bluuebunny/crossref_metadata_2025 huggingface dataset:
Linearization of two-state thruster models
Authors: Adzkiya Dieky , Nurhadi Hendro , Herlambang Teguh
Published: June 2020

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

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

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

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

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

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

The 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

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

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

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

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

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

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

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

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

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

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

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

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%.
Feature selection with Lasso for classification of ischemic strokes based on EEG signals
Authors: Angga Yuwono Hendra , Kusuma Wijaya Sastra , Prajitno Prawito
Published: June 2020

Electroencephalography (EEG) is an electrical signal data that can describe brain activity in which the signal contains important information that can be used to detect several diseases. One of the diseases that can be detected by EEG signals is stroke. The most common type of stroke is the acute ischemic stroke (AIS) due to blockage of blood supply to the brain which can generate the tissue damage in the brain EEG signal recording uses several electrodes where the more electrodes used in the recording, the greater the number of EEG features produced (high dimensional data). This can make it difficult for models of machine learning to have optimal performance on high-dimensional data. In this study, for optimizing the performance of the machine learning model by selecting features with the Least Absolute Shrinkage and Selection Operator (Lasso) method, where this method can select the relevant features by shrinking some coefficients to zero. The type of classification used in this study is random forest with features used for classification are Brain Symmetry Index (BSI), Delta-Alpha Ratio (DAR), Delta-Theta-Alpha-Beta Ratio (DTABR). The results showed that the Lasso method can optimize the performance of learning machines with an accuracy value of 75% with 24 features out of 45 features.
Predictive maintenance magnetic sensor using random forest method
Authors: Aji A S , Sashiomarda J A , Handoko D
Published: June 2020

BMKG has observations of earth’s magnets which are scattered in Indonesia. The BMKG earth magnetic sensor produces real-time data output. This research focuses on predictive maintenance models on earth magnetic sensors based on data output. The resulting data output is in the form of a delimited format in the form of spaces so that it is easy to process. The magnetic component used is the total component data (F) from the earth’s magnetic sensor. Data processing using python scripts with the algorithm used is the random forest method by comparing the resulting value difference to find out whether the data generated is still in tolerance or not. The results of the prediction model with the number of estimators 10 produce RF Score = 0.98 and MAE = 0.83.
Real time monitoring state-of-charge battery using internal resistance measurements for remote applications
Authors: Alif Kurniawan Taufiq , Natajaya Aldyan , Sidi Priambodo Purnomo , Wibisono Gunawan
Published: June 2020

Currently, the use of batteries as energy storage applications in various fields initiates many researchers to maximize the battery performance. One of the most important things to prevent a battery from over-charging or discharging issue is an accurate State-of-Charge (SoC) estimation of the battery. In this paper, real time monitoring SoC battery for the remote applications is proposed by calculating the battery’s internal resistance when charging or discharging. When charging process, the battery’s internal resistance (ric
) is low and will increase according with increasing the level of SoC. While at the discharging process, the battery’s internal resistance (rids
) is low and will increase in proportional to the decreasing of the SoC level. The calculation of rids
and rich
are conducted by measuring open circuit voltage, load voltage, load current, and charging current using a voltage divider mechanism on the Arduino Uno and current sensors, respectively. LORA RA-02 SX 1278 433 MHz is used to transmit the battery parameters from the remote area (transmitter) to the server (receiver). Then the SoC will be estimated based on internal resistance calculation using these parameters on the server. With a simple structure, the proposed systems can be applied to the future remote real time monitoring battery systems.
Design analysis of consolidation of cellular operators in Indonesia
Authors: Wibisono Gunawan , Fistarini Ria
Published: June 2020

To increase the network capacity demands cellular operators have to add sites, use technology with a high efficiency spectrum, and increase spectrum allocation. The limited frequency spectrum becomes an obstacle for operators in increasing the availability of system capacity, which in turn can reduce the quality of mobile broadband services. Indonesian cellular operators are expected to have a spectrum deficit of around 400 - 450 MHz in 2020. One way to overcome spectrum deficits is consolidation between cellular operators. It is therefore very interesting to conduct a consolidation research of Indonesian operators and evaluate and analyze their impact on reducing spectrum deficits and competition. In this research the consolidation design was carried out with the following provisions: a maximum of two operators, migration of spectrum two of the consolidated operators that were not contiguous was carried out to a minimum, the consolidated spectrum of results is a contiguous frequency, and no spectrum divestment. The consolidation scenario of Indonesian cellular operators is simulated on operators namely Tsel, XL, Isat, and H3I operating at frequencies of 900, 1800 and 2100 MHz in six regional mobile broadband services namely Sumatra, Java, Bali Nusa Tenggara, Kalimantan, Sulawesi and Maluku Papua. There are three consolidation scenarios. Scenario I consolidation consisted of H3I+Isat consolidation, XL+Tsel, scenario II consolidation consisted of H3I+XL consolidation and Isat+Tsel consolidation, and scenario III consolidation consisted of H3I+Tsel and Isat+XL consolidation. First evaluated consolidation which gives the least spectrum deficit. Then the consolidation scenario is evaluated using company operational and financial data to decide which operator consolidation provides efficiency and fair competition. It can be shown from the results that the best technically consolidated operators may not necessarily provide good financial results.
Prediction of PM2.5 and PM10 parameters using artificial neural network: a case study in Kemayoran, Jakarta
Authors: Putra A M M B , Martarizal  , Putra R M
Published: June 2020

It was recorded that in August 2019 the case of acute respiratory infection in Indonesia had doubled compared to the previous months. This is in line with the increasing levels of PM10 and PM2.5 in several regions in Indonesia. In the end the public is increasingly aware of the importance of air quality information. Prediction of air quality will greatly help the public to anticipate the dangers of declining air quality. The use of Artificial Neural Network can be a solution in making daily air quality forecasts whose parameters are not linear. This research shows that utilization of historical data parameters of temperature, humidity, air pressure, rainfall, sun exposure and wind speed as well as BMKG’s PM10 and PM2.5 data is able to produce forecasting modeling for PM2.5 and PM10 concentrations in the Kemayoran area, Jakarta by utilizing Artificial Neural Network Modeling. The result is success to make prediction of PM2.5 and PM10 and it will be better if more historical data applied.
Identification system for beeswax on Malang apple using VNIR imaging
Authors: Praditya Naufal , Harmoko Saputro Adhi
Published: June 2020

Wax coating identification on fruits is very difficult without a non-destructive method. In general, destructive methods were used to identify wax or coatings by soaking the fruit in hot water or using a mixture of vinegar and water. There are also destructive systems that was used such as gas chromatography linked with mass spectrometry, but this method takes much time and difficult to operate. Visible Near Infrared Imaging (VNIR) becomes the alternate solution to identify wax on the surface of the fruit without spoiling the quality of the fruit. In this study, identification system for beeswax application on apples has been made successfully. The process starts through image acquisition, image correction, object detection, window averaging, classification model, and the coating status. The VNIR image was acquired on a wavelength range from 400 to 1000 nm. The data was divided for training and testing the classification model using cross-validation method, then the model was evaluated using confusion matrix. Several classification models were used to compare the result and to conclude which model gives the best accuracy for identification and classification problems. The accuracy of the three models were 72.92% for PCA-SVM model, 81.25% for DT model, and 91.67% for RF model.
The influence of particle size to diffusivity of nanogold particles based on Brownian motion
Authors: Zulfahmi  , Handoko Djati , Prajitno Prawito , Isnaeni
Published: June 2020

Diffusivity calculation has been conducted by many researchers in various methods. One ingenious and sample-efficient way to determine the diffusivity is the examination under the microscope by using microbead random movements, called Brownian motion, through the footage of its movements. This study was conducted to observe the diffusivity of nanogold particles towards the use of various microbead sizes. The one-micron-sized microbead was mixed into nanogold particles solution and prepared onto slide glass, so was the three micron-sized and five-micron-sized microbead. The footage of microbead movements for each size is then tracked and processed using MATLAB image processing to obtain the mean square displacement (MSD) of the microbead and then fitting it to time to find the sample diffusivity. As a result, the nanogold diffusivity observed using one-micron, three-micron, and five-micron-sized microbead is respectively around 5.66 x 10−17 cm2s−1
, 3.45 x 10−17 cm2s−1
, and 1.71 x 10−17 cm2s−1
. Thus, the nanogold diffusivity observed using one-micron-sized microbead is greater than three-micron and five-micron-sized microbead, which can be concluded that the bigger of microbead size used, the smaller diffusivity obtained.
The advantage of blown fiber technology for out site plan network deployment than conventional cabled optical fiber system in Depok apartment project
Authors: Priyo Hutomo Sri , Wibisono Gunawan
Published: June 2020

The current deployment of optical fiber networks in several major cities in Indonesia is intensive. Development of fiber as the backbone or last mile for special services and almost all of us have encountered. Maybe one of them is a network deployment studio in one of the Apartment Projects in Depok City. The population of Depok reaches 4% per year higher than the national growth, the number of students and students who reach more than 80 thousand who live in Depok from only 2 campuses namely the University of Indonesia and Gunadarma University make the residential business growth both in the form of residential horizontal (boarding rooms) ) or vertical residential (Apartment). Developers are competing to build Apartments which, of course, are potential new revenue and new markets for Internet & Pay-TV Providers. The problem of the length of time the deployment of network infrastructure, traffic is not taken into account and still prioritizes the quality and cost that remains efficient become an issue of concern to the Provider. Blown Fiber is a new technology with four main components namely products, blowing devices, optical fiber bundles, and terminating/connecting hardware. This technology results in more cost-efficient, more flexible designs, better work costs in installation, termination and cheaper testing compared to conventional optical fiber deployment technology. The implementation of Blown Fiber in a deploying studio in one of the Apartments in Depok specifically on the Out Site Plan (OSP) turned out to provide convenience and acceleration in terms of network deployment.
Automatic take-off landing quadcopter control on dynamics platform
Authors: Dutasatria Akmal , Darma Surya
Published: June 2020

SAR (Search and Rescue) become an interesting topic discussed worldwide because of its urgency to save humans life. Recent natural disaster in Palu, Central Sulawesi Indonesia demonstrates the lack of mobility which can cause a problem for the SAR team reaching the victim within the isolated area. Uneasy job for the SAR team become more challenging in time response and in finding and saving disaster victims. Consider the fact, there is a need to develop more efficient and effective way to search and rescue the survivors. The using of Quadcopter can answer the problems. Unfortunately the Quadcopter still conventionally controlled by a remote and further it has to be on static ground whenever its take off or landing. This paper reports a Quadcopter fitted with dynamical autonomous take off and landing systems. Thus it can carry out the advantage from a tactical SAR vehicles or other moving platforms. Using object detection approach, The navigation system in an image-based control quadcopter or called visual servoing is the use of machine vision as a control of the closed loop position for movement. Images can be detected using YOLOv3 Real Time Object Detector, and tracks it by estimating the motion of objects in successive video frames. By using 3D reconstruction method the distance and position of the designated target and the quadcopter could be determined. Then the estimation of the relative position of the object is used as input for the control system on the quadcopter using PID controller. The controller commands the quadcopter to approach the target, while the image processing checks the relative position between the two. If the position satisfies the minimum landing parameter, then the controller commands a landing. While for take off we implement the controller to maintain its equilibrium and sufficient power to throttle.
Parasitic resistance calculation of PV module at various irradiance based on three condition Lambert-W
Authors: Umar Lazuardi , Wati Agustina , Wiyadi Eri , Hamzah Yanuar
Published: June 2020

Serial and parallel parasitic resistances of the photovoltaic (PV) module are needed to determine the characteristics and performance of the module. Its values are constant for a long period operation. Characterization of PV modules using direct irradiation of sunlight is rather difficult to obtain constant radiation under a clear sky condition and the measurement should be taken in a short time period less than 5 minutes. In this work, Rs and Rsh values were determined by characterizing PV module at various levels of sunlight intensity and modeled after Lambert-W function. A Solarland SLP100S-12 monocrystalline 100Wp photovoltaic module was illuminated at different intensity 100%, 75%, 50%, and 25 % using filters covered the PV module surface. Based on the measured I-U curves, three important parameters are generated for the Lambert-W calculation: short-circuit current (Isc), open-circuit voltage (Uoc), and also the current-voltage at the Maximum Power Point (Imp, Ump). The calculated values were 0.63Q + 0.027 for Rs and 93.2Q + 0.588 for Rsh and relative constant for filter variation which are not influenced by the intensity of the sun.
Prediction system for pH measurement on Brassica oleraceae (Red Cabbage) using machine learning regression
Authors: Wulan Hastuti Dian , Harahap Marlina , Adila Ferdiansyah Faizal , Harmoko Saputro Adhi , Imawan Cuk
Published: June 2020

pH is an important unit to represent the chemical condition of a liquid, solid substance, food nutrition, and microbial activity as well. pH value is also commonly used to detect the behaviour of chemical substances. Measurement of pH value can be shown by color changes of the substance based on the acidity condition from the measured environment. In this research, the colorimetric based on machine learning and pH value detected from the color information for point-of-care applications. For this investigation, we used the pH buffer solution and natural dyes derived from Brassica oleraceae (Red Cabbage) that shows colorimetric response gradually shifted from red to green along with the increasing of pH from 2.00 (acid) to 11.00 (alkaline). In this paper, we propose a method for predicting pH value based on Artificial Neural Network Regression (ANNR) and K-Nearest Neighbour Regression (KNNR) with RGB, HSV and LAB color space. As a result, the performance (99.83% ± 0.11) of this method could estimate the pH reasonably well for point-of-care application.
Design and analysis of air quality monitoring system PM10 and PM2.5 integrated with weather parameters (a case study on Margonda Raya street Depok)
Authors: Simanullang R , Soekirno S , Larassari H A
Published: June 2020

An observation of air quality is very important related to the increasing pollution in Indonesia resulted from the use of motor vehicles, industrial activities, wildfires, and others. It triggers the increase of PM10 and PM2.5 particulate pollutants in the atmosphere. Meteorological factors influence the fluctuation of PM10 and PM2.5 concentration. The solution to overcome the problem is the design of IoT-based PM10 and PM2.5 digital monitoring system that is integrated with parameters of temperature, humidity, wind speed and direction. The design system consists of sensor hardware ZH03A laser dust sensor, SHT11 temperature and humidity sensor, and JL-FS2 wind speed and direction. Data were processed on Arduino ATMega2560-based microcontroller and then sent to the server using internet so that they could be displayed on website. The information system on the website was developed using PHP and HTML. The device had been tested with calibration and comparison methods. As the results of the research, the device could be operated properly and the measuring results were displayed on web in real time to provide air quality information. The correlation of PM source concentrations with meteorological parameters is that temperature (positive correlation), wind speed (positive correlation), relative humidity (negative correlation) and based on the direction of wind, the area is dominated by west winds.
Developing a system to determine impact force in tennis
Authors: Bakhtiar Syahrial , Harris Sujae Ian , Kudo Shige , Rizal Wan Zakaria Wan , Ong Alex , Hamill Joseph
Published: June 2020

The purpose of this project was to develop a system that could estimate impact force in tennis forehand stroke. Such estimation is critical feedback during training. Method: A tennis racket was used for this study. A strain gauge was embedded into the body of the racket. Changes in strain measurement (analogue signal) was converted to digital signal using the AD converter and was synced with the motion capture system. Calibration of the strain gauge was conducted by hanging fixed weights of equal increment on the racket and expressed as a relation of fixed weight mass and strain data (captured on motion capture) using linear regression equation. The equations summation of forces was used to determine the impact force. Results and Discussions: The peak impact resultant force estimates were similar to those reported in the literature. Despite the sampling frequency of 200Hz, data estimated from this study may give a representation of peak resultant impact force as the data were not filtered. Conclusion: The system developed in this study may be suitable to estimate peak resultant impact forces. Coaches could simply use the data gathered and in future, synchronise with an app on mobile devices to establish impact force directly and instantaneously with acceptable accuracy.
Simple gold nanoparticles production method by ablated laser: Diameter modification
Authors: Pambudi S , Isnaeni  , Handoko D
Published: June 2020

Recently, an improved interest in gold nanoparticles (AuNPs) with an interesting phenomenology such as plasmon resonance, has been aroused. There are many methods to synthesized AuNPs. We have successfully fabricated AuNPs base on laser ablation method. The pulsed Nd:YAG laser ablated at 1064 wavelength to a pure gold plate. The frequency was adjusted in low range to produce low energy density laser beam. Three different solution (aqueous, polyvinyl alcohol and polyethylene glycol) was applied to modify AuNPs diameter. The modified nanoparticles diameter was observed by mean UV-Vis spectroscopy exhibit different absorption peak wavelength. For comprehensive discussion, the spectrum was compared to simulation tool on MATLAB. Interestingly, AuNPs diameters have been modified by using different solution.
Influence of the liquid injection hole to ripple frequency of the QCM sensor
Authors: Pratiwi Retno A , Akbar Muchammad A , Sakti Setyawan P
Published: June 2020

The liquid injection is one of the crucial roles in the used of QCM sensors in a liquid application. Liquid sample injection should be controlled. As the liquid injected onto the QCM sensor surface using peristaltic pump, a short pressure pulse exists. The short pulse affect the stability of the resonance frequency of the QCM sensor. The pulsation flow of the peristaltic pump leads to a ripple resonance frequency of the QCM sensor. Resonance frequency measurement of the QCM sensor in the reaction cell injected using the peristaltic pump has been measured. Different injection holes size was made to observe the effect to the sensor stability. The result showed that frequency of the QCM sensor has a ripple frequency as the liquid injected using the peristaltic pump. It was observed that bigger injection hole at the exit flow resulted in a smaller ripple frequency. Further investigation is required to get the smallest ripple p frequency during the liquid injection using the peristaltic pump.
Synthesis of silver nanoparticles (AgNPs) using Sodium Chloride (NaCl) for Iron (III) ions detection based on colorimetric and optical changes
Authors: Retno Yuniarni Diah , Intan Pratiwi Nur , Umar Aminah , Imawan Cuk
Published: June 2020

Iron ions (Fe3+) is one of the most hazardous metals found in the water supply. The contamination of that metal originated from the corrosion process of pipes and cracks from waste disposal sites. High levels of iron would affect a bad impact to the environment. The current study aimed to synthesize silver nanoparticles (AgNPs) for heavy metals detection using a method which depends on colorimetric and optical changes. The approach to synthesize AgNPs adapted from polyol reduction method, i.e. by mixing polyvinyl alcohol (PVA), sodium chloride (NaCl) and silver nitrate (AgNO3). The colorimetric response of AgNPs to Fe3+ ions was observed visually and measured quantitatively by a spectroscopic method using a UV-Vis spectrophotometer. This work shows that the colloidal AgNPs were sensitive to identify Fe3+ ions.
Design of neural network and PLC-based water flow controller
Authors: Ahmad Burhanuddin , Prajitno Prawito
Published: June 2020

Flow rate is a fundamental physical quantity in the fluid transportation system from one place to another. To achieve this, a reliable controller that is able to produce a constant flowrate in industry is needed. The most used flow controllers in industries are PID-based controllers that are implemented using PLCs. However, there are still shortcomings, they can perform poorly in some applications, for example in the highly nonlinear system which cannot be overcome by conventional PID controllers. There are some other limitations of PID controller, such as PID has the overshoot and undershoots in the output of controlled system and PID gives late response in this study, a neural network-based flow controller is proposed to deal with that problems. The controller will be operated in a miniature plant which consists of a water tank, water pump, a control valve, and a flow transmitter. Due to PLC limitation that cannot be programmed with common programming languages such as MATLAB, a personal computer (PC) is used to run the proposed neural network controller. The PC communicates with the PLC using OPC (OLE for Process Control) server, while the PLC reads the flow transmitter and also controls the control valve directly based on the result output of the neural network controller. In order to evaluate the performance of the proposed controller, several experiments have been conducted. The performance of the proposed controller has been compared with the conventional PID controller. It shows that neural network-based controller outperformed the conventional PID controller, in terms of maximum overshoot and steady-state error, where the neural network controller has maximum overshoot = 5.36% and steady-state error = 0.85%, while the PID controller has 11.3% for overshoot and 1.10 % for steady-state error.
A simple colorimeter based on microcontrollers to detect food dyes
Authors: Yulkifli  , Wulandari D A , Ramli R , Etika S B , Imawan C
Published: June 2020

A simple colorimeter has been successfully designed using a microcontroller to detect food dyes. This article describes the performance specifications and design specifications of the colorimeter that was designed as a detector for food dyes using a photodiode sensor and a light emitting diode lamp as a source. System performance specifications consist of mechanical systems that are supported by electronic systems. Data collection techniques were carried out directly and indirectly. Color absorption data were measured directly using an ultraviolet-visible spectrophotometer and indirect absorption data is determined by the voltage that was processed by the microcontroller. The test was carried out by measuring 10 variations in the concentration of food dye liquid, in the range of 0.1% - 1.0%. Measurements were made with 10 repetitions. The data were analyzed in two ways, statistically and graphically. The accuracy of the colorimeter design was done by comparing it with the measurement results from the ultraviolet-visible spectrophotometer. The average percentage of errors are 1.7% and the average relative accuracy of the system is 93.3%. These results indicate that a simple colorimeter can be used to measure the concentration of food dyes quickly and with good accuracy.