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Proceeding of the Electrical Engineering Computer Science and Informatics
Published by Institute of Advanced Engineering and Science
ISSN : 2407439X     EISSN : -     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Proceeding of the Electrical Engineering Computer Science and Informatics publishes papers of the "International Conference on Electrical Engineering Computer Science and Informatics (EECSI)" Series in high technical standard. The Proceeding is aimed to bring researchers, academicians, scientists, students, engineers and practitioners together to participate and present their latest research finding, developments and applications related to the various aspects of electrical, electronics, power electronics, instrumentation, control, computer & telecommunication engineering, signal processing, soft computing, computer science and informatics.
Arjuna Subject : -
Articles 649 Documents
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Aquatic Iguana: A Floating Waste Collecting Robot with IoT Based Water Monitoring System Mirza Turesinin; Abdullah Md Humayun Kabir; Tanzina Mollah; Sadvan Sarwar; Shazzad Hosain
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.v7.2081

Abstract

Water pollution is a major problem worldwide. In order to tackle the pollution and keeping the water resources clean, this paper presents an affordable and advanced floating garbage removing robot called "Aquatic Iguana". The robot moves around the surface of the water and collects floating waste material such as plastic, packets, leaves, etc. Along with the waste-collecting system, the robot also includes water monitoring with pH, turbidity, temperature sensors, and a live streaming feature, increasing the capacity to a greater extent. We have developed this robot to ensure the cleaning of water resources and to create a strong data set of water quality for future predictions. The use of this technology will ensure the safety of all aquatic animals and plants.
Analysis on the Cogging Torque of Permanent Magnet Machine for Wind Power Applications Tajuddin Nur; Linda Wijayanti; Anthon de Fretes; Karel Octavianus Bachri
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.v7.2082

Abstract

This paper discusses the new feature implemented in most social media messaging applications: the unsent feature, where the sender can delete the message he sent both in the sender and the recipient devices. This new feature poses a new challenge in mobile forensic, as it could potentially delete sent messages that can be used as evidence without the means to retrieve it. This paper aims to analyze how well Autopsy open-source mobile forensics tools in extracting and identifying the deleted messages, both that are sent or received. The device used in this paper is a Redmi Xiaomi Note 4, which has its userdata block extracted using linux command, and the application we’re using is WhatsApp. Autopsy will analyze the extracted image and see what information can be extracted from the unsent messages. From the result of our experiment, Autopsy is capable of obtaining substantial information, but due to how each vendor and mobile OS store files and databases differently, only WhatsApp data can be extracted from the device. And based on the WhatsApp data analysis, Autopsy is not capable of retrieving the deleted messages. However it can detect the traces of deleted data that is sent from the device. And using sqlite3 database browser, the author can find remnants of received deleted messages from the extracted files by Autopsy.
Performance Comparison of Schedulers in MmWave Communication using NS-3 Victor Lamboy Sinaga; Rakhmat Yuniarto; Tofan Hermawan; Ruki Harwahyu; Riri Fitri Sari
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.v7.2083

Abstract

Millimeter-wave (mmWave) has proven to provide the bandwidth requirement for the new radio (NR) on 5G. MmWave has been developed as a new technology to support enhanced mobile broadband (eMBB), massive machine-type communication (mMTC), and ultra-reliable low latency communication (URLLC). Since using a high frequency, mmWave also has some disadvantages that could not be avoided, such as small coverage, high signal attenuation, limited against some obstacles, and sensitive to the influence of signal quality. This paper discusses the effect of signal quality on 5G performance using mmWave while sending or receiving packet data by using three types of the scheduler, such as Round Robin, Proportional Fairness, and Max Rate scheduler. Signal quality will impact the value of modulation and coding scheme (MCS) that will be used. Our experiments using NS-3 based on the scenario showed that in the same location and number of UEs, performance throughput using Round Robin and Max Rate with excellent signal strength could reach the maximum throughput. The use of Proportional Fairness could lead only to reaching 50% of the maximum throughput. On the other hand, the use of the Proportional Fairness scheduler causes the weak signal to be unstable. Using Round Robin scheduler, the throughput is more stable. Different from the result using the Max Rate scheduler, the UE with the best signal quality compared to other UEs, was the only UE that get the resources allocation.
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.
Prototype Design of Mobile Application 'Hydrolite' for Hydroponics Marketplace Salsabila Ramadhina; Angga Aditya Permana; R Taufiq
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.v7.2085

Abstract

Hydroponics is one of the effective farming methods to apply in big cities because it does not require extensive agricultural land. In addition, hydroponic products are cleaner, higher quality and free from pesticides. However, the development of hydroponic products in Indonesia is relatively slow. One of the factors causing the slow development of hydroponic agribusiness is that online sales media for hydroponic products are still limited, especially android-based e-marketplace application. Hydrolite is present as an e-marketplace that specifically sells vegetables grown using the hydroponic method, and sells all the equipment needed to farm hydroponically. Hydrolite is a prototype e-marketplace application designed using the Marvelapp platform. Further, Marvelapp is one of the best prototyping tools to support application development on mobile devices.
Automatic Grading System for Spreadsheet Formula Kurniandha Sukma Yunastrian; Saiful Akbar; Fitra Arifiansyah
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.v7.2086

Abstract

Spreadsheet is one of the tools that can be used to learn data analysis. Data analysis in spreadsheet can be done using formula. Spreadsheet tools can also be used for exams. For the assessment, there is a problem when the number of answers that need to be checked is large, that is it takes a long time to check all the answers. For this reason, an automatic grading system (autograder) that can evaluate formula in spreadsheet is needed. The method used in developing the autograder system is matching the answer key formula with the student's answer formula. The autograder system assesses the answer by calculating the similarity of the student's answer formula with the answer key formula. This paper explains how to build an autograder system that can evaluate the formula. At the end, an autograder system has been built successfully. It has been tested with 43 testcases and all of them are passed.
Implementation of Secure Work From Home System Based on Blockchain using NS3 Simulation Mega Apriani; Diwandaru Rousstia; Fajar Rifai; Ruki Harwahyu; Riri Fitri Sari
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.v7.2087

Abstract

Work from Home (WFH) is an activity carrying out official duties, completing outputs, coordination, meetings, and other tasks from the residence of employees. Implement WFH many users use the zoom application has vulnerabilities. The network architecture used refers to the simple experiment network. In Secure WFH there are 3 offices connected through a router. Each client in each office is connected to the router via a Virtual Private Network (VPN) on a peer-to-peer (P2P). That architecture has 18 nodes that will be simulated. Secure WFH simulation with blockchain combines secure WFH with a bitcoin code simulator from Arthur Gervais's. Implementation of blockchain on secure WFH can increase security but the resulting speed decreases. The decrease in speed when implementing secure WFH is due to the generate block process and the verification process.
Designing Android-Based Fasting Reminder (Shiyam) Applications Salsabila Ramadhina; Desi Nurnaningsih; Angga Aditya Permana; Ahmad Rodoni
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.v7.2088

Abstract

Indonesia is a country with Muslim majority. Muslims implement fasting as one of important Islamic pillar. Information regarding fasting is substantial for Muslims, especially warnings of imsak, sahur and iftar times. Integration of information related to fasting schedules and provisions in mobile devices especially Android is a promising solution for Muslims. So that, the design of the fasting reminder (Shiyam) application is notable to perform. This application was developed based on the Waterfall model which emphasizes the development of systematic and sequential information systems. The implementation of the Shiyam application which focuses on the aspect of fasting can provide detailed fasting-related information and provides warnings at the time of imsak, iftar and sahur which can help Muslims in carrying out their worship.
Data Reduction Approach Based on Fog Computing in IoT Environment Rawaa Majid Obaise
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.v7.2089

Abstract

This paper investigates a data processing model for a real experimental environment in which data is collected from several IoT devices on an edge server where a clustering-based data reduction model is implemented. Then, only representative data is transmitted to a cloud-hosted service instead of raw data. In our model, the subtractive clustering algorithm is employed for the first time for streamed IoT data with high efficiency. Developed services show the real impact of data reduction technique at the fog node on enhancing overall system performance. High accuracy and reduction rate have been obtained through visualizing data before and after reduction.
Software Defect Prediction Using Neural Network Based SMOTE Rizal Broer Bahaweres; Fajar Agustian; Irman Hermadi; Arif Imam Suroso; Yandra Arkeman
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.v7.2090

Abstract

Software defect prediction is a practical approach to improve the quality and efficiency of time and costs for software testing by focusing on defect modules. The defect prediction software dataset naturally has a class imbalance problem with very few defective modules compared to non-defective modules. Class imbalance can reduce performance from classification. In this study, we applied the Neural Networks Based Synthetic Minority Over-sampling Technique (SMOTE) to overcome class imbalances in the six NASA datasets. Neural Network based on SMOTE is a combination of Neural Network and SMOTE with each hyperparameters that are optimized using random search. The results use a nested 5-cross validation show increases Bal by 25.48% and Recall by 45.99% compared to the original Neural Network. We also compare the performance of Neural Network based SMOTE with SMOTE + Traditional Machine Learning Algorithm. The Neural Network based SMOTE takes first place in the average rank.

Page 64 of 65 | Total Record : 649

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