Pub Date : 2019-09-01DOI: 10.1109/ICITACEE.2019.8904440
Surjandy, Erick Fernando, Meyliana, Y. Eni, Alexandra Joya, Dimitrij Fajar Satria Dharma
Online Transportation System rapidly growing in Indonesia contemporary. Several researches performed and reported that passenger of online mostly female. However, the passenger data very valuable and monetized, the transaction of selling account offer online. Therefore, the research will explore the data privacy factor of female passenger online transportation system. The study conducted by using SPSS Tools with correlation bivariate technique to explain the correlation of data privacy factor with the female passenger background. The 408 respondent of female online transportation passenger. The research found 8 correlations factor between background respondent and data privacy. The 8 correlations factor found become the novelty of this research, and it will be valuable for future research.
{"title":"Data Privacy factor of Female passenger's data in Indonesia Online Transportation System","authors":"Surjandy, Erick Fernando, Meyliana, Y. Eni, Alexandra Joya, Dimitrij Fajar Satria Dharma","doi":"10.1109/ICITACEE.2019.8904440","DOIUrl":"https://doi.org/10.1109/ICITACEE.2019.8904440","url":null,"abstract":"Online Transportation System rapidly growing in Indonesia contemporary. Several researches performed and reported that passenger of online mostly female. However, the passenger data very valuable and monetized, the transaction of selling account offer online. Therefore, the research will explore the data privacy factor of female passenger online transportation system. The study conducted by using SPSS Tools with correlation bivariate technique to explain the correlation of data privacy factor with the female passenger background. The 408 respondent of female online transportation passenger. The research found 8 correlations factor between background respondent and data privacy. The 8 correlations factor found become the novelty of this research, and it will be valuable for future research.","PeriodicalId":319683,"journal":{"name":"2019 6th International Conference on Information Technology, Computer and Electrical Engineering (ICITACEE)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126408652","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 : 2019-09-01DOI: 10.1109/ICITACEE.2019.8904223
Elfira Nureza Ardina, E. Wardihani, Samuel Beta Kuntardjo
Wireless Sensor Network (WSN) is one type of distributed wireless network consisting of a set of sensor nodes for the process of sensors, monitoring, sending data and information to users through internet communication without usicables. The Process of propagating data transmission between on WSN is strongly influenced by the condition of the media being passed. Media open space conditions without obstruction is of course different from the conditions there are obstacles (in forms such as buildings, surrounding signal interference, vehicle traffic and so on). In this study we will observe the characteristics of propagation that occur on the railroad track, when there is a train passing or not crossing. The propagation characteristics observed were pathloss and fading. Pathloss is a signal attenuation that result in the loss of the amount of power in a certain distance, while fading is a change in phase, the polarization of a signal against time. The purpose of the research that will be carried out is to analyze the characteristics of propagation in WSN data that occurs along the railroad tracks when there is / does not pass trains. The results will be compared with the characteristics of the propagation model in open space without obstacles and the formulation theory of propagation characteristics. The research method created is to create a system design to be able to know RSSI data along the railroad track from the data obtained will be analytic analysis to find the magnitude of pathloss and fading. From the simulation and analytic results the propagation model will be reduced along the railroad track.
{"title":"The Track Characteristics and The Propagation Model in Train Traffic For Automatic Traffic Door System","authors":"Elfira Nureza Ardina, E. Wardihani, Samuel Beta Kuntardjo","doi":"10.1109/ICITACEE.2019.8904223","DOIUrl":"https://doi.org/10.1109/ICITACEE.2019.8904223","url":null,"abstract":"Wireless Sensor Network (WSN) is one type of distributed wireless network consisting of a set of sensor nodes for the process of sensors, monitoring, sending data and information to users through internet communication without usicables. The Process of propagating data transmission between on WSN is strongly influenced by the condition of the media being passed. Media open space conditions without obstruction is of course different from the conditions there are obstacles (in forms such as buildings, surrounding signal interference, vehicle traffic and so on). In this study we will observe the characteristics of propagation that occur on the railroad track, when there is a train passing or not crossing. The propagation characteristics observed were pathloss and fading. Pathloss is a signal attenuation that result in the loss of the amount of power in a certain distance, while fading is a change in phase, the polarization of a signal against time. The purpose of the research that will be carried out is to analyze the characteristics of propagation in WSN data that occurs along the railroad tracks when there is / does not pass trains. The results will be compared with the characteristics of the propagation model in open space without obstacles and the formulation theory of propagation characteristics. The research method created is to create a system design to be able to know RSSI data along the railroad track from the data obtained will be analytic analysis to find the magnitude of pathloss and fading. From the simulation and analytic results the propagation model will be reduced along the railroad track.","PeriodicalId":319683,"journal":{"name":"2019 6th International Conference on Information Technology, Computer and Electrical Engineering (ICITACEE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127810716","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 : 2019-09-01DOI: 10.1109/ICITACEE.2019.8904198
Sumardi, H. Afrisal, Taufik Rahmadani, Wisnu Dyan Nugroho, Dhamastya Adhi Putra
Inertial navigation systems is used to determine the attitude estimation and bearing navigation of a quadrotor. The design implemented in this research uses IMU (Inertial Measurement Unit) and GPS (Global Positioning System) sensor. The attitude estimates are obtained from a complementary filter by combining the measurements from the IMU sensor. Bearing navigation can determine the quadrotor's rotation by calculating the the difference between the actual value of the quadrotor and the given setpoint Longitude-Latitude value. By this research, the average error of GPS sensor is 3,86 m, average error of compass is 3,4°, average error of attitude estimation is roll: 23,63°,pitch: 16,67°, and yaw: 14,88°, bearing angle and yaw rotation direction calculations performed by the system are correct.
{"title":"Inertial Navigation System of Quadrotor Based on IMU and GPS Sensors","authors":"Sumardi, H. Afrisal, Taufik Rahmadani, Wisnu Dyan Nugroho, Dhamastya Adhi Putra","doi":"10.1109/ICITACEE.2019.8904198","DOIUrl":"https://doi.org/10.1109/ICITACEE.2019.8904198","url":null,"abstract":"Inertial navigation systems is used to determine the attitude estimation and bearing navigation of a quadrotor. The design implemented in this research uses IMU (Inertial Measurement Unit) and GPS (Global Positioning System) sensor. The attitude estimates are obtained from a complementary filter by combining the measurements from the IMU sensor. Bearing navigation can determine the quadrotor's rotation by calculating the the difference between the actual value of the quadrotor and the given setpoint Longitude-Latitude value. By this research, the average error of GPS sensor is 3,86 m, average error of compass is 3,4°, average error of attitude estimation is roll: 23,63°,pitch: 16,67°, and yaw: 14,88°, bearing angle and yaw rotation direction calculations performed by the system are correct.","PeriodicalId":319683,"journal":{"name":"2019 6th International Conference on Information Technology, Computer and Electrical Engineering (ICITACEE)","volume":"145 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114310082","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 : 2019-09-01DOI: 10.1109/ICITACEE.2019.8904344
Gede Putra Kusuma, Kristopher David Harjono, Muhammad Taufik Dwi Putra
Weighted Longest Increasing Subsequence (WLIS) and its improvement, Best Increasing Subsequence (BIS) are two methods that has been proposed for pair verification in object instance recognition using local features. Tested on the Stanford Mobile Visual Dataset (SMVS), the BIS achieves better performance than WLIS on most categories, except for the “video frames” category. In this paper we propose several modifications to BIS which resulted in a better overall performance compared to the WLIS and the basic BIS approaches. On average, the proposed Best Score Increasing Subsequence (BSIS) performs 4.53% better than the BIS and 9.43% better than the WLIS.
{"title":"Geometric Verification Method of Best Score Increasing Subsequence for Object Instance Recognition","authors":"Gede Putra Kusuma, Kristopher David Harjono, Muhammad Taufik Dwi Putra","doi":"10.1109/ICITACEE.2019.8904344","DOIUrl":"https://doi.org/10.1109/ICITACEE.2019.8904344","url":null,"abstract":"Weighted Longest Increasing Subsequence (WLIS) and its improvement, Best Increasing Subsequence (BIS) are two methods that has been proposed for pair verification in object instance recognition using local features. Tested on the Stanford Mobile Visual Dataset (SMVS), the BIS achieves better performance than WLIS on most categories, except for the “video frames” category. In this paper we propose several modifications to BIS which resulted in a better overall performance compared to the WLIS and the basic BIS approaches. On average, the proposed Best Score Increasing Subsequence (BSIS) performs 4.53% better than the BIS and 9.43% better than the WLIS.","PeriodicalId":319683,"journal":{"name":"2019 6th International Conference on Information Technology, Computer and Electrical Engineering (ICITACEE)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124605159","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 : 2019-09-01DOI: 10.1109/ICITACEE.2019.8904112
Salam Hamdan, A. Awajan, Akram Al-Kouz
Due to the improvement in technology, smart devices and smart applications are included in most of human life aspects, and in order to make the interconnection between human and these applications and devices simpler, making these devices and applications understand the spoken language is essential. Speech recognition is the field that is meant to analyze and understand the spoken language. In this paper a new model is proposed to classify the Arabic words into two classes: subject name class or object name class. The Mel Frequency Cepstral Coefficient transformation is used to extract the features from the uttered words, and finally a MAHALANOBIS DISTANCE is used to classify the words using MATLAB tool. The data set that is used contained of 100 Arabic words 50 are subject names and 50 are object names. The results show that the accuracy of detecting subject and object name is 96%. (Abstract)
{"title":"Using Minimum Distance to Classify Uttered Arabic Words into Subject - Object Name","authors":"Salam Hamdan, A. Awajan, Akram Al-Kouz","doi":"10.1109/ICITACEE.2019.8904112","DOIUrl":"https://doi.org/10.1109/ICITACEE.2019.8904112","url":null,"abstract":"Due to the improvement in technology, smart devices and smart applications are included in most of human life aspects, and in order to make the interconnection between human and these applications and devices simpler, making these devices and applications understand the spoken language is essential. Speech recognition is the field that is meant to analyze and understand the spoken language. In this paper a new model is proposed to classify the Arabic words into two classes: subject name class or object name class. The Mel Frequency Cepstral Coefficient transformation is used to extract the features from the uttered words, and finally a MAHALANOBIS DISTANCE is used to classify the words using MATLAB tool. The data set that is used contained of 100 Arabic words 50 are subject names and 50 are object names. The results show that the accuracy of detecting subject and object name is 96%. (Abstract)","PeriodicalId":319683,"journal":{"name":"2019 6th International Conference on Information Technology, Computer and Electrical Engineering (ICITACEE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133256689","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 : 2019-09-01DOI: 10.1109/ICITACEE.2019.8904311
D. F. Murad, Adhi Gustian Iskandar, Erick Fernando, Tica Shinta Octavia, Deryan Everestha Maured
In recent years, various online learning models called Massive Online Open Courses (MOOC) have been mediated by smart and effective computers that play an important role in the acquisition of knowledge for learning. Discussion forums, also referred to as a means to discuss all learning materials and conference systems, are also a means to discuss the material as a substitute for face-to-face meetings between students and lecturers. This phenomenon is also found in online learning. Unfortunately, online learning is not supported by 24-hour real-time lecturer responses. Therefore, the purpose of this study is to identify, analyze needs, and design Chatbots that can be used as role models to develop LMS as an intelligent academic information system, especially to support 24 hours of interactive learning processes in all subjects. This study uses the Natural Language Processing approach to generate responses such as daily conversations. The analysis is done and used to design chatbots that can maximize LMS work that is smart and can help student learning activities, especially around the most frequently asked questions. After being tested on several subjects in the Information System Engineering group, it is known that Chatbot can interact with students like having daily conversations. In the future, the results of this study are used as supporting systems for recommendations on smart LMS.
{"title":"Towards Smart LMS to Improve Learning Outcomes Students Using LenoBot with Natural Language Processing","authors":"D. F. Murad, Adhi Gustian Iskandar, Erick Fernando, Tica Shinta Octavia, Deryan Everestha Maured","doi":"10.1109/ICITACEE.2019.8904311","DOIUrl":"https://doi.org/10.1109/ICITACEE.2019.8904311","url":null,"abstract":"In recent years, various online learning models called Massive Online Open Courses (MOOC) have been mediated by smart and effective computers that play an important role in the acquisition of knowledge for learning. Discussion forums, also referred to as a means to discuss all learning materials and conference systems, are also a means to discuss the material as a substitute for face-to-face meetings between students and lecturers. This phenomenon is also found in online learning. Unfortunately, online learning is not supported by 24-hour real-time lecturer responses. Therefore, the purpose of this study is to identify, analyze needs, and design Chatbots that can be used as role models to develop LMS as an intelligent academic information system, especially to support 24 hours of interactive learning processes in all subjects. This study uses the Natural Language Processing approach to generate responses such as daily conversations. The analysis is done and used to design chatbots that can maximize LMS work that is smart and can help student learning activities, especially around the most frequently asked questions. After being tested on several subjects in the Information System Engineering group, it is known that Chatbot can interact with students like having daily conversations. In the future, the results of this study are used as supporting systems for recommendations on smart LMS.","PeriodicalId":319683,"journal":{"name":"2019 6th International Conference on Information Technology, Computer and Electrical Engineering (ICITACEE)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128329686","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 : 2019-09-01DOI: 10.1109/ICITACEE.2019.8904162
Iwan Binanto, H. L. Hendric Spits Warnars, N. F. Sianipar, B. S. Abbas
This paper provides information about open source softwares that most often used as a tool to analyze data generated from the Liquid chromatography-mass spectrometer (LC-MS) instrument and including a little discussion about how LC-MS works. LC-MS consists of Liquid Chromatography and Mass Spectrometer analytical instruments. This device extensively used in Metabolomics, because it provides more comprehensive information about the metabolites. It also shows the breadth of the diversity of chemical compounds in metabolites that make difficult and time-consuming to identification of metabolite's structures. This is an obstacle in efficient and accurate identification. So, many open source softwares developed to simplify and speed up the analysis and interpretation of LC-MS result. There are popular open source softwares. We compiling mini review of this open source softwares. The conclusion is open source softwares quite helpful in terms of data analysis and interpretation of compounds contained, but no one has provided a single interpretation, still need experts for reliable interpretation.
{"title":"LC-MS Analysis: Mini Review Frequently Used Open Source Softwares","authors":"Iwan Binanto, H. L. Hendric Spits Warnars, N. F. Sianipar, B. S. Abbas","doi":"10.1109/ICITACEE.2019.8904162","DOIUrl":"https://doi.org/10.1109/ICITACEE.2019.8904162","url":null,"abstract":"This paper provides information about open source softwares that most often used as a tool to analyze data generated from the Liquid chromatography-mass spectrometer (LC-MS) instrument and including a little discussion about how LC-MS works. LC-MS consists of Liquid Chromatography and Mass Spectrometer analytical instruments. This device extensively used in Metabolomics, because it provides more comprehensive information about the metabolites. It also shows the breadth of the diversity of chemical compounds in metabolites that make difficult and time-consuming to identification of metabolite's structures. This is an obstacle in efficient and accurate identification. So, many open source softwares developed to simplify and speed up the analysis and interpretation of LC-MS result. There are popular open source softwares. We compiling mini review of this open source softwares. The conclusion is open source softwares quite helpful in terms of data analysis and interpretation of compounds contained, but no one has provided a single interpretation, still need experts for reliable interpretation.","PeriodicalId":319683,"journal":{"name":"2019 6th International Conference on Information Technology, Computer and Electrical Engineering (ICITACEE)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116783802","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 : 2019-09-01DOI: 10.1109/ICITACEE.2019.8904091
Sumardi, H. Afrisal, Taufik Rahmadani, Wisnu Dyan Nugroho, Dhamastya Adhi Putra
Inertial navigation systems is used to determine the attitude estimation and bearing navigation of a quadrotor. The design implemented in this research uses IMU (Inertial Measurement Unit) and GPS (Global Positioning System) sensor. The attitude estimates are obtained from a complementary filter by combining the measurements from the IMU sensor. Bearing navigation can determine the quadrotor's rotation by calculating the the difference between the actual value of the quadrotor and the given setpoint Longitude-Latitude value. By this research, the average error of GPS sensor is 3,86 m, average error of compass is 3, 4°, average error of attitude estimation is roll: 23,63 °pitch: 16,67°, and yaw: 14,88°. bearing angle and yaw rotation direction calculations performed by the system are correct.
{"title":"Inertial Navigation System of Quadrotor Based on IMU and GPS Sensors","authors":"Sumardi, H. Afrisal, Taufik Rahmadani, Wisnu Dyan Nugroho, Dhamastya Adhi Putra","doi":"10.1109/ICITACEE.2019.8904091","DOIUrl":"https://doi.org/10.1109/ICITACEE.2019.8904091","url":null,"abstract":"Inertial navigation systems is used to determine the attitude estimation and bearing navigation of a quadrotor. The design implemented in this research uses IMU (Inertial Measurement Unit) and GPS (Global Positioning System) sensor. The attitude estimates are obtained from a complementary filter by combining the measurements from the IMU sensor. Bearing navigation can determine the quadrotor's rotation by calculating the the difference between the actual value of the quadrotor and the given setpoint Longitude-Latitude value. By this research, the average error of GPS sensor is 3,86 m, average error of compass is 3, 4°, average error of attitude estimation is roll: 23,63 °pitch: 16,67°, and yaw: 14,88°. bearing angle and yaw rotation direction calculations performed by the system are correct.","PeriodicalId":319683,"journal":{"name":"2019 6th International Conference on Information Technology, Computer and Electrical Engineering (ICITACEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126617113","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 : 2019-09-01DOI: 10.1109/ICITACEE.2019.8904125
Ratna Aminah, A. H. Saputro
Diabetes is a disease whose initial symptoms are often undetectable. As a result, many cases of diabetes are not detected early. Iridology can be an alternative to detect diabetes early. This method can reveal the state of the organ in the body before the appearance of symptoms of a disease. In this paper, a diabetes prediction system based on iridology or through iris images was constructed using machine learning. Machine learning used to simplify the detection process. The developed system consists of eye image acquisition instruments and image processing algorithms. Iris images were captured using Camera Iriscope Iris Analyzer Iridology. The GLCM (Gray Level Co-Occurrence Matrix) method is used for feature extraction processes to obtaining texture characteristics in the image. The kNN (k Nearest Neighbor) method are used to classify diabetic and non-diabetic classes. The classification results are then validated by using the k-fold cross-validation method and evaluated by using the confusion matrix. Two subject groups were evaluated: one was 16 subjects non-diabetic and 11 subjects diabetic. The results show that the accuracy is 85.6%, false-positive rate (FPR) is 11.07%, false-negative rate (FNR) 20.40%, specificity 0.889, and sensitivity 0.796.
{"title":"Diabetes Prediction System Based on Iridology Using Machine Learning","authors":"Ratna Aminah, A. H. Saputro","doi":"10.1109/ICITACEE.2019.8904125","DOIUrl":"https://doi.org/10.1109/ICITACEE.2019.8904125","url":null,"abstract":"Diabetes is a disease whose initial symptoms are often undetectable. As a result, many cases of diabetes are not detected early. Iridology can be an alternative to detect diabetes early. This method can reveal the state of the organ in the body before the appearance of symptoms of a disease. In this paper, a diabetes prediction system based on iridology or through iris images was constructed using machine learning. Machine learning used to simplify the detection process. The developed system consists of eye image acquisition instruments and image processing algorithms. Iris images were captured using Camera Iriscope Iris Analyzer Iridology. The GLCM (Gray Level Co-Occurrence Matrix) method is used for feature extraction processes to obtaining texture characteristics in the image. The kNN (k Nearest Neighbor) method are used to classify diabetic and non-diabetic classes. The classification results are then validated by using the k-fold cross-validation method and evaluated by using the confusion matrix. Two subject groups were evaluated: one was 16 subjects non-diabetic and 11 subjects diabetic. The results show that the accuracy is 85.6%, false-positive rate (FPR) is 11.07%, false-negative rate (FNR) 20.40%, specificity 0.889, and sensitivity 0.796.","PeriodicalId":319683,"journal":{"name":"2019 6th International Conference on Information Technology, Computer and Electrical Engineering (ICITACEE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127508608","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 : 2019-09-01DOI: 10.1109/ICITACEE.2019.8904278
A. Nursyahid, Tholud Aprilian, T. A. Setyawan, Helmy, Ari Sriyanto Nugroho, Deddy Susilo
The agricultural sector is an important sector for economic growth in Indonesia. This was indicated by the data from the Indonesian Ministry of Agriculture that stated the Gross Domestic Product (GDP) from 2013 to 2017 in the agricultural sector grew by 9.90%. Based on this data, a research that could help farmers in terms of improving the quality of their crops by providing plants with sufficient water intake was made. With this system, farmers will be able to monitor soil moisture using a laptop or a phone. In this research we evaluate the QoS of the communication between LoRa device. This system works by using a LoRa device operating at 433 MHz paired on 2 Nodes and 1 Gateway. Each node will be given 3 soil moisture sensors that will monitor soil moisture. Then, the sensor data will be sent to the gateway via a LoRa device. In the controlling mode, LoRa average delay and data loss are 196.96 ms (node1), 207.39 ms (node2) and 4.45% (node1), 10.03% (node2). That monitoring value is good value based on ETSI standard. But, in the monitoring mode, LoRa average delay are up to 10 s and average data loss are 6.67% from node1 and 13.34 % from node2.
农业部门是印尼经济增长的重要部门。印尼农业部的数据表明，从2013年到2017年，农业部门的国内生产总值(GDP)增长了9.90%。基于这些数据，一项研究可以通过为植物提供足够的水分来帮助农民提高作物的质量。有了这个系统，农民就可以用笔记本电脑或手机监测土壤湿度。本文对LoRa设备间通信的QoS进行了评价。该系统采用433mhz的LoRa设备，在2节点1网关上配对。每个节点将配备3个土壤湿度传感器，用于监测土壤湿度。然后，传感器数据将通过LoRa设备发送到网关。在控制模式下，LoRa平均时延为196.96 ms (node1)，数据丢失为207.39 ms (node2)，数据丢失为4.45% (node1)， 10.03% (node2)。该监测值是基于ETSI标准的良好值。但在监控模式下，LoRa的平均时延高达10 s, node1的平均数据丢失率为6.67%，node2的平均数据丢失率为13.34%。
{"title":"Automatic Sprinkler System for Water Efficiency Based on LoRa Network","authors":"A. Nursyahid, Tholud Aprilian, T. A. Setyawan, Helmy, Ari Sriyanto Nugroho, Deddy Susilo","doi":"10.1109/ICITACEE.2019.8904278","DOIUrl":"https://doi.org/10.1109/ICITACEE.2019.8904278","url":null,"abstract":"The agricultural sector is an important sector for economic growth in Indonesia. This was indicated by the data from the Indonesian Ministry of Agriculture that stated the Gross Domestic Product (GDP) from 2013 to 2017 in the agricultural sector grew by 9.90%. Based on this data, a research that could help farmers in terms of improving the quality of their crops by providing plants with sufficient water intake was made. With this system, farmers will be able to monitor soil moisture using a laptop or a phone. In this research we evaluate the QoS of the communication between LoRa device. This system works by using a LoRa device operating at 433 MHz paired on 2 Nodes and 1 Gateway. Each node will be given 3 soil moisture sensors that will monitor soil moisture. Then, the sensor data will be sent to the gateway via a LoRa device. In the controlling mode, LoRa average delay and data loss are 196.96 ms (node1), 207.39 ms (node2) and 4.45% (node1), 10.03% (node2). That monitoring value is good value based on ETSI standard. But, in the monitoring mode, LoRa average delay are up to 10 s and average data loss are 6.67% from node1 and 13.34 % from node2.","PeriodicalId":319683,"journal":{"name":"2019 6th International Conference on Information Technology, Computer and Electrical Engineering (ICITACEE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116706291","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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