Jurnal Teknologi Informasi Cyberku
Jurnal Teknologi Informasi - Jurnal CyberKU is an open access journal, published by Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro. The journal is intended to be dedicated to the development of Information Technology related to Intelligent System, and Business Intelligence. Topics of interest include, but are not limited to: Artificial Intelligence, Machine Learning, Data Mining, Image Processing, Computer Vision, Text Processing, Signal Processing, Speech Recognition, Software Engineering, Decision Support System, IT Governance, eBusiness, Game Technology, Multimedia, eLearning, Computational Education, Computational Engineering, Mobile Computing, Internet of Things.
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<![CDATA[KOORDINASI NONPLAYER CHARACTER FOLLOWER MENGGUNAKAN ALGORITMA POTENTIAL FIELDS BERBASIS MULTIBEHAVIOUR ]]>
<![CDATA[Latius Hermawan]]>;
<![CDATA[Mochamad Hariadi]]>;
<![CDATA[Ruri Suko Basuki]]>
<![CDATA[ Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 13 No 1 (2017): Jurnal Teknologi Informasi CyberKU Vol. 13, no 1 ]]>
Publisher : <![CDATA[Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro ]]>
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<![CDATA[Games have become popular among the people, as a form of entertainment, social support interaction between them . NPC behavior modeling is an important issue in realizing the intelligence of computer games . In NPC team - mate, AI needed to help regulate the behavior of team - mate who played alongside or under the command of a human player to assist players in achieving the goal. Potential fields is described as the iron particles are moving towards the object through the magnetic field created by the target object . This movement depends on the existing magnetic field , the particles will be drawn towards the goal , or just the opposite of the iron particles will be rejected by the magnetic field at the time met an obstacle . In this study , the data obtained by reading the references relating to the title to find out the problems faced in coordinating the team in the game . From the study , analyzed the needs of the games that will be made to the AI model that will be used for team coordination . Only then designed a game that can resolve the issue . After the game was made , the game will be tested by several methods , so it will look the difference . The expected outcome of this study is to model the NPC behavior Follower and adjust the position of the player in accordance with the AI have been made . So players will not quickly lose the game and can finish coordinate with the NPC Follower followed by adjusting the movement of NPC Follower to the players during the attacks , NPC Follower still within range radius of the player to protect the player]]>
<![CDATA[PENERAPAN ALGORITMA C4.5 BERBASIS ADABOOST UNTUK PREDIKSI PENYAKIT JANTUNG ]]>
<![CDATA[Abdul Rohman]]>;
<![CDATA[Vincent Suhartono]]>;
<![CDATA[Catur Supriyanto]]>
<![CDATA[ Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 13 No 1 (2017): Jurnal Teknologi Informasi CyberKU Vol. 13, no 1 ]]>
Publisher : <![CDATA[Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro ]]>
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<![CDATA[Heart disease is the occurrence of partial or total blockage of a blood vessel over, as a result of the self peyumbatan deep chemical energy supply to the heart muscle is reduced, resulting in impaired balance between supply and needs .Research in predicting heart disease have been carried out by several previous investigators. In this study will be done for heart disease prediction algorithm using C4.5 and improved the performance of C4.5 algorithm using Adaboost method is implemented on the data of heart disease patients. From the test results by measuring method using a C4.5-based Adaboost, confusion matrix, and the ROC curve, it is known that C4.5 algorithms yield accuracy values 86,59%, AUC values obtained after 0.957 and optimized by using the method to be 92,24% Adaboost, the AUC to 0.982. by looking at the accuracy and AUC values after the optimizations, the algorithmbased C4.5 classification Adaboost into the category of groups is very good, because AUC values between 0.90 – 1.00]]>
<![CDATA[ANALISIS DAN PERANCANGAN MODEL FUZZY UNTUK SISTEM PAKAR PENDETEKSI TINGKAT KESUBURAN TANAH DAN JENIS TANAMAN ]]>
<![CDATA[Amiril Mukminin]]>;
<![CDATA[Heru Agus Santoso]]>;
<![CDATA[Catur Supriyanto]]>
<![CDATA[ Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 13 No 1 (2017): Jurnal Teknologi Informasi CyberKU Vol. 13, no 1 ]]>
Publisher : <![CDATA[Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro ]]>
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<![CDATA[Tillage that is not appropriate to the characteristics of plant type can easily causethe plants to wilt and plant growth is not maximal. These factors areoften the main cause of crop failure that is not known by the farmers. Therefore, an expert system is designed to detectthe soil fertility for types of plant using the fuzzy logic, which is expected to help the farmers in choosing the right types of plant with an appropriate of certain level of soil fertility. The measurement results obtained have been appropriate with the calculations and criteria of the land that has been entered.]]>
<![CDATA[DETEKSI PEMALSUAN COPY-MOVE PADA CITRA DIGITAL MENGGUNAKAN METODE DISCRETE COSINE TRANSFORM (DCT) DAN SCALE INVARIANT FEATURE TRANSFORM (SIFT) ]]>
<![CDATA[Ela Gusvita Sari Damanik]]>;
<![CDATA[Boko Susilo]]>;
<![CDATA[Endina Putri P]]>
<![CDATA[ Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 13 No 1 (2017): Jurnal Teknologi Informasi CyberKU Vol. 13, no 1 ]]>
Publisher : <![CDATA[Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro ]]>
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<![CDATA[Copy-move forgery is a type of image that is most commonly used. This technique is easy to use by many people. This, application can be used to detect copy-move forgery in digital image. The application convert the input image from RGB to graysacle. Then apply Discreate Cosine Transform method to perform the image decomposition, and to extract the image features with the SIFT. Then feature extraction results are clustered using nearest neigbour and estimated by geometric transformation using RANSAC method. SIFT local features is better for some geometric transformation, such as rotation and scaling which used in this study. Result showed that this application is able to detect copy-move forgery in digital images with or without rotation and scaling attacks up to 100% with threshold in 0.10.]]>
<![CDATA[MODEL KLASTERISASI GENRE CERPEN KOMPAS MENGGUNAKAN K-MEANS ]]>
<![CDATA[Hario Guritno]]>;
<![CDATA[Stefanus Santosa]]>
<![CDATA[ Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 13 No 1 (2017): Jurnal Teknologi Informasi CyberKU Vol. 13, no 1 ]]>
Publisher : <![CDATA[Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro ]]>
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<![CDATA[Information in the form of a text document can be found at any time on print media. Every time the community is faced with the current wave of information like the arrival in the form of unstructured text documents and have penetrated our lives and culture. Unstructured information comes closer all the entities of the world community. The mass media published the newspaper every day is the biggest contributor to human relations around the world. KOMPAS newspaper published every Sunday always insert the rubric of short stories in it. There is a problem to distinguish the genre of stories with one another. This research proposed a model of classify KOMPAS short stories with K-Means algorithm to get the solution. Accuracy of this proposed model using the Davies Bouldin Index (DBI) is 0.001.]]>
<![CDATA[PENENTUAN TINGKAT KELULUSAN TEPAT WAKTU MAHASISWA STMIK SUBANG MENGGUNAKAN ALGORITMA C4.5 ]]>
<![CDATA[Hermansyah Nur Ahmad]]>;
<![CDATA[Vincent Suhartono]]>;
<![CDATA[Ika Novita Dewi]]>
<![CDATA[ Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 13 No 1 (2017): Jurnal Teknologi Informasi CyberKU Vol. 13, no 1 ]]>
Publisher : <![CDATA[Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro ]]>
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<![CDATA[Timely graduatuion rates in college could not be consideres easy and trivial. Many cases found that the share of the number of students who did not get in and who have completed their studies so that the build up of high numbers of students in every period. I need to know the factors cause students not graduating on time. Classification data mining techniques can be used to predict student graduation rates. The algorithm used is algoritmic C 4.5 with data as much as 200 students study computer engineering programs STMIK Subang. The result of the classification process is evaluated by using the confusion matrix, ROC Curve, Recall. Based on experimental results and evluation is done then it can be inferred that the algorithm C 4.5 accurately applied to determine the level of students graduation. After testing the prediction accuracy resulting from trials reached 95,00% of the classification result generate information in the from of graph in the form of the curve results from the decision tree that is useful for institutions of higher education in taking policy.]]>
<![CDATA[PENENTUAN JURUSAN SISWA SEKOLAH MENENGAH ATAS DISESUAIKAN DENGAN MINAT SISWA MENGGUNAKAN ALGORITMA FUZZY C-MEANS ]]>
<![CDATA[Altanova Reza]]>;
<![CDATA[Abdul Syukur]]>;
<![CDATA[Moch Arief Soeleman]]>
<![CDATA[ Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 13 No 1 (2017): Jurnal Teknologi Informasi CyberKU Vol. 13, no 1 ]]>
Publisher : <![CDATA[Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro ]]>
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<![CDATA[Majors are held no valid high school in Indonesia is conducted when students are still in grade X. This includes the areas of interest Majors Natural Sciences, Social Sciences, and science of language. Majors will depend on the capability of student achievement in the areas of interest / courses available and in accordance with the conditions at the school. If it is not possible then the only department of particular interest are provided in school. The results of tests that tested students' interest through psychological tests aimed to help the school and the students themselves so that later, the lessons will be given to students become more focused as it has in accordance with the capability in the field of interest. Fuzzy C-Means algorithm is an algorithm that is easy and is often used in the technique of grouping the data as it makes an estimate efficient and does not require a lot of parameters. Several studies have concluded that the Fuzzy C-Means algorithm can be used to classify data based on certain attributes. In this study will be used Fuzzy C-Means algorithm to classify the student data High School (SMA) based on the value of the core subjects for the majors that are appropriated to the interests test results. The study also examined the level of accuracy of Fuzzy C-Means algorithm in determining the majors in high school. Application of Fuzzy C-Means algorithm in determining the majors in the 278 high school students were tested in this study, indicating that the FCM algorithm has a good degree of accuracy (in an average of 82.01%) by including interest test scores compared with the manual method based on the selection of individual students only 63.67%.]]>
<![CDATA[PREDIKSI KELULUSAN MAHASISWA TEPAT WAKTU BERDASARKAN USIA, JENIS KELAMIN, DAN INDEKS PRESTASI MENGGUNAKAN ALGORITMA DECISION TREE ]]>
<![CDATA[Agus Romadhona]]>;
<![CDATA[Suprapedi Suprapedi]]>;
<![CDATA[Heribertus Himawan]]>
<![CDATA[ Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 13 No 1 (2017): Jurnal Teknologi Informasi CyberKU Vol. 13, no 1 ]]>
Publisher : <![CDATA[Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro ]]>
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<![CDATA[Prediction of the study period in college is needed in determine the accuracy of the students study period according to the specified time so that wisdom of prevention related to the study period is no ton time could be done. This research aims to find patterns to predict the timely graduation of students usingdata mining techniques and models to predict long period of study was Decision tree algorithm C4.5 to compare with ID3 and CHAID algorithms using test data to determine the percentage of precision, recall and accuracy is obtained that the algorithm Decision Tree C4.5 has a better performance compared with other algorithms. From this research it was found that the prediction of the students study period are affected by incoming students age, gender, GPA semesters 1 through 4 semesters GPA and the most influential is the 4th semester GPA of students graduate on time with a value of 0.340 gain of all attributes. Decision tree algorithm C4.5 reaches the highest accuracy on the amount of data 389 with 91.51% accuracy values for k-fold=3, 90.75 for k-fold = 5 and 90.77 with k-fold = 10, While ID3 and CHAID algorithms achieving a low accuracy value. So thus the value accuracy of Decision Tree algorithm C4.5 is better than the ID3 and CHAID algorithm. In this research, training data are used as much as 389. To see better performance in the accuracy of the results of each algorithm, thus for furthermore research the number of data records used training process should be improved.]]>
<![CDATA[PROTOTYPE LAMPU LALU LINTAS ADAPTIF BERBASIS MULTI AGENT MANGGUNAKAN LOGIKA FUZZY YANG TERTANAM PADA MICROCONTROLLER ]]>
<![CDATA[Adrin T]]>;
<![CDATA[Heribertus Himawan]]>;
<![CDATA[Suprapedi Suprapedi]]>
<![CDATA[ Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 12 No 2 (2016): Jurnal Teknologi Informasi CyberKU Vol. 12, no 2 ]]>
Publisher : <![CDATA[Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro ]]>
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<![CDATA[Traffic light is a very important tool for urban life in regulating the smooth flow of traffic on the highway. The use of traffic lights are now much more applied using static timing system or a traffic light system which does not know the condition of the crossing are many vehicles or fewer. Timing pattern that is applied from one segment to another segment is set in rotation. In the study conducted to design a traffic light prototype based on multi- agent using fuzzy logic which is planted on the microcontroller. There are two parts and types of microcontrollers are used to design the prototype. The first part, the Slave microcontroller Atmega 32 and the second type, the type of Master mikontroler Atmega 128. Traffic light system which can adapt to the environment made the crossing. If there is a deviation of the queue of vehicles which have very much, then the green light time longer than the deviation that only have a little queue of vehicles. Thus, the traffic light is more adaptive to the dynamic vehicle that will cross the intersection. Traffic lights can also communicate with traffic lights nearest neighbors in both directions. Communication is done through mutual give information about the number of vehicles that left deviation towards each junction nearest neighbors. Results of this study found that the performance of fuzzy logic embedded in the microcontroller can control traffic lights with dynamic adaptive to existing vehicles on Line 1, Line 2 and Line 3. Prototype designed traffic lights represent the environmental conditions that have multiple intersections and each intersection has four traffic lights that can communicate with Multi Agent another intersection nearest neighbors.]]>
<![CDATA[ANALISIS KERANJANG PASAR UNTUK REKOMENDASI PRODUK (CONSUMER GOOD) MENGGUNAKAN FP-GROWTH DENGAN KLASTERISASI CLARANS ]]>
<![CDATA[Stefanus Santosa]]>;
<![CDATA[Jadi .]]>
<![CDATA[ Jurnal Teknologi Informasi - Cyberku (JTIC) Vol 12 No 2 (2016): Jurnal Teknologi Informasi CyberKU Vol. 12, no 2 ]]>
Publisher : <![CDATA[Program Pascasarjana Magister Teknik Informatika, Universitas Dian Nuswantoro ]]>
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<![CDATA[Market basket analysis is a generic term for methodology that study the composition of a basket of products. It has the objective of indentifying products, or groups of products, that tend to occur together (are associated). The discovery of this relationship can help merchant to develop a strategy of sales to consider the goods are often purchased with by customer. The knowledge that obtained market analysis basket is very important, because it can help recommendations product and promotion products so marketing strategy to be more appropriate. Market basket analysis can approach with Association Rule, such as apriori and FP-Growth. But they are a number of technical issues relating to the most common recommendations techniques. Association Rule tend to ignore the large itemset, To overcome these problems, existing attributes clustered to form groups of the same attributes and then determine the association patterns in each group. This study will use CLARANS algorithm for clustering on sales data and apply the FP-Growth algorithm to approach the association in each cluster. So that the product recommendations to customers to be more accurate because the Dataset that will be associated to be smaller. To the experimentally determined value of Minimum Support is 70% - 100% and Confidence Minimum value 70% - 100%. From the measurement results using Support, Confidence and Lift Ratio isfound that a high number of rule in third cluster.]]>
