Prototype Sistem Pakar Diagnosis Penyakit Diabetes

Every member of the community can experience a variety of diseases. The disease can be known from the symptoms it produces, but to know the exact type of disease, needed a doctor or a health professional. Since the number of doctors or health professionals is very limited and can not overcome the problems of the community at the same time, a system that has the capability of a doctor or health professional is required, which in this system contains the expertise of a physician or health professional on diseases and diseases. In this study was designed expert system using rule base (reason based reasoning) with forward chaining and backward chaining inference method that is intended to assist the community in diagnosing the disease. This disease diagnostic expert system developed has advantages in ease of access and ease of use. With the features that are owned, expert systems for the diagnosis of diseases that built can be used as a tool for disease diagnosis and can be accessed by the public to overcome the problem of limited number of doctors or health experts in helping people diagnose the disease

Prototype Sistem Pakar untuk Penjadwalan

Scheduling is a complex problem, which requires huge resource to solve. The resources required include faculty, lecturer, classrooms, and the period of time for teaching. The solution of academic scheduling in large scale still face up so many obstacles to done manually. The college has to give a schedule in certain time when every academic activity is not crash. Scheduling is needed to anticipate crash of students hours to study and lectures time to teach. Scheduling have to fill the boundary and condition so that it convenient when it used. Under these conditions, a system is needed to set the schedule will not crash so as to improve the work of everyone. The possibility to find the best result and the implemented method approach to solve the problem is use constrain satisfaction method. Making this scheduling application is started with build table of combination from class data, room data, lecture data and time slot and followed by initiation and calculation with genetic algorithm. During the process, we generate the time and room data of each lecturer and test if crash or no crash. From the result, indicate fine schedule means there is no crash between each other and all class can be scheduled. Scheduling is optimal if all of space and time that is provided can be filled without happen crash

Pengukuran Jarak Objek Pejalan Kaki terhadap Kamera Menggunakan Kamera Stereo Terkalibrasi dengan Segmentasi Objek Histogram Of Oriented Gradient

The distance measurement of pedestrian object to camera using a calibrated stereo camera has been investigated. The study was conducted by comparing Data-A and Data-B with different conditions and environment data interpretation. The stereo vision methods include camera calibration, image rectification, disparity counting, three-dimensional reconstruction and object segmentation. The object segmentation is performed using the Histogram of Oriented Gradient feature to segment pedestrian object. Meanwhile, to determine the distance value is based on the information of the centroid of the bounding box segmented object.The calculations were performed using the Euclidian Distance calculation method to find the shortest distance between the centroid of the bounding box with both cameras. From the research results, the best accuracy was obtained with measurement error of 4%

Sistem Monitoring Kendaraan secara 3D dengan Sensor Tekanan Udara dan Global Positioning System (GPS) Berbasis Web secara Realtime

A research on telemetry or remote measurement has been conduced, for the parameters of the position of a moving object, ie the vehicle. Parameters such as latitude and longitude position is obtained from the GPS receiver (Global Positioning System). GPS receiver is used Ublox Noe 6 M. In addition it's also added a altitude parameter, which is obtained by converting the changes of air pressure. Sensor BMP180 used to measure air pressure. Both of these devices are read and controlled by a microcontroller ATmega328 with the Arduino software. The GPS receiver to get latitude and longitude coordinates from the satellite. Coodinates data is sent to a microcontroller, combined with altitide data, then data sent to the database server using internet with GSM network. In this system used web interface that allows users to monitor the position of the vehicle, without necessary for special receiving station. Based on the results of validation latitude and longitude coordinates from the GPS receiver, with GARMIN GPS devices with the GPSMAP 78s series, this GPS receiver has the highest standart deviation ± 0.000006 degrees for the longitude and ± 0.000012 for latitude. The position of the vehicle in form of latitude and longitude coordinates, then illustrated on Google Maps. The results of this study, acqusition system that has been mounted on the vehicle position coordinates can transmit data to the server, and the data transmission process becomes faster and cheaper. This system will continue sends the data for vehicles that are in the area covered by the GSM network provider. Lack of this system is data transmission medium that is highly dependent on the availability of the GSM network. If the GSM network is weak, it can cause failures in data transmission

Analisis Citra Ct Scan Kanker Paru Berdasarkan Ciri Tekstur Gray Level Co-occurrence Matrix Dan Ciri Morfologi Menggunakan Jaringan Syaraf Tiruan Propagasi Balik

The research about analysis of CT Scan image of lung cancer based on texture feature Gray Level Cooccurrence Matrix (GLCM) and morphological using neural network back propagation has been done. Lung cancer is cancer that general occurred in the word. In 2012, 1,8 million new cases lung cancer and 1,6 million mortality because lung cancer. The research aim to analysis CT Scan image of lung cancer based on texture feature Gray Level Co-occurrence Matrix (GLCM) and morphological using artificial neural network back propagation and calculated accuracy of testing artificial neural network back propagation. This research conducts pass through stages of segmentation, feature extraction and classfication. Texture and morphological feature extraction are obtained from the thresholding segmentation. The result of feature extraction are value contrast, correlation, energy, homogeneity and area ratio then used to input in process training and testing using neural network back propagation. Process training is conducts since 4 second with number of iteration 113 iteration. In proces training from 86 train data image, 85 image is able to classified, so acurracy of training up to 98,83% and in process testing from 57 test data, 56 test data is able to classified, so test accuracy value up to 98,24%

Simulator Input-output Sistem Kontrol Menggunakan Raspberry Pi

In this research has been made I / O simulator which is a tool to simulate input and output of a control system using Raspberry Pi. Raspberry Pi has 26 GPIO (General Purpose Input and Output) pins that can be used to control inputs and outputs on the I / O simulator. The 26 GPIO pins are divided into two main systems, is 13 GPIO pins that are odd numbered as inputs and 13 other GPIO pins which are even numbered as outputs. The Raspberry Pi GPIO pins are ordered as inputs and outputs using Python programming languages. The command is done by reading the switch as input signal input, then Raspberry Pi process the input signal and send data as output signal with LED flame on the I / O Simulator. The I / O simulator can simulate logic gates, as AND, OR, NOT, and ADD, and can run mini distillation plant

Aplikasi Pengolahan Citra Pada Raspberry Pi Untuk Membedakan Benda Berdasarkan Warna Dan Bentuk

Computer technology has been developed to support problem solving in human life. Nowadays, minicomputer has been the focus of development for its practicality. The role of technology has progressed from word processing programs to digital image processing programs. Digital image processing is one of technology processing using computer vision. The role of digital image processing is a common process in industries and has been use to increase their productivity. One of those utilizations is image processing in beverage industries to detect the number of empty bottles in crates. Digital processing which supports industries has been a factor to increase productivity. The innovation in the research was utilizing minicomputer called raspberry to be integrated with image processing system and motor servo control. The result is a system to distinguish various objects based on their colors and shapes using image processing system on raspberry based on open CV and to control motor servo to classify objects. The accuracy to classify red circular objects was 92,5% , for green circular objects was 97,5% , and red rectangular objects was 97,5% by using camera resolution 480x320

Pendeteksi Kelelahan Mata Pengemudi Kendaraan Menggunakan Metode Segmentasi Warna dalam Ruang Warna YCBCR

The progress and technology in development of transportation is increasing. However, this is also accompanied by the emergence of some undesirable negative effects such as increased number of traffic accidents. The increase in number of accidents is usually caused by various factors including human factors, vehicle factors, and environmental factors. The human factor is one of the most frequent factors causing traffic accidents. This system is designed as the manufacture of detection software for detect the condition of eyestrain in the driver of the vehicle using a camera connected to the computer as an image input device and measured performance of system develeopment. The method used in this system is to detect faces with segmentation RGB color to YCBCR color, eye detect with Roberts edge and the last method of simple logic as a classification of eye conditions. The system shows the results of classification with the highest accuracy is on video 1 of 85.40% and the lowest accuracy in video 7 is 13.67% whereas, the highest accuracy warning results on video 5 with 94.4% and the least accurate accuracy of warning with 25.26%

Rancang Bangun Sistem Pengaturan Kelembaban Tanah secara Real TIME Menggunakan Mikrokontroler dan Diakses di Web

A research on telemetry or remote measurement, for the parameters of soil moisture and temperature of the object remains in the form of agricultural land. The measured parameters such as soil moisture values are obtained from soil moisture sensors. In addition added also parameter value air temperature obtained by measuring the air temperature. In order to measure the air suh used sensor DS18B20. Both of the devices are read and controlled by a microcontroller ATmega328 with the Arduino software. Recipients get the value of soil moisture humidity value from the sensor. Data such as soil moisture and temperature value of the air is sent to the microcontroller, then transmitted to the database server by using the Internet network GSM. The system will be automatically watering when the soil moisture values are below standard. The system is using web interface that allows users to monitor soil conditions without the need for special receiver station. The results of this study, the system can perform the measurement values of soil moisture and air temperature to the server and perform automatic watering. This reasearch used three medium, wherein each soil moisture rises up to 99% in the first and second medium, in the third medium soil moisture rises up to 97%. The increase in the value of soil moisture caused by the automatical watering is based on parameter moisture used

Pengiriman Data Hasil Pengukuran Parameter Lingkungan Menggunakan Jaringan Seluler dengan Raspberry Pi sebagai Node

In this research has built a data delivery system of environmental parameters from Raspberry Pi into a webserver database for monitoring temperature, humidity, and light intensity in realtime, which used two Raspberry Pi as the two sensor nodes. Data from measurement of temperature, humidity, and light intensity of the sensor node is transmitted into the webserver via the mobile network, then the data is stored in a MySQL database, then the data is displayed in the form of websites. Applications to display the information of temperature, humidity and light intensity are made in the form of web programming with PHP and HTML discussed. With the appearance of the web is expected to facilitate the users to access through related information anywhere and anytime with the terms connected to the network internet. from this study, obtained results Raspberry Pi is able to transmit the observed data well into the webserver with a minimum data transmission delay of 1 second and 12 second maximum delay for a sensor node-1 and minimum delivery delays 1 second and 13 second maximum delay for sensor node-2