Parallel Session 2
Saturday, July 17 1:30 - 3:00
1:30 Sorting Algorithm for Medium and Large Data Sets Based on Multi-Level Independent Subarrays
In this paper, we propose a new low-complex preprocessing that enables conventional data sorting algorithms to be more efficient for medium and large data sets in a serial/parallel realization. First, we divide the main array into independent
subarrays by a multi-level mean-based division. It is realized by calculating the mean value of each level as the pivot to divide its elements into two parts, greater and lower than the pivot, almost in the same lengths with a lower randomness rate to the main array. Then, subarrays can be sorted by the conventional sorting algorithms in a sequential serial realization to extract sorted data gradually or parallel realizations by using independent multi-core structures. It also holds the stability and adaptivity features of the sorting algorithm, if any. The effectiveness of the mean-based pivot to the random one is investigated. To show the superiority of the proposed idea, the simulation results are compared in view of the running time and the number of swaps required to the conventional and proposed serial and parallel Insertion-sort in different lengths of data. Finally, the complexity order of the proposed algorithm in serial and parallel implementations is compared to the conventional one.
1:45 Classification Hoax News of Covid-19 on Instagram Using K-Nearest Neighbor
The world was shocked by the outbreak of a virus known as COVID-19 in Wuhan, China. The spread of the virus is increasingly spreading to all countries in the world, including Indonesia. In Indonesia, information about the COVID-19 virus can be found on various social media, one of which is Instagram. Starting from scratch are found positive cases of COVID-19 in Jakarta. Until now, many news provider’s accounts found COVID-19 uploaded on Instagram allows the spread of false news. The spread of fake news has greatly affected the handling of this COVID-19 pandemic. The number of hoax news COVID-19 spread on Instagram makes this study using Instagram as a media data retrieval. Therefore research is needed on classifying hoax news about COVID-19 on news accounts on Instagram. This study uses the K-Nearest Neighbor method to classify COVID-19 news on news accounts on Instagram. This research will classify Instagram based on valid news posts on 30 news accounts on Instagram containing news about COVID-19. The news reference used for categorizing hoaxes is from the @turnbackhoaxid account. In using the K-Nearest Neighbor method, the TF-IDF modeling is applied in conducting assessments and weighting. The research results by using the K-Nearest Neighbor method have a presentation accuracy of success 90%, where the precision value is 83%, recall 100%, and f1-score 91% can solve the problem spread of fake news in Indonesian about COVID-19 on news accounts on Instagram.
2:00 Steganalysis of Adaptive Image Steganography using Convolution Neural Network and Blocks Selection
The method of detecting secret information in images in order to discriminate between a suspect and carrier images are known as image steganalysis. Since content-adapted steganographic methods adaptively integrate knowledge into regions with distortion based rich textures, state-of-the-art steganalysis approaches with the development of steganography technology cannot achieve the required detection performance. This makes it difficult to extract effective steganalysis features. Due to impressive performance of Convolution Neural Network (CNN) in the field of image processing, a growing number of research papers are focusing on developing steganalysis methods based on the CNN. Moreover, most research works rely on the entire image to extract the steganalysis features. In this paper, we introduce a new image steganalysis method by designing an entropy-based regional selecting method, and a new CNN framework to discriminate between a stego and cover image. We design a new approach for image block selection that finds the blocks with the highest entropy, allowing the CNN to concentrate on complex textures in image regions while reducing computational complexity. To allow feature diversity, we built a new CNN framework composed of two subnets of different kernel sizes, which we then repeatedly combined and separated. Those two aspects are consequently improved the performance with a reasonable number of epochs for training. When the results of the experiments are compared, our proposed method can lead to improve the detection accuracy of content-adaptive steganographic methods.
2:15 Classification Auction Motorcycle and Car In South Jakarta District Attorney Using Naïve Bayes
Prosecutor’s Office as an institution plays a role in enforcing the law, especially in the field of prosecution. Goods used or goods resulting from a criminal act will be confiscated and then confiscated by the state. As a result of goods resulting from a criminal act, said goods are to be auctioned off. Based on the Regulation of the Minister of Finance Number 27 / PMK.06 / 2016 regarding instructions for auction implementation, an auction is an open sale of goods to the public with the highest price bid in writing or orally, and can be done online or offline. The South Jakarta District Prosecutor’s Office must determine the grade of the items being auctioned. However, it took a month for determining the quality to be categorized. So research is needed to classify the quality of the items being auctioned. The need to classify auctions, especially motorbikes and cars, to shorten the time in classifying and classifying vehicles. The auction classification is based on the standard condition. The assessment in the form of this grade applies to the category of engine, exterior, and interior car, vehicle year, letter in the form of SNTK, BPKB and vehicle keys. This study uses the Naïve Bayes method to classify auction items at the South Jakarta District Prosecutor’s Office. The results of this study have an accuracy value of 74%, 44% precision, 50% recall and 44% f1-score on motor vehicles and 57%, 44% precision, 50% recall and 44% f1-score on car vehicles.
2:30 A Network of Object-Oriented Software Metrics’ Parameters
The use of software metrics has become a crucial tool during the software design phase. The quality of software design can be measured using these metrics. Therefore, it is important to understand software metrics in a way that makes it wiser to select a particular metric in the software design assessment process. To calculate the value of a metric, it is needed to have its parameters involved. Hence, each metric consists of one or several parameters. Many of the object-oriented metrics have parameters in common. This means a parameter can be associated with several metrics. In this case, understanding the relations among parameters may help developers when selecting metrics during the software design phase, which makes the assessment process accurate, wiser, and reduce time consumption. In this work, we deeply investigate the relations among object-oriented metrics’ parameters using concepts inspired from complex networks. The dataset used in this paper was collected from trusted and accredited resources in Software Engineering field. The dataset contains the main 104 object-oriented metrics and their parameters. The results showed important facts about the relations among metrics’ parameters. We believe that this is the first kind of work that investigates the relations among object-oriented metrics’ parameters.
2:45 Indicators on the Feasibility of Curfew on Pandemics Outbreaks in Metropolitan/Micropolitan Cities
The year 2020 had witnessed the greatest health crisis in history due to the spread of the Covid-19 virus. Most of the world-wide countries have been affected by the pandemic in terms of different life sectors such as economic, education, trading, to mention but a few. This is, in fact, due to adopting Lockdown or Curfew strategies aiming at mitigating the spread of the disease. However, many indicators should be taken into consideration before adopting such strategies (e.g., population distribution). Moreover, adopting a particular strategy may work in a particular geographical area, but it may not work in other areas. This issue has not been given enough attention in the literature. Therefore, the contribution of this work is to investigate the impact of the population distribution of cities (e.g., Iraq) on the current pandemic outbreaks. The experiments demonstrate that it is not necessary to adopt a particular strategy for the whole country. This means, a strategy could be efficiently applied in a city but it might be not efficient in another city. The results of this work can be further used to minimizing the loss in economic under the current pandemic.
1:30 Artificial Potential Field Algorithm for Obstacle Avoidance in UAV Quadrotor for Dynamic Environment
Artificial potential field (APF) is the effective real-time guide, navigation, and obstacle avoidance for UAV Quadrotor. The main problem in APF is local minima in one obstacle of multiple obstacles. In this paper, some modifications and improvements of APF will introduce to solve one obstacle local minima, two obstacle local minima, and Goal Not Reachable Near Obstacle (GNRON). The result shows that the improved APF has the best result because can reach the goal position in all of the examination. Meanwhile, the APF with virtual force has the fastest time to reach goal however still has a problem in GNRON. It is concluded that the APF needs to be modified thus the algorithm can pass all of the local minima problems.
1:45 Prediction of the Unemployment and Bank Interest Rates on Changes in the Stock Price Index
Investment is the activity of saving or placing funds in a certain period with the hope that the storage will cause a gain or increase in investment value. Investments can be in the form of shares. Stock is proof of ownership of the value of a company. The influencing factors are the composite stock price index. The composite stock price index is one of the stock market indices used by the Indonesia Stock Exchange. As an indicator of stock price movements, this index includes price movements of all preferred stocks listed on the Indonesian stock exchange. In this study, we analyze the relationship between the composite stock price index with interest rates and the unemployment rate. Multiple linear regression is a continuation of simple linear regression. When simple linear regression provides only one independent variable (x) and one dependent variable (y). Multiple linear regression to cover the weakness of simple linear regression when there are more than one independent variable and one dependent variable (y). From our test results, the unemployment rate with the composite stock price index has a negative correlation, while the credit interest rate with the composite stock price index has a positive correlation, and predictions with the input data have a value close to the true value, which is 95%
2:00 Data Efficient Video Transformer for Violence Detection
in smart cities, violence event detection is critical to ensure city safety. Several studies have been done on this topic with a focus on 2d-Convolutional Neural Network (2d-CNN) to extract spatial features from each frame, followed by Recurrent Neural Networks (RNN) and its variants as a temporal features learning method. On the other hand, the transformer network has achieved a great result in many areas the bottleneck for transformers is the need for large amounts of data to achieve good results. In this paper, we propose a data-efficient video transformer based on the transformer network as a Spatio-temporal learning method with a pre-trained 2d-Convolutional neural network (2d-CNN) as an embedding layer for the input data. The model has been trained and tested on the Real-life violence dataset (RLVS) and achieved an accuracy of 96.25%. A comparison of the result for the suggested method with previous techniques illustrated that the suggested method provides the best result among all the previous studies in the field of violence detection.
2:15 Network Science as a Forgery Detection Tool in Digital Forensics
Forgery detection of documents is considered a challenging task in the field of digital forensics. The detection process is usually complex and needs a lot of stages, which consumes time and effort. The limitation of the literature is in providing methods that can be efficiently and easily adopted with minimum cost. This work proposes a novel approach for detecting counterfeit/ forged documents. The proposed approach is based on network science approaches for analyzing documents’ ink spectrums aiming to detect whether a document was counterfeited or forged. To this end, Laser-Induced Breakdown Spectroscopy (LIBS) is used to retrieve the spectrums of the original and questioned documents. The extracted spectrums are formalized to create a dataset, which contains nodes (spectrums) and edges (correlations among spectrums). Then, the dataset is used to generate a network of spectrums that represented both the original and questioned documents. After that, the generated network is visualized and clustered. The detection process is mainly based on the information provided by network clusters (e.g., number of clusters). The results showed that the proposed approach was efficient in distinguishing documents. Moreover, the proposed approach was able to distinguish a document itself whether it was counterfeited by extracting the clusters of the questioned document.
2:30 Data Quality Management Maturity: Case Study National Narcotics Board
Data quality determines the organization’s decision-making, strategic planning, and organizational resources components in achieving organizational goals. Data quality must be a concern in government organizations. Research Data and Information Center (RDIC) National Narcotics Board (NNB) is a work unit whose main tasks and functions are data and information services. As the main problem, several work units do not yet understand the importance of data quality, which carries out their data collection in their own format, as it is known that drug data is unique data. Hence, it is necessary to measure the maturity of Data Quality Management (DQM). This research is qualitative research conducted by assessing the working group team in data and information using Loshin’s data quality framework to measure the data quality RDIC NNB. The results showed that the maturity level is repeatable (level 2). Many improvements need to increase the maturity level of data quality. The characterizations that have not yet been implemented are mapping on data quality DMBOK2 activities. RDIC needs to formulate data governance policies, data standards, data steward, and data quality monitoring systems to improve data quality.
1:30 Solar Cell Based Integrated Sensor System Monitoring on Smart IoT
The garden light is one of a public facility that serves to give illumination on each of the existing parks in the city. Most of the park lighting systems in Indonesia, the garden light outages are still handled manually by relying on information from the community to report via the command center or checking manually by patrol. In this study, we proposed, a system monitoring tool garden light solar cell that can be accessed through the website. Monitoring the performance of park lights with remotely and real-time is one application of the smart city concept. Namely by facilitating the monitor process and automatic battery power check. The result of the existing problems in the field, monitoring tool designed garden light solar cell-based website using a microcontroller connected ESP8266 Node MCU internet network so that it is able to display voltage and current data on photovoltaics, batteries, and lights. Other functions of this tool to monitor the condition of the lamp flame or outages on Garden lights solar cell and know the layout of the existing garden light poles in the field. This research has been tested directly in public parks in the city of Surabaya, with the accuracy of updating information at 100% and the accuracy level of the battery at 98.78%
1:45 Real-Time Examination System For New Students At Pandemic Time Covid 19 Using Fuzzy Logic
In this paper, it is a solution to assist government policies in reducing the spread of the 2019 coronavirus disease (COVID-19) at Mercu Buana University, where the system is designed to function as an online admissions interface using fuzzy logic with artificial intelligence. Where the system is fully automatic, starting from processing input data and output data in the form of selection results made by the system in real-time. Fuzzy logic for the lower limit value which is considered very low is 50 and the upper limit is 55. For the low category value, the lower limit is 50 and the upper limit is 65. For medium category values the lower limit is 63 and the upper limit is 78. And for high category values, the limit is lower than 77, and an upper limit of 85.
2:00 Visual Editor for Streamlining P4-based Programmable Parser Development
P4 language enables new protocol development for advanced networking tasks such as dynamic monitoring, custom tunneling & routing, in-switch attack detection, and soon. Nevertheless, developing a P4 program is challenging for those who either lacking programming skills or advanced networking. This paper proposed a visual editor to ease the development of P4 programmable parser which is the first and fundamental step in P4 development. The editor offers two functionalities, the creation of custom protocols & protocols parser, and code generation for testing purposes.
For evaluations, we run a compatibility test to ensure that P4-switch can parse any packet solely based on bit-by-bit extraction. We created a custom protocol by using Scapy’s protocol binding and send the packet through the P4 switch. The custom protocols use the same bit structure as the standard protocols, such as Ethernet, IP, TCP, UDP, and MPLS, but have different naming. The result showed that the receiver host recognized the custom protocols as the standard ones since the P4-switch treat them based on their bit structure. At last, except for the packet processing part, all of the evaluations are done without writing any codes since they were generated by the editor.
2:15 SimRouter: Message routing based on Similarity and Relative Probable Positions of nodes in DTNs
Delay tolerant networks (DTNs) have the major challenge of unpredictable topology due to nodes’ mobility and intermittent connections between nodes.
Researchers have proposed various routing schemes to route packets effectively and efficiently within the given constraints, but we are still far from a perfect protocol. We propose a novel multi-copy protocol SimRouter for such networks, leveraging the additional information about the network, to make the routing decisions. SimRouter uses relative probable positions of the nodes and their similarity to route messages effectively with low overhead. Each node estimates and stores the relative probable positions of other nodes and a vector containing the number of times other nodes came in contact with it. The decision whether to replicate a message to another node or not is taken considering the two factors. Firstly, how similar the two nodes are in terms of their contact history and secondly, the relative positions of the nodes with respect to the destination node. The proposed protocol outperforms the current state of art multi-copy protocols specifically for high traffic loads.
2:30 A Fast Sub-Optimum Access Point Selection in Ultra-Dense Networks
Solving the main optimization problem, including a large number of access points and user equipment in ultra-dense networks (UDNs) using the Munkres algorithm, is a time-consuming solution. In this paper, we propose two new ideas for selecting the appropriate access points (APs) in UDNs that reduce the complexity order and find the suboptimum solution efficiently. Applying the first idea, all user equipment (UE) that are out of access points’ service area and all access points that cannot
find any user equipment in their service area are removed. In this case, the solutions of the conventional and proposed version of the Munkres algorithm are the same, which offers a high total sum value of the signal to noise ratios (SNRs). Still, it does not guarantee minimum interference. Hence, as the second idea, we consider estimation of the signal to interference plus noise ratio (SINR), entitled by average-SINR and random-SINR, and solve the optimization problem, including a large number of access points and a variable number of user equipment densely
distributed. The simulation results show the effectiveness of the proposed algorithms in the view of sum-rate, the number of successful user equipment, and computational complexity for an area, including 250 APs and a variable number of UEs.
2:45 Integrated Strategy Framework To Improve Quality Of Network on The BMKG Communication Network System
BMKG (Meteorology, Climatology and Geophysics Agency) is an organization with a service function that provides information on Meteorology, Climatology, Air Quality, and Geophysics. Good data management is the main focus of BMKG’s business activities to produce fast, precise, accurate, wide-coverage, and understandable information. A reliable and speedy Local Area Network (LAN) and Wide Area Network (WAN) communication infrastructure can help analyze data and disseminate public information. To get the quality of the communication network system, the authors measure network parameters on the network infrastructure at BMKG, such as access speed and transmission capacity, from the sending point to the receiving point. The parameters used are jitter, delay (latency), packet loss and throughput. This measurement uses the Iperf/Jperf tools to measure throughput bandwidth and packet loss in a network system. This QoS parameter follows the standards set by the Telecommunications and Internet Protocol Harmonization Over Networks (TIPHON). The results and analysis of QoS measurements show that, in general, some buildings during office hours and non-office hours show good results. To excellent results, ideally the TIPHON standard, the authors describe the proposed integrated framework, including the End-User layer, the application layer, the system layer, the investment layer and the hardware layer. The proposed integrated framework is a concept to improve the quality of a better network. So that, in general, it can produce the outcome of improving the performance of the network system, especially in the BMKG and can minimize economic losses to social impacts, in this case, a disaster
1:30 The Analysis of High Power Amplifier Distortion on the MIMO-GFDM Systems
Generalized Frequency Division Multiplexing (GFDM) is a flexible waveform possible choice for the next communication system that offers advantages such as low out-of-band (OOB) and high spectral. The High Power Amplifier (HPA) is operated close to the saturation region for increased efficiency. However, working in that area will result in nonlinear distortion. In this paper, we investigated the effect of HPA in the GFDM Multiple Input Multiple Output (MIMO) system. The model used is the Rapp Model. In this paper, the Bit Error Rate (BER) of the MIMO-GFDM system with HPA through the Additive White Gaussian Noise (AWGN) channel will be explored. The output of the simulation shows that the nonlinear distortion effect will cause the signal constellation to propagate. Besides, there was an increase in the BER value for the HPA system.
1:45 Experimental Characterization of Miniaturized Meander Line-Based 4×4 Butler Matrix
In this paper, an experimental characterization is performed to verify the concept of miniaturized 4×4 Butler matrix design using meander line technique. A meander line-based 4×4 Butler matrix prototype is designed and fabricated on an FR4 epoxy dielectric substrate with the thickness of 0.8 mm. Some key parameters of Butler matrix including the magnitude and phase responses are characterized and investigated through several measurements. The characterization results demonstrate that the meander line-based 4×4 Butler matrix takes the size of 57.5 mm by 136.4 mm shows good magnitude and phase performances. The measured -10 dB reflection coefficient fractional bandwidth of 16.25% could be attained at the frequency range of 2.15 GHz to 2.54 GHz. Meanwhile, at the operating frequency of 2.4 GHz the measured average phase difference between the adjacent output ports of 41.49o was achieved. Here, the use of meander line technique could exhibit a size miniaturization of 34.29% to the footprint of conventional 4×4 Butler matrix.
2:00 Outage Probability Analysis of Full-Duplex UAV-assisted Wireless System over Rician fading channel
The deployment of unmanned aerial vehicles (UAV)as a mobile relay is an emerging technique in cooperative wireless communication system. In this paper, we analyze the performance of UAV assisted full, half duplex (FD)(HD) cooperative communication in a dual hop scenario, which consists of a base station, an energy harvesting enabled UAV as relay and a desired user. For our desired system, we derived the closed form expressions for outage probability, throughput by adopting decode and forward protocol (DF) employed over rician fading channel. We also presented the impact of self-interference on system performance in FD systems. The results shows that, performance of the system improved by increasing the rician factor (K). Finally, Numerical results were plotted based on obtained expressions.
2:15 Design GUI Filter Infinite Impulse Response (IIR) for Noise Reduction While Real Time using LabVIEW
An audio that is produced from an object that vibrates in the audio frequency range (can be heard by humans). Sound is also a source of information where if the information obtained is interrupted due to noise or interference, the information obtained can be wrong or not as expected. To reduce the existence of these errors, many filters are now used to overcome noise in the sound. The filter is a device used to hold the unwanted and one of the filters is the Infinite Impulse Response (IIR) to reduce noise. In addition to knowing the characters of audio signals that have not been filtered and those that already have, use an application called LabVIEW (Laboratory Virtual Instrument Engineering Workbench) where this application can be used and observed very easily.
2:30 Spectrum Fee License Analysis on 3.5, 26, and 28 GHz Frequency For 5G Implementation in Indonesia
Cellular technology that is currently being planned to release is 5G technology that will be released in 2022 in Indonesia by using frequencies at 3.5, 26, and 28 GHz. To maintain economic stability in Indonesia, especially in the field of non-tax revenue, it is needed to examine how much the Spectrum Fee is paid by the operator to the government. The formula of Bandwidth Spectrum License has set by the Government through the Ministry of Communications and Informatics. To analyze the suitability of the spectrum fee values and operators revenue the writer readjusts the value of normalization factor (K) where this value is given by 4 options which are 100%, 75%, 50%, and 25% of the K values obtained. As a result, The calculation of Spectrum Fee using 100% of K factor resulting Rp. 1,6 Trillion for the mid-band, while for the high-band resulting Rp. 6,4 Trillion. Spectrum fee is reduced in proportion to the decrease in the K Factor used. so that the K factor of 25% resulting Rp. 400 Billion for the mid-band, while for the high-band resulting Rp. 1,6 Trillion. In general, the use of high-band results in higher spectrum fees, this is due to the use of bandwidth that is 4 times higher than the mid-band and the higher K factor value.
2:45 Segmenting the Subscribers of An Indonesian 4G Service Operator Using RFM Method
The aggressiveness of competitions that occur among providers has progressively made the rivalry of the telecommunications industry in Indonesia increasingly tighter. Even in the pandemic which have caused customers’ purchasing power decreasing, it turns out the competition intensity in the telecommunication industry shows the contrary, this is proven by all the providers eager to compete in offering variety of services which attractive both in price and other benefits to acquire the customers of other providers. The intense competition motivates each provider in a particular way to manage the customers service optimally. The process which utilized by cellular providers to make existing and new customers become loyal and expected to provide greater revenue than it was previously, is becoming incredibly important. In order for providers to accommodate the customers’ needs and able to execute the correct marketing strategy, this research will conduct the customers segmentation, in which there are stages that must be done in segmenting the customers by dividing several customer groups that reflects the same needs and capabilities using the RFM Modeling. The analysis in RFM Modeling is based on three main indexes of customer behavior, which are recency, frequency and monetary. Therefore, the providers will be able to predict the customer’s purchasing behavior and create an exact strategy to provide interesting suitable offers for the customer or even personalized, in hope to form loyal customers and contribute greater ARPU than it was before.