bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamic encryption method of user privacy data based on association rules hiding
Authors: Li Zongrong , Li Nanfang , Yuan Xuebin , Zhao Lei , Ma Xuezhi , Li Shengchun
Published: February 2021

Because the traditional data encryption method remains unchanged after the key is generated, the encryption scheme is single, the encryption cost is high, and it is easy to be cracked. Aiming at the above problems, the dynamic encryption method of user privacy data based on association rules hiding is studied. Based on the DGHV encryption scheme, a dynamic encryption scheme is designed to hide the mined user privacy data association rules. After the key is processed by confounding method, the dynamic encryption process of data is completed. By comparing with the traditional methods, it is verified that the encryption efficiency of the studied method is increased by at least 26.2%, which has the advantage of low encryption cost.
Probabilistic model of wind power output considering temporal autocorrelation and cross-correlation with forecast output
Authors: Sun Yue , Zhou Jiahao , Huang Wei , Yan Jiahao , Tie Yingqi , Lai Weibin , Cheng Xin , Jiao Dan , Xie Kaigui
Published: February 2021

Wind power output possesses temporal autocorrelation and cross-correlation with the forecast output. However, these two types of correlations are quite different. Existing studies fail to model them simultaneously, which reduces the accuracy of the conditional probability distribution of wind power output and has a negative effect on the economic operation of wind power systems. Therefore, this paper proposes a method for modeling the conditional probability distribution of wind power output that can take both correlations into account. The copula function is used to separately model the dependency between wind power outputs and the uncertainty of actual/forecast output. Based on pair-copula theory, the modeling of the conditional probability distribution of wind power output with respect to the two correlations is broken down into the chain transfer process of the traditional two-dimensional copula function. The probability distribution function of wind power output can be obtained as long as enough historical data is available. No specific forecast techniques are required. Using the actual wind field output data in Belgium, the proposed method is compared with the methods that only consider one of the correlations to prove its effectiveness.
Variation of PM2.5 concentration at some typical districts in Chengdu
Authors: Tang Hong
Published: February 2021

Aerosol particles are one of the most variable components in the Earth’s atmosphere. The study of aerosol properties plays an important role in science and application. The PM2.5 concentration at different locations in Chengdu city is studied in this paper. In order to measure the PM2.5 concentration at different locations in Chengdu city, three areas including the commercial district, the university area and the overpass in the main road are choose to represent the typical locations. The variation of PM2.5 concentration with time at different locations and different dates are tested with the particle instrument. According to these results, it is obvious to understand that the PM2.5 concentration is different at different location even within the same time. If with the conditions of rainfall and wind, the PM2.5 concentration will be reduced rapidly.
Calculation method of line loss rate of photovoltaic station based on PCA-GRNN
Authors: Li Yuan , Liu Jing , Tan Huang , Li Yajie , Diao Xinping , Yao Li , Xu Zhiguang
Published: February 2021

Line loss rate of substation area is a comprehensive economic and technical index of power companies. With the continuous expansion of grid connected scale of distributed generation, accurate calculation of line loss rate of substation area with distributed generation is imminent. In this paper, considering the basic operation attributes and the grid connection attributes of distributed energy, a calculation method of line loss rate of substation area based on principal component analysis and generalized regression neural network is proposed. Firstly, the influence factors of line loss are extracted for the area containing photovoltaic distributed generation, and the feature dimension is reduced through principal component analysis; secondly, the reduced features are used as the feature input of generalized regression neural network for training, and the error between the training results and the real line loss is analyzed; finally, the ability of the proposed algorithm in the area identification of high line loss rate is tested. The results show that the generalized regression neural network trained in this paper has good generalization ability, the calculation error of online loss rate is small, and the identification of high loss area has high accuracy.
Design of control algorithm based on high voltage transformer
Authors: Shixi Su , Hui Luo , Zhikun Liao
Published: February 2021

Based on the application of transformers in switching power supplies, the article makes a kind of digital algorithm control. Through the 32 series’ chip to control the start and maintain state of the equipment, the node voltage is continuously collected and the output is corrected in real time to ensure that the equipment remains stable. The article provides a complete algorithm design process and ideas including the calculation of the timer parameters, the configuration process of ADC voltage acquisition. Finally, the experimental verification is carried out to ensure the feasibility of the algorithm.
Study of Fault Diagnosis Distribution Network Based on Rough Set and Artificial Intelligence
Authors: Zhou Hui , Wang Zhong , Shi Chunqing , Liu Chaoying , Zhao ShiQin , Zhang Ninghuan
Published: February 2021

The current real-time data collected by the power grid includes remote measurement, remote signaling, and other fault factors. The research in this paper is based on the fault diagnosis technology of rough set theory and self-learning theory, taking fault influencing factors as conditional attributes, fault type as decision-making attribute, and generating rough set rule table through self-learning reduction through a large number of fault history records, the influence of meteorological factors, environmental factors, equipment factors and other factors on the probability of equipment failure, which can realize the route Risk level prediction and fault location. Case analysis shows that the distribution network diagnosis technology based on rough set plays an extremely important role in predicting the risk level of each section of the line and positioning after a fault occurs.
Research and Application of Algorithm Based on Maximum Expectation and Collaborative Filtering In Recommended System
Authors: Fan Ying , Ma Huan , Chen Zhongyang , Shen Keli
Published: February 2021

The problem of sparse information is easily found in information searching for new users in recommended system, and it also has difficulty in recommending related modules. In view of the problem, the maximum expectation algorithm in demographics is adopted to cluster users for neighbouring users, and then it is regarded as an input of collaborative filtering algorithm. As the users’ scores on different projects represent their preference, certain demand relevance exists in similar users when evaluating the same project. And this kind of relevance degree varies with the change of individual demand. Therefore, a cooperative filtering algorithm based on the change of user’ demand is put forward by introducing a time weight function, which alleviates the shortness of traditional cooperative filtering recommendation algorithm. By tracking the needs of users, the scoring matrix can be predicted. According to experiments comparison, this algorithm can help solve the problem of sparseness of user’s scoring matrix and the recommendation quality is improved.
Design of topic Web crawler based on improved PageRank algorithm
Authors: Yu Linxuan , Li Yeli , Zeng Qingtao
Published: February 2021

With the continuous development of network information technology, the network is filled with a large number of all kinds of unstructured data called big data. However, this data is not easily stored in a local database. People realize that it is essential to get useful information from the Internet efficiently. The effort to gather information by human hands has led to the emergence of web crawler technology. However, the existing search engines still have shortcomings in topic similarity judgment and web page sorting algorithm. Therefore, this paper applies PageRank algorithm to topic crawler, constructs a vertical search engine, and introduces topic relevance factor to suppress "topic drift" according to the shortcomings of PageRank algorithm.
Method for Predicting Cutter Remaining Life Based on Multi-scale Cyclic Convolutional Network (MSRCNN)
Authors: Li Tao , Yu YinQuan , Yang JinWen , Zhang Long , Tu WenBin , Yong Hao
Published: February 2021

In the process of predicting the remaining cutter life (RUL), the deep learning method such as convolutional neural network (CNN) does not consider the time correlation of different degradation states, which directly affects the accuracy of the remaining cutter life prediction. To extract the features with time series information to predict the RUL more effectively, this paper proposes a new deep neural network, which is named the multi-scale cyclic convolutional neural network (MSRCNN). In the MSRCNN, a cyclic convolutional layer is constructed to simulate the time correlation of different degradation states for mining the timing characteristics of the data. Multi-scale features are extracted through multi-scale convolution, and the convergence of parameters is improved by layer-by-layer training and fine-tuning. Finally, the RUL is predicted based on the features. The comparison with the published prediction methods of CNN and recurrent neural network (RNN) models proves that our proposed method (MSRCNN) is effective and superior in improving the accuracy of RUL prediction.
A Real-Time Oocyte Polar Body Detection Method
Authors: Yongxing Zhang , Liqun Li , Juan Liu , Huiquan Wang , Dan Zhang
Published: February 2021

Based on the extensive application requirements of cell micromanipulation in bioengineering, this paper focuses on the intracytoplasmic sperm injection technology of assisted reproductive technology in the field of obstetrics and gynecology, and develops algorithms to automatically and accurately identify the position of the polar body of the oocyte, laying a foundation for the realization of sperm and oocyte automated injection. This paper proposes an algorithm that can accurately locate polar body of oocyte; this method uses a lightweight U-Net network to semantically segment oocyte images and extract their edges, and then search for polar body based on image edges. This method has been verified on 524 pictures of mice oocyte, which is real-time and robust.
Evaluation on non-visual effects of lighting based on both physiological parameters and subjective ratings
Authors: jiaqi JU , hong SUN , ke XU , ting XU , yan JIN
Published: February 2021

This article explores the influence of different colors of lights on human physiological parameters and at the same time the effects on human emotions, and tries to explore the inner connection of the changes. It helps us to better understand the color of lighting and apply it in daily life or commercial purpose, Then the experience of visual sensation will be enhanced. This article examines the changes in physiological parameters and the subjective emotional ratings triggered by the six lighting conditions such as red, green, blue, warm white, cold white and darkness. From the experiment results, the changes of physiological parameters and subjective emotions can be observed under different lighting conditions, which can be applied to guide lighting design and projects.
The PINNs method discovery to the solution of coupled Wave- Klein-Gordon equations
Authors: Wang Tianyi , Chi Xuebin
Published: February 2021

Recently, the research of PDEs is regarded as one of the most important disciplines. Almost all scientific problems can be described by a differential equation, especially, many physical phenomena can be described by the system of coupled Wave-Klein-Gordon equations, which plays an important role in high-performance computing, control engineering, and electronic power system. Consequently, in our work, we use the PINNs to solve the numerical solution of coupled Wave-Klein-Gordon equations, to help us better understand the nonlinear physical phenomena, and to promote the rapid development of various fields such as in high-performance computing, control engineering, and electronic power system.
Sentiment analysis of movie reviews based on deep learning
Authors: Zhang Fuqian , Zeng Qingtao , Lu Likun , Li Yeli
Published: February 2021

In recent years, with the rapid development of NLP (Natural Language Processing) and deep learning, public opinion and public opinion on the Internet have decreased a lot compared to the past. Many Internet users have changed from mere "bystanders" to disseminators of Internet information. Movie review sentiment analysis technology is an emerging category in the field of information mining. More and more people have joined the "review army". The quality of a movie is closely related to movie reviews! The manual screening method not only consumes a lot of manpower and material resources, but also is inefficient. Therefore, the use of deep learning-based sentiment analysis has become the current general trend. Based on the principle of word mosaic (word vector) and deep learning, this paper proposes a movie review sentiment analysis technology based on deep learning and machine learning word mosaic. Experiments show that the method used in this article has reached the correct rate of emotional classification of movie reviews. 83.13%, the experimental results prove the practicability and scalability of this method and the effectiveness of this method.
Multi-timescale Distributed Model Predictive Control for Large-Scale Systems and a Case Study
Authors: Zhao Xiaoming , Zhang Wenli , Zhang Weidong , Zhang Wenzhao
Published: February 2021

To solve the control problem effectively of complicated large scale system with obvious difference in the dynamic response at each channel, a strategy based on multi-timescale and distributed communication mode is presented. These systems can be regarded as combinations of fast system and slow system, the response speeds of which are in two-time scale. The algorithm takes into account the fast and slow characteristics and the coupling relationship of each subsystem, uses the Nash optimal idea and the multi-time standard information prediction method to realize the optimization control of the whole system. A simulation example is given to illustrate the effectiveness.
Concentration Effect of Ethanol Extract Pinus merkusii Leaves Litter on Zea mays L. Seed Germination
Authors: Retnoningrum Mita Dewi , Setiawan Mohammad Arfi
Published: February 2021

Human resources is one of the main factor in forest management, so it is important to develop a model of community-based forest management through agroforestry system. The agroforestry system in Trenggalek was implemented by combining a pine plant with Bisi-2 corn varieties. However, the presence of dry pine leaves litter suspected to contain allelopathy, thus make the percentage of germination of seed corn in a low. This study aimed to determine the concentration effect of ethanol extract of pine leaves litter (Pinus merkusii) on the germination of seed corn (Zea mays L.) Bisi-2 varieties. The research design that used Completely Randomized Design and four replications with concentration variations of 0% (control), 10%, 15%, 20% and 25%. Based on ANOVA and Duncan Multiple Range Test with significant level of 5% showed that there was the influence of the ethanol extract of pine leaves litter on the germination of seed corn Bisi-2 varieties. The higher concentration, make the germination of corn seeds more inhibited.
The Profile of Delay Erasure Time and Imaging Plate Sizes to Dark Noise Evaluation in Carestream Computed Radiography System
Authors: Setiawan Agung Nugroho , Onney Ney Da , Jannah Marichatul , Prastanti Agustina Dwi
Published: February 2021

Increasing delay time between erasure and image acquisition can lead to the appearance of dark noise on the Computed Radiography (CR) imaging plate (IP). The purpose of this study is to investigate the time delay of the last erasure that can be affected in dark noise appearance of four sizes Carestream CR’s imaging plate in Radiology Laboratory of Poltekkes Kemenkes Semarang. This study used a quantitative experimental method. Each size of IP was exposed with one of Hand, Cranium, Chest, and Abdomen anthropomorphic phantom, read on CR, and left for 0 hours, 1 hour, 3 hours, 6 hours, 9 hours, 12 hours and 24 hours to produce blank images. The blank images after post-processing were evaluated with qualitative and quantitative criteria. Qualitative criteria produced uniformity images, without ghost images artifact. While quantitative criteria were determined by the exposure index value, pixel value, and pixel value standard deviation calculated by ImageJ. The results of this study showed that all of the IPs did not pass the criteria. Dark noise appeared in 0 hours after the last erasure shown from un-uniformity images, ghost images artifact, PV, and PVSD were overpassed the standard values. Dark noise has increased the time delay between last erasure and subsequent use. The imaging plate must be erased before it acquires the next images.
Development of Macromedia Flash-Based Mathematics Learning for Elementary School Students
Authors: Mahendra Maulana Rais , Supriansyah  , Zulherman
Published: February 2021

One of the learning media that needs to be developed is Macromedia Flash-based learning media the purpose of this study was to develop mathematics learning media in the form of a Macromedia application in solid Geometry for fifth-grade students of SDN Paseban 01 Pagi. The development research method used is Research and Development (R&D), with the ADDIE development model. At the analysis stage, a problem analysis and needs analysis are carried out. At the design stage, an initial design is made which is then validated by material experts and media experts. At the implementation stage, the design of instructional media was tested on 24 students of SDN Paseban 01 Pagi. The evaluation stage aims to analyze expert validation data and student trials. The data collected using the observation method were qualitatively analyzed. The validation data were then evaluated qualitatively and quantitatively in summary. The results showed that Macromedia flashed on space building materials that had been developed based on expert media assessments in terms of display feasibility 85% with highly viable categories, 83% writing learning design with highly feasible categories, engineering and software aspects with highly feasible categories so that the overall assessment of 83% with categories was very feasible. Material expert assessment in terms of feasibility of displaying 90% material with very decent category, 93% learning media utilization aspect with very decent category, quiz aspect 90% with the category is very feasible so overall assessment 91% with the category is very feasible. The trial of the learners was obtained as a result of the 84% display feasibility aspect with a very decent category, the presentation aspect of the material 81% with a very decent category, the aspect to the engineering and software appeal 83% with the category is very feasible so the overall assessment of 83% with the category is very feasible. Based on the results of this acquisition, it can be concluded that the Macromedia Flash application on spatial geometry material is very suitable for use as a learning medium in mathematics subjects.
The Implementation of Fuzzy-C Means to Categorize Poverty Data in Riau Province
Authors: Mustakim  , Saputa Hadi Eka , Mutasir  , Nuryanti  , Salmiah
Published: February 2021

Riau Province was the 13th in line as the poverty contributor in Indonesia. It was because of the fund from government was not properly distributed. Therefore, an identification system to distribute the poverty funding was needed in order to reach the citizens in poverty. Based on the available parameter, it could accelerate the eradication of poverty. Poverty caused by various factors, i.e. educational background, living environment, job and health. One of the solutions to distribute the fund properly was by categorizing the poverty data. This research used Fuzzy Clustering Means (FCM) method because every area has the possibility to become part of each cluster with different membership level between score 0 and 1. The recommended parameter was w = 2, Max_iter = 100, ε = 0.1, P0 = 10.000.0000, t = 1, C = 3 with Partition Coefficient Index (PCI) validity score 0.47. The web built based-system uses programming language PHP with Framework YII 2 Advanced. All clustered data was analyzed based on poverty variable level that was dominant in range of regency and District.
The Classification Status of River Water Quality in Riau Province Using Modified K-Nearest Neighbor Algorithm with STORET Modeling and Water Pollution Index
Authors: Mustakim  , Rosdina  , Ramadhani Dian , Afdal M. , Rahmawita Medyantiwi
Published: February 2021

The Department of Environment and Forestry, Pollution and Environmental Damage Control Division, has an active role in monitoring water quality in Riau Province. The rivers that are still monitored and managed are Kampar River, Siak River and Indragiri River. Division of Environment Pollution calculates river quality status manually using Microsoft Excel, this is not maximally done since this important information should be processed quickly. Division of water pollution must determine the right calculation to get the results of the water quality status. Because of many calculation formulas set by the government, the commonly used method is the STORET method and the Pollution Index. So, in overcoming the problem of classification, the researcher proposes the use of learning methods that can predict or determine the status of water quality with classification techniques on data mining that is Modified K-Nearest Neighbor (MKNN) which is a modification of K-NN. The calculation of the MKNN algorithm produced the highest accuracy of 85.10% at K = 5 using STORET result data as training data. While, using the Pollution Index data results, the highest accuracy is 76.92% at K = 1. Based on the analysis with attribute analysis, the attributes that influence the determination of river water quality are BOD, COD, NH3, Fecal Coli and Total Coli. This result can be taken into consideration by the Division of Environmental Pollution in the process of overcoming and reducing pollutant overload that exceeds quality standards.
Technology of Auto Teller Machine Interface: Accessibility for Bank Customer with Visual Impairments
Authors: Subekti Priyo , Hafiar Hanny , Setianti Yanti
Published: February 2021

Auto Teller Machine (ATM) is one of the banking facilities that attract customers with visually impaired to take advantage of banking services. However, there are still some obstacles faced to utilize technology related to ATM, this is because the technology owned by a number of ATMs is not in accordance with the conditions of customers with visual impairments. Therefore, this study aims to determine the ability of customers with visual impairments in operating ATM machines and determine the difficulties experienced when operating them. This research uses a quantitative descriptive research method by using the main research instrument in the form of a questionnaire and supporting data obtained through focus group discussions conducted with a number of respondents selected purposively. The results show that there are several difficulties faced by customers with visual impairments when using ATM facilities provided by banks. These difficulties include difficulty accessing ATM locations, queuing to use ATMs, inserting cards and taking cash out of ATM machines, taking proof of transaction slips, and difficulties when experiencing errors when using ATM machines that are not equipped with security personnel, so they have difficulty reporting the obstacles they face. While the most common difficulties experienced by customers with visually impairments when dealing with ATM machines are accessing information contained on the ATM screen, entering the pin number on the ATM machine that is not equipped with a button that can help customers with visually impaired, following the instructions for use listed on the ATM screen, as well as typing on the ATM screen type touch screen.
System Development Management E-School as a Students Information Media
Authors: Febrianty  , Hadiwijaya Hendra , Octafian D. Tri
Published: February 2021

The Filial e-school website of LPKA Class I Palembang has indeed provided supporting learning materials for students for formal education at elementary, junior high, and high-school levels. However, entrepreneurship-materials are not yet available on the website as an effort to equip the future of students after leaving LPKA is very important to be improved. The development of e-school Filial LPKA was carried out by presenting entrepreneurial materials interactively. The method used in developing entrepreneurship learning multimedia video tools is the Multimedia Development Life Cycle (MDLC) method. Entrepreneurship-material is presented in a multimedia video format that can be accessed by students at a booth in the LPKA environment. The booth provided is equipped with a set of multimedia personal computers that are connected to the internet network. Each student is given their respective account by the LPKA to be able to access entrepreneurial-material video content on the e-school website with the URL address:https://e-schoolfiliallpka.com. Every student who accesses this e-school website, can interact directly with the system provided, for example by asking questions about the entrepreneurial video material being watched and questions will be answered by practitioners/contributors, students can also express their interest by giving likes. LPKA can also monitor student visit charts for each video material they watch and graphics of student favorite video material. The LPKA party can find out the area of interest of each student that is available so that this effort is expected to increase the motivation and ability of their entrepreneurs in the future. The e-school website also provides a virtual online gallery space for students’ work so that the products of entrepreneurship while at LPKA can be exhibited to the public so that the wider community can find out and visit online and in this way is expected to increase their confidence in the work.
Why is the Application Programming Interface the backbone of a Smart City?
Authors: Wahyuni Fitria , Fitriati Rachma
Published: February 2021

Improved informatiAbstractcommunication technology, causing smart city initiatives have developed in major cities in the world since the last decade. Smart cities aim to create sustainable urban development. Through the Ministry of Communication and Information of the Republic of Indonesia implemented the “100 cities to smart city” program, which began in 2017. The purpose of this article is to analyze the Application Programming Interface (API) as the Smart City backbone in Samarinda as a buffer city for the capital of the Republic of Indonesia in 2024 This study uses a qualitative approach with data collection techniques through in-depth interviews, FGD, observation and emphasizes on document analysis. This study provides the following conclusions. First, Samarinda City Government has carried out various transformations and innovations so that the city of Samarinda is competitive and ready to become a buffer city for the Republic of Indonesia’s capital in 2024. Second, infrastructure development is necessary as a means of supporting smart cities. To facilitate the implementation of API in Samarinda City. Recommendations from this research for the successful implementation of API in Samarinda City as a buffer for the nation’s capital in 2024 are as follows. First, there needs to be a more comprehensive strengthening of policies and regulations because there are regional apparatus of the Samarinda City Government that have an information system that is not integrated with the API. Second, there needs to be an increase in human resources, especially the State Civil Apparatus and / or Civil Servants, directly related to API. This study proves that there are no consolidated standards or best practices for smart governance because each city can implement different governance frameworks and models in achieving smart cities according to their local wisdom and city resources.
Prediction System of Facility Maintenance using Weight Product (WP) Algorithm
Authors: Enggari Sofika , Rani Larissa Navia , Marfalino Hari , Putra Deri Marse
Published: February 2021

This study aims to create a decision support system in determining the priority of facilities maintenance work. The current priority system of maintenance work is based on various criteria with uncertainties that often results in work that is not completed or requires a long time to work on it. It happens because the scheduling of maintenance priorities is wrong. Therefore, it needs a method of selecting priority maintenance in order to get a more accurate decision. This decision system design uses the WP method to consider the maintenance department to determine the priority selection of facility maintenance. The basic concept of the WP method is the method of solving using multiplication to link the attribute rating, where the rating must be raised first with the weight of the attribute in question. This process is the same as the normalization process. Based on this study, the results were obtained in the form of a priority level of maintenance work quickly and precisely on target from the results of the assessment and calculation of the priority level of maintenance work. Thus, using this method can increase the accuracy by 80% in determining the priority of the facility maintenance that will be conducted.
Consumption Analysis of Caffeine Using Mobile Application
Authors: Wijaya I Nyoman Yudi Anggara , Artana I Made , Dewi Nyoman Ayu Nila , Paramitha A.A. Istri Ita , Estiyanti Ni Made
Published: February 2021

Coffee is one of popular drinks in public because of its unique taste and flavor. Coffee contains caffeine, a psychoactive that is used to reduce fatigue and sleepiness. Daily caffeine consumption showed that average caffeine consumption of a person was 180.94 mg to 319.32 mg per day. Excessive caffeine consumption can disturb health of an individual. Coffee is a major source of caffeine throughout the world. Indonesia has traditional coffee preparations, namely “kopi joss” Ideal proportion of coffee consumption of the ‘kopi joss’ can be determined based on body weight. Therefore, a mobile application is developed in order to help users in determining amount of caffeine contained in coffee powder based on weight of the coffee, and especially to know ideal amount of coffee consumption based on a bodyweight.
Mask R-CNN for Indonesian Shadow Puppet Recognition and Classification
Authors: Sudiatmika Ida Bagus Kresna , Artana Made , Utami Nengah Widya , Putra Made Adi Paramartha , Dewi Eka Grana Aristyana
Published: February 2021

Region-based Convolutional Neural Networks (R-CNN) have achieved remarkable achievements in object recognition and detection. In this paper, Mask R-CNN is introduced to detect and recognize Indonesian Shadow Puppet patterns. Indonesian Shadow Puppet (Wayang) is one of the traditional Indonesian arts that depict stories, one of the stories is the Mahabharata. Our aim for conducting this research is to protect Indonesian Puppets (Wayang) from extinction through systemic pattern recognition. The algorithm used in this study is Mask R-CNN. Mask R-CNN training to recognize Indonesian Shadow Puppet requires many labels that are difficult to obtain. Therefore, the authors carried out data augmentation to add datasets to improve training. Furthermore, testing is done using several learning rates. This test is done using a Cloud GPU. The results of the tests show that the accuracy of the training obtained is 92.04% and the accuracy of validation with the learning rate value set is 0.0001. Testing the model in this study successfully tested the puppet pattern.
Optimization of Unsupervised Learning in Machine Learning
Authors: Sibyan Hidayatus , Suharso Wildan , Suharto Edi , Manuhutu Melda Agnes , Windarto Agus Perdana
Published: February 2021

The Ombudsman of the Republic of Indonesia (hereinafter referred to as the Ombudsman) is a state institution (independent) that has the authority to oversee the administration of public services. The purpose of this study is to analyze the completion of reports/complaints from the public by using unsupervised learning techniques in machine learning. The data source used is the statistical report/public complaints based on the classification of the reporter and how to submit it in each provincial regional office (simpel.ombudsman.go.id). The unsupervised learning techniques in machine learning that are used are clustering (k-medoids) and classification (C4.5) which are part of data mining. k-medoids is tasked with mapping community reports/complaints based on provincial regional offices. The results of the mapping will be classified to get the range of values from the existing mapping. The calculation process uses the help of RapidMiner software. The distribution labels used were 4 clusters namely the percentage of completion of the “very good” report (C1) of 9 provinces; percentage of “good” report completion (C2) of 10 provinces; percentage of completion of “lacking” reports (C3) of 11 provinces; percentage of “bad” report completion (C4) of 3 provinces. The Davies-Bouldin Index value on the map is 0.530 (optimal). The results of the mapping can be information in improving the quality of public services in the completion of the report including the provinces included in the C3 and C4 clusters with the percentage of report completion classification (C4 = 0 - 20.70% and 20.70% > C3 < 47.69%).
Application of Backpropagation Algorithm for Handwriting Recognition
Authors: Farlinda Sustin , Yunus Muhammad , Pratama Mudafiq Riyan , Prakoso Bakhtiyar Hadi , Rahagiyanto Angga , Susilowati Dyah , Dasriani Ni Gusti Ayu , Hakim Lukmanul , Anam Khairil
Published: February 2021

Handwritten letter recognition is one form of pattern recognition. The introduction of letters looks simple to humans, but it becomes a tough task for computer programs to complete. In recognizing someone’s handwriting, a computer program trained first. This study discusses how a computer recognizes a digital image pattern in the form of handwritten letters using the backpropagation algorithm. The backpropagation algorithm used in making this system is backpropagation with momentum. The network architecture used consists of an input screen with 64 neurons, a hidden screen consisting of 46 neurons, and an output screen with five neurons. Before the recognition process, input image with image format (jpg) processed first, which includes scaling, grayscale, and binarization. The trial results show that the system can recognize handwriting with an accuracy of up to 65%.
The Mamdani Fuzzy Logic Engineering Analysis for Determining Weather Forecast
Authors: Harahap Aris Munandar , Suwilo Saib , Sembiring Rahmat Widia
Published: February 2021

Many people rely on life in the form of climate cycles, such as farmers, fishermen, traders, and so on. This resulted in the emergence of a lot of pressure from various groups of people who needed accurate information on climate information and created various ways to carry out weather forecasts. Weather forecasts are examples of problems that often have unclear or obscure answers. Fuzzy Logic is a technique to solve this problem, so the technique used is The Mamdani as its application in the weather forecast system. Analyzing the results of weather forecasts that occur in Indonesia requires a system to know the accuracy of the data generated, so it is necessary to create a system for forecasting weather based on parameters that are inputted using the Fuzzy The Mamdani technique so that weather forecasts can be more accurate and efficient. This study predicts the weather using fuzzy The Mamdani logic techniques using the Fuzzy and Matlab toolbox as a determinant of an estimate of the weather cycle that is prioritized to be determined, namely the degree of membership functions and the rules used. Fuzzy logic with The Mamdani technique is very good to use as a weather forecast because it has an accuracy level of above 60%. Therefore, the more variables that are used as input, the better (accurate) output will be.
Login Security Using One Time Password (OTP) Application with Encryption Algorithm Performance
Authors: Kurniawan Dwi Ely , Iqbal Mohd , Friadi John , Hidayat Fendi , Permatasari Ririt Dwiputri
Published: February 2021

During the Covid-19 pandemic, almost all jobs and activities to be limited, relying on the internet network. Data security in an internet network is most important and needs to be a concern for internet users. The internet network is a public network, which is vulnerable to security attacks. Attacks may occur to retrieve user data in the form of a username and password. This study conducts system design to improve the security of the username and password data when logging into web applications. Login using One-Time Password (OTP) verification by implementing the AES algorithm and Blowfish to encrypt the verification code. The verification code uses an SMS gateway. Testing is done by looking at security performances and comparing the performance of the Blowfish and AES algorithm. The results of the design research show that OTP is running well where the AES algorithm performance has advantages in terms of encryption and decryption speed compared to the Blowfish algorithm with a difference of ± 0.015 milliseconds for encryption and ± 0.04 milliseconds for decryption.
Image Processing Identifacation for Indonesian Cake Cuisine using CNN Classification Technique
Authors: Kurnia Dian Ade , Setiawan Andi , Amalia Dita Rizki , Arifin Rita Wahyuni , Setiyadi Didik
Published: February 2021

Indonesia is famous for its traditional food that is popular both domestically and abroad. A number of cakes are among the favorite traditional foods. There are types of cakes that can be processed in Indonesia, such as kue dadar gulung, kastangel, klepon, lapis, lumpur, putri salju, risoles and serabi. The most of types of cakes available, visually the human recognize are easy, however computer visiion requires a special technicality in identifying the object of the image to the type of cakes. Therefore, to recognize objects in the form of images from cakes as one of Indonesia’s traditional foods, deep learning algorithm techniques can be used, namely Convolutional Neural Network (CNN). In this paper, the CNN Algorithm technique will be applied to 1676 datasets consisting of 80% training data and 20% testing data in which there are images of traditional cakes from Indonesia. The stages are carried out through preprocessing, operational datasets, visualization datasets, modeling techniques, performance evaluations, errors analysis which finally result in the conclusion that performance evaluation reaches 65.00%.
Solar-Cell Implementation for Supporting Tourist Facilities and Tourism Promotion Media
Authors: Hendri H. , Awal H. , Mardison
Published: February 2021

Solar-Cell panels function is to capture the energy of sunlight and then convert it into electrical energy. In this tool, Solar-Cell panels can move according to the tilt of the sun’s direction of motion so that the captured sunlight can be maximized. The electrical energy is used for free tourist facilities such as lighting, internet wi-fi, charging electronic devices, CCTV, and LCD. This tool will be placed in one of the tourist attractions in the city of Padang. So far, based on observations, tourists do not like to linger in tourist attractions because of the lack of free facilities for tourists. They cannot charge their gadgets, cannot access free internet, feel unsafe because there are no CCTV cameras and no audio-visual media. The purpose of this tool is made to increase the number of tourist visits to tourist attractions in Padang so that it can increase the PAD of Padang.
Intermittent versus continuous social media exposure for energy consumption and human eye health
Authors: Suherman S , Siregar Yulianta , A-Khowarizmi
Published: February 2021

Social media has taken a lot from human life, not only time, activities, social approaches, finance and health. Social media absorbs battery the most among other applications. This is a result of overwhelming personal interest on social media content. In fact, continuous operation drains mobile battery faster, radiates continuous electromagnetic waves and emits heat to eyes. This paper shows that the intermittent exposure on using social media applications on mobile phone, not only conserves energy, but also reduces eye health risk. Since 3 ° C eye temperature rises may lead to eye cataract, eye temperature rise as result of electromagnetic radiation and heat light exposure should be as low as possible. Intermittent social media exposure results 3.1% lower energy consumption and 22.8% slower eye temperature rise.
The LCL filter design for three phase DC-AC voltage converter
Authors: Hasan S , Suherman  , Saragi D P , Siregar Y , Al-Akaidi M
Published: February 2021

This paper discusses LCL filter design to apply for a three phase DC-AC converter from a DC source of distributed generator to a three phase power system. System is transformer less, using H-bridge switching with 6 IGBTs, modelled by using PSIM to deliver 20 kW 400V source to a three phase 380 V 50 Hz system. the LCL filter requires inductors 518,564 μH and 311.13 μH, capacitor of 65.74μF. The loss resistance is 0.573 Ohm. The LCL filter is able to smooth DC-AC converter output starts from 0.005 s.
Video streaming application with post-decoding concealment technique
Authors: Suherman  , Al-Akaidi Marwan , Siregar Yulianta
Published: February 2021

WiMAX employes high speed wireless technology and enables high bit rates real time video streaming in wireless environment. Many researchers have proposed various techniques and methods to evaluate and improve video transmission over WiMAX. However, dropped packets seem always exist. This paper implements java based video streaming application over WiMAX network and examines whole frame post-decoding concealment method to reduce dropped packet effect. The result is that packet drop impact in frame can be reduced with PSNR improvement about x dB. However, as concealment performed after decoding, there is additional delay in displaying the image which causes short flicker.
Study the electrical, thermal behaviour of (glass/jute) fibre hybrid composite material
Authors: Hamdan Zahra K. , Ogaili Ahmed Ali Farhan , metteb Zaineb w. , Abdulla Fadhel Abbas
Published: February 2021

This study focused on the electrical and thermal properties of many natural composite material specimens. In this study, three kinds of composite materials were used epoxy, jute, and fibreglass. The first type was epoxy-strengthened glass fibre with volume fraction (50%), the second type of Hybrid natural jute, and glass fibre strengthened epoxy of (50%) thickness proportion (25%glass fibre + 25 %jute). Finally, the third type of natural fibre (jute) was strengthened with a volume fraction of epoxy (50%). This research was studied the thermal and electrical conductivity for three types of composite. Results revealed that the values of thermal conductivity and electrical conductivity for fibreglass/epoxy composite samples outweigh two other forms.
The Effect of River Meanders on River Morphology
Authors: Juliandar Mangambit , Nuryono Budi , Siahaan Yakub , Trimo Didik , Mahardika Andrew Ghea
Published: February 2021

Meander is a change in the flow of a river that forms a Semicircle or like the letter S whose fingers are irregular or irregular due to horizontal and centrifugal pressure. One of them that has a meander river is in citarum watershed, located in Majalaya Sub-district, Kab. Bandung. There is a change in the morphology of the river so that the geometry of the river changes from its original shape. The purpose and purpose of the Research to analyze the value of speed, meander fingers, and the morphological influence of rivers so that the problems that arise can be reduced and the benefits/potential possessed can be optimized. The research method used comparative causal methods (causal relationships). The results suggest meander river like the letter S is quite Ideal. Materials along the meander section contain clay, gravel, sand and macaques, clay stones and ash and black stones. Meander River with a length of ± 975 m is divided into five segments, namely. It was then concluded that V<, Q< → Rc > and V>, Q> → Rc < as well as morphological types A, E, G, F & DA.
Development of Automatic Oil Refueling System Model based on Internet of Things
Authors: Ramady Givy Devira , Lestari Ninik Sri , Mahardika Andrew Ghea , Fadriani Hetty , Santoso Purwadi Budi , Hidayat Rahmad
Published: February 2021

The current application of technology has played a large role in human activities, especially in industry. One of the technologies applied is an automatic filling and packaging system for cooking oil using a filling machine. The application of cooking oil packaging technology using modern machines is usually carried out in the large-scale cooking oil industry. However, the packaging for bulk cooking oil which is common in traditional markets that are classified as a small scale still uses the conventional method of measuring and packaging it. To improve the quality of bulk cooking oil sales and answer this problem, we need a tool that can fill the oil with an adjustable number of measures as needed and has high accuracy and can be run automatically. This research uses descriptive qualitative research methods, this type of qualitative descriptive research displays the results of the data as they are without any manipulation or other treatment processes. The overall results of the work system design of this tool discuss the results of the automatic oil filling system and the sending of oil expenditure data to the Antares ID webserver. The resulting delay value is still below the normal limit, which is around 1-2 seconds. The deviation that occurs is in the ratio 0.11 and the percent error is in the range of 0.2%.
Effect of temperature variation on the fluctuation of a sessile bubble rising in a stagnant medium
Authors: Faik A M E D , Mohammed A A
Published: February 2021

The present work represents an experimental investigation of the flow dynamics and features of a rising isolated bubble within a stagnant water column under variable temperature. The experimental tests have been carried out using high speed imaging with backlighting. Five different values of the water temperature (namely 10, 20, 30, 40, and 50°C) have been implemented during the experiments. The studied features are the bubble size (diameter and circumference), bubble shape (sphericity and aspect ratio), bubble rising velocity, in addition to the bubble zigzag motion features (angle, maximum horizontal diameter, velocity, and occurrence time portion). The obtained results showed that as the temperature increases, the degree of bubble zigzag motion from its vertical path increases, which means the flow of the bubble becomes less stable. Bubble diameter is shown to be irresponsive to temperature for small value increase, whereas, for greater temperature magnitudes (from 30 to 50°C) it is shown to be proportional. All other features are shown to be proportional to temperature variation. The zigzag motion features are also shown to be proportional to water temperature variation except the average occurrence time is inversely proportional to this change.