bluuebunny/crossref_metadata_2025_split huggingface dataset:
Implementation of Kalman filter algorithm on reduced models using Linear Matrix Inequality method and its application to measurement water level
Authors: Estuningsih Nenik , Fatmawati  , Apriliani Erna 
Published: June 2020

Abstract
This paper presents the model reduction and estimation of the state variables of the water level system using the Linear Matrix Inequality (LMI) method and the Kalman filter algorithm. We assume the system is asymptotic stable, controllable and observable, then we reduce it by LMI method. The reduced system obtained is a system that remains asymptotic stable, controllable, and observable. The reduction error using LMI method is smaller than the reduction error using Balanced Truncated (BT) method and Singular Perturbation Approximation (SPA) method. Next, we implemented the Kalman filter algorithm in the original system and the system was reduced by LMI method.
Linearization of two-state thruster models
Authors: Adzkiya Dieky , Nurhadi Hendro , Herlambang Teguh 
Published: June 2020

Abstract
A thruster is a device used for station keeping, attitude control, in the reaction control system, or long-duration, low-thrust acceleration. Thruster is one of the main components in autonomous surface vehicle. In this paper, we discuss the linearization of two-state thruster model by using the Jacobian method.
Predicting hoax spread in Indonesia using SIRS model
Authors: Oktaviansyah Eka , Rahman Arif 
Published: June 2020

Abstract
Hoax or fake news can spread easily through the internet like an epidemic. In Indonesia, hoaxes are common that it becomes a serious problem. We predicted the spread of hoaxes in Indonesia by using the Susceptible-Infected-Recovered-Susceptible (SIRS) epidemic model where the susceptible is the person who ignores the news, the infected is the person who shares the news without fact-checking it, and the recovered is the person who fact-checks the news. This paper uses data from the Indonesia Telematics Society (MASTEL) concerning the behavior of Indonesian people in 2017 and 2019 when receiving trending news. We also use data on the number of internet users in Indonesia obtained from the Indonesia Internet Service Providers Association (APJII). This model has a disease-free equilibrium which is unstable and an endemic equilibrium which is asymptotically stable. The basic reproduction number of this model, which is 5.614455426, shows that the spread of hoaxes in Indonesia will increase because the behavior of sharing the news without fact-checking it will spread in the society until it reaches endemic equilibrium.
Enhancement of the Improved Recursive Method for Multi-objective Integer Programming Problem
Authors: Al-Rabeeah Masar , Al-Hasani Ali , Kumar Santosh , Eberhard Andrew 
Published: June 2020

Abstract
In this paper, we developed a new algorithm to find the set of a non-dominated points for a multi-objective integer programming problem. The algorithm is an enhancement on the improved recursive method where the authors have used a lexicographic method for analysis. In this approach a sum of two objectives is considered as one weighted sum objective for each iteration. Computational results show that the proposed approach outperforms the currently available results obtained by the improved recursive method with respect to CPU time and the number of integer problems solved to identify all non-dominated points. Many problems such as assignment, knapsack and travelling salesman have been investigated on different sized problems. The benefit of this approach becomes more visible with the increase in the number of objective functions.
An Error-Free Transformation for Matrix Multiplication with Reproducible Algorithms and Divide and Conquer Methods
Authors: Ozaki Katsuhisa 
Published: June 2020

Abstract
This paper discusses accurate numerical algorithms for matrix multiplication. Matrix multiplication is a basic and important problem in numerical linear algebra. Numerical computations using floating-point arithmetic can be quickly performed on existing computers. However, the accumulation of rounding errors due to finite precision arithmetic is a critical problem. An error-free transformation for matrix multiplication is reviewed in this paper. Such a transformation is extremely useful for developing accurate numerical algorithms for matrix multiplication. One advantage of the transformation is that it exploits Basic Linear Algebra Subprograms (BLAS). We provide a rounding error analysis of reproducible algorithms for matrix multiplication based on the error-free transformation. In addition, we propose an error-free transformation for matrix multiplication that can be utilized with the divide and conquer methods.
Interval-parametric synthesis of a robust controller on a base of characteristic polynomial with desired stability in a sector
Authors: Gayvoronskiy S A , Ezangina T , Khozhaev I 
Published: June 2020

Abstract
In the paper a characteristic polynomial of a linear control system which coefficients include interval parameters of a control object and adjustable parameters of a controller is considered. In order to find polytope of controller parameters providing desired sector stability of a polynomial, values of polynomial coefficients limits are found on a base of desired oscillability degree of a system. On a base of these calculations a controller synthesis method is developed. Application example of the method proposed is also provided.
Sentiment classification of hotel service review on traveloka sites using naïve bayes classifier (NBC) and binary logistic regression
Authors: Rahmaningrum Silvia Astri , Oktaviana Pratnya Paramitha 
Published: June 2020

Abstract
Utilization of social media sites such as Traveloka can help hotel marketing by providing information as review related to search and hotel bookings online. The given review could be a feedback to the related hotel as well as to assist visitors in choosing the right hotel. Feedback information as a review is important data text, so we need to develop a method to classifiy it then the right method used for classifying text data is text mining. Sources of data are obtained from web scraping process which aims to obtain online data on website page by collecting visitor review’s of Favehotel and Gunawangsa Hotel from Traveloka sites. Text mining methods used in this study is Naïve Bayes Classifier (NBC) and Binary Logistic Regression which is the process of sentiment labeling based on Lexicon dictionary. Word cloud visualization shows that the highest keywords that lead to the both of the hotel with the largest positive sentiment are ‘clean’ and ‘comfortable’. A comparison methods between NBC and Binary Logistic Regression for Favehotel and Gunawangsa Hotel obtained a decision that Binary Logistic Regression method with SMOTE was better than NBC where AUC value in testing data for Favehotel is 0.84 and Hotel Gunawangsa is 0.82.
Deriving a six-dimensional mathematical model of an unmanned underwater vehicle motion control system with interval parameters
Authors: Gayvoronskiy S A , Khozhaev I , Ezangina T 
Published: June 2020

AbstractThe paper is dedicated to a problem of mathematical modeling of a motion control system for unmanned underwater vehicle. The proposed model considers interval parametric uncertainty of underwater vehicle itself and water environment, nonlinearity of control object and actuator of the system and interaction between its control channels. In order to derive the model several objectives were accomplished: a mathematical model of underwater vehicle motion in a viscous fluid in all six degrees of freedom was derived; mathematical model of separate thruster and whole propulsion and steering system was derived; both model were linearized with the help of interval linearization method and, finally, a structure of the whole motion control system was determined. The model is applicable for simulation modeling of underwater vehicle motion and for analysis and synthesis of motion control systems in condition of interval parametric uncertainty.
LU-Cholesky QR algorithms for thin QR decomposition in an oblique inner product
Authors: Terao Takeshi , Ozaki Katsuhisa , Ogita Takeshi 
Published: June 2020

Abstract
This paper concerns thin QR decomposition in an oblique inner product. Cholesky QR is known as a fast algorithm for thin QR decomposition. On the other hand, this algorithm is not applicable for ill-conditioned matrices. The preconditioned Cholesky QR algorithms named LU-Cholesky QR for thin QR decomposition are recently proposed. We apply these preconditioning techniques to thin QR decomposition in an oblique inner product.
Implementation of social media mining for decision making in product planning based on topic modeling and sentiment analysis
Authors: Irawan M I , Wijayanto R , Shahab M L , Hidayat N , Rukmi A M 
Published: June 2020

Abstract
The development of information and communication technology, especially on the social media field, brings a wide change in product planning in company. At this time, a company can identify the opportunity for product planning based on customers’ opinion through Twitter’s postings. This opportunity can be used to increase the competitiveness and defend from the competitors. The main method that is used in this research is social media mining based on topic modeling and sentiment analysis. The topic that is widely discussed by the customers is identified as the importance degree and the result of sentiment analysis is identified as the satisfaction degree. We successfully apply topic modeling with Latent Semantic Analysis and K-Means cluster and sentiment analysis with lexicon dictionary from Hutto and Gilbert. Using McDonald’s 2000 tweets, it can be concluded that “service in the morning” has the highest opportunity degree and it is categorized at under-served thing. It gives us a meaning that “service in the morning” is one of the service which has a great chance at the market.
Numerical Solution of Unsteady A12O3
-Water Nanofluid Flow Past A Magnetic Porous Sliced Sphere
Authors: Widodo Basuki , Nugraha Adhi Surya , Thahiruddin Muhammad 
Published: June 2020

Abstract
This study aims to investigate the MHD stagnation point flow of Al2O3
-Water nanofluid with mixed convection effect pass a sliced magnetic porous sphere. The unsteady Al2 O3
-Water nanofluid mixed convection boundary layer flows the stagnation point is an interesting study. This implementation of this concept can use in the problems of engineering and industrial fields such as propulsion ships system, oil drilling, chemical piping, and nuclear reactor coolant. In this paper, we consider the effect of magnetic, porosity, and slicing angel parameters towards the velocity and temperature profiles. We construct a mathematical model of MHD flow in Al2O3
-Water nanofluid to obtain dimensional governing equations. Then, the equations converted into non-dimensional equations by using non-dimensional variables and unsimilarity equations using stream function. The solution of the model solved by numerically using the Keller-Box scheme. The velocity and temperature profiles are determined for various non-dimensional parameters such as magnetic parameter, sliced angle, and porosity parameter. We obtain that the velocity of Al2O3
-Water nanofluid decreases but the temperature decreases when magnetic parameters increases. For the porosity parameter increases then the velocity of the fluid decreases but the temperature of the fluid increases. For the sliced angle parameter increases then the velocity of the fluid increases but temperature of the fluid decrease. For the volume fraction parameter increases then the fluid velocity decreaes but the fluid temperature increases.
Identification of the decline in learning outcomes in statistics courses using the chi-squared automatic interaction detection method
Authors: Prasetyono H , Abdillah A , Anita T , Nurfarkhana A , Sefudin A 
Published: June 2020

Abstract
The decline in learning outcomes in Statistics is a problem that must be immediately solved. Many factors affect learning outcomes such as; intelligence, interest, talent, motivation, learning patterns, learning resources, and so on. The data used in this study are secondary data from TU-FIPPS and BAAK which consists of data on final grades of Statistics students of the Economic Education Study Program, Indraprasta PGRI University. In addition, researchers also use primary data collected through surveys. Data analysis using the Chi-squared Automatic Interaction Detection (CHAID) method. Based on the results of this study, explanatory variables that affect the decline in student learning outcomes Statistics are variables of motivation and group learning frequency. The explanatory variable which has the strongest influence with the decrease in student learning outcomes Statistics is motivation. The value of the accuracy of student classifications produced using CHAID analysis of eighty-five point one percent. The classification tree model of CHAID analysis in this study is better and more accurate for estimating the decline in learning outcomes Statistics in the downward category than in the non-down or very down categories.
A Study on Optimization Algorithms in MPC
Authors: Nakagaki Yuki , Zhai Guisheng 
Published: June 2020

Abstract
We consider the implementation problem of Model Predictive Control (MPC) especially for linear control systems. In the real time computation of MPC, we need to choose an optimization method to solve at each sampling periods. For this purpose, we suggest a new combination of the existing numerical calculation methods to speed up the computer calculation. More precisely, we first introduce the well known KKT theorem in optimization problems, which is used in the MPC calculation procedure. Secondly, we review the MPC calculation and present a linear Lagrangian algorithm for the KKT theorem, which is combined with Wolfe conditions and Dual method. Finally, in order to demonstrate the proposed approach, we provide one numerical example and another example for stabilization of inverted pendulums.
Status and Prospect of KOTO-I
Authors: Tung Y-C 
Published: June 2020

Abstract
KOTO is the first experiment with the designed sensitivity of O(10−11) to probe for new physics through the rare

K
L
0

→

π
0

ν

ν
¯

decay. From 2017 to 2019, there were critical changes in the data acquisition system that further improved the research potential of KOTO for diverse research topics. In this article, we present the new trigger system of KOTO and several byproduct analysis.
Influence of the Nitrogen exposure time to the plasma treatment on the wettability of polystyrene surfaces
Authors: Masruroh  , Satriyo Wibowo Gigih , Santjojo Dionysius J. D. H. 
Published: June 2020

Abstract
The wettability of material can change from hydrophobic to hydrophilic when treated using plasma nitrogen. The present work investigated the influence of the plasma treatment duration on the modification of polystyrene’s surface coating on a glass surface. The polystyrene layer was produced by means of spin coating method with the rotational speed of 3000 RPM for 1 minute. The plasma was established by a 2 MHz RF generator at the power of 40 watts, pressure of 0.3 Torr, flow rate 40 mL/min. The samples were treated at various exposure time which were 2 min, 5 min, 10 min, and 15 min. The wettability of the polystyrene was measured using a contact angle measurement before and after the nitrogen plasma treatment. Polar functional groups related to the wettability were observed by a Fourier Transform Infrared (FTIR). The longer the treatment duration, the smaller the contact angle was observed. A very low contact angle of 6.42° was achieved at a power of 40 watt at 0.3 torr for the exposure time of 15 min. This means that the surface of the polystyrene changed to super hydrophilic or super wetting. The FTIR results show the spectra of NH2 and C-H functional group at the wavenumber of 3485 cm1 and 2962 cm1, respectively. These functional groups indicate the existence of the polar groups, which contribute to the change of surface hydrophobicity into hydrophilicity.
Cloud detection method for Pleiades images using spectral indices
Authors: Prabowo Y , Candra D S , Ali S 
Published: June 2020

Abstract
Satellite images such as Pleiades have been widely used to monitor the earth. But there is a main issue regarding cloud cover which interferes the information of the images. Another issue is that there are very few studies discussing cloud detection for very-high-spatial-resolution such as Pleiades imagery. In this study, we proposed a cloud detection approach for Pleiades images to address these issues. In the first step, whiteness test was used to detect thick cloud. We also used modified HOT test in the second step to address the issue of detecting thin cloud. We modified the original HOT algorithm to decrease the omission error especially caused by thin cloud. We used visual assessments to evaluate the results. As a result, we found that cloud can be detected accurately by combining these algorithms. The results showed that the proposed approach can be used to detect cloud for Pleaides-1A images.
Unmanned aerial vehicle object tracking and following
Authors: Haris Indra Fadhillah Ahmad , Taqwim Safrudin Ahsanu , Darma Surya 
Published: June 2020

Abstract
Today, the use of Quadcopter on human activities are increasingly dominant, especially in the field of search and rescue. One of the most challenging case on SAR using Unmanned Aerial Vehicle quadcopter is tracking and following an object which is newly recognized. The system could track any kind of object which the user choose in real time and the object could be immediately recognize. After the object recognized, the quadcopter could track and follow the object with a high degree of precision. This research reports the results of design and program for quadcopter control that can track and follow a 3D objects which was initially determined first. The algorithm for tracking system used several method from image processing to extract the information from the image (feature extraction base on color), then the information will be used as a reference movement quadcopter in following the target. The object tracking system, used various methods of image processing in the domain of HSV-RGB, Camshift, and Kanade-Lucas-Tomasi Tracker to optimizing 2D tracking system and increase the succes rate of the program. While the method of distance estimation using the camera calibration towards the distance. Output from the tracking system are the object coordinates (x, y, z). This information is fed back to the quadcopter Robot Operating System (ROS) as the error between the positions of the camera with the position of objects, and is known as Visual Servoing. Quadcopter control system using PID constants in the leading to the movement of the pitch, throttle, and roll, to maintain the position of quadcopter towards the target and follow an object moving forwards or backwards.
Infant cry classification using CNN – RNN
Authors: Nadia Maghfira Tusty , Basaruddin T. , Krisnadhi Adila 
Published: June 2020

Abstract
The study of infant cry recognition aims to identify what an infant needs through her cry. Different crying sound can give a clue to caregivers about how to response to the infant’s needs. Appropriate responses on infant cry may influence emotional, behavioral, and relational development of infant while growing up. From a pattern recognition perspective, recognizing particular needs or emotions from an infant cry is much more difficult than recognizing emotions from an adult’s speech because infant cry usually does not contain verbal information. In this paper, we study the problem of classifying five different types emotion or needs expressed by infant cry, namely hunger, sleepiness, discomfort, stomachache, and indications that the infant wants to burp. We propose a novel approach using a combination of Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) that acts as feature extraction and classifier method at once. Particularly, CNN learns salient features from raw spectrogram information and RNN learns temporal information of CNN obtained features. We also apply 5-folds cross-validation on 200 training data set and 50 validation data set. The model with the best weight is tested on 65 test set. Evaluation in Dunstan Baby Language dataset shows that our CNN-RNN model outperforms the previous method by average classification accuracy up to 94.97%. The encouraging result demonstrates that the application of CNN-RNN and 5-folds cross-validation offers accurate and robust result.
Design of water height detector model in runway based on internet of things
Authors: Aulia Mardiah Puti , Yohandri  
Published: June 2020

Abstract
The runway of an aircraft is designed to keep it dry even if it rains to avoid hydroplaning. Hydroplaning is a plane slip on the runway due to standing water. In accordance with regulations from the Derektorat Bandara, Ditjen Perhubungan Udara NO. KP 212 in 2017, the operational requirement for runways to be able to serve landings and aircraft flights is when there is a maximum of 3 mm of standing water on the runway surface. The design of the water level detector model on the runway uses the Arduino Mega 2560 as a microcontroller which processes and sends the detected data to the thingspeak via the internet network. Performance specifications for water level detector models are water level sensor designs, U detector pipes, runways, electronic circuits. The water level sensor is a touch sensor that is designed and printed on a PCB board with vertical strip designs. Detected data will be processed in Arduino Mega 2560 and typed into the thingspeak page using the internet network. Data output can be accessed via a PC connected to the internet network. The results of comparison with standard tools found the average percentage of errors for the vertical sensor strip design was 4.98%. From the comparison results, the average percentage of accuracy for the vertical sensor strip design is 95.01% with precision of 84.77%.
Design of automatic infusion monitoring system based on Arduino
Authors: Sifa Fauziyyah Auliya , Yohandri  
Published: June 2020

Abstract
Intravenous Fluids Drops are very important for the process of healing or treatment for patients. The function of infusion is to replace the loss of fluids or nutrients in the body. In Indonesia, monitoring system of condition about infusion is still done manually, but for the cases such a large hospitals which is the number of patients is not balanced by medical personnel, it is becomes ineffective so that it can cause mistakes in monitoring. A very serious mistake can occur are too late in replacing the infusion. The solution to solve this problem is to make an automatic infusion monitoring system with an alarm warning. This research is experimental research. The measurement technique taken is direct and indirect measurement. Direct measurement data is mass of infusion and indirect measurment data is the number of infusion drops and the percentage of remaining intravenous fluid. The purpose of this research is to determine the design spesifications and peformance spesification of the instrument. The sensor used to measure infusion drops per minute is photogate and to measure the infusion volume is load cell. The display is use TFT LCD and using buzzer for alarm warning. The accuracy of infusion drops per minute system is 0, 97 with error 2, 15% and accuracy of infusion fluid percentage system is 0, 98 with error 1, 47%.