bluuebunny/crossref_metadata_2025_split huggingface dataset:
Utilization of the Android physics virtual lab application to improve understanding of light and optics concepts
Authors: Erfan M , Maulyda M A , Hidayati V R , Widodo A , Ratu T 
Published: February 2021

AbstractThis research aims to analyze the effectiveness of the application of virtual laboratories based on android applications on the learning outcomes of prospective elementary school teacher students about light and optics concept in daily life. This research is a quantitative with one group pre-test post-test design. The treatment given was in the form of learning about light and optics concepts using the AndroidPhysics Virtual Labapplication. The sample in this study was taken using cluster random sampling technique and obtained class 5H (24 students) as the sample. The data in this research were obtained by tests carried out before treatment (pre-test) and after treatment (post-test). The data from pre-test and post-test result were tested for normality, then paired t-test, N-gain test and Effect Size test were performed. The N-gain test value that have been obtained was 0.784 (high category) and the coefficients of effect size test results was 1.781 with the strong effect category and from the t-test results there was significant difference between students’ understanding of concepts light and optics before and after learning. with the AndroidPhysics Virtual Labapplication, so from this study it can be concluded that the AndroidPhysics Virtual Labapplication is effective in enhancing students’ understanding about light and optics concepts of prospective elementary school teachers.
Comparison of the simple additive weighting saw method and multi-objective optimization by ratio analysis MOORA
Authors: Arief Muhammad , Triayudi Agung , Sholihati Ira Diana 
Published: February 2021

AbstractThe manual assessment process is very likely to be at risk of errors and sometimes there is nepotism fraud and takes a long time due to the large number of employees. Currently, the East Jakarta Administration City Water Resources Water Resources Department does not yet have a special method and application that is used for evaluation and performance appraisal. Therefore, the purpose of this research is to build a decision support system using the simple additive weighting (SAW) method and multi-objective optimization by ratio analysis (MOORA). With the hope that it will make it easier to carry out the process of evaluating and appraising employee performance and can be carried out objectively with predetermined criteria.
User Satisfaction Analysis for Event Management Systems Using RAD and PIECES Framework
Authors: Julian Budi , Triayudi Agung , Benrahman  
Published: February 2021

Abstract
The National University Information System Student Association often holds events or activities every period it takes place but has not been integrated and well managed. Many problems were caused, such as: large costs, data loss, long queuing services, and large human resources. Seeing from these conditions, the authors conducted a study that aims to determine the level of user satisfaction analysis of the event management information system that has been designed for the activities of the National University Information System Student Association. This study uses 3 methods, namely Rapid Application Development (RAD), Waiting Line and PIECES. The average result of the analysis of respondents on questions on the performance aspect was 4.35, the information aspect was 3.6, the economic aspect was 4.45, the control & security aspect was 3.50, the efficiency aspect was 3.64 and the services aspect was 3,825. From the results of the average assessment of the total score for the PIECES aspect, it was obtained 3,894 or 77.88% of respondents said they were satisfied with this system. This research contributes to the governance of activities organized by the Information Systems Student Association so that they can be well integrated and managed.
Comparison of the K-Nearest Neighbor algorithm and the decision tree on moisture classification
Authors: Nurdiawan Odi , Kurnia D. A , Solihudin Dodi , Hartati Tuti , Suprapti Tati 
Published: February 2021

Abstract
Soil moisture is a parameter needed by plants in terms of plant growth. In determining the appropriate soil moisture for plants requires a control system. This study uses a comparison of KNN and decision tree algorithms with the aim of being able to determine soil calcification with yield parameters namely moist and dry, so that it has good accuracy compared to the accuracy of the Decision Tree algorithm with an accuracy of 55.77% with dry class recall of 62.69% moist 51.92% dry precision class 58.33% humid 47.37% and K-Nearest Neighbor with 72.69% accuracy dry class recall 80.60% humid 63.16% dry precision class 72.00% humid 73.47%. The results of the above model testing can be concluded that the K-Nearest Neighbor is the most accurate algorithm for classification of moist soil
Comparison of machine learning algorithm for Santander dataset
Authors: Wijaya Yudhistira Arie , Suarna Nana , Iin  , Hamonangan Ryan , Nining R 
Published: February 2021

Abstract
The dataset for Santander banks is released on kaggle.com to decide whether the customer makes a transaction or not. The classes in this dataset are 2 with 200,000 entries in records. Earlier experiments using the regression algorithm led to a precision rate of 89%. In this analysis, the best accuracy value from the algorithm was obtained by using 6 different algorithms, namely Support for the Vector Machine (SVM), Neural Network (NN), Naive Bayes (NB), Decision Tree (DT). Before performing the data mining with the algorithm, preprocessing is carried out using a normalizing technique using the range transformation method with values 0 and 1. From the study, the best results were obtained in a Decision Tree 96.03% accurate algorithm, 95.82%, and 95.71%, 95.38%, 90.42%, 90.42%, and Naive Bayes 14.69%. The algorithms of the Decision Tree are 95.03%, 95.71% and 92%. Except for the Naïve Bayes algorithm, the precise value is better than previous study.
Clustering of internet network usage using the K-Medoid method
Authors: Martanto  , Anwar Saeful , Rohmat Cep Lukman , Basysyar Fadhil Muhammad , Wijaya Yudhistira Arie 
Published: February 2021

Abstract
The use of the internet network at Wahidin Vocational High School (SMK) Cirebon City is a very significant need in supporting the progress of learning. The ease of using the internet has made the academic community free to use the internet network facilities provided by the school and carry out the activities they want without any control. Causing the academic community to freely access the web that is not related to ongoing education, and certainly this matter will be very disturbing in the teaching and learning process. This matter is in order to identify accurate analysis also using Information Mining as information processing. After that, using the clustering algorithm procedure is K-Medoid. The K-Medoid procedure is able to carry out information grouping on the use of social media access which is often accessed by the academic community throughout the school. Grouping using the K-medoids algorithm can be known that the use of internet network access is on average used to access social media compared to accessing E-learning. It is suitable from the results of research that was tried if the use of WhatsApp reached an average of 126 users, after that accompanied by Instagram, its usage reached an average of 108 users, then accompanied by E-Learning, the average usage reached 90 users, after that it was accompanied by Facebook and YouTube which an average of 71 users. Thus, from the research that has been tried, it is necessary to implement layer 7 protocol firewall security to block social media access so that internet network access at Wahidin Vocational High School (SMK), Cirebon City. Used as a suitable early idea is to facilitate the academic community to maximize E-learning education.
Market basketball analysis algorithm for determining products association
Authors: Basysyar Fadhil Muhammad , Dwilestari Gifthera , Bahtiar Agus , Martanto  , Nuris Dienwati Nisa 
Published: February 2021

Abstract
Market basket analysis may be a technique identify the association between couple’s products purchased jointly and identify cases. Scene an occurrence is when two or more things happening. Market basket analysis makes rules if-then, scenario for instance, if an item purchased a and b will likely. bought items rule is probability in nature or, in other words, they are available from the incident. In observation the frequency is that the proportion of a basket of things which will be employed interesting. Rule, price, product placement and various varieties of cross-selling strategy. In order to create it easier to grasp, think in terms of market research handbasket in a very supermarket. Market basket analysis taking data on the transactions containing an inventory of all items that bought by customers in a very purchase. The technique is ascertaining the relations which product bought on other products. This relationship then wont to construct the containing the if-then items purchased. Market basket analysis also called a rule association or analysis affinity, learning may be a technique data processing can be used in numerous fields, as education, marketing, informatics and science. The aim is to include retailer’s awareness of buyers’ actions in order for the retailers with knowledge about the actions of purchasers, which will allow the tailor to make the right choices. All of the numerous market basket algorithms available to try to do. Algorithms, whose current work is on statics and which did not catch data changes in time, but algorithms not only intended to mine static information, but also provided new ways of calculating modifications on paper-listed association processing rules, and provide new algorithms that could stimulate market engagement and encourage up-selling.
Automatic monitoring system for the elderly based on internet of things
Authors: Chyan Phie 
Published: February 2021

Abstract
The population group aged 60 years and over based on the age category from the Indonesian Ministry of Health is included in the elderly category and based on population projection data for 2020 the number reaches 27.08 million people or around 9.9% of the total Indonesian population. As a vulnerable age group, the elderly has several characteristics, namely physical abilities that have begun to decline and even some have disabilities which can prevent them from being able to take action when something is harmful to them physically. This study focuses on building an automatic monitoring system for the elderly in a closed environment. The system will monitor in a non-stop and real-time way using a variety of hardware equipped with sensors and artificial intelligence algorithms implemented in the system software so that the system can track the subject’s position, learn the subject’s behavior and then be able to detect abnormal behavior, for example in the elderly. the subject falls down, wobbles, shows an expression of panic or pain. The final result of this research is an automatic monitoring system which consists of the integration of various hardware and software which are interconnected in a computer network for monitoring and protection of the elderly.
An automated length measurement system for tilapia fish based on image processing technique
Authors: Damanhuri Nor Salwa , Zamri Mohammad Faiz Mohammad , Othman Nor Azlan , Shamsuddin Sarah Addyani , Meng Belinda Chong Chiew , Abbas Mohd Hussaini , Ahmad Anita 
Published: February 2021

Abstract
In aquaculture industry, measurement of fish length plays an important role in monitoring and determining fish growth, gender, age and reproduction. Currently, fish rearing industries are using measuring wooden board or acrylic plastic with the scale attached to the board itself. However, this method is causing a stress on the fish when measuring their length alive. Furthermore, manual measurement of fish length one by one using measurement board is time-consuming. Hence, this research presents an automated system that is able to measure fish length specifically tilapia fish by using image processing technique and Graphical User Interface (GUI). This automated GUI system is developed for end user and it is able to measure the length of tilapia automatically and accurately. The system is designed by using image processing tool, which consists of image segmentation and feature extraction to get the fish-shaped region. Based on the results, the GUI system is able to measure automatically and accurately the fish length based on the fish image. This developed system resulting with a 8.50% mean relative error and 91.50% accuracy of the tilapia fish length measurement for a 20 cm distance between the digital camera and the tilapia fish. These results show that the proposed system is capable to produce faster results and yield accurate length measurement of the tilapia fish. Thus, with this automated system, it is potentially assisting in fish reproduction and growth for aquaculture industry especially for tilapia industry.
Avoided emissions resulting from grid-tied solar photovoltaic generation in the Philippines: an energy-based analysis
Authors: Enano Nelson Jr , Barroca Renyl , Montecastro Doris 
Published: February 2021

Abstract
One of the motivations of deploying renewable energy is its promise to reduce emissions. The accounting of emissions, however, becomes challenging and complex in the case of grid-tied PV system as it also derives energy from the centralized grid where the energy comes from a mix of resource. The amount of avoided emissions is highly variable. The study focused on the determination of avoided emissions resulting from grid-tied solar photovoltaic (PV) generation of Ateneo de Davao University Jacinto Campus in the Philippines. The results show that the small size of PV systems impacts only the marginal generating plant which is normally a hydro, diesel or natural gas-fired generator and largely depends on which grid the consumer is located. It shows that the energy generation of the PV acts like a peak shaving mechanism that reduces the system load. The solar PV of the university was simulated and the avoided emissions (CO2, SO2, NOx, PM10, PM2.5, NH3, VOCs, and Hg) were quantified through energy-based approach.
Evaluating windowing based continuous ST with deep learning for detection and classifying PQDs
Authors: Daud K , Mansor MBM , Soh ZH Che , Samat AA Abd , Shafie MA , Ismail AP , Abdullah MH 
Published: February 2021

Abstract
This paper discusses the performance of evaluating a windowing based continuous S-Transform (ST) with deep learning classifier for the detection and classifying of interrupt and transient disturbances. The primary purpose is to analyze the detection and classification of voltage interrupt and transient using ST as a signal processing technique. The detection technique is divided into half-cycle and one-cycle windowing techniques (WT with both cycles used for the purpose of comparison. The disturbances signal was create using MATLAB programming language and set in the form of m-file. ST was used to extract the significant feature in a form of scattering data from the disturbances signal. Then, the scattering data was used to build the detection interface inside the disturbances signal. The scattering data is an input for neural network (NN) to classify the percentage accuracy of the disturbances signal. This analysis presents the suitable windowing technique that can provide smooth detection and suitable characteristics to produce high accuracy percentages in the classification of power quality disturbances (PQDs).
Fridge load management system with AI and IOT alert
Authors: Soh Zainal Hisham Che , Ag Ku Izzul Hamzi Ag Jaafar , Sulaiman Siti Noraini , Abdullah Syahrul Afzal Che , Ibrahim Mohammad Nizam , Aslina Abu Bakar 
Published: February 2021

Abstract
The technological development nowadays has allowed the use of smart appliances and machines almost anywhere. The refrigerator is considered one of the most significant appliances that is being used in almost every place for the purpose of storing foods, drinks, and medicines at cold temperatures, and in a sealed place to avoid it from being exposed. Therefore, a system is introduced which can manage fridge load with AI and IoT alert. Using object detection, the system is able to detect types of drinks which are cans and bottles. The dataset images of cans and bottles is trained using two models, Faster R-CNN and SSD mobilenet. The system will count the number of drinks detected by the camera, which the data obtained is sent to IoT cloud which is Ubidots. The Ubidots dashboard will show the number of drinks detected and the stock availability. In the same time, if the number of drinks detected is zero, it will send a notification via the Telegram to alert the user that the drinks are out of stock. Using this system is better since it only need to use a camera as the medium to detect products instead of using many sensors which cause wiring hassle.
Experimental study of flame propagation and stability of (ILPG)
Authors: Saleh Mustafa Abdullah , Alwan Fouad Saleh 
Published: February 2021

Abstract
The Study of the premixed and vertical flow makes a special significance in industrial burners design and application of industrial stoves. It included a laboratory study of the flame propagation and stability of liquid petroleum gas (LPG) for a vertical burner of different diameters and a study of the effect of isolating the flame from the external environment by an inert gas which is nitrogen gas. It also included a new experimental and numerical simulation to understand the effect of using inert Nitrogen gas (Nitrogen jacket) on properties of flame propagation in Vertical burner. Accordingly, the test device was modified. The necessary measuring devices were added. It was equipped with an internal nitrogen gas isolation system to determine the properties of the previously mixed vertical flame stability. The experimental combustion tests have been done by using (LPG) under Laboratory conditions (Tu = 298 K, Pu =1 atm), with high range of air to fuel mixing ratio. The percentage of the maximum value for premixed flame burning velocity between (without N2 and with N2) for burner diameters (9,13,16 mm) were (3.4%,6.02%,2.99%) respectively
New quantum circuit architecture for classifying big data
Authors: Solikhun  , Efendi Syahril , Zarlis Muhammad , Sihombing Poltak 
Published: February 2021

Abstract
This research is motivated by the incomplete use of quantum in existing learning algorithms, so that the proposed learning algorithm is not optimal. Research (Fahri & Neven, 2018) shows that the proposed method of architectural form still uses classical architecture but inputs, weights and targets already use a quantum approach. Based on the results of previous studies, it shows that quantum computing is better than classical computation. Many researchers use quantum computing in the proposed learning algorithm. The model proposed is a quantum circuit architecture with the quantum perceptron method consisting of a quantum bit gate that uses a quantum computational approach as the architecture of the quantum perceptron learning algorithm. Then the authors conduct training and testing of the proposed quantum circuit architecture to test the quantum circuit model that the author proposes. The result of this research is a quantum circuit model with the quantum perceptron method which can be used to solve the learning optimization problem by using a quantum circuit architecture with 5 measurement measurements to show error training and testing = 0, with 9 measurements showing an error training of 1.13%, error testing 2.06%.
Design and development of biomass gasifier reactor to produce syngas
Authors: Arief Suardi N C , Antono Vendy , Prayudi  , Nurhasanah Roswati 
Published: February 2021

Abstract
Gasification process is strongly influenced by the gasifier reactor to produce syngas. This study aims to design and make an updraft type of gasifier reactor without blower so that it does not require electric power in its operation, but use power from engine suction. This gasifier design is suitable for small scale power plants which are not connected to the main electricity network (off-grid system) in rural and remote areas. Materials used in manufacturing the gasifier reactor are consist of type 304 3 mm stainless steel, 3 mm diameter of stainless steel pipe, 3 mm iron plate, and fire cement. The experiment and test results show that the highest efficient and the most optimal biomass in the gasification process is coconut shell charcoal, because coconut shell charcoal has a dense structure and at the time of the experiment, coconut shell charcoal was filled 15 cm below the gas outlet pipe hole. From the economic value of the gasifier reactor that has been produced, the lowest cost result is diesel with EFB charcoal, because in this experiment EFB is the biomass that is not purchased. The additional use of empty bunches of charcoal is able to save 50% diesel usage
Study of minimum requirements of confinement in concrete columns confined with WRG in moment resisting frames
Authors: Kusuma Benny 
Published: February 2021

Abstract
The national concrete standard SNI 2847:2013 which refers to the ACI 318M-11 has not accommodated the influences of the axial load and deformation parameters as performance requirement, where both parameters are very critical to affect the required confining steel of concrete columns. This study presents the test results of reinforced concrete columns confined with WRG which were designed according to ACI standards. The test results were analyzed using several codes such as SNI 2847:2013, ACI 318M-14, CSA A23.3-04, and NZS 3101-06 standards. Furthermore, the minimum confinement equation is proposed for the design of columns confined with WRG, then it is also compared with selected confinement provisions. The study results showed that the equation for confining reinforcement adopted in the SNI 2847:2013 or ACI 318-11 is very conservative compared to other codes when applied to low axial load levels (≤ 0.25 Agf’c), but relatively less conservative or unsafe if the axial load level is greater than 0.3. From result of evaluation show that CSA A23.3-04 provide most conservative result for confinement design. The additional confinement design equations at ACI 318M-14 has been improve confinement design of ACI Code. Compared with SNI requirements, which do not depend on the level of axial load on the column, the equations proposed here would allow reduced confining reinforcement for columns with higher axial load. Overall, the proposed equation presents the best correlation to actual drift capacity of columns, and in addition it can be used for columns reinforced with WRG-transverse reinforcement having a yield strength higher than 500 MPa. The study also provides the recommendation for further refinement of SNI 2847 in the future related to the requirement of WRG confinement in concrete columns of Special Moment Frames in highly seismic regions.