Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231857
Ni Nyoman Ayu Indah Trisnayanthi, J. Pratilastiarso, D. Satrio
Analysis of fuel consumption is important in order to determine the performance of a Steam Power Plant. Excessive fuel consumption can reduce Power Plant efficiency. Efficiency of the Power Plant can be improved by replacing the type of fuel. The heating value of different fuels in each type will produce different combustion values. The heat of this combustion will affect the efficiency and fuel consumption. For this reason, an analysis of the effect of fuel replacement has been carried out on the performance and fuel consumption of the Steam Power Plant. This study analysis uses Cycle Tempo software. The fuel used is natural gas, residual oil or Marine Fuel Oil (MFO) and Biosolar B30. The results showed the highest efficiency produced by Biosolar B30 with value of 31.78%. The least fuel consumption is produced by natural gas fuel with total consumption of natural gas in 1 year of operations is 277.198 million liters/year. This study shows that although the highest efficiency is produced by Biosolar B30 fuel, the lowest amount of fuel consumption is produced by natural gas. The low calorific value of Biosolar B30 fuel causes the amount of fuel used during the combustion process to become more. High calorific value of natural gas fuel causes the amount of fuel consumption during 1 year of operation to be less. This causes the lowest fuel consumption value is produced by natural gas fuel.
{"title":"Effects of Fuel Replacement on the Performance and Fuel Consumption of Steam Power Plant","authors":"Ni Nyoman Ayu Indah Trisnayanthi, J. Pratilastiarso, D. Satrio","doi":"10.1109/IES50839.2020.9231857","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231857","url":null,"abstract":"Analysis of fuel consumption is important in order to determine the performance of a Steam Power Plant. Excessive fuel consumption can reduce Power Plant efficiency. Efficiency of the Power Plant can be improved by replacing the type of fuel. The heating value of different fuels in each type will produce different combustion values. The heat of this combustion will affect the efficiency and fuel consumption. For this reason, an analysis of the effect of fuel replacement has been carried out on the performance and fuel consumption of the Steam Power Plant. This study analysis uses Cycle Tempo software. The fuel used is natural gas, residual oil or Marine Fuel Oil (MFO) and Biosolar B30. The results showed the highest efficiency produced by Biosolar B30 with value of 31.78%. The least fuel consumption is produced by natural gas fuel with total consumption of natural gas in 1 year of operations is 277.198 million liters/year. This study shows that although the highest efficiency is produced by Biosolar B30 fuel, the lowest amount of fuel consumption is produced by natural gas. The low calorific value of Biosolar B30 fuel causes the amount of fuel used during the combustion process to become more. High calorific value of natural gas fuel causes the amount of fuel consumption during 1 year of operation to be less. This causes the lowest fuel consumption value is produced by natural gas fuel.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130941326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231702
A. Ramadhan, A. Wijayanto, H. Oktavianto
This paper proposes a development of a smart home system for assisting elderly people by implementing an Audio Event Recognition (AER). By listening to the sound in the environment, the AER recognizes audio events that have been trained and then produces a useful information. There are four pretrained audio events namely door knock, can dropped, kettle sound, and rain sound. The audio in the environment is sampled for 5 seconds. Then, the sampled audio is processed into a spectrogram with a size of 128 x 76 pixels. The spectrogram serves as an input image for the Convolutional Neural Networks (CNN) to be recognized. Finally, after the spectrogram is recognized, the system produces information and transmit it to the cloud to be gathered by a smartphone. The system was implemented using Raspberry Pi 4. The experimental results show an accuracy rate of 97.5 % and 85% with a background noise of less than 40 dB and around 40 - 60 dB, respectively.
本文提出了一种智能家居系统的开发，通过实施音频事件识别(AER)来帮助老年人。通过聆听环境中的声音，AER识别经过训练的音频事件，然后产生有用的信息。有四种预先训练的音频事件，即敲门声、罐子掉落声、水壶声和雨声。环境中的音频采样5秒。然后，将采样的音频处理成大小为128 x 76像素的频谱图。频谱图作为卷积神经网络(CNN)的输入图像进行识别。最后，在光谱图被识别后，系统产生信息并将其传输到云端，由智能手机收集。该系统是在Raspberry Pi 4上实现的。实验结果表明，在背景噪声小于40 dB和40 ~ 60 dB时，该方法的准确率分别为97.5%和85%。
{"title":"Implementation of Audio Event Recognition for The Elderly Home Support Using Convolutional Neural Networks","authors":"A. Ramadhan, A. Wijayanto, H. Oktavianto","doi":"10.1109/IES50839.2020.9231702","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231702","url":null,"abstract":"This paper proposes a development of a smart home system for assisting elderly people by implementing an Audio Event Recognition (AER). By listening to the sound in the environment, the AER recognizes audio events that have been trained and then produces a useful information. There are four pretrained audio events namely door knock, can dropped, kettle sound, and rain sound. The audio in the environment is sampled for 5 seconds. Then, the sampled audio is processed into a spectrogram with a size of 128 x 76 pixels. The spectrogram serves as an input image for the Convolutional Neural Networks (CNN) to be recognized. Finally, after the spectrogram is recognized, the system produces information and transmit it to the cloud to be gathered by a smartphone. The system was implemented using Raspberry Pi 4. The experimental results show an accuracy rate of 97.5 % and 85% with a background noise of less than 40 dB and around 40 - 60 dB, respectively.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130073673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231572
Dwi Evita Febrianti Irfat, I. G. Puja Astawa, Aries Pratiarso
Rapidly growing demand for high data rates in wireless communication systems is the cause of the merging of Multiple Input Multiple Output (MIMO) and Orthogonal Frequency Division Multiplexing (OFDM) techniques. MIMO-OFDM technique needs Radio Frequency (RF) front end in each antenna, which is not effective for large dimensional antenna size. Therefore, RF front end on the receiver side will be simplified using a single RF technique based on the Electrically Steerable Parasitic Array Radiator (ESPAR) antenna. In real life, a channel cannot be ideal. Therefore, before the signal is transmitted, that signal must be coded to minimized errors when the data transmission process. Convolutional code is a coding technique that can detect and correct error bit (error control coding) and that it is expected to reduce the quantity of Bit Error Rate (BER). In this research, a simulation is designed to analyze single RF performance on the MIMO-OFDM system using Vertical Bell Laboratories Space-Time (VBLAST) detection for convolutional code encoder and Viterbi decoder. The result simulation shows that the channel estimation technique works well on the MIMO-OFDM system using single RF, which is shown in the magnitude and phase curves against the subcarrier index between the theory channel and the estimated channel are at almost the same points. VBLAST-ZF detector performance is shown in the BER curve against SNR, where the difference BER value for SNR value 10 dB between the theory channel and the estimated channel is 0.001499. Channel coding technique using convolutional code encoder and Viterbi decoder with a rate of ½ works well on the MIMO-OFDM system using single RF which is shown in the BER curve against SNR, where BER value with coding technique is smaller than BER value without coding technique.
{"title":"Analyze of Single RF Front End Performance on MIMO System using V-BLAST Detection for Convolutional Code Encoder and Viterbi Decoder","authors":"Dwi Evita Febrianti Irfat, I. G. Puja Astawa, Aries Pratiarso","doi":"10.1109/IES50839.2020.9231572","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231572","url":null,"abstract":"Rapidly growing demand for high data rates in wireless communication systems is the cause of the merging of Multiple Input Multiple Output (MIMO) and Orthogonal Frequency Division Multiplexing (OFDM) techniques. MIMO-OFDM technique needs Radio Frequency (RF) front end in each antenna, which is not effective for large dimensional antenna size. Therefore, RF front end on the receiver side will be simplified using a single RF technique based on the Electrically Steerable Parasitic Array Radiator (ESPAR) antenna. In real life, a channel cannot be ideal. Therefore, before the signal is transmitted, that signal must be coded to minimized errors when the data transmission process. Convolutional code is a coding technique that can detect and correct error bit (error control coding) and that it is expected to reduce the quantity of Bit Error Rate (BER). In this research, a simulation is designed to analyze single RF performance on the MIMO-OFDM system using Vertical Bell Laboratories Space-Time (VBLAST) detection for convolutional code encoder and Viterbi decoder. The result simulation shows that the channel estimation technique works well on the MIMO-OFDM system using single RF, which is shown in the magnitude and phase curves against the subcarrier index between the theory channel and the estimated channel are at almost the same points. VBLAST-ZF detector performance is shown in the BER curve against SNR, where the difference BER value for SNR value 10 dB between the theory channel and the estimated channel is 0.001499. Channel coding technique using convolutional code encoder and Viterbi decoder with a rate of ½ works well on the MIMO-OFDM system using single RF which is shown in the BER curve against SNR, where BER value with coding technique is smaller than BER value without coding technique.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114936736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231772
A. Anggraini, Entin Martiana Kusumaningtyas, Ali Ridho Barakbah, M. T. Fiddin Al Islami
PDAM (Regional Drinking Water Company) is a company that provides clean water. PDAM develops their services with by considering complaints, suggestions and complaints from users. Over time PDAM services users are increasing thus allowing the number of complaints to also increase and PDAM is impossible to analyze the complaint data using the manual data. In this research proposes ideas to analyze PDAM complaints data with rule based sentiment analysis and categorization methods. The rule based sentiment analysis in this research used twelve rules, where the uniqueness of this rule based is a detection conjunction. Indonesian conjunction detection is the first method available in Indonesia. Detection of conjunction is proposed to find out whether conjunction has an important influence in the meaning of a sentence. The result of sentiment analysis is a score from complaint sentence are negative, positive or neutral. And categorization is a method to provide sentence score including complaints on turbid, leaky water, leakage, meters, usage, or not getting water. An experiment sentiment analysis was conducted on 392 data containing conjunctions and have score manually sentiment. The accuracy value obtained used rule based with conjunctions detection increases 13% than rule based do not use conjunction detection. And the accuracy value of categorization on 100 complaint data are 84% true and 16% false. So for High accuracy values in Conjunction detection needs to notice the context of the sentence and word dictionary and in categorization must also notice to words and write priority categories in the program.
{"title":"Indonesian Conjunction Rule Based Sentiment Analysis For Service Complaint Regional Water Utility Company Surabaya","authors":"A. Anggraini, Entin Martiana Kusumaningtyas, Ali Ridho Barakbah, M. T. Fiddin Al Islami","doi":"10.1109/IES50839.2020.9231772","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231772","url":null,"abstract":"PDAM (Regional Drinking Water Company) is a company that provides clean water. PDAM develops their services with by considering complaints, suggestions and complaints from users. Over time PDAM services users are increasing thus allowing the number of complaints to also increase and PDAM is impossible to analyze the complaint data using the manual data. In this research proposes ideas to analyze PDAM complaints data with rule based sentiment analysis and categorization methods. The rule based sentiment analysis in this research used twelve rules, where the uniqueness of this rule based is a detection conjunction. Indonesian conjunction detection is the first method available in Indonesia. Detection of conjunction is proposed to find out whether conjunction has an important influence in the meaning of a sentence. The result of sentiment analysis is a score from complaint sentence are negative, positive or neutral. And categorization is a method to provide sentence score including complaints on turbid, leaky water, leakage, meters, usage, or not getting water. An experiment sentiment analysis was conducted on 392 data containing conjunctions and have score manually sentiment. The accuracy value obtained used rule based with conjunctions detection increases 13% than rule based do not use conjunction detection. And the accuracy value of categorization on 100 complaint data are 84% true and 16% false. So for High accuracy values in Conjunction detection needs to notice the context of the sentence and word dictionary and in categorization must also notice to words and write priority categories in the program.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133838894","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231770
Khoirul Anwar, Muhammad Abdul Haq, Iwan Kurnianto Wibowo, M. Bachtiar
ERSOW robot soccer that participated in the Indonesian Wheeled Robot Soccer Contest, has many abilities such as object detection and classification, control and navigation system, self-localization and mapping, and also real-time communication between each other. This research focusing on object detection and classification on the robots as one of important processes to provide main data sources for all further actions. Therefore, this process takes longer computation time to detect and classify multiple objects, to improve detection and classification performance speed without sacrifice the accuracy value, we proposed GPU parallel computing on offline training phase and online inference phase. In the offline training phase, the neural network model can be trained in parallel processes using selected GPU hardware. As a result of training, we can transfer learning the model knowledge to another host. The experiments on the NVIDIA Jetson AGX Xavier board show that the custom model as the result of the offline training phase achieves more than 30 fps and pre-trained model SSD-MobileNet-v2 achieve more than 99 fps.
{"title":"GPU Parallel Computing for Detection and Classification Object in Robot Soccer ERSOW","authors":"Khoirul Anwar, Muhammad Abdul Haq, Iwan Kurnianto Wibowo, M. Bachtiar","doi":"10.1109/IES50839.2020.9231770","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231770","url":null,"abstract":"ERSOW robot soccer that participated in the Indonesian Wheeled Robot Soccer Contest, has many abilities such as object detection and classification, control and navigation system, self-localization and mapping, and also real-time communication between each other. This research focusing on object detection and classification on the robots as one of important processes to provide main data sources for all further actions. Therefore, this process takes longer computation time to detect and classify multiple objects, to improve detection and classification performance speed without sacrifice the accuracy value, we proposed GPU parallel computing on offline training phase and online inference phase. In the offline training phase, the neural network model can be trained in parallel processes using selected GPU hardware. As a result of training, we can transfer learning the model knowledge to another host. The experiments on the NVIDIA Jetson AGX Xavier board show that the custom model as the result of the offline training phase achieves more than 30 fps and pre-trained model SSD-MobileNet-v2 achieve more than 99 fps.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"212 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133643402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231940
Ihda Rasyada, Yuliana Setiowati, A. Barakbah, M. T. Fiddin Al Islami
BPJS Kesehatan is a corporation in Indonesia which aim organizing health insurance program. By increasing the number of BPJS Kesehatan’s members every year, BPJS Kesehatan should be able to do all its services well so that its members can get their rights. BPJS Kesehatan performance can be assessed from the public response, one of the social media used by public to share their responses to BPJS Kesehtaan’s service is Twitter. BPJS Kesehatan can use these responses to find out people's opinions on their services. Therefore, this study proposes a new approach to analyzing public opinion using the field of scientific computational linguistics. Specifically by making a computing system with features, 1) Sentiment analysis using the effective models method which sees a different degree for each adjective in the commentary. Affective model is a new approach in Indonesian Language that evaluates each adjective has a different level of pleasure and arousal. This method collects adjectives in Indonesian into a context and assigns different values to each adjective. This value is obtained from the adjective mapping results from Russel's Circumplex model of affect, we also sees words that have affect polarity in a sentence and words that affect the degree of affection in a sentence. 2) Categorization, this feature is to categorize comments into types of BPJS Kesehatan’s services. There are 10 service categories, each of categories has keywords. System identified the keywords in each comment and calculated similarity with existing categories. Total data that has been obtained is SS3S2 tweets. For each data obtained sentiment value will be calculated and categorized, this system will show which service category has positive or negative sentiment. The test method uses data that has been labeled manually before and then is tested using a program. From 211 tweets that have been labeled manually, the sentiment analysis program has succeeded in achieving an accuracy of 83.4% and the categorization program produces an accuracy of 81.05%.
{"title":"Sentiment Analysis of BPJS Kesehatan’s Services Based on Affective Models","authors":"Ihda Rasyada, Yuliana Setiowati, A. Barakbah, M. T. Fiddin Al Islami","doi":"10.1109/IES50839.2020.9231940","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231940","url":null,"abstract":"BPJS Kesehatan is a corporation in Indonesia which aim organizing health insurance program. By increasing the number of BPJS Kesehatan’s members every year, BPJS Kesehatan should be able to do all its services well so that its members can get their rights. BPJS Kesehatan performance can be assessed from the public response, one of the social media used by public to share their responses to BPJS Kesehtaan’s service is Twitter. BPJS Kesehatan can use these responses to find out people's opinions on their services. Therefore, this study proposes a new approach to analyzing public opinion using the field of scientific computational linguistics. Specifically by making a computing system with features, 1) Sentiment analysis using the effective models method which sees a different degree for each adjective in the commentary. Affective model is a new approach in Indonesian Language that evaluates each adjective has a different level of pleasure and arousal. This method collects adjectives in Indonesian into a context and assigns different values to each adjective. This value is obtained from the adjective mapping results from Russel's Circumplex model of affect, we also sees words that have affect polarity in a sentence and words that affect the degree of affection in a sentence. 2) Categorization, this feature is to categorize comments into types of BPJS Kesehatan’s services. There are 10 service categories, each of categories has keywords. System identified the keywords in each comment and calculated similarity with existing categories. Total data that has been obtained is SS3S2 tweets. For each data obtained sentiment value will be calculated and categorized, this system will show which service category has positive or negative sentiment. The test method uses data that has been labeled manually before and then is tested using a program. From 211 tweets that have been labeled manually, the sentiment analysis program has succeeded in achieving an accuracy of 83.4% and the categorization program produces an accuracy of 81.05%.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121795206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231917
Rendy Wahyu Prihantio, Ida Anisah, A. Wijayanti, M. Anggraeni
Considering the advantages of digital TV broadcasting, Analog Switch Off (ASO) has been carried out in total in many countries. However, until the beginning of 2019, ASO had not been fully implemented in Indonesia. This is certainly influenced by various parties ranging from the government as a regulator, TV stations as service providers, and the public as consumers. Research related to performance evaluation of digital TV broadcast especially DVB-T2 standards has been conducted in urban areas in several countries. But there is no research related to exploring the performance of terrestrial digital TV in urban, especially discuss the bit error rate of digital TV broadcasts using the DVB-T2 standard. To oversee the process of migrating analog TV broadcasts to digital TV broadcasts in Indonesia, we conducted a study of digital terrestrial TV broadcasts, in particular, the evaluation of BER and CNR in urban areas through the results of field measurements in Surabaya. We have measured a bit error rate of two TV stations that have carried out digital broadcasts using DVB-T2 standard in Surabaya, namely TV X and TV Y. Each TV station has a transmitter in Sambikerep sub-district for TV X and Sawahan sub-district for TV Y. Measurements were taken at 22 points in Surabaya as one of the representatives of urban areas for the fixed condition. The results of field measurements show that TV X and TV Y have not fully provided adequate broadcasts in the city of Surabaya. There are two blank spots in Kusuma Bangsa Street and Dr. Ir Soekarno Street. Unfortunately, the results of field measurements at Oso Wilangun recorded a bit error rate up to touch 9.9 x 10-2. It means that of the 100 bits sent to have an error at the receiver of almost 10%. Oso Wilangon is the farthest measurement point of TV Y where the distance is around 10.28 km and this area is bordered by Gresik. But officially this area is still included in the city of Surabaya which should be within the coverage area of the TV Y. With this case, TV stations should improve their broadcasts, such as re-adjust the signal transmit power to cover the blank spot area.
考虑到数字电视广播的优势，模拟关闭(ASO)已在许多国家全面实施。然而，直到2019年初，ASO才在印度尼西亚全面实施。这当然受到多方的影响，包括作为监管机构的政府、作为服务提供者的电视台和作为消费者的公众。有关数字电视广播特别是DVB-T2标准性能评价的研究已经在一些国家的城市地区展开。但目前还没有对城市地面数字电视性能的研究，特别是对DVB-T2标准下数字电视广播误码率的研究。为了监督印度尼西亚将模拟电视广播迁移到数字电视广播的过程，我们对数字地面电视广播进行了研究，特别是通过在泗水的实地测量结果对城市地区的BER和CNR进行了评估。我们测量了两个在泗水使用DVB-T2标准进行数字广播的电视台的误码率，即TV X和TV y。每个电视台在Sambikerep街道有一台发射机，TV X和TV y在Sawahan街道有一台发射机。测量在泗水的22个点进行，作为固定条件下城市地区的代表之一。实地测量的结果表明，TV X和TV Y在泗水市没有完全提供足够的广播。在Kusuma Bangsa街和Dr. Ir Soekarno街有两个空白点。不幸的是，Oso Wilangun的现场测量结果记录了高达9.9 x 10-2的误码率。这意味着发送的100个比特中，接收端有近10%的错误。Oso Wilangon是TV Y最远的测量点，距离约10.28 km，与Gresik接壤。但是官方上这个区域仍然包括在泗水市，应该在TV y的覆盖范围内。在这种情况下，电视台应该改善他们的广播，比如重新调整信号发射功率来覆盖空白区域。
{"title":"Bit Error Rate Evaluation of Digital Terrestrial TV Broadcast Based on Field Measurement in Urban Area","authors":"Rendy Wahyu Prihantio, Ida Anisah, A. Wijayanti, M. Anggraeni","doi":"10.1109/IES50839.2020.9231917","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231917","url":null,"abstract":"Considering the advantages of digital TV broadcasting, Analog Switch Off (ASO) has been carried out in total in many countries. However, until the beginning of 2019, ASO had not been fully implemented in Indonesia. This is certainly influenced by various parties ranging from the government as a regulator, TV stations as service providers, and the public as consumers. Research related to performance evaluation of digital TV broadcast especially DVB-T2 standards has been conducted in urban areas in several countries. But there is no research related to exploring the performance of terrestrial digital TV in urban, especially discuss the bit error rate of digital TV broadcasts using the DVB-T2 standard. To oversee the process of migrating analog TV broadcasts to digital TV broadcasts in Indonesia, we conducted a study of digital terrestrial TV broadcasts, in particular, the evaluation of BER and CNR in urban areas through the results of field measurements in Surabaya. We have measured a bit error rate of two TV stations that have carried out digital broadcasts using DVB-T2 standard in Surabaya, namely TV X and TV Y. Each TV station has a transmitter in Sambikerep sub-district for TV X and Sawahan sub-district for TV Y. Measurements were taken at 22 points in Surabaya as one of the representatives of urban areas for the fixed condition. The results of field measurements show that TV X and TV Y have not fully provided adequate broadcasts in the city of Surabaya. There are two blank spots in Kusuma Bangsa Street and Dr. Ir Soekarno Street. Unfortunately, the results of field measurements at Oso Wilangun recorded a bit error rate up to touch 9.9 x 10-2. It means that of the 100 bits sent to have an error at the receiver of almost 10%. Oso Wilangon is the farthest measurement point of TV Y where the distance is around 10.28 km and this area is bordered by Gresik. But officially this area is still included in the city of Surabaya which should be within the coverage area of the TV Y. With this case, TV stations should improve their broadcasts, such as re-adjust the signal transmit power to cover the blank spot area.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"20 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123517318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231567
Yunia Ikawati, M. A. Al Rasyid, Idris Winarno
E-learning is distance learning that uses computer technology, networks of computers and the internet. E-Learning allows students to study via computers in their respective places without having to go to study/lectures in class physically. Moodle is a Learning Management System that is used as a medium for delivering E-Learning. The problem that often arises in e-learning is that in the learning process, students interact more with e-learning media so that teachers will find it difficult to monitor student behavior when using learning media. In fact, students in some cases tend to drop out or attend lesser classes. Moodle can capture student interactions and activities while studying online using log files. From the results of student interactions and activities on e-learning, it can be used to determine their learning style. Identifying student learning styles can improve the performance of the learning process. This research suggests an approach to automatically predicting learning styles based on the Felder and Silverman learning style (FSLSM) model using the Decision Tree algorithm and the ensemble Gradient Boosted Tree method. We've used actual data sets derived from e-learning program log files to perform our work. We use precision and accuracy to assess the results. The results show that our approach is delivering excellent results.
电子学习是使用计算机技术、计算机网络和互联网的远程学习。电子学习允许学生在各自的地方通过电脑学习，而不必去教室学习或上课。Moodle是一个学习管理系统，被用作提供电子学习的媒介。在电子学习中经常出现的问题是，在学习过程中，学生与电子学习媒体的互动更多，教师在使用学习媒体时难以监控学生的行为。事实上，在某些情况下，学生往往会退学或参加较少的课程。Moodle可以使用日志文件捕捉学生在线学习时的互动和活动。根据学生在网络学习上的互动和活动的结果，可以用来确定他们的学习风格。识别学生的学习风格可以提高学习过程的表现。本研究提出了一种基于Felder and Silverman学习风格(FSLSM)模型的学习风格自动预测方法，该方法采用决策树算法和集成梯度提升树方法。我们使用了来自电子学习程序日志文件的实际数据集来执行我们的工作。我们用精密度和准确性来评估结果。结果表明，我们的方法取得了很好的效果。
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Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231664
R. Amalia, A. G. Safitra, Alvin Christian Elby
Double-pipe heat exchanger (DPHE) is one of the type of heat exchangers which usually used for low capacity application. This heat exchanger generally consist of two concentric pipe with plain or finned inner pipe. One fluid flow through the inner pipe, and the other fluid flow through the annulus pipe in counter flow condition to get highest performance for given surface area. This heat exchanger is widely used because it’s simple, economically, easy construction, cheaper, greater flow capacity, easier maintenance, and better thermal performance than the others. Double-pipe heat exchanger performance is determined based on heat transfer coefficient, pressure drop and effectiveness. Heat transfer efficiency and pressure drop are defined in terms of the Nusselt (Nu) number and the friction factor (f), respectively. The purpose of this study is to analyze the performance of multiple pipe heat exchangers by varying the Reynolds number as follows 2500, 3500, 4500, 5500, and 6500 using Ansys Fluent software. Based this research, it is found that the increase Nre (reynold number), Nu (nusselt number) and e (effectiveness) are also increasing, and f (friction factor) is decreasing. The Nusselt number is increased 2.13 times from 22.68 to 48.33, the friction factor decreased 2.44 times from 0.083 to 0.034, and the effectiveness increased 1.36 times from 0.225 to 0.306.
{"title":"Numerical Study on Heat transfer and Pressure Drop Characteristic in Double Pipe Heat Exchanger","authors":"R. Amalia, A. G. Safitra, Alvin Christian Elby","doi":"10.1109/IES50839.2020.9231664","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231664","url":null,"abstract":"Double-pipe heat exchanger (DPHE) is one of the type of heat exchangers which usually used for low capacity application. This heat exchanger generally consist of two concentric pipe with plain or finned inner pipe. One fluid flow through the inner pipe, and the other fluid flow through the annulus pipe in counter flow condition to get highest performance for given surface area. This heat exchanger is widely used because it’s simple, economically, easy construction, cheaper, greater flow capacity, easier maintenance, and better thermal performance than the others. Double-pipe heat exchanger performance is determined based on heat transfer coefficient, pressure drop and effectiveness. Heat transfer efficiency and pressure drop are defined in terms of the Nusselt (Nu) number and the friction factor (f), respectively. The purpose of this study is to analyze the performance of multiple pipe heat exchangers by varying the Reynolds number as follows 2500, 3500, 4500, 5500, and 6500 using Ansys Fluent software. Based this research, it is found that the increase Nre (reynold number), Nu (nusselt number) and e (effectiveness) are also increasing, and f (friction factor) is decreasing. The Nusselt number is increased 2.13 times from 22.68 to 48.33, the friction factor decreased 2.44 times from 0.083 to 0.034, and the effectiveness increased 1.36 times from 0.225 to 0.306.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"312 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117060829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-01DOI: 10.1109/IES50839.2020.9231938
W. T. Sesulihatien, Dia Bitari Mei Yuana, A. Basuki
This paper deals with Larvae detection. There are 2 larvae in a similar genre, physically similar, but one larva (Aedes) is a vector of dangerous dengue fever, while Culex is not. Kinematic feature: velocity and acceleration, are employed to distinguish them. Video data of 120 samples are analyzed. The process consists of optical flow for image analysis, velocity and acceleration of motion for drawing the pattern, deviation standard for classifying, and Web-GIS user interface for displaying the result. The accuracy of the system is 91.6%.
{"title":"Kinematic Feature for Classifying Larvae: Aedes Larvae and Culex Larvae","authors":"W. T. Sesulihatien, Dia Bitari Mei Yuana, A. Basuki","doi":"10.1109/IES50839.2020.9231938","DOIUrl":"https://doi.org/10.1109/IES50839.2020.9231938","url":null,"abstract":"This paper deals with Larvae detection. There are 2 larvae in a similar genre, physically similar, but one larva (Aedes) is a vector of dangerous dengue fever, while Culex is not. Kinematic feature: velocity and acceleration, are employed to distinguish them. Video data of 120 samples are analyzed. The process consists of optical flow for image analysis, velocity and acceleration of motion for drawing the pattern, deviation standard for classifying, and Web-GIS user interface for displaying the result. The accuracy of the system is 91.6%.","PeriodicalId":344685,"journal":{"name":"2020 International Electronics Symposium (IES)","volume":"281 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132070970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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