IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
Indonesian Journal of Computing and Cybernetics Systems (IJCCS), a two times annually provides a forum for the full range of scholarly study . IJCCS focuses on advanced computational intelligence, including the synergetic integration of neural networks, fuzzy logic and eveolutionary computation, so that more intelligent system can be built to industrial applications. The topics include but not limited to : fuzzy logic, neural network, genetic algorithm and evolutionary computation, hybrid systems, adaptation and learning systems, distributed intelligence systems, network systems, human interface, biologically inspired evolutionary system, artificial life and industrial applications. The paper published in this journal implies that the work described has not been, and will not be published elsewhere, except in abstract, as part of a lecture, review or academic thesis.
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<![CDATA[Data Mining Untuk Mengetahui Tingkat Loyalitas Konsumen Terhadap Merek Kendaraan Bermotor dan Pola Kecelakaan Lalulintas di DIY ]]>
<![CDATA[Agus Sasmito Ariwibowo]]>;
<![CDATA[Edi Winarko]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 5, No 3 (2011): November ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.5205
<![CDATA[Abstract— 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.]]>
<![CDATA[Klasifikasi Varietas Tanaman Kelengkeng Berdasarkan Morfologi Daun Menggunakan Backpropagation Neural Network dan Probabilistic Neural Network ]]>
<![CDATA[Hermawan Syahputra]]>;
<![CDATA[Agus Harjoko]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 5, No 3 (2011): November ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.5206
<![CDATA[Pengenalan daun memainkan peran penting dalam klasifikasi tanaman dan isu utamanya terletak pada apakah fitur yang dipilih stabil dan memiliki kemampuan yang baik untuk membedakan berbagai jenis daun. Pengenalan tanaman berbantuan komputer merupakan tugas yang masih sangat menantang dalam visi komputer karena kurangnya model atau skema representasi yang tepat. Fokus komputerisasi pengenalan tanaman hidup adalah untuk mengukur bentuk geometris berbasis morfologi daun. Informasi ini memainkan peran penting dalam mengidentifikasi berbagai kelas tanaman. Pada penelitian ini dilakukan pengenalan jenis tanaman berdasarkan fitur yang menonjol dari daun seperti fisiologis panjang (physiological length), lebar (physiological width), diameter, keliling (leaf perimeter), luas (leaf area), faktor mulus (narrow factor), rasio aspek (aspect ratio), factor bentuk (form factor), rectangularity, rasio perimeter terhadap diameter, rasio perimeter panjang fisiologi dan lebar fisiologi yang dapat digunakan untuk membedakan satu sama lain. Berdasarkan hasil pengujian, ditunjukkan bahwa hasil pencocokkan daun kelengkeng dengan menggunakan neural network lebih baik dibandingkan dengan hasil pencocokkan daun kelengkeng dengan menggunakan probabilistic neural network. Akan tetapi ekstraksi fitur dengan menggunakan morfologi belum dapat memberikan informasi pembeda yang signifikan bagi pengenalan tanaman varitas kelengkeng berdasarkan daunnya.Keywords— klasifikasi, morfologi daun, neural network, probabilistic neural network]]>
<![CDATA[Class Association Rule Pada Metode Associative Classification ]]>
<![CDATA[Eka Karyawati]]>;
<![CDATA[Edi Winarko]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 5, No 3 (2011): November ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.5207
<![CDATA[Frequent 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.]]>
<![CDATA[Penentuan Klas Sidik Jari Berdasarkan Arah Kemiringan Ridge ]]>
<![CDATA[Sri Suwarno]]>;
<![CDATA[Agus Harjoko]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 5, No 3 (2011): November ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.5208
<![CDATA[Researches on fingerprint classification are generally based on its features such as core and delta. Extraction of these features are generally preceded by a variety of preprocessing. In this study the classification is done directly on the fingerprint image without preprocessing. Feature used as the basis for classification is the direction of the ridge. The direction of the ridge is determined by the slope of the blocks that are exist on every ridge. Fingerprint image is divided into blocks of size 3x3 pixels and the direction of each block is determined. Direction of the slope of the block are grouped into 8, these are north, north-east, east, south-east, south, south-west, west and north-west. The number of blocks in each direction form the basis of classification using Learning Vector Quantization network (LVQ). This study used 80 data samples from the database of FVC2004. This model obtained classification accuracy of up to 86.3%. Keywords—fingerprint, classification, ridge, LVQ]]>
<![CDATA[Penapisan Derau Gaussian, Speckle dan Salt&Pepper Pada Citra Warna ]]>
<![CDATA[Ika Purwanti Ningrum]]>;
<![CDATA[Agfianto Eko Putra]]>;
<![CDATA[Dian Nursantika]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 5, No 3 (2011): November ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.5209
<![CDATA[Quality 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&Pepper]]>
<![CDATA[PENDEKATAN ALGORITMA GENETIKA DALAM MENYELESAIKAN PERMASALAHAN FUZZY LINEAR PROGRAMMING ]]>
<![CDATA[Siska Dewi Lestari]]>;
<![CDATA[Subanar Subanar]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 5, No 3 (2011): November ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.5211
<![CDATA[Fuzzy linear programming is one of the linear programming developments which able to accommodate uncertainty in the real world. Genetic algorithm approach in solving linear programming problems with fuzzy constraints has been introduced by Lin (2008) by providing a case which consists of two decision variables and three constraint functions. Other linear programming problem arise with the presence of some coefficients which are fuzzy in linear programming problems, such as the coefficient of the objective function, the coefficient of constraint functions, and right-hand side coefficients constraint functions. In this study, the problem studied is to explain the genetic algorithm approach to solve linear programming problems where the objective function coefficients and right-hand sides are fuzzy constraint functions.PT Dakota Furniture study case provides a linear programming formulation with a given objective function coefficients and right-hand side coefficients are fuzzy constraint functions. This study describes the use of genetic algorithm approach to solve the problem of linear programming of PT Dakota to maximize the mean income. The genetic algorithm approach is done by simulate every fuzzy number and each fuzzy numbers by distributing them on certain partition points. Then genetic algorithm is used to evaluate the value for each partition point. As a result, the Final Value represents the coefficient of fuzzy number. Fitness function is done by calculating the value of the objective function of linear programming problems. Empirical results indicated that the genetic algorithm approach can provide a very good solution by giving some limitations on each fuzzy coefficient.Genetic algorithm approach can be extended not only to resolve the case of PT Dakota Furniture, but can also be used to solve other linear programming case with some coefficients in the objective function and constraint functions are fuzzy.Keywords : Genetic Algorithm, Fuzzy Linear Programming, Linear Programming, Two-Phase Simplex Method]]>
<![CDATA[SIM Kemiskinan Sebagai Dasar Informasi Geografis Untuk Pemetaan Prioritas Pengentasan Kemiskinan di Kabupaten Banjarnegara ]]>
<![CDATA[Aji Supriyanto]]>;
<![CDATA[Edy Winarno]]>;
<![CDATA[Agus Prasetyo]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 5, No 3 (2011): November ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.5212
<![CDATA[Program pengentasan kemiskinan merupakan prioritas bagi pemerintah daerah Kabupaten Banjarnegara yang harus ditangani. Penelitan ini bermaksud merancang bangun sebuah sistem informasi yang mengolah data penduduk yang dapat diolah menjadi sebuah informasi kemiskinan yang dapat diakses melalui web dengan menggunakan standar indikator kemiskinan menurut BPS. Metode yang digunakan dalam penelitian ini adalah dengan cara action research dan model pengembangan sistem informasi adalah secara terstruktur menggunakan waterfall. Hasil dari penelitian ini adalah dapat menyajikan informasi yang dapat menetukan kriteria kemiskinan dengan model singgle-criteria maupun multiple-criteria sesuai kebutuhan indikator kemiskinan yang ditentukan hingga pada tingkat desa, serta memberikan informasi tentang jenis-jenis bantuan yang telah diberikan pada setiap penduduk berdasarkan nama dan alamat (by name by address). Hasil selanjutnya adalah dapat dijadikan sebagai dasar pemetaan digital (Sistem Informasi Geografis/SIG) untuk menentukan kantong kemiskinan di suatu daerah, dengan memberikan pewarnaan yang menjadi indikator tingkat kemiskinan. Kata Kunci : kemiskinan, sistem informasi, penduduk, indikator BPS, GIS.]]>
<![CDATA[SPASIAL DATA MINING MENGGUNAKAN MODEL SAR-KRIGING ]]>
<![CDATA[Atje Setiawan]]>;
<![CDATA[Rudi Rosadi]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 5, No 3 (2011): November ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.5213
<![CDATA[The region of Indonesia is very sparse and it has a variation condition in social, economic and culture, so the problem in education quality at many locations is an interesting topic to be studied. Database used in this research is Base Survey of National Education 2003, while a spatial data is presented by district coordinate as a least analysis unit. The aim of this research is to study and to apply spatial data mining to predict education quality at elementary and junior high schools using SAR-Kriging method which combines an expansion SAR and Kriging method. Spatial data mining process has three stages. preprocessing, process of data mining, and post processing.For processing data and checking model, we built software application of Spatial Data Mining using SAR-Kriging method. An application is used to predict education quality at unsample locations at some cities at DIY Province. The result shows that SAR-Kriging method for some cities at DIY for elementary school has an average percentage error 6.43%. We can conclude that for elementary school, SAR-Kriging method can be used as a fitted model. Keywords— Expansion SAR, SAR-Kriging, quality education]]>
<![CDATA[Analisis dan Perancangan Sistem Manajemen Event Berbasis Mobile Push Notification ]]>
<![CDATA[Ardiansyah Ardiansyah]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 5, No 3 (2011): November ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.5214
<![CDATA[Konvergensi teknologi Internet dan piranti mobile/smartphone saat ini bisa dimanfaatkan secara optimal sebagai salah satu media promosi dan pengelolaan sebuah acara. Dengan keberadaan teknologi push service akan memungkinkan setiap informasi acara baru dapat diterima oleh calon peserta yang prospektif. Selain itu pula dengan mengusung teknologi cloud computing, setiap penyelenggara acara cukup menggunakan service yang disediakan khusus di server Internet untuk mengelola acara yang akan diselenggarakan tanpa harus menyediakan infrastruktur sendiri. Pada penelitian ini telah berhasil dibuat rancangan sistem manajemen acara (event) yang diselenggarakan oleh event organizer atau sering disebut EO. Rancangan yang dibuat meliputi struktur tabel, menu hingga antarmuka aplikasi meliputi antarmuka berbasis web untuk administrator EO dan antarmuka berbasis mobile iPhone untuk user. Keywords: event, push notification, mobile, antarmuka.]]>
<![CDATA[PENERAPAN SISTIM PENDUKUNG KEPUTUSAN DALAM SISTEM PENGUJIAN COMPUTERIZED ADAPTIVE TESTING ]]>
<![CDATA[Rukli Rukli]]>;
<![CDATA[Sri Hartati]]>
<![CDATA[ IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Vol 5, No 3 (2011): November ]]>
Publisher : <![CDATA[IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia. ]]>
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DOI: 10.22146/ijccs.5215
<![CDATA[This study aims to make design decision support system adaptive to examinee ability to go to college.Decision support systems are made using one parameter logistic model by taking into account the difficulty level of questions adapted to the ability of the examinee. Questions are selected so that the items follow the ability of examinee more accurate assessment of ability with a lesser number of items.CAT a web-based applications require lesser number of items in determining the ability of examinee. College can determine the appropriate characteristics of the ability of examinee acceptance criteria for each department with domain weighting, and then determine the minimum level of capability that will be received and an appropriate amount to be received. Key word: Decision Support System, Computerized Adaptive Testing]]>
