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Indonesia is a tropical country that experiences forest fires every year. Forest fires occur due to a prolonged summer season. A major effect of forest fires that commonly occurred in Indonesia is the respiratory disorder and the visual impairment caused by the thick smoke that can experienced by the people who lives around the forest. The effects of forest fire fumes when the forest fire spread across the bigger land or area are also experienced by neighboring countries such as Malaysia, Singapore and Brunei Darussalam. Forest is a habitat for many animals, one of which is a bird. Birds are able to communicate with their colonies through sound. The bird sound during communication to the group can be in the form of calls, marriage invitations, and warnings of danger or threat of forest fires. This paper presents bird sounds classification study using one of Deep Learning (DL) algorithms i.e. Convolutional Neural Network (CNN) method. The CNN method is used to classify bird sounds in the two conditions: (1) under normal circumstances or conditions, and (2) under threated or panic condition. The bird sound data used in this study were collected from the local birds in Indonesia. The classification result of two bird sounds based on CNN method achieved up to 96.45%. This paper is a preliminary study for bio inspired early warning of forest fires based on the sound of birds.

In this work, the solar water collector flow tube geometry is modified as curved and spiral to enhance the system’s performance. The investigation is carried out experimentally under the meteorological conditions of the Kovilpatti region (9°10 ′ 0 ″ N, 77°52 ′ 0 ″ E), Tamil Nadu, India. The flow pipes of the solar water heater are made of copper material which has higher thermal conductivity to recover the water heat as thermal energy. The influence of the mass flow rate (MF) on the flow pipes with respect to the surface temperature for various configurations of the flow tubes is investigated. The two MFs of 0.0045 kg/s and 0.006 kg/s are tested. The MF of 0.006 kg/s yields the maximum efficiency of 73% compared to the other MF. The straight, curved, and spiral tubes yielded the maximum efficiency of 58%, 62%, and 69%, respectively, at 0.0045 kg/s. Similarly, the MF of 0.006 kg/s obtained an efficiency of 62%, 65%, and 73% for straight, curved, and spiral flow tubes, respectively. The economics and exergy of the system are analyzed. The maximum exergy efficiency of the collector is estimated to be 32% for the MF of 0.0045 kg/s for the spiral flow collector, and for the 0.006 kg/s MF, the obtained exergy efficiency is 27% for the spiral flow water heater. The economic analysis revealed that the expense is $0.0608 and $0.0512 worth of hot water produced for the domestic space heating.

In Polarimetric SAR (PolSAR) and synthetic aperture radar (SAR) requires efficient filtering approach for effective processing of captured quad-polarized images. Due to polarization speckles arises in the captured PolSAR images which causes complexity in collection of data from PolSAR images. This limitation has been overcome through application of effective despeckling technique for efficient processing of PolSAR images. Several techniques have been evolved over past three decades to reduce those speckle in image captured by PolSAR, and recent research studies illustrated a efficient trend for filtering local single-point to non-local patch-based or global collaborative filtering. In this paper, applied contourlet technique for effective despeckling of PolSAR images. This contourlet transformation technique perform thresholding and transformation for efficient despeckling of captured images. Contourlet transformation technique is applied in PolSAR images with speckle and performance metrices are observed. Contourlet technique is comparatively examined with conventional transformation technique which involved in despeckling of images. Analysis of results exhibited that DWT (Discrete Wavelet Transform) approach exhibits similar performance related to contourlet transformation technique. Through analysis of results it is observed that computation time also significantly reduced in contourlet transformation rather than conventional technique. Further mean and window sizing also significantly maintained in contourlet technique for various noise variance.

Waste disposal of expended lithium-ion batteries enables recovery, recycling and reduction of greenhouse gas emissions. Complete discharge of electrochemical devices, especially release through electrode material and current collector (copper/aluminum foils). The release among electrode material particles, is the essential requirement for ensuring the energy yield of polymer electrolytes. In this work, existing technologies which used release electrode materials with spent lithium-ion batteries. Treating the underlying effects of lithium-ion battery oxidation is especially complex of the indirect pathways identified. Aging mechanisms are also divided into three degradation modes (DMs) for simplicity: loss of conductivity, a deficit of active material, and decline of lithium production. It’s launched the lithium-ion secondary battery structure and assemblies outlined all forms of recycling processes from spent lithium-ion secondary batteries and provided some examples of common mixed recycling processes. Also, the problems and prospects of their recycling technology is discussed.

Wind energy is a created due the uneven heating of the earth surface and Coriolis acceleration. Wind energy source is capable of continuously and sustainably producing energy from renewable sources (RES). However, energy generation from the wind power plant has number of issues, such as initial investment costs, wind power plant stationary properties and difficulty in identifying wind power zones. Three deep learning algorithms are utilized in the study for predict short-term wind power generation from wind speed data. We suggested a system that would effectively predict wind power values of wind power by utilizing machine learning algorithms. The machine algorithms adopted for this study is Long Short-Term Memory (LSTM), Gated Reference Unit (GRU) and Recurrent Neural Network (RNN). The models proposed are applied in six times to the projection of wind farm output. The error analysis to balance performance and other approaches is carried out. More concerns are also discussed on short-term wind energy forecasts accuracy improvement. Furthermore, the results have shown that machine learning models can be used in locations other than models. This research showed that, if the basic location model is reasonable, machine learning algorithms could be efficiently used before installation of the wind power plants in an unknown geographical area.

Present research study shows the evacuated tubes coupled with solar still to enhance the yield. Basin area of 1-meter square taken for the experiments and 14 evacuated tubes have been used at a lower side of the still. Calcium stones as sensible heat storage material (SHSM) have also been utilized to enhance the yield in present work. Three modes of experiments have been performed namely conventional solar still (CSS), solar still with evacuated tubes (SSET) and solar still with evacuated tubes and calcium stones (SSETCS) during January to June 2019 at Patan District, Gujarat. Groundwater was taken as feed water in present experiments. It was examined that the average yield was enhanced by 113.52 % and 104.68 % by use of SSET and SSETCS. The payback time (PBT) also determined in current work, and it was 237 for SSETCS. At last, it was concluded that the calcium stones are good SHSM to reduce water quantity and accumulate the heat during the daytime.

In the present work, transient liquid phase bonding (TLP) of stainless steel 316 L to Ti-6Al-4 V using simultaneously both Cu and Ni interlayers was performed and effect of bonding temperature (950 to 1050 °C) on microstructure and mechanical properties of the joints was studied. The joint zones were analyzed using scanning electron microscopy (SEM) equipped with energy dispersive spectroscopy (EDS). Microhardness and shear strength tests were also applied to evaluate the mechanical properties of the joints. The results showed that various eutectic phases and intermetallic compounds were formed at the interface; however, diversity of intermetallics was different in the joint zone for each specimen which can be due to the bonding temperature and type of eutectic phase transformation. The more increase of bonding temperature to higher than 1000 °C, the more deterioration in mechanical properties of the bonded joints is led so that the shear strength decreased from 385 MPa (maximum value) to 257 MPa.

Solar irradiance forecasting is an inevitable and most significant process in grid-connected photovoltaic systems. Solar power is highly non-linear, and thus to manage the grid operation efficiently, with irradiance forecasting for various timescales, such as an hour ahead, a day ahead, and a week ahead, strategies are developed and analysed in this article. However, the single time scale model can perform better for that specific time scale but cannot be employed for other time scale forecasting. Moreover, the data consideration for single time scale forecasting is limited. In this work, a multi-time scale model for solar irradiance forecasting is proposed based on the multi-task learning algorithm. An effective resource sharing scheme between each task is presented. The proposed multi-task learning algorithm is implemented with a long short-term memory (LSTM) neural network model and the performance is investigated for various time scale forecasting. The hyperparameter estimation of the proposed LSTM model is made by a hybrid chicken swarm optimizer based on combining the best features of both the chicken swarm optimization algorithm (CSO) and grey wolf optimization (GWO) algorithm. The proposed model is validated, comparing existing methodologies for single timescale forecasting, and the proposed strategy demonstrated highly consistent performance for all time scale forecasting with improved metric results.

The durability and reliability of battery management systems in electric vehicles to forecast the state of charge (SoC) is a tedious task. As the process of battery degradation is usually non-linear, it is extremely cumbersome work to predict SoC estimation with substantially less degradation. This paper presents the SoC estimation of lithium-ion battery systems using six machine learning algorithms for electric vehicles application. The employed algorithms are artificial neural network (ANN), support vector machine (SVM), linear regression (LR), Gaussian process regression (GPR), ensemble bagging (EBa), and ensemble boosting (EBo). Error analysis of the model is carried out to optimize the battery’s performance parameter. Finally, all six algorithms are compared using performance indices. ANN and GPR are found to be the best methods based on MSE and RMSE of (0.0004, 0.00170) and (0.023, 0.04118), respectively.

One of the biggest challenges is towards ensuring large-scale integration of photovoltaic systems into buildings. This work is aimed at presenting a building integrated photovoltaic system power prediction concerning the building’s various orientations based on the machine learning data science tools. The proposed prediction methodology comprises a data quality stage, machine learning algorithm, weather clustering assessment, and an accuracy assessment. The results showed that the application of linear regression coefficients to the forecast outputs of the developed photovoltaic power generation neural network improved the PV power generation’s forecast output. The final model resulted from accurate forecasts, exhibiting a root mean square error of 4.42% in NN, 16.86% in QSVM, and 8.76% in TREE. The results are presented with the building facade and roof application such as flat roof, south façade, east façade, and west façade.

In this study, the potential of Ge44 and Al22P22 as anode electrodes of Li-ion, Na-ion, and K-ion batteries were investigated via density functional theory. The effect of halogen doping of Ge44 and Al22P22 on ability of metal-ion battery was examined. Obtained results shown that Al22P22 as anode electrode in metal-ion batteries has higher potential than Ge44. Calculated results shown that K-ion battery has higher cell voltage and higher performance than Li-ion and Na-ion batteries. Results display that halogen doping increase the cell voltage and performance of studied metal-ion batteries. Calculated results indicated that F‑doped metal-ion batteries have higher cell voltage and higher performance than Cl- and Br-doped metal-ion batteries. Finally it can be concluded that F-doped Al21P22 as anode electrode in K-ion battery has the highest performance.

Three-pass Protocol is a method or technique that can be used by 2 (two) sender and recipient of the message to communicate with each other using XOR function, the problem that occurs is when the communication process there is parties who can know the messages sent from the sender to the recipient. To solve the problem we need an algorithm in this case Pohlig-Hellman algorithm, the use of Pohlig-Hellman algorithm on Three-pass Protocol ensures the security of messages sent by the sender to the receiver because each sender and receiver uses keys p, e, and d which is a number random and d is the inverse modulo of p and e of the sender and receiver, the results of this research suggest that it is impossible for the attacker or cryptanalyst to know the correct message quickly despite having adequate computer resources.

Disaster like the supercyclone Amphan which devastated the states of West Bengal and Odisha in India caused severe disruption to the life, and led to widespread economic losses which surpassed the proficiency of the society to overcome with sustenance from its own assets. The main prospect for disaster risk reduction lies in decreasing susceptibility and exposure to such hazards. In our study, we targeted identification and lessening the factors driving the risk, to understand risks of hazards such as Amphan. Thereafter, we explained the pathways of understanding disaster risks and ways of building resilience involving every section of society, government, nongovernmental organizations including the private sector which may influence sustainable development. We summarized that disaster mitigation required a people-oriented multi-sector methodology which may help build resilience to manifold, surging and interrelating hazards and generating principles of deterrence and resilience through all societal sections. The developmental plan of actions discussed to ensure disaster resilience, needs to permeate through all societal levels including the financial structure, risk-sharing strategies and social safety device mechanisms. Significant prospects to achieve synergies between actions intended to strengthen resilience may help to achieve progress towards the achievement of disaster risk reduction. Understanding the risk of a disaster like Amphan, developing resilience against it to create sustainable development had not been explored previously. The paper reported insight into the ways adapted by central & state government and the local bodies to reduce the risk and build resilience against a disaster like Amphan.

The combination of Steganography and cryptography algorithms can improve the security of data you want to keep secret. Pixel Value Differencing (PVD) algorithm combined with Word Auto Key Encryption (WAKE) algorithm and Modular Multiplication Block Cipher algorithm can produce good ciphertext and inserted on image media by using PVD algorithm that convert each ciphertext into pixel.

Modern digital life have been produce giant data in every sectors. This big data need new approach as cloud computing term. The combination of these two technology have been used by SMEs. Smartphones enable the dissemination of the applications to customers around the world. Three most popular sectors in adopting big data and cloud computing are market places business, online transportation, and online travel agents. The study showed that the adoption of big data and cloud computing gained big success for SMEs.

Currently, data security is crucial so as not to fall into the hands of irresponsible, steganography and cryptography is a technique commonly used to secure information from irresponsible parties by using computational algorithms such as Pixel Value Differencing Algorithm on steganography process and GOST (Government Standard) for the cryptographic process, so that the process of insertion of messages (steganography) in the image will be encrypted first newly inserted, this process is expected to increase the security of confidentiality and integrity because Pixel Value Differencing Algorithm process used to add messages by changing the hexadecimal pixel color with hexadecimal message Encryption algorithm GOST.

Deep learning is an encouraging approach for extracting precise information from raw sensor data from IoT devices. In this paper, Hashed Needham Schroeder (HNS) Cost Optimized Deep Machine Learning (HNS-CODML) method for secure Industrial IoT data transmissions via cloud environment has been proposed by indicating the necessity of providing Industrial IoT security using machine learning technique. First, HNS Public Key Generation (PKG) mechanism computes the public key and a flag value, then using public key, the execution time has been improved as only authenticated cloud users (CU) are allowed to exchange the data/messages via secured channel and can be trained; thus the cost function can be computed using two passes. In the first pass, the cost function has been measured while in second pass, the overall cost function is obtained, therefore reducing the computational cost (CC) and communication overhead (CO), making the entire process much easier to monitor and control.

Image magnification is one of the branches in digital image processing that is often required in various applications such as in the field of medicine, multimedia, and in satellite imagery. As technology grows, more and more methods are used for image enlargement. In this study, the image enlargement process performs by using Bi-Cubic spline interpolation method, and the result of image try to compare between the original one and picture after enlargement.

Computer and web security system is an attempt to avoid attacks from crackers because a form and method of crime on internet network can not be predicted. Therefore, we just keep trying to use various methods in securing the system that is running. It is the same in web testing that can be accessed online by people who are not responsible from along distance to change and remove the test results or even damage the web testing system. So, the purpose of this paper is to design and implement web security testing system by using semantic comparison method to avoid structured query language injection (SQLI) attack and to do security on web testing application using Message Digest 5 encryption (MD5). Research data were obtained by using direct observation and documentation and literature review. After the design and application of the system, it can be obtained that by using semantic comparison method in web testing can prevent the occurrence of SQL injection attacks and can secure account from web testing users by using MD5.

This paper aims to facilitate the owner to control water pump machine from the vacuum, and the condition of the water is it full or not in house or apartment. The current control system still has many limitations in controlling the water pump machine at home or apartment. The water machine control system was designed with device that has a smart surveillance system that can be accessed with Android smartphone and all information from or to machine control system will command by using SMS, this device create a development of Arduino UNO microcontroller technology that allows the reading of the GSM Module and connected with SMS Gateway. Experiment results facilitate real-time water control and much easy for the owner to control water tank.

Data security on Radio Frequency Identification (RFID) cards for parking security applications need to be applied for more protection especially information on RFID cards, as well as to improve security on RFID access authentication and verification using cryptography algorithm, one of the algorithms that can be used for authentication and verification in RFID communication process is International Data Encryption Algorithm (IDEA) algorithm, the results obtained that the data security on RFID can work well.

Security in a transaction activity is crucial, in digital communication that irresponsible parties can tap all objects sent in the form of bits, the use of cryptographic algorithms such as Base64 and Word Auto Key Encryption can be a solution that produces a secure ciphertext, base64 algorithm which can encode all objects such as text, image, and audio files into text form and the result is re-secured with Word Auto Key Encryption algorithm, the results of this research get better security by combining the two algorithms.

Decision Support System is a system commonly used to assist management in assisting decision-making in top managerial sections, Multi-Criteria Decision Making (MCDM) is one of many decision-making methods that can be used to select the best alternative from a number of alternatives based on certain criteria, one of the methods that can be utilized is the Elimination Et Choix Traduisant la Realite (ELECTRE) method that works based on the concept of outranking using pairwise comparisons of each alternative based on appropriate criteria, this paper applies the ELECTRE method in a web based application that can be employed for input and output dynamic for alternative, criteria, user values and also a fast ranking process, the choice of web based application because there is many research about decision support system but only few that applied to application, and this research tries to applied ELECTRE method to web based application.

Keeping the data intact without changing becomes an important factor in a communication, the data itself has many forms such as text data, audio data, image data and for secure every form data an algorithm Base64 are needed, Base64 algorithm is used as data format to transmit data due to the result of base64 itself, but Base64 algorithm is not safe enough because it is easy to decoding and get the original form data, therefore need additional security and in this research combined with Hashing Variable Length (HAVAL) algorithm, HAVAL algorithm has a way work secures and compresses plaintext, so the encoding result from Base64 is re-secured and compressed using HAVAL algorithm with length of hashing 32 bit or 4 bytes so when data transmission process will not take many bytes of data compared with Base64 algorithm

The Consumer Price Index is an index which calculates the average change in prices over a period, of a set of goods and services consumed by the population/households within a specific time. In this paper will be discussed about the forecasting of consumer price index of Indonesia using forecast package with R Software. The forecasting process this data using algorithms popularized by Rob J. Hyndman and Yeasmin Khandakar in 2008. By using this method, it is obtained a suitable ARIMA model to forecast CPI data Indonesia. The model most suitable time series is ARIMA (1,0,0).

Decision Support System is a system commonly used to assist management in assisting decision-making in top managerial sections, Multi-Criteria Decision Making (MCDM) is one of many decision-making methods that can be used to select the best alternative from a number of alternatives based on certain criteria, one of the methods that can be utilized is the Elimination Et Choix Traduisant la Realite (ELECTRE) method that works based on the concept of outranking using pairwise comparisons of each alternative based on appropriate criteria, this paper applies the ELECTRE method in a web based application that can be employed for input and output dynamic for alternative, criteria, user values and also a fast ranking process, the choice of web based application because there is many research about decision support system but only few that applied to application, and this research tries to applied ELECTRE method to web based application.

The security and confidentiality of information becomes an important factor in communication, the use of cryptography can be a powerful way of securing the information, IDEA (International Data Encryption Algorithm) and WAKE (Word Auto Key Encryption) are some modern symmetric cryptography algorithms with encryption and decryption function are much faster than the asymmetric cryptographic algorithm, with the combination experiment IDEA and WAKE it probable to produce highly secret ciphertext and it hopes to take a very long time for cryptanalyst to decrypt the information without knowing the key of the encryption process.

K-Means Clustering (KMC) is a technique used in performing data groupings. The data classification procedure is based on the degree of membership of each member. The purpose of this study is to group the existing Provinces in Indonesia based on Population Density, School Participation Rate, Human Development Index, and Open Unemployment Rate using K-Means Clustering. The result reveals 5 large clusters in each center in South Sumatra, Lampung, DKI Jakarta, Central Java, and West Kalimantan.

Cryptography is a field of science that can be learned to secure data and information, cryptography is used in almost all communications both in network and non-network; and one of the algorithms could use is RC4 algorithm, publication about RC4 algorithm is quite a lot but the discussion is dominant only theory alone does not complete the RC4 algorithm process in detail and applications only show input and output none of the processes include, in this research paper illustrates the process of RC4 algorithm in detail and with visualization to demonstrates the work of RC4 algorithm to make it easiest for readers to learn cryptography

Developing country mostly left behind in adopting e-Government system. Miss-interpretation is assuming e-Government only about the application of technology made fail implementation. It is a whole philosophy that explores a human-citizen centered aspect in organized societies. Further, successful information system determined by user acceptance. Therefore, the evaluation of the performance of e-Government is one of the basic objectives of current government reformation. The research focus is to identify and explore the extent of user acceptance toward e-Government system. The research methodology used in this research is survey based on a questionnaire with TRAM approach and distributed to 230 respondents as customers that had been using e-Government services provided by X institution. The result of the study showed that the personality traits of TR significantly influenced cognitive dimensions of TAM. Through empirical demonstrations indicated that the TRI was said to be antecedents to TAM. The optimism dimension had higher coefficient among others, exhibit the technology users convince that the new technology will improve their productivity, while discomfort had no impact since the users have no doubt or hesitate to use technology.

FTP (File Transfer Protocol) is one of the earliest Internet protocols developed. An FTP server can be accessed by using a URI (Universal Resource Identifier), using FTP file exchange between client and server is easier to do because the communication is done directly without going through an intermediary, for communication using FTP need to be designed an application that allows communication between the client and server directly without using the browser, for it is designed an FTP application using programming language in this case is Borland Delphi programming language, the ease of sending files between computers based on IP is a value added from the FTP application that is designed because most existing FTP applications can only send files between the server and the client in the internet network means that online must not be local area network or wide area network.

The steganography process combines mathematics and computer science. Steganography consists of a set of methods and techniques to embed the data into another media so that the contents are unreadable to anyone who does not have the authority to read these data. The main objective of the use of base64 method is to convert any file in order to achieve privacy. This paper discusses a steganography and encoding method using base64, which is a set of encoding schemes that convert the same binary data to the form of a series of ASCII code. Also, the EoF technique is used to embed encoding text performed by Base64. As an example, for the mechanisms a file is used to represent the texts, and by using the two methods together will increase the security level for protecting the data, this research aims to secure many types of files in a particular media with a good security and not to damage the stored files and coverage media that used.

Searching is a common process performed by many computer users, Raita algorithm is one algorithm that can be used to match and find information in accordance with the patterns entered. Raita algorithm applied to the file search application using java programming language and the results obtained from the testing process of the file search quickly and with accurate results and support many data types.

A radiation pattern of a reconfigurable pixel structure antenna that operates in three steerable beam directions of {-40º, 0º, 40º} is presented. The proposed antenna consists of a circular driven structure on the bottom layer with a pixel structure placed in the top layer. The pixel structures of small square-shaped metallic patches are used to provide beam steering reconfiguration capabilities to the antenna. The adjacent pixels are connected by PIN diode switches with ON/OFF status to change the electrical geometry of the pixel surface, which changes the current distribution on the antenna, thus provides reconfigurability in beam steering direction. The proposed antenna operates at 9.5GHz frequency for X-Band radar application. This antenna is capable to achieve a tolerable return loss of less than -10dB with an average gain of 8 dBi at all desired angles.

The fabrication of starch-hydroxyapatite (HA) scaffolds was conducted previously by using corn, tapioca and rice. Here, local brown rice was chosen as the source of starch since different type of rice may give different outcome of in term of the scaffold’s materials characteristics. The main aim of this study is to obtain a brown rice starch-hydroxyapatite (HA) composite scaffolds that could imitate the structure and the characteristics of a natural bone. The fabrication process involved solvent casting and particulate leaching method which using NaCl as a porogen agent. Four ratios of starch-HA were fabricated with concentration of starch 50wt%, 60wt%, 70wt% and 80wt%. Afterward, the effects of the brown rice starch on the scaffolds were investigated by water absorption test and Scanning Electron Microscope (SEM). Here, only 50wt% and 60wt% ratio of starch-HA can be used to fabricate tissue scaffolds using solvent casting and particulate leaching method. Hence, the 60wt% ratio scaffolds has the highest water absorption of all and the pore’s size observed through SEM corresponded to this. The FTIR also shows there are more interactions between Brown Rice starch and HA for the 60wt% ratio.

Data Mining is a process of exploring against large data to find patterns in decision making. One of the techniques in decision-making is classification. Classification is a technique in data mining by applying decision tree method to form data, algorithm C4.5 is algorithm that can be used to classify data in tree form. The system has been built that shows the results of good performance and minimal error in view of the system that is able to distinguish the anomaly traffic with normal traffic. Data mining inventory system applications can facilitate the control of inventory in the company to reduce production costs.

Decision Support System is an interactive system that supports decision in the decision-making process through alternatives derived from the processing of data, information and design of the models. Selection decision support system of chemical fertilizer in fruit plant is expected to help anyone who wants to cultivate fruit trees can determine the chemical fertilizer as expected based alternatives and criteria set by the user. In this research method used is TOPSIS Method and Method of Fuzzy Logic. TOPSIS method is one of multiple criteria decision making method that uses the principle that the alternatives selected must have the shortest distance. Fuzzy Logic is a methodology of control systems troubleshooting, the fuzzy logic stated that everything is a binary which means it is only two possibilities, "Yes or No", "True or False", "Good or Bad", and others. Therefore, all of these can have a membership value of 0 or 1.

Security issues are an important part of everyday life. A vital link in security chain is the identification of users who will enter the room. This paper describes the prototype of a secured room access control system based on face recognition. The system comprises a webcam to detect faces and a solenoid door lock for accessing the room. Every user detected by the webcam will be checked for compatibility with the database in the system. If the user has access rights then the solenoid door lock will open and the user can enter the room. Otherwise, the data will be sent to the master user via Android-based smartphone that installed certain applications. If the user is recognized by the master user, then the solenoid door lock will be opened through the signal sent from the smartphone. However, if the user is not recognized, then the buzzer will alert. The main control circuit on this system is Raspberry pi. The software used is OpenCV Library which is useful to display and process the image produced by webcam. In this paper, we employ Haar Cascade Classifier in an image processing of user face to render the face detection with high accuracy.

The induction motor has in the industry . More attention has been a focus to develop and design of induction motor drive. With the method of vector control novelty prove the efficiency of induction motor over their entire speed range. In this paper desirable to design a loss minimization controller which can improve the efficiency. Also, this research described Modeling of an induction motor with core loss included. Realization of methods vector control for an induction motor drive with loss element included. The case of the loss minimization condition. The procedure was successful to calculate the gains of a PI controller. Though the problem of obtaining a robust and sensorless induction motor drive is by no means completely solved, the results obtained as part of this work point in a promising direction.

Congklak is a favorite populist game played at least 2 (two) players or in this article were human user and computer (AI). An essential point of playing congklak is to collect as many congklak seeds as possible to win the game, to win form from congklak it need a technique and it’s different for each players. Breadth First Search algorithm is a search algorithm which process to visit each node and the neighbors node to generate optimal graph that gives the best solution to computer (AI) and in this case were to complete the congklak game. Breadth First Search algorithm could be uses an alternative solution for optimal solution to win congklak with the help of mathematical computation.

Cybercrime is one of the most serious threats. Efforts are made to reduce the number of cybercrime is to find new techniques in securing data such as Cryptography, Steganography and Watermarking combination. Cryptography and Steganography is a growing data security science. A combination of Cryptography and Steganography is one effort to improve data integrity. New techniques are used by combining several algorithms, one of which is the incorporation of hill cipher method and Morse code. Morse code is one of the communication codes used in the Scouting field. This code consists of dots and lines. This is a new modern and classic concept to maintain data integrity. The result of the combination of these three methods is expected to generate new algorithms to improve the security of the data, especially images.

Membership function is a curve that shows mapping the input data points into the value or degree of membership which has an interval between 0 and 1. One way to get membership value is through a function approach. There are some membership functions can be used on mamdani fuzzy inference system. They are triangular, trapezoid, singleton, sigmoid, Gaussian, etc. In this paper only discuss three membership functions, are triangular, trapezoid and Gaussian. These three membership functions will be compared to see the difference in parameter values and results obtained. For case study in this paper is admission of students at popular school. There are three variable can be used, they are students' report, IQ score and parents' income. Which will then be created if-then rules.

Symmetric type cryptography algorithm is known many weaknesses in encryption process compared with asymmetric type algorithm, symmetric stream cipher are algorithm that works on XOR process between plaintext and key, to improve the security of symmetric stream cipher algorithm done improvisation by using Triple Transposition Key which developed from Transposition Cipher and also use Base64 algorithm for encryption ending process, and from experiment the ciphertext that produced good enough and very random.

Prediction using a forecasting method is one of the most important things for an organization, the selection of appropriate forecasting methods is also important but the percentage error of a method is more important in order for decision makers to adopt the right culture, the use of the Mean Absolute Deviation and Mean Absolute Percentage Error to calculate the percentage of mistakes in the least square method resulted in a percentage of 9.77% and it was decided that the least square method be worked for time series and trend data.

One of the roles of decision support system is that it can assist the decision maker in obtaining the appropriate alternative with the desired criteria, one of the methods that could apply for the decision maker is SMART method with multicriteria decision making. This multi-criteria decision-making theory has meaning where every alternative has criteria and has value and weight, and the author uses this approach to facilitate decision making with a compelling case. The problems discussed in this paper are classified into problems of a variety Multiobjective (multiple goals to be accomplished) and multicriteria (many of the decisive criteria in reaching such decisions).