO channel with additive white Gaussian noise (AWGN) shows that our proposed method can learn the different characteristics affecting the channel with limited number of pilot signals. Extensive experiments show that the proposed method was able to outperform the existing state-of-the-art end to end reinforcement learning method. The results demonstrate that the proposed method learns and predicts the stochastic time varying channel characteristic accurately at receiver’s end.
PID Controller Design for Mobile Robot Using Bat Algorithm with Mutation (BAM) Dwi Pebranti; Luhur Bayuaji; Yogesvaran Arumgam; Indra Riyanto; Muhammad Syafrullah; Nurnajmin Qasrina Ann Ayop
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.1996

Abstract

By definition, a mobile robot is a type of robotthat has capability to move in a certain kind of environmentand generally used to accomplish certain tasks with somedegrees of freedom (DoF). Applications of mobile robots coverboth industrial and domestic area. It may help to reduce risk tohuman being and to the environment. Mobile robot is expectedto operate safely where it must stay away from hazards such asobstacles. Therefore, a controller needs to be designed to makethe system robust and adaptive. In this study, PID controller ischosen to control a mobile robot. PID is considered as simpleyet powerful controller for many kind of applications. Indesigning PID, user needs to set appropriate controller gain toachieve a desired performance of the control system, in termsof time response and its steady state error. Here, anoptimization algorithm called Bat Algorithm with Mutation(BAM) is proposed to optimize the value of PID controller gainfor mobile robot. This algorithm is compared with a wellknownoptimization algorithm, Particle Swarm Optimization(PSO). The result shows that BAM has better performancecompared to PSO in term of overshoot percentage and steadystate error. BAM gives 2.29% of overshoot and 2.94% ofsteady state error. Meanwhile, PSO gives 3.07% of overshootand 3.72% of steady state error.
Design and Implementation of Web-based Church Information Systems (Case Study : HKBP Kebon Jeruk) Armando Ondihon Kristoper Purba; Supardi Supardi; Ernawati Dewi; Meilieta Anggriani Porrie; Muhammad Syafrullah
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.2001

Abstract

HKBP Kebon Jeruk Church has a lot of data consisting of church data, Pastor data, Church server data, family data, marital data, baptismal data, and also about church agenda such as the schedule of activities Church, schedule of church service. The problem in HKBP Kebon Jeruk is that the Data is provided and managed manually, as well as difficulties in finding the necessary information. Therefore, the system needs to be built by the HKBP Kebon Jeruk Church to request church management data.The method used in the HKBP Kebon Jeruk system is the Extreme Programming method, and the analysis used is the PIECES analysis. The result of this research is to build the HKBP Kebon Jeruk system according to the needs of the user.
Implementation of Image Segmentation Techniques to Detect MRI Glioma Tumour Siti Rafidah Binti Kassim; Setyawan Widyartoh; Mohammad Syafrullah; Krisna Adiyarta; Widya Kumala Sari
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 6: EECSI 2019
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v6.2011

Abstract

Image identification to detect a tumour needs several stages of image processing along with identifying analysis. To get an accurate segmentation of the tumour contour and to identify brain tumour based on brain magnetic resonance imaging (MRI), a suitable techniques and stages of image processing are required to be applied. One technique of mid-level image processing became an objective this work. The objective of the study is to segment the boundary of tumour by applying the Modification of Region Fitting (MRF) method in term of data fitting. The performance of the Region Scalable Fitting (RSF) method and Modified Region Scalable Fitting (MRSF) is evaluated by comparing the number of iterations. As the result, the MRF method has successfully segmented the initial region of braintumour images.
Person tracking with non-overlapping multiple cameras Sanjay Kumar Sonbhadra; Sonali Agarwal; Muhammad Syafrullah; Krisna Adiyarta
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 7, No 1: EECSI 2020
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v7.2049

Abstract

Monitoring and tracking of any target in a surveillance system is an important task. When these targets are human then this problem comes under person identification and tracking. At present, large scale smart video surveillance system is an essential component for any commercial or public campus. Since field of view (FOV) of a camera is limited; for large area monitoring, multiple cameras are needed at different locations. This paper proposes a novel model for tracking a person under multiple non-overlapping cameras. It builds the reference signature of the person at the beginning of the tracking system to match with the upcoming signatures captured by other cameras within the specified area of observation with the help of trained support vector machine (SVM) between two cameras. For experiments, wide area re-identification dataset (WARD) and a real-time scenario have been used with color, shape and texture features for person's re-identification.
Email classification via intention-based segmentation Sanjay Kumar Sonbhadra; Sonali Agarwal; Muhammad Syafrullah; Krisna Adiyarta
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 7, No 1: EECSI 2020
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v7.2084

Abstract

Email is the most popular way of personal and official communication among people and organizations. Due to untrusted virtual environment, email systems may face frequent attacks like malware, spamming, social engineering, etc. Spamming is the most common malicious activity, where unsolicited emails are sent in bulk, and these spam emails can be the source of malware, waste resources, hence degrade the productivity. In spam filter development, the most important challenge is to find the correlation between the nature of spam and the interest of the users because the interests of users are dynamic. This paper proposes a novel dynamic spam filter model that considers the changes in the interests of users with time while handling the spam activities. It uses intention-based segmentation to compare different segments of text documents instead of comparing them as a whole. The proposed spam filter is a multi-tier approach where initially, the email content is divided into segments with the help of part of speech (POS) tagging based on voices and tenses. Further, the segments are clustered using hierarchical clustering and compared using the vector space model. In the third stage, concept drift is detected in the clusters to identify the change in the interest of the user. Later, the classification of ham emails into various categories is done in the last stage. For experiments Enron dataset is used and the obtained results are promising.
Aggressive driving behaviour classification using smartphone's accelerometer sensor Sanjay Kumar Sonbhadra; Sonali Agarwal; Muhammad Syafrullah; Krisna Adiyarta
Proceeding of the Electrical Engineering Computer Science and Informatics Vol 7, No 1: EECSI 2020
Publisher : IAES Indonesia Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eecsi.v7.2091

Abstract

Aggressive driving is the most common factor of road accidents, and millions of lives are compromised every year. Early detection of aggressive driving behaviour can reduce the risks of accidents by taking preventive measures. The smartphone's accelerometer sensor data is mostly used for driving behavioural detection. In recent years, many research works have been published concerning to behavioural analysis, but the state of the art shows that still, there is a need for a more reliable prediction system because individually, each method has it's own limitations like accuracy, complexity etc. To overcome these problems, this paper proposes a heterogeneous ensemble technique that uses random forest, artificial neural network and dynamic time wrapping techniques along with weighted voting scheme to obtain the final result. The experimental results show that the weighted voting ensemble technique outperforms to all the individual classifiers with average marginal gain of 20%.
SISTEM PEMERIKSA KEAMANAN INFORMASI MENGGUNAKAN NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY (NIST) CYBERSECURITY FRAMEWORK Victor Ilyas Sugara; Hadi Syahrial; Muhammad Syafrullah
KOMPUTASI Vol 16, No 1 (2019): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Publisher : Ilmu Komputer, FMIPA, Universitas Pakuan

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (523.331 KB) | DOI: 10.33751/komputasi.v16i1.1591

Abstract

Masalah kemanan informasi dapat mempengaruhi operasional di suatu perusahaan/organisasi. Resiko yang timbul dapat berakibat proses bisnis tidak optimal, kerugian finansial, berkurangnya kepercayaan pelanggan, menurunnya reputasi dan yang paling buruk adalah hancurnya bisnis perusahaan. Untuk itu diperlukan suatu cara untuk memonitor keamanan informasi di perusahaan ini secara periodik. Metode yang bisa digunakan sebagai best practise  adalah National Institute of Standards and Technology (NIST) Cybersecurity Framework. Framework ini menyediakan mekanisme penilaian yang memungkinkan organisasi/perusahaan menentukan kemampuan cybersecurity saat ini, menetapkan sasaran individual, dan membuat rencana untuk memperbaiki dan memelihara program cybersecurity. Dari penelitian ini didapatkan hasil pengujian untuk fungsi Mengenali (Identify) sebesar 16.67%, Melindungi (Protect) sebesar 32.86%, Mendeteksi (Detect) sebesar 25%, Menanggapi (Respond) sebesar 23.33% dan Memulihkan (Recover) sebesar 58.33%. Namun untuk keseluruhan nilai NIST Security Framework yang didapat hanya 27.55%.
Co-Authors Abdul Rahman Abdul Rahman Wahid Abhishek Abhishek Abhishek Singh Abhishek, Abhishek Achmad Maulana Achmad Solichin Adiyarta, Krisna Agarwal, Prachi Agarwal, Sonali Agarwal, Sonali Agarwal, Sonali Agung Darmawan Agus Riyanto Alvian Winata, Arif Andrico Andrico Anggraini, Triana Aria Mustofa Hidayat Armando Ondihon Kristoper Purba Arumgam, Yogesvaran Bayuaji, Luhur Darmawan, Agung Devit Setiono Dewi Kusumaningsih Dewi, Ernawati Dhannuri, Syam Prasad Dwi Pebranti Dwi Pebrianti Elizabeth Yohanes Emil Salim Ernawati Dewi Esti Setiasih Gaol, GA Monang Lumban Hadi Syahrial Hadjianto, Mardi Hanif, Raihan Labib Indra Riyanto Irawan Irawan Irawan Irawan Jamhari Jamhari Java, Muhammad Arya K Singh Kalyzta, Juan Kassim, Siti Rafidah Binti Krisna Adiyarta Kusumaningsih, Dewi Luhur Bayuaji M. Ivan Putra Eriansya Makhdum Rosadi Martono Martono Maulidia, Mia Meilieta Anggriani Porrie Mohammad Fadhil Abas Muhammad Azhar Mujahid Muhammad Azhar Rasyad Muhammad Hasanul Huda Mutiarawan, Rezza Anugrah Nagabhushan, P. Narinder Punn Nugraha Abdullah, Indra Nurnajmin Qasrina Ann Nurnajmin Qasrina Ann Ayop P. Nagabhushan Painem, Painem Pandu Pradinata Pebranti, Dwi Porrie, Meilieta Anggriani Prachi Agarwal Prasetiamaolana, Eko Pudoli, Ahmad Punn, Narinder Purba, Armando Ondihon Kristoper Purwanto Purwanto Qasrina Ann Ayop, Nurnajmin Rakesh Kumar Yadav Ramdhan, Syaipul Ratna Kusumawardani Ratna Kusumawardani, Ratna Rezza Anugrah Mutiarawan Rianto, Yan Ridho Saputra Rizki Aji Wibowo Roeswidiah, Ririt Rusdah Rusdah Ruwirohi, Jan Everhard S. Venkatesan Sadhana Tiwari Sambhavi Tiwari Samidi Samidi Sanjay Kumar Sonbhadra Sanjay Kumar Sonbhadra Sari, Widya Kumala Setyawan Widyartoh Shekhar Verma Shkehar Verma Singh, Abhishek Singh, K Siti Rafidah Binti Kassim Sonali Agarwal Sonali Agarwal Sonali Agarwal Sonbhadra, Sanjay Kumar Sonbhadra, Sanjay Kumar Sumarudin, Muhammad Supardi Supardi Supardi Supardi Supardi, Supardi Syaddad, Muhammad Sulthan Syaiful Anwar Syaipul Ramdhan Syam Prasad Dhannuri Thisa Tri Utami Tiwari, Sadhana Tiwari, Sambhavi Tutik Sri Susilowati Venkatesan, S. Verma, Shekhar Verma, Shkehar Victor Ilyas Sugara Widdy Chandra Permana Widya Kumala Sari Widyartoh, Setyawan Windarto, Windarto Yadav, Rakesh Kumar Yan Rianto Yodi Susanto Yogesvaran Arumgam Yulianawati Yulianawati Yulianawati Zulkarnaen Noor Syarif