2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)最新文献_第6页

Forecasting Total Population Using Chen, Cheng, and Markov Chain Fuzzy Time Series Models 用陈、程和马尔可夫链模糊时间序列模型预测总人口

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271682

M. Bettiza

{"title":"Forecasting Total Population Using Chen, Cheng, and Markov Chain Fuzzy Time Series Models","authors":"M. Bettiza","doi":"10.1109/ICITEE49829.2020.9271682","DOIUrl":"https://doi.org/10.1109/ICITEE49829.2020.9271682","url":null,"abstract":"Indonesia is a country with a very large population and a fairly high population growth. Population growth is one of the important indicators in demography that will affect the availability of food, land and employment. Hence, population growth data is very important to government when designing development policies. The fuzzy time series models have been widely used in previous studies to forecast enrollment data, stock exchanges and others. In this study, three types of fuzzy time series models were used namely Chen, Cheng, and Markov Chain models to predict the total population in Tanjugpinang city, Riau Islands Province. The models are compared based on error analysis, namely: Mean Average Percentage Error (MAPE) and Root Mean Square Error (RMSE) values. The results showed that Markov chain model yielded a very low MAPE, namely 0.0457%. The MAPE value for the Cheng model is 0.0535%, while the MAPE value for the Chen model as the reference model is 0.1428%. Based on the RMSE calculation, the Markov chain gives the best results with a value of 145, RMSE for Cheng 149 and the Chen model gives an RMSE value of 345. The best model obtained for population forecasting is the Markov chain as it has the smallest RMSE, and also the Markov chain model is the most accurate model in the used dataset based on the MAPE value.","PeriodicalId":245013,"journal":{"name":"2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125657910","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}

引用次数: 2

Building Effective and Efficient Procedure for Preprocessing Marketplace Data 建立有效和高效的程序来预处理市场数据

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271717

Usman Bustaman, Dhiar Niken Larasati, Zulfa Hidayah Satria Putri, Siti Mariyah, Takdir, S. Pramana

引用次数: 2

Evaluation of BER Performance for M-Ary QAM OFDM Through Wireless Channel by Controlling PAPR at the Transmitter 通过无线信道控制发射机的PAPR来评估M-Ary QAM OFDM的误码率性能

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271679

Vincent, A. Suhartomo

{"title":"Evaluation of BER Performance for M-Ary QAM OFDM Through Wireless Channel by Controlling PAPR at the Transmitter","authors":"Vincent, A. Suhartomo","doi":"10.1109/ICITEE49829.2020.9271679","DOIUrl":"https://doi.org/10.1109/ICITEE49829.2020.9271679","url":null,"abstract":"The implementation of FFT in OFDM system may provide many advantages, such as the bandwidth becomes more efficient and the signal performance over fading channel is better than single carrier signal. However, the PAPR of the signal is high and it can reach 10 dB, which is equivalent to a peak power that is 10 times higher than the average power. This way, the usage of FFT-based OFDM is not very efficient, especially in terms of power consumption at the transmitter. In this paper, a simulation was done to evaluate the BER performance of the signal with the implementation of several PAPR reduction techniques, such as the wavelet transform, Partial Transmit Sequence (PTS) technique, and also the clipping technique. The implementation was done with the 16 QAM and 64 QAM, and also the signal was sent through Rayleigh fading channel. The result shows that for 16 QAM, the best result is achieved by using db1 with PTS technique. With Eb/No value of 20 dB, the BER can be 10−3, which is 7 dB better than the normal FFT-based OFDM system. As for 64 QAM, the best result is achieved by the usage of normal db3 without PTS nor clipping technique. With Eb/No value of 24 dB, the BER can be 10−3, which is 4.5 dB better than FFT-based OFDM system.","PeriodicalId":245013,"journal":{"name":"2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134368908","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}

引用次数: 1

Adaptive Neuro-Fuzzy Inference System on Aquaphotomics Development for Aquaponic Water Nutrient Assessments and Analyses 自适应神经模糊推理系统在水培水体养分评价与分析中的应用

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271736

Sandy C. Lauguico, R. Baldovino, Ronnie S. Concepcion, Jonnel D. Alejandrino, Rogelio Ruzcko Tobias, E. Dadios

{"title":"Adaptive Neuro-Fuzzy Inference System on Aquaphotomics Development for Aquaponic Water Nutrient Assessments and Analyses","authors":"Sandy C. Lauguico, R. Baldovino, Ronnie S. Concepcion, Jonnel D. Alejandrino, Rogelio Ruzcko Tobias, E. Dadios","doi":"10.1109/ICITEE49829.2020.9271736","DOIUrl":"https://doi.org/10.1109/ICITEE49829.2020.9271736","url":null,"abstract":"Water quality monitoring, assessment, and analysis in an aquaponics system are vital procedures in maintaining a productive and an efficient ecosystem for cultivars being cultured. However, these require labor-intensive, long-standing, and high-priced laboratory methods, as water quality and its nutrients are dependent on micro-biological and physio-chemical variables. To reduce the use of costly sensors and the time consumed for expensive calculations, an Adaptive Neuro-Fuzzy Inference System (ANFIS)-based aquaphotomics approach is conducted on this study. Water samples were collected from a pond water of an aquaponics system (AP) where species of fish are cultivated. The samples went through aquaphotomics with the aid of spectrophotometer and was applied on to near infrared, visible light, and ultraviolet (NIR-Vis-UV) spectrum with wavelength range of 100 to 1000 nm. Spectrometry was utilized to determine three significant nutrient compounds which are the nitrate, phosphate, and potassium. Temperature, power of hydrogen (pH), and electrical conductivity sensors (EC) were used simultaneously to serve as data attributes in predicting the three compounds assigned as targets. Feature selection algorithms such as Minimum Redundancy Maximum Relevance (MRMR) and Univariate Feature Ranking for Regression Using F-Tests (UFT) were used to determine the two most significant predictor relative to a specific target. Results showed that MRMR with ANFIS is best used for predicting Phosphate with R2 value of 0.8284. The UFT with ANFIS produced the best performance for regressing Nitrate and Potassium with R2 values of 0.9321 and 0.9961 respectively.","PeriodicalId":245013,"journal":{"name":"2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133846910","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}

引用次数: 16

Measurement of Export Data Quality Using Task-Based Data Quality (TBDQ): Case Study of the Directorate General of Customs and Excise 使用基于任务的数据质量(TBDQ)测量出口数据质量:海关总署案例研究

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271755

I. N. Prama Pradnyana, Dhea Junestya Pradipta, Y. Ruldeviyani

{"title":"Measurement of Export Data Quality Using Task-Based Data Quality (TBDQ): Case Study of the Directorate General of Customs and Excise","authors":"I. N. Prama Pradnyana, Dhea Junestya Pradipta, Y. Ruldeviyani","doi":"10.1109/ICITEE49829.2020.9271755","DOIUrl":"https://doi.org/10.1109/ICITEE49829.2020.9271755","url":null,"abstract":"The Indonesian Directorate General of Customs and Excise (DGCE), as the regulator of export policies in Indonesia, is required to have good quality export data. However, in its management, export data were reported to have persistent problems based on reports of export evaluations and the results of data cleansing with relevant stakeholders. These problems should be addressed immediately because export data is vital for Indonesia, therefore it is necessary to measure the quality of export data at the Indonesian DGCE. One of the benefits of measuring export data is to investigate existing data problems, hence it is easier to set a number of improvements. This study uses the Task-Based Data Quality (TBDQ) framework because it matches the characteristics of the export information system. The dimensions used in this study are Completeness, Accuracy, Timeliness, and Consistency determined from interviews with experts. The results showed that the quality of export data is not yet optimal with the highest anomaly percentage of 1.4494%. Improvements of the anomalous data are made based on the Improving Task by the weighting calculation, that has been done using the Analytic Hierarchy Process (AHP) so that the problems of data accuracy and differences in the results of data cleansing can be eliminated.","PeriodicalId":245013,"journal":{"name":"2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131166835","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}

引用次数: 1

Unit Commitment with Primary Frequency Regulation Consideration in the Southern Sulawesi Power System 南苏拉威西电力系统中考虑一次频率调节的机组承诺

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271759

C. Nugraha, Lesnanto Multa Putranto, Muhammad Isnaeni Bambang Setyonegoro, Sarjiya, S. Isnandar

{"title":"Unit Commitment with Primary Frequency Regulation Consideration in the Southern Sulawesi Power System","authors":"C. Nugraha, Lesnanto Multa Putranto, Muhammad Isnaeni Bambang Setyonegoro, Sarjiya, S. Isnandar","doi":"10.1109/ICITEE49829.2020.9271759","DOIUrl":"https://doi.org/10.1109/ICITEE49829.2020.9271759","url":null,"abstract":"To increase the penetration level of renewable energy generation, the readiness of the existing power system needs to be considered, especially in terms of the system’s ramping rate and frequency response capability. Even, a high penetration level of renewable energy can potentially reduce generating units generation cost, the system capability to perform the frequency response is decreased. For this reason, the quality of the frequency response needs to be considered in operation planning. In this paper, a unit commitment model was developed with considering the adequacy of primary frequency regulation (PFR). The effect of PFR constraints was analyzed by comparing the scheduling results and the frequency response with the conventional UC models. The result of this research shows that by considering the PFR constraints, the optimization results in an increasing number of committed generating units, thus resulting in more distributed reserves. The additional constraints increase the conventional unit generation costs from $48,017 to $51,636 on the simulated scenario. However, the proposed model shows its advantages in the system dynamic frequency performance, shown by an increase in frequency nadir and steady-state frequency of 490 mHz and 70 mHz respectively during low load conditions.","PeriodicalId":245013,"journal":{"name":"2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131232196","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}

引用次数: 0

Fixed Point Arithmetic Implementation of Digital Proportional - Resonant Single-Phase Current Controllers 数字比例谐振单相电流控制器的定点算法实现

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271678

I. Setiawan, A. Hidayatno, Haris Kuspranoto, T. Andromeda, M. Facta, H. Hermawan

引用次数: 2

Performance Analysis of Message Broker for Communication in Fog Computing 雾计算中通信消息代理的性能分析

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271733

Aditya Bagaskara, Setyorini Setyorini, Aulia Arif Wardana

{"title":"Performance Analysis of Message Broker for Communication in Fog Computing","authors":"Aditya Bagaskara, Setyorini Setyorini, Aulia Arif Wardana","doi":"10.1109/ICITEE49829.2020.9271733","DOIUrl":"https://doi.org/10.1109/ICITEE49829.2020.9271733","url":null,"abstract":"In this research, performance testing is performed between the two most popular message brokers, which commonly used in the enterprise, namely RabbitMQ and Apache Kafka in the fog computing environment. REST API is a method that implements the HTTP protocol and commonly used in the Internet of Things as a communication media between devices. Hence the performance will degrade when the amount of request is abundant and less reliable due to its synchronous communication. By using a message broker as the medium of communication between devices in fog computing, each connected device will not rely on each other and will make the message delivery more guaranteed. By reason, this research will implement a message broker for communication between devices in fog computing. Today there are many message brokers developed by various companies or communities. Choosing an unsuitable message broker can cause performance degradation, which results in a chaotic IoT system. The test results show that Apache Kafka has a higher throughput than RabbitMQ when the message size is calculable. However, when the message size is myriad, RabbitMQ is much better because the bottleneck of disk I/O usage occurred in Kafka. Nevertheless, in latency testing, RabbitMQ is always better even though the difference is not too far. This testing can also be concluded that the use of message broker in fog computing that extends the cloud computing architecture proven effective in implementing the IoT system.","PeriodicalId":245013,"journal":{"name":"2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116011587","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}

引用次数: 5

Maize field area detection in East Java, Indonesia: An integrated multispectral remote sensing and machine learning approach 印度尼西亚东爪哇玉米田面积检测:综合多光谱遥感和机器学习方法

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271683

A. Wijayanto, Dwi Wahyu Triscowati, Arif Handoyo Marsuhandi

{"title":"Maize field area detection in East Java, Indonesia: An integrated multispectral remote sensing and machine learning approach","authors":"A. Wijayanto, Dwi Wahyu Triscowati, Arif Handoyo Marsuhandi","doi":"10.1109/ICITEE49829.2020.9271683","DOIUrl":"https://doi.org/10.1109/ICITEE49829.2020.9271683","url":null,"abstract":"An accurate and high quality of agricultural monitoring and statistics commonly requires a huge amount of resources in terms of human, cost, and time. In this paper, we introduce a cost-efficient, scalable, and accurate framework for multilabel classification of the maize (corn) field area using remote sensing approaches. Official statistical survey results are used to provide the ground truth labels. Five vegetation indices, which include the enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), normalized difference water index (NDWI), normalized difference built-up index (NDBI), and visible atmospherically resistant index (VARI), are used to enhance the multitemporal features and predictor variables. We train an ensemble machine learning model, random forest (RF) as the classifier. Experiments are carried out to detect maize field areas in ten regencies of East Java, Indonesia using multispectral imagery data acquired by Landsat-8, Sentinel-1, and Sentinel-2 satellites. The results show that our proposed approach gains a promising accuracy of up to 87 percent in detecting maize field area. We believe that our framework could be beneficial to support and improve the quality of official statistics in the agricultural sector.","PeriodicalId":245013,"journal":{"name":"2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126784704","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}

引用次数: 14

Characteristics of Partial Discharge Inception Voltage Patterns Using Antenna in Air Insulation 空气绝缘天线局部放电起始电压特征

2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2020-10-06 DOI: 10.1109/ICITEE49829.2020.9271773

I. M. Yulistya Negara, D. Fahmi, D. A. Asfani, I. G. N. Satriyadi Hernanda, Juan Christian Soebagio, Violyn Yulistika Siahaan

{"title":"Characteristics of Partial Discharge Inception Voltage Patterns Using Antenna in Air Insulation","authors":"I. M. Yulistya Negara, D. Fahmi, D. A. Asfani, I. G. N. Satriyadi Hernanda, Juan Christian Soebagio, Violyn Yulistika Siahaan","doi":"10.1109/ICITEE49829.2020.9271773","DOIUrl":"https://doi.org/10.1109/ICITEE49829.2020.9271773","url":null,"abstract":"High voltage equipment can be damaged when there is a failure of the insulation. Failure would be indicated by the Partial Discharge (PD) phenomenon during the pre-breakdown condition. PD detection methods commonly used, such as thermography and acoustic emission (AE), still have some weaknesses. Based on these conditions, this study discusses the detection method of PD containing Ultra High Frequency (UHF) in air insulation using an antenna that can capture electromagnetic waves. The electrodes used are needle to plane. The variables used are the shape and distance of the electrode. Characteristics analyzed during Partial Discharge Inception Voltage (PDIV). The data retrieved would be processed so that it would display Phase Resolved Partial Discharge (PRPD). The results obtained from the antenna would be compared with the leakage current method using the High Frequency Current Transformer (HFCT). PDIV pattern can be observed in the PRPD analysis, and each electrode has the characteristics of PD at a specific phase angle. The dominant PD point electrodes occur at an angle of 331.2 ° to 342 °, the dominant PD box electrodes occur at an angle of 334.8 ° to 356.4 °, and the dominant PD blunt electrode occurs at an angle of 306 ° to 313.2 °. So, it can be concluded that the loop antenna can detect and observe PDIV patterns in air insulation.","PeriodicalId":245013,"journal":{"name":"2020 12th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121701930","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}

引用次数: 0