IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
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Data Mining Untuk Mengetahui Tingkat Loyalitas Konsumen Terhadap Merek Kendaraan Bermotor dan Pola Kecelakaan Lalulintas di DIY
Get PDFAbstract— The data of vehicle sales and traffic accident can be processed into information that is important for vehicle dealers and the Police Department. Those important information researched are the level of consumer loyalty to the vehicle brands and to predict the vehicle’s brands that will be purchased by a consumer. The study also tries to analyze the traffic accident data to find out is there any link between the occurrence of an accident to a certain brand of vehicle. This research implementing data mining method called ‘rule based classification’ to establish the sales of vehicles rules by which can be used to classify consumer into group level of brand loyalty and also estimate the brand of the next vehicle’s brand that will be purchased by the consumer. This research will process the data traffic accident by using data mining techniques called Apriori Method. Apriori Method is used to identify a pattern of accidents based on brand, type of vehicles, and the vehicle’s color. The results are used to estimate whether there is any correlation between the occurrences of a traffic accident to a particular brand. The result can help companies or vehicle dealers to obtain information about the level of the consumer’s brand loyalty to the dealer’s brand and to predict the brand that the consumer would be buy for the next vehicle. The result can also help the Police Department to find out whether there is any correlation between the occurrence of traffic accidents to the brand, type and the color of vehicle. Keywords— rule based classification, apriori, brand loyalty, traffic accident
Class Association Rule Pada Metode Associative Classification
Get PDFFrequent patterns (itemsets) discovery is an important problem in associative classification rule mining. Differents approaches have been proposed such as the Apriori-like, Frequent Pattern (FP)-growth, and Transaction Data Location (Tid)-list Intersection algorithm. This paper focuses on surveying and comparing the state of the art associative classification techniques with regards to the rule generation phase of associative classification algorithms. This phase includes frequent itemsets discovery and rules mining/extracting methods to generate the set of class association rules (CARs). There are some techniques proposed to improve the rule generation method. A technique by utilizing the concepts of discriminative power of itemsets can reduce the size of frequent itemset. It can prune the useless frequent itemsets. The closed frequent itemset concept can be utilized to compress the rules to be compact rules. This technique may reduce the size of generated rules. Other technique is in determining the support threshold value of the itemset. Specifying not single but multiple support threshold values with regard to the class label frequencies can give more appropriate support threshold value. This technique may generate more accurate rules. Alternative technique to generate rule is utilizing the vertical layout to represent dataset. This method is very effective because it only needs one scan over dataset, compare with other techniques that need multiple scan over dataset. However, one problem with these approaches is that the initial set of tid-lists may be too large to fit into main memory. It requires more sophisticated techniques to compress the tid-lists
Penapisan Derau Gaussian, Speckle dan Salt&Pepper Pada Citra Warna
Get PDFQuality of digital image can decrease becouse some noises. Noise can come from lower quality of image recorder, disturb when transmission data process and weather. Noise filtering can make image better becouse will filtering that noise from the image and can improve quality of digital image. This research have aim to improve color image quality with filtering noise. Noise (Gaussian, Speckle, Salt&Pepper) will apply to original image, noise from image will filtering use Bilateral Filter method, Median Filter method and Average Filter method so can improve color image quality. To know how well this research do, we use PSNR (Peak Signal to Noise Ratio) criteria with compared original image and filtering image (image after using noise and filtering noise).This research result with noise filtering Gaussian (variance = 0.5), highest PSNR value found in the Bilateral Filter method is 27.69. Noise filtering Speckle (variance = 0.5), highest PSNR value found in the Average Filter method is 34.12. Noise filtering Salt&Pepper (variance = 0.5), highest PSNR value found in the Median Filter method is 31.27. Keywords— Bilateral Filter, image restoration, derau Gaussian, Speckle dan Salt&Peppe
A Web Based Expert System for Identifying Bloomed Plants
No full textThis research discusses the development of a web based expert system for identifying bloomed plants. The identification is based on the seven visible features of a bloomed plant, i.e. the root type, the type of the plant, the shape of the flowers, the shape of the leaves, the height of the plant, and the length and the width of the leaves. For inference process, the forward chaining method is used. The system is developed using PHP as the programming language and MySQL as the database management system. Based on some testing conducted to the system, it can be concluded that the system can identify bloomed plants with the accuracy of 100%. The system can accommodate the update on its knowledge as long as the update is only on the available features in the system. This drawback can be used as starting point for the future development of the system
The Balinese Unicode Text Processing
Get PDFIn principal, the computer only recognizes numbers as the representation of a character. Therefore, there are many encoding systems to allocate these numbers although not all characters are covered. In Europe, every single language even needs more than one encoding system. Hence, a new encoding system known as Unicode has been established to overcome this problem. Unicode provides unique id for each different characters which does not depend on platform, program, and language. Unicode standard has been applied in a number of industries, such as Apple, HP, IBM, JustSystem, Microsoft, Oracle, SAP, Sun, Sybase, and Unisys. In addition, language standards and modern information exchanges such as XML, Java, ECMA Script (JavaScript), LDAP, CORBA 3.0, and WML make use of Unicode as an official tool for implementing ISO/IEC 10646. There are four things to do according to Balinese script: the algorithm of transliteration, searching, sorting, and word boundary analysis (spell checking). To verify the truth of algorithm, some applications are made. These applications can run on Linux/Windows OS platform using J2SDK 1.5 and J2ME WTK2 library. The input and output of the algorithm/application are character sequence that is obtained from keyboard punch and external file. This research produces a module or a library which is able to process the Balinese text based on Unicode standard. The output of this research is the ability, skill, and mastering of 1. Unicode standard (21-bit) as a substitution to ASCII (7-bit) and ISO8859-1 (8-bit) as the former default character set in many applications. 2. The Balinese Unicode text processing algorithm. 3. An experience of working with and learning from an international team that consists of the foremost experts in the area: Michael Everson (Ireland), Peter Constable (Microsoft US), I Made Suatjana, and Ida Bagus Adi Sudewa
Evaluation Existential of Medical Record Laboratory at the Diploma 3 Program for Medical Record & Health Information, Mathematics and Natural Science Faculty, Gadjah Mada University
No full textThe availability of Medical Record Laboratory to support Medical Record education is one that the education provider should prepare. In addition, education providers should also organize the usage, instrument provision, HRD provision and clear planning and objectives.The present research used evaluation topic on the existence of Medical Record Laboratory at the Diploma 3 Program for Medical Record and Health Information, MIPA Faculty, Gadjah Mada University. This topic was used by considering the Government Regulation on education provision, especially Medical Record Education (The Regulation of Minister Health Number 1192/Menkes/Per/X/2004) as thinking base. Data were taken from initial survey that the Laboratory was considered as not maximally performed. Base on instrument availability, this laboratory had no complete instrument, especially manually data processing completeness. Moreover, in fact, the usage and planning on this facility had not been well organized, while there was mostly high demand on the usage. To this end, evaluation was highly required for future progress. Evaluation was gradually performed. First was evaluation on input related technology, human resources, costs, facilities and management. Second was evaluation on process related to whether the planned activities had been completed or not. Third, evaluation on inputs related to attitudes, norms and skill knowledge of those involved in the laboratory (staffs, students, and stakeholder).The present research exploited descriptive method with qualitative approach using single data variable (the existence of Medical Record Laboratory at the Diploma 3 Program for Medical Record and Health Information Gadjah Mada University). Data were collected using source triangulation approach through data cross-checking with fact from other sources. Data analysis was performed by comparing data taken to the existing standard (Government Regulation and theory). To simplify discussion, data were discussed based on principle elements of health services, among others, including: inputs, process, and outputs.Evaluation on the existence of laboratory was presumably exploited to consider future development and management as expected that this Laboratory could be taken as example for medical record management in hospitals
An Evaluation of Suitable Landscape to Crop Food Cultivation By Using Neural Networks
No full textoai:journal.ugm.ac.id:article/17Penentuan jenis tanaman pangan yang sesuai ditanam pada lahan tertentu berdasarkan nilai-nilai karakteristik lahan sangat diperlukan sebagai pendukung pengambilan keputusan, koordinasi, dan pengendalian bagi para peneliti, praktisi, dan perencana penggunaan lahan, sehingga kerugian (finansial) yang cukup besar tidak terjadi nantinya. Program komputer dengan menggunakan Jaringan Syaraf Tiruan (JST) metode Learning Vector Quantization (LVQ) dapat digunakan sebagai alat yang tepat dalam memberikan informasi tanaman yang cocok ditanam dengan mudah, cepat, dan akurat. Data pelatihan didapat dari kombinasi nilai karakteristik lahan yang termasuk dalam kelas kesesuaian S1 dan S2. Hasil pengujian menunjukkan bahwa nilai Eps (error minimum yang diharapkan) = 0.005, nilai ?? ?? = 0.05, nilai maksimum epoh = 10, dan nilai pengurangan learning rate sebesar 0.1*?? ?? merupakan nilai-nilai yang cukup efektif dan efisien dalam melakukan prediksi jenis tanaman pangan yang sesuai ditanam pada lahan tertentu karena tingkat ketepatan prediksinya adalah 100%
An Application of Fuzzy Inference System by Clustering Subtractive Fuzzy Method for Estimating of Product Requirement
No full textModel fuzzy memiliki kemampuan untuk menjelaskan secara linguistik suatu sistem yang terlalu kompleks. Aturan-aturan dalam model fuzzy pada umumnya dibangun berdasarkan keahlian manusia dan pengetahuan heuristik dari sistem yang dimodelkan. Teknik ini selanjutnya dikembangkan menjadi teknik yang dapat mengidentifikasi aturan-aturan dari suatu basis data yang telah dikelompokkan berdasarkan persamaan strukturnya. Dalam hal ini metode pengelompokan fuzzy berfungsi untuk mencari kelompok-kelompok data. Informasi yang dihasilkan dari metode pengelompokan ini, yaitu informasi tentang pusat kelompok, digunakan untuk membentuk aturan-aturan dalam sistem penalaran fuzzy. Dalam skripsi ini dibahas mengenai penerapan fuzzy infereance system dengan metode pengelompokan fuzzy subtractive clustering, yaitu untuk membentuk sistem penalaran fuzzy dengan menggunakan model fuzzy Takagi-Sugeno orde satu. Selanjutnya, metode pengelompokan fuzzy subtractive clustering diterapkan dalam memodelkan masalah dibidang pemasaran, yaitu untuk memprediksi permintaan pasar terhadap suatu produk susu. Aplikasi ini dibangun menggunakan Borland Delphi 6.0. Dari hasil pengujian diperoleh tingkat error prediksi terkecil yaitu dengan Error Average 0.08%
The Prediction of Medical Decision Post Operative of the Major Operation using Neural Networks
No full textThe exact handling to the postoperative inpatient of the major operation in the restoration period, became one of the factors that very important for the success of the process of medical treatment on the whole. By paying attention to the development of signs and vital signs from the patient, could be made medical by one decision took the form of the further action for the handling of the patient. Using backpropagation neural networks, could be made by a system that could carry out the prediction (forecast) the medical decision that will be taken to the postoperative patient the major's operation. After trining, by accepting sign input and the vital sign of the patient, the system could determine the action that will be carried out against the patient. From results of the test of the application program showed that the backpropagation neural networks could do the prediction of the medical decision with the success to 80%. Therefore, output from the system could be used as consideration of the doctor to decide the further action for the patient
Implementation for Chipper's Software - NHILL
No full textSandi (cipher) adalah suatu jenis bahasa yang banyak digunakan dalam proses penyampaian pesan yang bersifat rahasia. Pengkajian penyandian yang merupakan kode rahasia dimulai sejak awal adanya komonikasi tertulis. Namun akhir-akhir ini kriptografi mendapat perhatian karena dianggap mampu memelihara keleluasaan pribadi atau kelompok dari pesan yang dipancarkan melalui komonikasi umum. Tulisan ini memuat laporan penelitian tentang tahap implementasi pengembangan perangkat lunak komputer yang bernama SoftHill yaitu perangkat lunak penyandian yang menerapkan metode penyandian N-Hill. Implementasi perangkat lunak ini dibangun berdasarkan pada dokumen analisis kebutuhan dan perancangan SoftHill yang laporannya dibuat pada tulisan di buku jurnal yang lain. Hasil implementasi perangkat lunak ini antar lain berupa algoritma beberapa proses penting dalam penyandian N-Hill diantaranya algoritma Proses Pkel, Proses PkonvN, Proses PkonvH, Proses Pkali dan Proses PInvers. Adapun intervase antar muka dibangun dengan menggunakan alat bantu pengembangan Delphi yang beroperasi di lingkungan sistem operasi Windows