Ahmad Ashari

Performance Comparison between Naïve Bayes, Decision Tree and k-Nearest Neighbor in Searching Alternative Design in an Energy Simulation Tool

Energy simulation tool is a tool to simulate energy use by a building prior to the erection of the building. Commonly it has a feature providing alternative designs that are better than the users design. In this paper, we propose a novel method in searching alternative design that is by using classification method. The classifiers we use are Naive Bayes, Decision Tree, and k-Nearest Neighbor. Our experiments hows that Decision Tree has the fastest classification time followed by Naive Bayes and k-Nearest Neighbor. The differences between classification time of Decision Tree and Naive Bayes also between Naive Bayes and k-NN are about an order of magnitude. Based on Percision, Recall, F- measure, Accuracy, and AUC, the performance of Naive Bayes is the best. It outperforms Decision Tree and k-Nearest Neighbor on all parameters but precision. Energy simulation tool is a tool to simulate energy use by a building prior to the erection of the building. The output of such simulation is a value in kWh/m 2 called energy performance. The calculation of the building energy performance must be carried out by developers as part of requirements to get permit to build the building. The building can only be built if the energy performance is below the allowable standard. In order to get building energy performance below the standard, architects must revise the design several times. And in order to ease the design work of the architects, an energy simulation tool must have a feature that suggests a better alternative design. Since the alternative design search is actually a classification problem, hence in this paper we propose a novel method to search alternative design by using classification method. The classification methods used in here are Decision Tree, Naive Bayes, and k-Nearest Neighbor. We will then compare the performance of these three methods in searching alternative design in an energy simulation tools.

Quadrotor flight stability system with Routh stability and Lyapunov analysis

UAV (Unmanned Aerial Vehicle) can fly autonomously or be controlled remotely by a pilot. Quadrotor as one type of UAV has been widely implemented in various needs. Its system design has a lot of control techniques involved. The design starts with the physical modeling. Quadrotor physical modeling is modeling based on the laws of physics as a theory and mathematical modeling of physical interpretation. The problem arises when actual plants are not fit with mathematical models that are used as the control design before. Such discrepancy arises because of external interference, plant parameters, and dynamics models that are nonlinear. If control systems are not designed to deal with non-linear interference, it is difficult to us to maintain quadrotor flight. Therefore, we need control methods that can be applied to linear and nonlinear systems. Routh Stability can be used to generate PID (Proportional Integral and Derivative) constants as a linear control method by using a Ziegler-Nichols. Lyapunov as a meth...

Design of agent framework using aspect oriented approach

Software agent system so far has been developed using object-oriented (OO) approach. In fact, OO analysis and design can not fully model mobile agent system. The main problem is crosscutting concerns (CCC) which makes modularization of program can not be clean. Aspect-oriented (AO) approach offers a solution for CCC problems in OO approach. This paper discusses AO approach used to modify an OO agent framework. Architectural design of agent system is proposed to be a fundamental solution. The design started from architectural level to get a comprehensive models. Transformation process from architectural level into implementation level in development of agent framework becomes an important part in the discussion to express clean model. A method that can be implemented to develop agent framework is by using AO to OO refactoring. The refactoring will transform OO agent framework into AO agent framework. The result of research get a zero average clone size (ACS). It showed that the design can be implemented cleanly at implementation level.

The use of video processing for quadrotor flight stability control monitoring

The quadrotor is one kind of Unmanned Aerial Vehicles (UAV). Quadrotor has the ability to hover with minimal translational velocity approaching a stationary state. This capability is supported by the four rotors. These rotors are used to lift the Quadrotor to fly. These rotors are placed on all four sides of the tip of Quadrotor. In order to fly with good stability, we can use an IMU sensor (Inertial Measurement Unit). Imu sensor consists of some DOF (degrees of freedom) sensors, such as 3-axis accelerometer sensor, 3-axis gyroscope sensor, 3-axis magnetometer sensor, and so on in accordance with the needs of flight. To test the stability of Quadrotor can be done by utilizing the video and image processing methods. This processing act as the ’eyes’ of Quadrotor. Sobel method as one of the image processing algorithms can be used to read the edges of the object. This method can measure the level of stability fly. But before reading the results of the edge must first be converted to black and white format. O...

Analysis of Zigbee Data Transmission on Wireless Sensor Network Topology

The purpose of this study is to measure the distance in the line of sight environment and to see the data resulted from zigbee transmission by using star, mesh and tree topologies by using delay, throughput and packet loss parameters. The results showed that star topology had the average value which tended to be stable on the measurement of throughput and packet loss because there was no router nodes in star topology so that the accuracy of data delivery was better and it had the smallest delay value because the number of nodes was less than in mesh and tree topology, while the mesh and tree topologies had a poor average value on throughput and packet loss measurements, since the mesh and tree topologies had to go through many processes in which they had to pass through the router node to transmit the data to the coordinator node. However, the mesh and tree topologies had an advantage in which the data delivery could go through more distances than the star topology and they could add more nodes.

Service orchestration using enterprise service bus for real-time government executive dashboard system

The increasing implementation of various platforms and technology of information systems also increases the complexity of integration when the integration system is needed. This is just like what has happened in most of government areas. As we have done from a case study in Sleman, a regency of Yogyakarta Indonesia, it has many departments that use different platform and technology on implementing information system. Integration services using point-to-point method is considered to be irrelevant whereas the number of services are growing up rapidly and more complex. So, in this paper we have proposed a service orchestration mechanism using enterprise service bus (ESB) to integrate many services from many departments which used their owned platform and technology of information system. ESB can be the solution of n-to-n integration problem and it strongly supports the implementation of service oriented architecture (SOA). This paper covers the analysis, design and implementation of integration system in government area. Then the result of this integration has been deployed as a single real time executive dashboard system that can be useful for the governance in order to support them on making decision or policy. Functional and performance testing are used to ensure that the implementation of integration does not disrupt other transaction processes.

Review of Ontology Evolution Process

Ontologies are formal artifacts that are designed to represent the knowledge related to a specific or generic domain in terms of the relevant concepts, relationships between these concepts and the instances of these concepts. Ontology evolution can be defined as the process to adapt and change the ontology in a timely and consistent manner. In this paper, we present a brief description of ontology evolution process of recent research.

Payload Formats and Universal Data for Near Field Communication

NFC has a variant where Type 1 with NFC-A, Type 2 with NFC-A, Type 3 with NFC F, and Type 4 with NFC-B. In its application, the use of NFC is based on its tag type. If we go further, each type has similarities and differences. We can look at the various parameters, but for now we will look at 4 parameters, namely Sequence format, Bit level coding, frame format and data & payload format. From the four parameters, compared to the parameter value and obtained the difference and the equation. With that use, an mobile application only runs in one type, while for another type must be modified. To overcome this, it is proposed a framework that can handle the tags of different types. Proposals are made for universal data and payload formats, and the expectations can be recognized by all NFC tag reading tools. Architectures are built with attention to the similarities and differences for each type. For above four parameters. Beginning with getting the data for the use of the most tag type, then made the proposed universal data format. Commonly used types are types 1 and 2. Of the two types, the differences of the four parameters are on the data and payload parameters. And more specifically on the CRC. Thus, a universal data and payload format with a specific CRC is used. General Terms Embedded system, proximity card technology.

A Model for Forecasting the Number of Cases and Distribution Pattern of Dengue Hemorrhagic Fever in Indonesia

Dengue Hemorrhagic Fever (DHF) ourbreaks is one of the lethal health problems in Indonesia. Aedes aegypti type of insect prolefiration as the main vector of DHF has affected climate factors, such as temperature, humidity, rainfall, and irradiation time. Therefore, to project the number of DHF cases is a very important assignment for the Ministry of Health to initiate contingencies planning as a prevention step in confronting the increasing number of DHF cases in nearby future. This study aims in developing a forecasting model in anticipating the number of cases and distribution pattern of DHF with multivariate time series using Vector Autoregressive Spatial Autocorrelation (VARSA). VARSA model uses multivariate time series, such as a number of DHF case, minimum temperature, maximum temperature, rainfall, average humidity, irradiation time and population density. This modeling is done in two steps: Vector Autoregressive modeling to predict the number of DHF cases and Local Indicators of Spatial Association (LISA) method to visualize distribution pattern of DHF based on the spatial connectivity of the number of DHF cases among the neighboring districts. This study covers 17 districts in Sleman Yogyakarta, resulting in low errors with Root Means Square Error (RMSE) of 2.10 and Mean Absolute Error (MAE ) of 1.51. This model produces smaller errors than using univariate time series methods, such as Linear regression and Autoregressive Integrated Moving Average (ARIMA).

Cloud-Based Processing on Data Science for Visualization

The big data processing and visualization have the challenge on method and process. The volume, variety, velocity, and veracity in the big data need to handle for visualizing the data. The research work investigates, design and develop cloud-based processing for data science visualization. The cloud-based processing used the data management that interact with Google drive, communicate with processing tools that deliver the system, and visualize with Google Fusion. The research uses financial banking data in Indonesia, that analyze based on geolocation, transaction flows, and networks. The research process consists of data mapping process, data tagging, data manipulation, and data visualization to resulting the data science visualization. The cloud-based processing present the data science process can be done use cloud. The research has a contribution on delivering cloud-based approach to handling data science visualization for big data.