IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
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Pemanfaatan Algoritma WIT-Tree dan HITS untuk Klasifikasi Tingkat Keberhasilan Pemberdayaan Keluarga Miskin
Get PDFThe successful rate of the poor families empowerment can be classified by characteristic patterns extracted from the database that contains the data of the poor families empowerment. The purpose of this research is to build a classification model to predict the level of success from poor families, who will receive assistance empowerment of poverty. Classification models built with WARM, which is combining two methods, they are HITS and WIT-tree. HITS is used to obtained the weight of the attributes from the database. The weights are used as the attributes’s weight on methods WIT-tree. WIT-tree is used to generate the association rules that satisfy a minimum weight support and minimum weight confidence. The data used was 831 sample data poor families that divided into two classes, namely poor families in the standard of "developing" and poor families in the level of "underdeveloped". The performance of classification model shows, weighting attribute using HITS approaches the accuracy of 86.45% and weighted attributes defined by the user approaches the accuracy of 66.13%. This study shows that the weight of the attributes obtained from HITS is better than the weight of the attributes specified by the user
Sistem Pendukung Keputusan Kelompok Pemilihan Tempat PKL mahasiswa dengan Menggunakan Metode AHP dan Borda
Get PDFThe right Placement Job Training (PKL) selection for the students is a very important thing, because it can maximize the abilities and talents of each student so that can produce graduates who are ready to compete in the world of work. The most common problem of PKL selection is the lack of competence in terms of the needs of the company, as well as the needs of students will be on PKL place selection. To overcome these problems required a computer system in the form of group decision support systems (GDSS) who can help South Aceh Polytechnic for the selection of the right vendors for students. In this study, Group decision support system developed by using AHP (Analytical Hierarchy Process) and Borda for group decision-making. AHP method is used to determine the weights of criteria and sub-criteria of each company where PKL alternative to alternative perangkingan company for each student from each of the decision makers. Borda method used for incorporation gradement results obtained by each decision maker so getting rank final and decisive recommendations PKL student places. Based on the outcome of a group decision support system in the form of a rank of criteria values of students to alternative company where PKL placement selection. And alternative companies that get the highest yield serve as recommendations PKL student placement decisions for computer engineering department Polytechnics South Aceh
SPK Rekomendasi Pemilihan Kandidat Pejabat Struktural Menggunakan Metode Profile Matching (Studi Kasus: Pemerintah Kota Tarakan)
Get PDFThrough the State Civil Apparatus Law, the Government attempt to reduce nepotism by creating an open competition system among civil servants in the process of filling positions. Regional Civil Service Agency (BKD) Tarakan already has personnel database and decision support system that can combine the existing database with the scoring model to get the candicate profile who fit with vacant positions is needed to support more objective performance.The Application of profile matching method in this decision support system is expected to help the candidate selection process on structural officer in the Government of Tarakan comply with the ability of a required field in a position. From the research we concluded that the change in the value of the candicate profile, and the number of subcriteria that used to categorize the positions can affect the closeness of candidates with vacant position and the use of profile matching method for case that the highest value is the best value requires that the ideal value used is the value the maximum in order to avoid exceeding the expectations of ideal.
Deteksi Perubahan Citra Pada Video Menggunakan Illumination Invariant Change Detection
Get PDF There is still a lot of juvenile delinquency in the middle of the community, especially people in urban areas, in the modern era. Juvenile delinquency may be fights, wild racing, gambling, and graffiti on the walls without permission. Vandalized wall is usually done on walls of office buildings and on public or private property. Results from vandalized walls can be seen from the image of the change between the initial image with the image after a motion.This study develops a image change detection system in video to detect the action of graffiti on the wall via a Closed-Circuit Television camera (CCTV) which is done by simulation using the webcam camera. Motion detection process with Accumulative Differences Images (ADI) method and image change detection process with Illumination Invariant Change Detection method coupled with image cropping method which carried out a comparison between the a reference image or image before any movement with the image after there is movement.Detection system testing one by different times variations, ie in the morning, noon, afternoon, and evening. The proposed method for image change detection in video give results with an accuracy rate of 92.86%
Case-Based Reasoning untuk Diagnosis Penyakit Jantung
Get PDFCase Based Reasoning (CBR) is a computer system that used for reasoning old knowledge to solve new problems. It works by looking at the closest old case to the new case. This research attempts to establish a system of CBR for diagnosing heart disease. The diagnosis process is done by inserting new cases containing symptoms into the system, then the similarity value calculation between cases uses the nearest neighbor method similarity, minkowski distance similarity and euclidean distance similarity. Case taken is the case with the highest similarity value. If a case does not succeed in the diagnosis or threshold <0.80, the case will be revised by experts. Revised successful cases are stored to add the systemknowledge. Method with the best diagnostic result accuracy will be used in building the CBR system for heart disease diagnosis. The test results using medical records data validated by expert indicate that the system is able to recognize diseases heart using nearest neighbor similarity method, minskowski distance similarity and euclidean distance similarity correctly respectively of 100%. Using nearest neighbor get accuracy of 86.21%, minkowski 100%, and euclidean 94.83
Aplikasi Rekomendasi Tempat Makan Menggunakan Algoritma Slope One pada Platform Android
Get PDF Food is one of the basic needs for human being. The needs of food will always increase unanimous with the number of people, so that many restaurants appear. Because of there are so many restaurants, it can arise a confusion when we want to choose a restaurant to eat. Therefore, an application which can give a restaurant recommendation will be built in this research. The recommendation given by the system is calculated using Slope One algorithm and the restaurants database is gathered from Google Places API. Slope One algorithm make the recommendation by summing the rating of a restaurants with the difference average to other restaurants. The application also had been tested to the user by using J.R.Lewis questionnaire with questions categories of application usefulness, information quality, and user interface quality. The results from the testing are user find the application useful to give the proper restaurant recommendation, the information quality is good, and the user interface quality is also good
Klasifikasi Belimbing Menggunakan Naïve Bayes Berdasarkan Fitur Warna RGB
Get PDFPost harvest issues on star fruit are produced on a large scale or industry is sorting. Currently, star fruit classified by rind color analysis visually human eye. This method does not effective and inefficient. The research aims to classify the starfruit sweetness level by using image processing techniques. Features extraction used is the value of Red, Green and Blue (RGB) to obtain the characteristics of the color image. Then the feature extraction results used to classify the star fruit with Naïve Bayes method. Starfruit image data used 120 consisting of 90 training data and 30 testing data. The results showed the classification accuracy using RGB feature extraction by 80%. The use of RGB as the color feature extraction can not be used entirely as a feature of the image extraction of star fruit
Rancang Bangun Plugin Protégé Menggunakan Ekspresi SPARQL-DL Dengan Masukan Bahasa Alami
Get PDFSemantic web is a technology that allows us to build a knowledge base or ontology for the information of the web page can be understood by computers. One software for building ontology-based semantic web is a protégé. Protege allows developers to develop an ontology with an expression of logic description. Protégé provides a plugin such as DL-Query and SPARQL-Query to display information that involve expression of class, property and individual in the ontology. The problem that then arises is DL-plugin Query only able to process the rules that involve expression of class to any object property, despite being equipped with the function of reasoning. while the SPARQL-Query plugin does not have reasoning abilities such as DL-Query plugin although the SPARQL-Query plugin can query memperoses rules involving class, property and individual. This research resulted in a new plugin using SPARQL-DL with input natural language as a protégé not provide a plugin with input natural language to see results from the combined expression-expression contained in the ontology that allows developers to view information ontology language that is easier to understand without having think of SPARQL query structure is complicated
Deteksi Dini Retinopati Diabetik dengan Pengolahan Citra Berbasis Morfologi Matematika
Get PDFDiabetic retinopathy is a complication caused by diabetes mellitus. Diabetic retinopathy, if not handled properly can lead to blindness. A necessary step to prevent blindness is early detection. Early detection can be done by finding the initial symptoms that microaneurysm. In this research, a system made to detect diabetic retinopathy using algorithms detection microaneurysm with mathematical morphology. The algorithm is divided into three stages of preprocessing, detecting candidate microaneurysm and postprocessing. In this research, the system will be made by using a raspberry pi as the media. To see how well the system detects diabetic retinopathy, the test will be done. in the tests performed, system obtained an accuracy of 90%, sensitivity 90, and specificity of 55% using data diaretdb1. While testing using data from e-ophtha obtained results with an accuracy of 70.5%, a sensitivity of 80% and a specificity of 60%
Sentimen Analisis Tweet Berbahasa Indonesia Dengan Deep Belief Network
Get PDFSentiment analysis is a computational research of opinion sentiment and emotion which is expressed in textual mode. Twitter becomes the most popular communication device among internet users. Deep Learning is a new area of machine learning research. It aims to move machine learning closer to its main goal, artificial intelligence. The purpose of deep learning is to change the manual of engineering with learning. At its growth, deep learning has algorithms arrangement that focus on non-linear data representation. One of the machine learning methods is Deep Belief Network (DBN). Deep Belief Network (DBN), which is included in Deep Learning method, is a stack of several algorithms with some extraction features that optimally utilize all resources. This study has two points. First, it aims to classify positive, negative, and neutral sentiments towards the test data. Second, it determines the classification model accuracy by using Deep Belief Network method so it would be able to be applied into the tweet classification, to highlight the sentiment class of training data tweet in Bahasa Indonesia. Based on the experimental result, it can be concluded that the best method in managing tweet data is the DBN method with an accuracy of 93.31%, compared with Naive Bayes method which has an accuracy of 79.10%, and SVM (Support Vector Machine) method with an accuracy of 92.18%