Pub Date : 2017-07-01DOI: 10.1109/QIR.2017.8168485
Prihandoko, Bertalya, Muhammad Iqbal Ramadhan
Indonesia is one of the countries with diverse morphology of the lands, high mountains, and the tropical climates of frequent high rainfall. This condition often causes natural disasters in some areas of the country, which sometimes are so terrible that make a lot of people are missing and suffering. In order to reduce the impact of natural disasters to the people and environment, a research was conducted by capturing data showing the occurrence of the disasters and data about the weather conditions for the last five years. Data is obtained from the official sites of Indonesian National Board for Disaster Management (BNPB) and Indonesian Agency for Meteorological, Climatological, and Geophysics (BMKG). This data is then analyzed by using clustering data mining techniques i.e. k-means algorithm and k-medoids algorithm. The two methods are frequently used to make some analysis of data to find some hidden information. The result shows that weather is not the only factor causing natural disaster. By using the result, the government can make some plans for natural disaster mitigations.
{"title":"An analysis of natural disaster data by using K-means and K-medoids algorithm of data mining techniques","authors":"Prihandoko, Bertalya, Muhammad Iqbal Ramadhan","doi":"10.1109/QIR.2017.8168485","DOIUrl":"https://doi.org/10.1109/QIR.2017.8168485","url":null,"abstract":"Indonesia is one of the countries with diverse morphology of the lands, high mountains, and the tropical climates of frequent high rainfall. This condition often causes natural disasters in some areas of the country, which sometimes are so terrible that make a lot of people are missing and suffering. In order to reduce the impact of natural disasters to the people and environment, a research was conducted by capturing data showing the occurrence of the disasters and data about the weather conditions for the last five years. Data is obtained from the official sites of Indonesian National Board for Disaster Management (BNPB) and Indonesian Agency for Meteorological, Climatological, and Geophysics (BMKG). This data is then analyzed by using clustering data mining techniques i.e. k-means algorithm and k-medoids algorithm. The two methods are frequently used to make some analysis of data to find some hidden information. The result shows that weather is not the only factor causing natural disaster. By using the result, the government can make some plans for natural disaster mitigations.","PeriodicalId":225743,"journal":{"name":"2017 15th International Conference on Quality in Research (QiR) : International Symposium on Electrical and Computer Engineering","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129212848","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 : 2017-07-01DOI: 10.1109/QIR.2017.8168504
Rosalia H Subrata, Julian Leonard Hardenberg, F. Gozali
Magnetic Levitation or maglev is a method to make an object float in open air without any physical support utilizing force created by electromagnetic repulsion surrounding the object to counter the effect of gravitational force of the object. The object can be levitated if the force created by electromagnetic repulsion equalizes the weight of the object. Lately, this method can be found in many applications such as maglev trains, maglev toys, maglev clock, etc. In this research, we want to show how the Proportional Integral Derivative Controller also known as PID Controller can be used to stabilize magnetically levitated objects. The electromagnetic field is generated by using copper wire coil with 15 millihenry inductance while the object consists of two neodymium permanent magnetic button. The weight and the size of the magnet is 22 grams in mass with 0.5 cm in diameter and 0.5 cm thick. An N-Channel MOSFET Transistor is used to adjust the position of the object with the electromagnetic coil. The PID Controller is used to find the characteristics of the system. The system will stabilize objects floating in many different positions. Arduino Uno microcontroller is used to perform the PID Controller processing with the feedback from the Hall Effect sensor of the system. It is found that with PID parameters Kp = 2.1 Ki = 19.5 and Kd = 0.0025, the objects can be floating with stable condition at the position 1.5 cm from effect hall sensor and with Kp = 0.6, Ki = 3.0 and Kd = 0.0006, the objects can be floating with stable condition at the position 2.0 cm from the Hall Effect sensor. The range in which objects can float with stable condition is between 0.5 cm and 2.5 cm from the Hall Effect sensor of the system.
磁悬浮是一种利用物体周围的电磁斥力产生的力来抵消物体重力的影响，使物体在没有任何物理支撑的情况下漂浮在露天的方法。如果电磁斥力产生的力与物体的重量相等，物体就能悬浮起来。近年来，这种方法在磁浮列车、磁浮玩具、磁浮钟等方面得到了广泛的应用。在本研究中，我们希望展示比例积分导数控制器也称为PID控制器如何用于稳定磁悬浮物体。电磁场是用15毫安电感的铜线线圈产生的，物体由两个钕永磁按钮组成。磁铁的重量和尺寸为22g，直径0.5 cm，厚0.5 cm。n沟道MOSFET晶体管用于用电磁线圈调节物体的位置。PID控制器用于寻找系统的特性。该系统将稳定漂浮在许多不同位置的物体。采用Arduino Uno微控制器，根据系统霍尔效应传感器的反馈对PID控制器进行处理。结果表明，当PID参数Kp = 2.1, Ki = 19.5, Kd = 0.0025时，物体可以在距离霍尔传感器1.5 cm处稳定漂浮;当PID参数Kp = 0.6, Ki = 3.0, Kd = 0.0006时，物体可以在距离霍尔传感器2.0 cm处稳定漂浮。物体在距离系统霍尔效应传感器0.5 cm ~ 2.5 cm范围内稳定漂浮。
{"title":"The use of pid controller to get the stable floating condition of the objects in magnetic levitation system","authors":"Rosalia H Subrata, Julian Leonard Hardenberg, F. Gozali","doi":"10.1109/QIR.2017.8168504","DOIUrl":"https://doi.org/10.1109/QIR.2017.8168504","url":null,"abstract":"Magnetic Levitation or maglev is a method to make an object float in open air without any physical support utilizing force created by electromagnetic repulsion surrounding the object to counter the effect of gravitational force of the object. The object can be levitated if the force created by electromagnetic repulsion equalizes the weight of the object. Lately, this method can be found in many applications such as maglev trains, maglev toys, maglev clock, etc. In this research, we want to show how the Proportional Integral Derivative Controller also known as PID Controller can be used to stabilize magnetically levitated objects. The electromagnetic field is generated by using copper wire coil with 15 millihenry inductance while the object consists of two neodymium permanent magnetic button. The weight and the size of the magnet is 22 grams in mass with 0.5 cm in diameter and 0.5 cm thick. An N-Channel MOSFET Transistor is used to adjust the position of the object with the electromagnetic coil. The PID Controller is used to find the characteristics of the system. The system will stabilize objects floating in many different positions. Arduino Uno microcontroller is used to perform the PID Controller processing with the feedback from the Hall Effect sensor of the system. It is found that with PID parameters Kp = 2.1 Ki = 19.5 and Kd = 0.0025, the objects can be floating with stable condition at the position 1.5 cm from effect hall sensor and with Kp = 0.6, Ki = 3.0 and Kd = 0.0006, the objects can be floating with stable condition at the position 2.0 cm from the Hall Effect sensor. The range in which objects can float with stable condition is between 0.5 cm and 2.5 cm from the Hall Effect sensor of the system.","PeriodicalId":225743,"journal":{"name":"2017 15th International Conference on Quality in Research (QiR) : International Symposium on Electrical and Computer Engineering","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124525274","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 : 2017-07-01DOI: 10.1109/QIR.2017.8168471
E. S. Julian, K. Prawiroredjo, G. Tjahjadi
The number of people with diabetes increases every year in the whole world, including Indonesia. Diabetes is a major cause of stroke, heart attack, kidney failure, lower limb amputation and one of the leading causes of death. In order to manage their blood glucose level, diabetics have to test their blood glucose level as often as possible according to certain medical guidance, diet, exercise and consume medicine regularly. Unfortunately, the current blood glucose testing is inconvenient and uncomfortable, even cause pain for diabetic or patient; therefore, a noninvasive blood glucose measurement is highly desirable. Although several research works have already been done in this area, a successful noninvasive method is still in search. In order to contribute in this research area, we study the effect of glucose concentration in solutions with different concentration to the output voltage of a near infrared sensor as a preliminary research to obtain a successful noninvasive blood glucose meter. In this paper, we reported the model of near infrared sensor output voltage as a function of glucose concentration. The main components of the near infrared sensor are a 1450 nm light emitting diode (LED) as light source, and a photodiode that is sensitive to that wavelength as the sensing device. The distance between LED and photodiode is 15mm. The solutions have 50 mg/dl, 100 mg/dl, 200 mg/dl, 300 mg/dl, and 400 mg/dl glucose concentrations. An acrylic cylinder with 40 mm diameter was filled with 5 ml glucose solution for each concentration. The results show that higher glucose concentrations produce lower sensor output voltages. The linear trend line shows good fit with those data. The value of correlation coefficient is −0.99, which indicates strong relationship between the sensor output voltages and glucose concentrations.
{"title":"The Model of near infrared sensor output voltage as a function of glucose concentration in solution","authors":"E. S. Julian, K. Prawiroredjo, G. Tjahjadi","doi":"10.1109/QIR.2017.8168471","DOIUrl":"https://doi.org/10.1109/QIR.2017.8168471","url":null,"abstract":"The number of people with diabetes increases every year in the whole world, including Indonesia. Diabetes is a major cause of stroke, heart attack, kidney failure, lower limb amputation and one of the leading causes of death. In order to manage their blood glucose level, diabetics have to test their blood glucose level as often as possible according to certain medical guidance, diet, exercise and consume medicine regularly. Unfortunately, the current blood glucose testing is inconvenient and uncomfortable, even cause pain for diabetic or patient; therefore, a noninvasive blood glucose measurement is highly desirable. Although several research works have already been done in this area, a successful noninvasive method is still in search. In order to contribute in this research area, we study the effect of glucose concentration in solutions with different concentration to the output voltage of a near infrared sensor as a preliminary research to obtain a successful noninvasive blood glucose meter. In this paper, we reported the model of near infrared sensor output voltage as a function of glucose concentration. The main components of the near infrared sensor are a 1450 nm light emitting diode (LED) as light source, and a photodiode that is sensitive to that wavelength as the sensing device. The distance between LED and photodiode is 15mm. The solutions have 50 mg/dl, 100 mg/dl, 200 mg/dl, 300 mg/dl, and 400 mg/dl glucose concentrations. An acrylic cylinder with 40 mm diameter was filled with 5 ml glucose solution for each concentration. The results show that higher glucose concentrations produce lower sensor output voltages. The linear trend line shows good fit with those data. The value of correlation coefficient is −0.99, which indicates strong relationship between the sensor output voltages and glucose concentrations.","PeriodicalId":225743,"journal":{"name":"2017 15th International Conference on Quality in Research (QiR) : International Symposium on Electrical and Computer Engineering","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114410157","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 : 2017-07-01DOI: 10.1109/QIR.2017.8168484
M. Akil, I. Nurtanio, R. Sadjad
The aim of this research is to design an implementation of the speech recognition system to control the speed of a DC motor. The Linear Predictive Coding (LPC) method is used in the speed recognition system, tuned by the Adaptive Neuro-Fuzzy Inference Systems (ANFIS) method. There are 5 (five) samples of voice signals in Bahasa Indonesia recognized by this system, i.e.: “Nyala”, “Lambat”, “Sedang”, “Cepat” and “Mati”. Every voice signal is repeated 5 (five) times until as many as 25 samples are recorded. Their voice characteristics are extracted using the LPC method represented by the LPC coefficients stored in a database system. The ANFIS method is implemented in 50 iterations to tune and to train the LPC coefficients until the least error, i.e. 0,00012446 is obtained. Voice samples originated from the internal database system are 83% successfully recognized by this system. However; samples extracted from the human voice signals of different persons — different sex from the person whose voice signals are recorded in the database system, and from various ages — are only 78,8% successfully recognized by the system. The output of the speech recognition system is coded into the ASCII Codes and converted into the PWM signal to control the speed of a DC motor.
{"title":"A DC motor speed control using the LPC-ANFIS speech recognition system","authors":"M. Akil, I. Nurtanio, R. Sadjad","doi":"10.1109/QIR.2017.8168484","DOIUrl":"https://doi.org/10.1109/QIR.2017.8168484","url":null,"abstract":"The aim of this research is to design an implementation of the speech recognition system to control the speed of a DC motor. The Linear Predictive Coding (LPC) method is used in the speed recognition system, tuned by the Adaptive Neuro-Fuzzy Inference Systems (ANFIS) method. There are 5 (five) samples of voice signals in Bahasa Indonesia recognized by this system, i.e.: “Nyala”, “Lambat”, “Sedang”, “Cepat” and “Mati”. Every voice signal is repeated 5 (five) times until as many as 25 samples are recorded. Their voice characteristics are extracted using the LPC method represented by the LPC coefficients stored in a database system. The ANFIS method is implemented in 50 iterations to tune and to train the LPC coefficients until the least error, i.e. 0,00012446 is obtained. Voice samples originated from the internal database system are 83% successfully recognized by this system. However; samples extracted from the human voice signals of different persons — different sex from the person whose voice signals are recorded in the database system, and from various ages — are only 78,8% successfully recognized by the system. The output of the speech recognition system is coded into the ASCII Codes and converted into the PWM signal to control the speed of a DC motor.","PeriodicalId":225743,"journal":{"name":"2017 15th International Conference on Quality in Research (QiR) : International Symposium on Electrical and Computer Engineering","volume":"193 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121073147","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 : 2017-07-01DOI: 10.1109/QIR.2017.8168506
D. A. Kurniawan, M. Syai’in, S. Kautsar, M. K. Hasin, Boedi Herijono, J. Endrasmono, R. Soelistijono, A. Wahidin, L. Subiyanto, A. Setyoko, A. Soeprijanto
This paper will present an implementation of Extreme Learning Machine (ELM) in Prototype of Hand Typist Robot (HTR). HTR is Typist Robot which is designed for quadriplegic people. HTR consists of two robotic arms with three dynamixel AX-12 that mounted on each arm. It is mean that each arm has 3 DOF. To operate HTR, user has to equipped with compass sensor (CMPS10), installed on the part of body that has good function. In this paper ELM is used to map and make decision between the signal which sending by CMPS10 and position of alphabet that will be reached by Robot Arm. The advantage of ELM is superior in training process and easy to implement. Using ELM, the relationship between input and output can be present only using one simple matrix. From the experiment result shown that 73 keys of computer keyboard can be reached by HTR with an error 5%. The error is accumulated errors which is caused by vibration of dynamixel AX-12 when it is moving. To minimize the error the HTR need to reset regularly.
{"title":"Hand typist robot modelling for quadriplegic person using extreme learning machine","authors":"D. A. Kurniawan, M. Syai’in, S. Kautsar, M. K. Hasin, Boedi Herijono, J. Endrasmono, R. Soelistijono, A. Wahidin, L. Subiyanto, A. Setyoko, A. Soeprijanto","doi":"10.1109/QIR.2017.8168506","DOIUrl":"https://doi.org/10.1109/QIR.2017.8168506","url":null,"abstract":"This paper will present an implementation of Extreme Learning Machine (ELM) in Prototype of Hand Typist Robot (HTR). HTR is Typist Robot which is designed for quadriplegic people. HTR consists of two robotic arms with three dynamixel AX-12 that mounted on each arm. It is mean that each arm has 3 DOF. To operate HTR, user has to equipped with compass sensor (CMPS10), installed on the part of body that has good function. In this paper ELM is used to map and make decision between the signal which sending by CMPS10 and position of alphabet that will be reached by Robot Arm. The advantage of ELM is superior in training process and easy to implement. Using ELM, the relationship between input and output can be present only using one simple matrix. From the experiment result shown that 73 keys of computer keyboard can be reached by HTR with an error 5%. The error is accumulated errors which is caused by vibration of dynamixel AX-12 when it is moving. To minimize the error the HTR need to reset regularly.","PeriodicalId":225743,"journal":{"name":"2017 15th International Conference on Quality in Research (QiR) : International Symposium on Electrical and Computer Engineering","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129389987","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 : 2017-07-01DOI: 10.1109/QIR.2017.8168492
Indah SurvyanaWahyudi, A. Affandi, M. Hariadi
By the growth of digital data which leads to more complex demands from user to find the information or items. Search engines solve most of the problems but have the drawback, it depends on the query/term that the user enter. The problem appears when the user forget or does not know the query that associated with the items. The Recommendation comes as a solution to provide personal information by studying the interaction of a user, user community, and items that have been recorded previously. Collaborative filtering as a method to provide personalized recommendations based on other users who have similar tastes. However, the results of collaborative filtering tend random, sometimes users need an item with similar genre/subjects. This paper discusses a model of a recommendation engine for new users with a method of collaborative filtering based on genre similarly with the aim of giving the smallest error with high precision. First filter we use Alternating Least Square-Weight Regularization (ALS-WR) is selected as algorithms for collaborative filtering. Second filter we use Cosine Similarity is selected as an algorithm for genre similarity. We use datasets from movielens.org. The RMSE on the first recommendation generated is 0.89 for 100K ratings, 0.86 for the 1M ratings, and 0.81 for the 10M rating. By iterative and training on larger data, it will make a better model, so RMSE can be smaller. They are concluded that ALS-WR able to deliver adaptive, with regulatory parameters that can be controlled and adjusted. The more data but the error on the wane, that is means this algorithm is suitable for growing data or big data. The item that has been sorted with the ALS-WR algorithm, letter approximated with cosine similarity, and with only 10 items movie displays with the highest degree of similarity, that be able to generate high precision.
{"title":"Recommender engine using cosine similarity based on alternating least square-weight regularization","authors":"Indah SurvyanaWahyudi, A. Affandi, M. Hariadi","doi":"10.1109/QIR.2017.8168492","DOIUrl":"https://doi.org/10.1109/QIR.2017.8168492","url":null,"abstract":"By the growth of digital data which leads to more complex demands from user to find the information or items. Search engines solve most of the problems but have the drawback, it depends on the query/term that the user enter. The problem appears when the user forget or does not know the query that associated with the items. The Recommendation comes as a solution to provide personal information by studying the interaction of a user, user community, and items that have been recorded previously. Collaborative filtering as a method to provide personalized recommendations based on other users who have similar tastes. However, the results of collaborative filtering tend random, sometimes users need an item with similar genre/subjects. This paper discusses a model of a recommendation engine for new users with a method of collaborative filtering based on genre similarly with the aim of giving the smallest error with high precision. First filter we use Alternating Least Square-Weight Regularization (ALS-WR) is selected as algorithms for collaborative filtering. Second filter we use Cosine Similarity is selected as an algorithm for genre similarity. We use datasets from movielens.org. The RMSE on the first recommendation generated is 0.89 for 100K ratings, 0.86 for the 1M ratings, and 0.81 for the 10M rating. By iterative and training on larger data, it will make a better model, so RMSE can be smaller. They are concluded that ALS-WR able to deliver adaptive, with regulatory parameters that can be controlled and adjusted. The more data but the error on the wane, that is means this algorithm is suitable for growing data or big data. The item that has been sorted with the ALS-WR algorithm, letter approximated with cosine similarity, and with only 10 items movie displays with the highest degree of similarity, that be able to generate high precision.","PeriodicalId":225743,"journal":{"name":"2017 15th International Conference on Quality in Research (QiR) : International Symposium on Electrical and Computer Engineering","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126216197","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 : 2017-07-01DOI: 10.1109/QIR.2017.8168457
F. Kurniawan, J. Sumantyo, Mujtahid, A. Munir
In this paper, an effect of truncation shape of left-handed circularly polarized (LHCP) X-band antenna against its axial ratio is investigated. The antenna which is designed to have the center frequency of 8.2GHz and the axial ratio bandwidth of 400MHz is intended to be implemented for satellite communication. It is deployed on an NPC-H220A dielectric substrate with the dielectric constant of 2.17 and the thickness of 1.6mm. The structure of antenna is constructed of two layer dielectric substrates in which the top side of first layer is for radiation element, then the top side of bottom layer is for feeding line and the bottom side of bottom layer is for groundplane. The truncation is set in the edge of radiation element at 45° from z-axis and 45° from x-axis. The investigation is performed by varying the shape of truncation on radiation element. Three different shapes of truncation, i.e. triangle-shaped, square-shaped, and ellipse-shaped, are applied for investigating the antenna parameter focused on its axial ratio. From the result, it shows that the antenna with ellipse-shaped truncation has the widest axial ratio bandwidth among other shapes ranges from the frequency of 7.89GHz to 8.4GHz.
{"title":"Effect of truncation shape against axial ratio of left-handed circularly polarized X-band antenna","authors":"F. Kurniawan, J. Sumantyo, Mujtahid, A. Munir","doi":"10.1109/QIR.2017.8168457","DOIUrl":"https://doi.org/10.1109/QIR.2017.8168457","url":null,"abstract":"In this paper, an effect of truncation shape of left-handed circularly polarized (LHCP) X-band antenna against its axial ratio is investigated. The antenna which is designed to have the center frequency of 8.2GHz and the axial ratio bandwidth of 400MHz is intended to be implemented for satellite communication. It is deployed on an NPC-H220A dielectric substrate with the dielectric constant of 2.17 and the thickness of 1.6mm. The structure of antenna is constructed of two layer dielectric substrates in which the top side of first layer is for radiation element, then the top side of bottom layer is for feeding line and the bottom side of bottom layer is for groundplane. The truncation is set in the edge of radiation element at 45° from z-axis and 45° from x-axis. The investigation is performed by varying the shape of truncation on radiation element. Three different shapes of truncation, i.e. triangle-shaped, square-shaped, and ellipse-shaped, are applied for investigating the antenna parameter focused on its axial ratio. From the result, it shows that the antenna with ellipse-shaped truncation has the widest axial ratio bandwidth among other shapes ranges from the frequency of 7.89GHz to 8.4GHz.","PeriodicalId":225743,"journal":{"name":"2017 15th International Conference on Quality in Research (QiR) : International Symposium on Electrical and Computer Engineering","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126311434","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 : 2017-07-01DOI: 10.1109/QIR.2017.8168519
Ishak Kasim, S. Abduh, Nur Fitryah
The demand of electricity transmission toward regions for society, industrial and other needs are increasing hence, making electricity transmission and distribution increased as well. The increase in electricity transmission and distribution requires addition of Substation construction. Substation constructions are crucial for economic growth in Indonesia. This research aims to design two models of grounding system, to determine permissible touch voltages and permissible step voltages, and to simulate both designs using CYMGrd Software, whereby both designs were compared to obtain optimal grounding system at 275 KV Betung Substation. With touch voltages and step voltages values of 1387.97 V and 364.6 KV in first model, and touch voltages and step voltages of 1247.2 V and 112.39 V in second model, both model did not exceed permissible touch voltages of 1409.58 V and permissible step voltages of 5050.1 V. Final result of this research showed that second design model was more optimal compared with the first design model.
{"title":"Grounding system design optimization on 275 KV betung substation based on IEEE standard 80-2000","authors":"Ishak Kasim, S. Abduh, Nur Fitryah","doi":"10.1109/QIR.2017.8168519","DOIUrl":"https://doi.org/10.1109/QIR.2017.8168519","url":null,"abstract":"The demand of electricity transmission toward regions for society, industrial and other needs are increasing hence, making electricity transmission and distribution increased as well. The increase in electricity transmission and distribution requires addition of Substation construction. Substation constructions are crucial for economic growth in Indonesia. This research aims to design two models of grounding system, to determine permissible touch voltages and permissible step voltages, and to simulate both designs using CYMGrd Software, whereby both designs were compared to obtain optimal grounding system at 275 KV Betung Substation. With touch voltages and step voltages values of 1387.97 V and 364.6 KV in first model, and touch voltages and step voltages of 1247.2 V and 112.39 V in second model, both model did not exceed permissible touch voltages of 1409.58 V and permissible step voltages of 5050.1 V. Final result of this research showed that second design model was more optimal compared with the first design model.","PeriodicalId":225743,"journal":{"name":"2017 15th International Conference on Quality in Research (QiR) : International Symposium on Electrical and Computer Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129116643","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 : 2017-07-01DOI: 10.1109/QIR.2017.8168445
Intan Ari Budiastuti, S. M. S. Nugroho, M. Hariadi
Inflation rate could describe economic growth and it is usually used by policy-maker to determine a monetary policy. The Consumer Price Index (CPI) is one of indicator used to measure inflation rate. Until now, the inflation calculations and CPI prediction are conducted on monthly even though it is now likely to predict them on daily basis by utilizing online commodity price movement. Daily predictions could become a tool to analyze the real value of the market and will allow policy-makers to make better policy. This is a preliminary research to develop daily CPI prediction model by using Big Data. This paper discussed daily prediction model by using real-time data (daily commodity price and exchange rate) and SVR method. Build a model focused on accuracy and execution time. Grid Search and Random Search method were applied to select the best parameter for SVR model. In addition, we compared SVR method with linear regression and Kernel Ridge Regression method. The results show that the prediction model using SVR-kernel RBF has MSE value, 0.3454, less than other methods. Execute time for process data show that Kernel Ridge method has training time 0.0698s, little faster than SVR method 0.134s.
{"title":"Predicting daily consumer price index using support vector regression method","authors":"Intan Ari Budiastuti, S. M. S. Nugroho, M. Hariadi","doi":"10.1109/QIR.2017.8168445","DOIUrl":"https://doi.org/10.1109/QIR.2017.8168445","url":null,"abstract":"Inflation rate could describe economic growth and it is usually used by policy-maker to determine a monetary policy. The Consumer Price Index (CPI) is one of indicator used to measure inflation rate. Until now, the inflation calculations and CPI prediction are conducted on monthly even though it is now likely to predict them on daily basis by utilizing online commodity price movement. Daily predictions could become a tool to analyze the real value of the market and will allow policy-makers to make better policy. This is a preliminary research to develop daily CPI prediction model by using Big Data. This paper discussed daily prediction model by using real-time data (daily commodity price and exchange rate) and SVR method. Build a model focused on accuracy and execution time. Grid Search and Random Search method were applied to select the best parameter for SVR model. In addition, we compared SVR method with linear regression and Kernel Ridge Regression method. The results show that the prediction model using SVR-kernel RBF has MSE value, 0.3454, less than other methods. Execute time for process data show that Kernel Ridge method has training time 0.0698s, little faster than SVR method 0.134s.","PeriodicalId":225743,"journal":{"name":"2017 15th International Conference on Quality in Research (QiR) : International Symposium on Electrical and Computer Engineering","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128904132","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 : 2017-07-01DOI: 10.1109/QIR.2017.8168455
T. Hasan, M. Tabe, D. Moraru, A. Afiff, A. Udhiarto, H. Sudibyo, D. Hartanto, A. Samanta, M. Muruganathan, H. Mizuta
Single-electron tunneling (SET) transistors have been studied for the past several decades because they are promising for low-power consumption and fundamental-level control of charge. The quantum dots (QDs) that are the main part of an SET transistor have been demonstrated in a variety of materials, but recently dopant-atoms in silicon have also been shown to work as QDs. However, a single conventional dopant-atom has usually a shallow ground state energy level below the conduction band edge (∼45 meV). This means that the tunnel barrier is relatively low and thermally-activated current can flow over the barrier. Therefore, the operation of dopant-atom SET transistors remains limited to low temperatures. In this work, we statistically analyze the key factors for raising the SET operation temperature up to room temperature (>300 K).
{"title":"A Statistical Study on the formation of a-few-dopant quantum dots in highly-doped Si nanowire transistors","authors":"T. Hasan, M. Tabe, D. Moraru, A. Afiff, A. Udhiarto, H. Sudibyo, D. Hartanto, A. Samanta, M. Muruganathan, H. Mizuta","doi":"10.1109/QIR.2017.8168455","DOIUrl":"https://doi.org/10.1109/QIR.2017.8168455","url":null,"abstract":"Single-electron tunneling (SET) transistors have been studied for the past several decades because they are promising for low-power consumption and fundamental-level control of charge. The quantum dots (QDs) that are the main part of an SET transistor have been demonstrated in a variety of materials, but recently dopant-atoms in silicon have also been shown to work as QDs. However, a single conventional dopant-atom has usually a shallow ground state energy level below the conduction band edge (∼45 meV). This means that the tunnel barrier is relatively low and thermally-activated current can flow over the barrier. Therefore, the operation of dopant-atom SET transistors remains limited to low temperatures. In this work, we statistically analyze the key factors for raising the SET operation temperature up to room temperature (>300 K).","PeriodicalId":225743,"journal":{"name":"2017 15th International Conference on Quality in Research (QiR) : International Symposium on Electrical and Computer Engineering","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127999314","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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