Fuzzy Inference Systems

Knowledge engineering is a systematic process of acquiring, representing, and managing knowledge to be applied in intelligent systems such as expert systems. This study aims to examine the fundamental concepts of knowledge engineering and its application in the development of rule-based expert systems. Through literature review and qualitative analysis, this research identifies the key stages of knowledge engineering and highlights the common challenges faced during implementation. The findings show that a deep understanding of the knowledge engineering process can significantly enhance the effectiveness and efficiency of expert systems in various fields of application.

We propose an automatic methodology framework for short-and long-term prediction of time series by means of fuzzy inference systems. In this methodology, fuzzy techniques and statistical techniques for nonparametric residual variance estimation are combined in order to build autoregressive predictive models implemented as fuzzy inference systems. Nonparametric residual variance estimation plays a key role in driving the identification and learning procedures. Concrete criteria and procedures within the proposed methodology framework are applied to a number of time series prediction problems. The learn from examples method introduced by Wang and Mendel (W&M) is used for identification. The Levenberg-Marquardt (L-M) optimization method is then applied for tuning. The W&M method produces compact and potentially accurate inference systems when applied after a proper variable selection stage. The L-M method yields the best compromise between accuracy and interpretability of results, among a set of alternatives. Delta test based residual variance estimations are used in order to select the best subset of inputs to the fuzzy inference systems as well as the number of linguistic labels for the inputs. Experiments on a diverse set of time series prediction benchmarks are compared against least-squares support vector machines (LS-SVM), optimally-pruned extreme learning machine (OP-ELM), and k-NN based autoregressors. The advantages of the proposed methodology are shown in terms of linguistic interpretability, generalization capability and computational cost. Furthermore, fuzzy models are shown to be consistently more accurate for prediction in the case of time series coming from real-world applications

This paper presents the Prototyping and Focused Discriminating (PFD) strategy for pattern recognition. This strategy takes benefits from the duality between model generation and discrimination. Both collaborate through a focusing mechanism that detects the conflicts between the class models and drive the discrimination. Classifiers based on this collaboration benefit from a set of useful properties. The Mélidis system illustrates this strategy and extends its possibilities, using a fuzzy framework. As shown by experiments, the resulting system provides an interesting compromise between accuracy and compactness. Experiments also demonstrate the interest of the new strategy and of its focusing mechanism.

In this paper, we compare the efficiency of two binary classifiers. The first one uses the Weighted Ordered Weighted Averaging (WOWA) aggregation function whose coefficients are learned thanks to a genetic algorithm. The second is based on an artificial neural network trained by a backpropagation algorithm. They are trained to be used in a multi-criteria decision system. These kind of multi-criteria system are more and more common in the cyber-defence field. In this work, we compare the performance of these two classifiers by using two criteria: Area Under the Curve of a Receiver Operating Characteristics (ROC) curve and the Area Under the Curve of a Precision-Recall (P-R) curve. This second criterion is more adapted for imbalanced dataset what is often the case in the cyber-security field. We perform a complete parameter study of these classifiers to optimize their performance. The dataset used for this work is a pool of Hypertext Preprocessor (PHP) files analyzed by a multiagent PHP webshell detector. We obtain different good results, especially for neural networks and highlights the advantage of the genetic algorithm method that allows a physical interpretation of the result.

Penelitian ini dibertujuan untuk: 1) Menganalisis pengaruh strategi produksi terhadap peningkatan kinerja IKM/UKM Penyamakan Kulit. 2) Menganalisis pengaruh teknologi yang digunakan oleh strategi produksi terhadap peningkatan kinerja IKM/UKM Penyamakan Kulit. 3) Menganalisis pengaruh strategi distribusi terhadap peningkatan kinerja IKM/UKM Penyamakan Kulit. 4) Menganalisis pengaruh teknologi yang digunakan oleh strategi distribusi terhadap peningkatan kinerja IKM/UKM Penyamakan Kulit. 5) Menganalisis pengaruh strategi pemasaran langsung terhadap peningkatan kinerja IKM/UKM Penyamakan Kulit. Menganalisis pengaruh teknologi yang digunakan oleh strategi pemasaran langsung terhadap peningkatan kinerja IKM/UKM Penyamakan Kulit. 7) Menganalisis pengaruh langsung strategi teknologi terhadap peningkatan

The current trend of increasing quality and demands of the final product is affected by time analysis of the entire manufacturing process. The primary requirement of manufacturing is to produce as many products as soon as possible, at the lowest possible cost, but of course with the highest quality. Such requirements may be satisfied only if all the elements entering and affecting the production cycle are in a fully functional condition. These elements consist of sensory equipment and intelligent control elements that are essential for building intelligent manufacturing systems. Intelligent manufacturing system itself should be a system that can flexibly respond to changes in entering and exiting the process in interaction with the surroundings. In this paper a concept of designing and building intelligent decision support systems in production management is introduced. The new approach to the design of intelligent management systems is proposed based on integration of artificial intelligence technologies (fuzzy logic, artificial neural networks ,expert systems and genetic algorithms) with exact methods and models of decisions search and simulation techniques. The proposed approach allows for creating intelligent decision support systems of complex, unstructured management problems in fuzzy conditions. The systems learn based on accumulated data and adapt to changes in operation conditions.

Frank t-norms are parametric family of continuous Archimedean t-norms which are also strict when the parameter is nonnegative. Very often, this family of t-norms is also called the family of fundamental t-norms because of the role it plays in several applications. In this paper, we study a nonlinear optimization problem with a special system of Fuzzy Relational Equations (FRE) as its constraints. We firstly investigate the resolution of the feasible solutions set when it is defined with max-Frank composition and present some necessary and sufficient conditions for determining the feasibility and some procedures for simplifying the problem. Since the feasible solutions set of FREs is non-convex and the finding of all minimal solutions is an NP-hard problem, conventional nonlinear programming methods may involve high computation complexity. Based on the obtained theoretical properties of the problem, a genetic algorithm is used, which preserves the feasibility of new generated solutio...

This paper compares a fuzzy model, expressed in rule-form, with a well known statistical approach (i.e. logistic regression model) for diagnostic decision making in patients with chronic nasal symptoms. The analyses were carried out using a database obtained from a questionnaire administered to 1359 patients with nasal symptoms containing personal data, clinical data and skin prick test (SPT) results. Both the fuzzy model and the logistic regression model developed were validated using a data set obtained from another medical institution. The accuracy of the two models in identifying patients with positive or negative SPT was similar. This study is a preliminary step to the creation of a software that primary care doctors can use to make a diagnostic decision, when deciding whether patients with nasal symptoms need allergy testing or not.

Kegiatan di komoditas pertembakauan saat ini masih menghadapi berbagai masalah didalam beberapa aspek. Tidak konsistennya jumlah dan mutu produk yang dihasilkan, produktivitas yang rendah, pasar yang belum terorganisasi dengan baik, pasar yang tidak transparan, dimana semua ini menyebabkan rendahnya perolehan harga dan rendahnya pendapatan petani serta lemahnya daya saing produk tembakau. PTPN X sebagai penghasil tembakau Na-Oogst terbesar di Indonesia harus dapat mengoptimalisasi dan meningkatkan fungsi dan peran lembaga pertembakauan, meskipun berbagai isu yang terkait dengan komoditas tembakau mendapatkan sorotan yang negatif terhadap produk tersebut. Meskipun demikian pangsa pasar produk-produk berbasis tembakau masih cukup menjanjikan sehingga perlu untuk dicarikan strategi yang tepat untuk menjaga eksistensi dan daya saingnya. Tujuan penelitian ini dibagi tiga, (1) Mengindentifikasi aktivitas Value Chain perusahaan tembakau cerutu milik SBU tembakau PTPN X; (2) Mengidentifikas...

The position control system of an electro-hydraulic actuator system (EHAS) is investigated in this paper. The EHAS is developed by taking into consideration the nonlinearities of the system: the friction and the internal leakage. A variable load that simulates a realistic load in robotic excavator is taken as the trajectory reference. A method of control strategy that is implemented by employing a fuzzy logic controller (FLC) whose parameters are optimized using particle swarm optimization (PSO) is proposed. The scaling factors of the fuzzy inference system are tuned to obtain the optimal values which yield the best system performance. The simulation results show that the FLC is able to track the trajectory reference accurately for a range of values of orifice opening. Beyond that range, the orifice opening may introduce chattering, which the FLC alone is not sufficient to overcome. The PSO optimized FLC can reduce the chattering significantly. This result justifies the implementation of the proposed method in position control of EHAS.

We instantiate a social things paradigm in terms of a social network of facts which drives our household appliances in our name. The appliances are connected to the network, directly receiving the sequence of instructions (parameter/value pairs) constituting the recipe to perform a task requested by the user. The recipes are issued by the computational intelligence algorithms in the core of the social network. Users, appliances and social network are part of an entire ecosystem that we realized in the frame of the EU project Social&Smart. In this paper we describe the architecture, the information infrastructure and the first achievements of the Social&Smart ecosystem within the general cadre of an Open Internet of Things (Open IoT).

Abstract: The flexibility, customization and localization offered by computer integrated manufacturings are attractive but generate a new class of management problems. Intelligent support systems are needed for the managing: planning, implementation, configuring and operating of intelligence manufacturing systems. This paper presents a project of intelligent system for assembly process planning. The paper includes a coincidence description of the chosen aspects of implementation of this intelligent system using technologies of artificial intelligence (neural networks, fuzzy logic, expert systems, neuro-fuzzy systems).

Sektor industri kecil sebagai salah satu alternatif penciptaan lapangan kerja yang banyak menyerap tenaga kerja yang sangat dibutuhkan seperti industri sandal sepatu di Kecamatan Waru. Jumlah pengrajin yang ada di Kecamatan Waru diharapkan mampu banyak menyerap tenaga kerja bagi penduduk di sekitar lokasi industri sehingga mampu membantu mengurangi jumlah pengangguran. Penelitian ini bertujuan untuk : (1) mengetahui karakteristik pengrajin industri sandal sepatu di Kecamatan Waru, (2) mengetahui peranan industri sandal sepatu terhadap penyerapan tenaga kerja di Kecamatan Waru, (3) mengetahui pemasaran dari industri sandal sepatu di Kecamatan Waru. Jenis penelitian ini termasuk penelitian survey. Subyek penelitian ini adalah semua pengrajin industri sandal sepatu yang ada di Kecamatan Waru sebanyak 58 pengrajin. Teknik pengumpulan data menggunakan kuisioner dengan metode wawancara, pengamatan, dan dokumentasi. Teknik analisis data menggunakan deskriptif kuantitatif dengan prosentase. Hasil penelitian menyatakan bahwa karakteristik pengrajin industri sandal sepatu di Kecamatan Waru Kabupaten Sidoarjo memiliki umur paling banyak yaitu 45-49 tahun, jenis kelaminnya dari 58 orang pengrajin terdapat enam orang perempuan, tingkat pendidikan pengrajin 74,2% adalah SMA, status kawin, pendapatan, banyaknya jam kerja, jumlah tanggungan keluarga, dan jumlah tenaga kerja yang dipekerjakan tidak lebih dari 19 orang. Peranan industri sandal sepatu dari 6 desa ini mampu menyerap tenaga kerja sebesar 2,54% (593 orang) dari jumlah keseluruhan tenaga kerja yang bekerja di sektor industri. Asal wilayah sebaran tenaga kerja pada industri ini yang masih dalam satu desa dimana industri itu berdiri ada 80,6% tenaga kerja, dalam satu Kecamatan Waru lain desa ada 14,7%, luar Kabupaten Sidoarjo 2,9% tenaga kerja. Pemasaran hasil produksi dari industri sandal sepatu di Kecamatan Waru hampir ke kota-kota besar di seluruh Indonesia. Jumlah produk yang dipasarkan sebanyak 11.401 kodi per bulan dengan nilai produk sebesar Rp. 4.743.085.000,-dan dipasarkan ke 9 kota di luar Pulau Jawa dan 18 kota yang ada di Pulau Jawa.

Tujuan pengabdian kepada masyarakat ini adalah: (1) mengeksplorasi dan menciptakan desain-desain alas kaki yang up to date sesuai dengan keinginan dan kebutuhan konsumen berbasis kearifan lokal, dan (2) membuat prototipe alas kaki untuk mendukung sektor Alas Kaki sebagai Industri Prioritas (Nawa Cita). Pemberdayaan masyarakat di Kelurahan Kemasan Kecamatan Krian sangat perlu mendapat perhatian khusus baik dari pemerintah maupun swasta serta dari civitas akademisi, karena masyarakat yang ada sudah mempunyai budaya kerja dibidang alas kaki. Oleh karena itu perlu upaya peningkatan dalam pemberdayaan masyarakat yang ada sesuai dengan kebutuhan dari masyarakat. Jumlah industri kecil khususnya dibidang alas kali ada 39 IKM dengan jumlah tenaga kerja sudah sangat besar totalnya yaitu 245 orang. Metode pelaksanaan yang akan diterapkan ini adalah benchmarking, design by drawing dan teknologi konstruksi alas kaki. Diberikan pembelajaran design by drawing adalah kegiatan yang melibatkan penala...

This research arises from a real life problem that a third party solution partner of health care insurance companies in Turkey faces. The company develops Electronic Claim Processing System (ECPS) that private health care insurance companies utilize in order to check and validate whether an expenditure (i.e., claims) of their customers abides by the rules of the contracts between the insurance companies and the customers as well as the insurance companies and the health care service providers. As part of their business, the company also trains and assists the health care service providers regarding to the ECPS and the regulation of the insurance companies. Every year their training staffs visit 400+ health care service providers in Istanbul and in order to reduce the total travelling cost and balance the workload among them is a problem that they face. A decision support system that utilizes fuzzy zoning as a solution for the planning problem that the company faces is being developed. In this paper the fuzzy zoning algorithm utilized for this purpose will be presented and its performance will be evaluated.

In this paper a new fuzzy system modeling (FSM) algorithm is introduced as a data analysis and approximate reasoning tool. The performance of the proposed algorithm is tested in two different data sets and compared with some well-known algorithms from the literature. In the comparison two benchmark data sets from the literature, namely the automobile mpg (miles per gallon) prediction and Box and Jenkins gas-furnace data are used. The comparisons demonstrated that the proposed algorithm can be successfully applied in system modeling.

Fuzzy systems approximate highly nonlinear systems by means of fuzzy "if-then" rules. In the literature, various algorithms are proposed for mining. These algorithms commonly utilize fuzzy clustering in structure identi…cation. Basically, there are three di¤erent approaches in which one can utilize fuzzy clustering; the …rst one is based on input space clustering, the second one considers clustering realized in the output space, while the third one is concerned with clustering realized in the combined input-output space. In this study, we analyze these three approaches. We discuss each of the algorithms in great detail and o¤er a thorough comparative analysis. Finally, we compare the performances of these algorithms in a medical diagnosis classi…cation problem, namely Aachen Aphasia Test. The experiment and the results provide a valuable insight about the merits and the shortcomings of these three clustering approaches.

A representação de conhecimento em aplicativos computacionais está cada vez mais presente, junto com a popularização de meios avançados de se interagir e utilizar o computador no cotidiano dos usuários. Os meios usuais de interação (através de teclados, mouses, e outros dispositivos) começam a dar lugar para novos meios (touchscreen, comandos de voz, gestos, entre outros), que buscam superar as limitações dos predecessores, incorporando inteligência e naturalidade de interação humano-computador. Para isso é necessário representar conhecimento do domínio da aplicação, de forma que o aplicativo possa reconhecer e processar a informação que o usuário humano está passando por computador através de gestos, movimentos do corpo ou fala. Nesse processo se envolvem técnicas de inteligência computacional, reconhecimento de padrões, visão computacional, entre outros. O conhecimento é geralmente representado, entre outros métodos, se usando Modelo de Markov Oculto (HMM-Hidden Markov Model) que é um modelo estocástico, representado através de grafos de estados que possuem probabilidades de transições entre si, e observações que são funções probabilísticas dos estados. O modelo HMM é definido mediante treino com o algoritmo de Baum-Welch que estima os valores das probabilidades de transição e de observação, com um critério de maximização, a partir de um conjunto de seqüências de dados. Posteriormente, com base nesse modelo treinado, novas seqüências de dados poderão ser classificadas e reconhecidas pelo algoritmo de Viterbi. O objetivo deste trabalho é definir um modelo de HMM que seja possível de se usar em reconhecimento de gestos, fala, e outros padrões. Nossa implementação está baseada em implementações disponíveis como software livre, na linguagem de programação C++, buscando adaptá-las ao uso específico neste projeto, em particular para reconhecimento de gestos de corpo e posteriormente para reconhecimento de fala.

This work deals with an HCR system using a genetic algorithm (GA) to estimate the kernel parameters of an SVM for the recognition of the MNIST database in order to increase the correctness percentage of the classifier with the best combination of parameters . Also discussed are digital image processing (PDI) techniques for image processing and feature extraction. The use of a GA together with an SVM proved to be effective, achieving high accuracy rates.Este trabalho aborda um sistema HCR utilizando um algoritmo genético (AG) para estimar os parâmetros do kernel de uma SVM para o reconhecimento dos caracteres manuscritos da base de dados MNIST com o objetivo de elevar o percentual de acertos do classificador com a melhor combinação dos parâmetros. Também são abordadas técnicas de processamento digital de imagens (PDI) para o tratamento das imagens e extração de características. A utilização de um AG em conjunto com uma SVM mostrou-se eficaz, alcançando elevadas taxas de precisão

As data become an increasingly important asset for organizations, so does the access control policies that protect aforesaid data. Many subjects (public, researchers, etc.) are interested in accessing these data, leading to the desire for simple access control. However, some scenarios use vague concepts, such as the "researcher's expertise", when making access control decisions. Therefore, access control models based on fuzzy logic have been proposed to handle these scenarios. However, subject attributes can change between access requests and are processed in non-trivial ways by these models to reach a decision. This makes it difficult to audit the capabilities of subjects and their permissions over resources, and consequently, the number of application scenarios naturally suffers. Hence, the contribution of this paper lies in proposing an optimized auditing algorithm that allows fuzzy policies to be validated before being used. An assessment is also carried out to validate the method and its effectiveness.

Sistem inforasi manajemen pengendalian dan evaluasi rencana pembangunan daerah (SIMPERDA) diperlukan untuk menjamin agar transformasi ekonomi dan digital pembangunan daerah di Kabupaten Deli Serdang 2022 dapat di laksanakan sesuai dengan rencana dan evaluasi secara efektif dan efisien sehingga peningkatan daya saing daerah dalam menarik investasi menjadi modal pembangunan jangka panjang, dalam rangka mengintegrasikan perencanaan strategis dan lintas perangkat daerah terhadap prioritas dan sasaran pembangunan  maka penggunaan teknologi informasi menjadi salah satu metode yang bisa menggabungkan laporan kegiatan seluruh ornganisasi perangkat daerah (OPD) dengan entry data target kegiatan,laporan realisasi fisik dan dana pembangunan tiap organisasi secara bulanan, triwulan sehingga rekonsiliasi dapat langsung dimonitoring dan evaluasi kepala daerah. Dalam melakukan penelitian ini penulis  langsung membuat Forum Grup Diskusi yang melibatkan 43 perangkat daerah dan menggunakan Analisis d...

Abstrak. Program Pembinaan dan pengembangan merupakan upaya yang dilakukan oleh pemerintah, dunia usaha dan masyarakat melalui pemberian bimbingan dan penyuluhan untuk menumbuhkan dan meningkatkan kemampuan usaha kecil agar menjadi usaha yang tangguh dan mandiri serta dapat berkembang menjadi usaha menengah dan besar. Penelitian ini bertujuan untuk mengetahui dampak Program Pembinaan dan pengembangan Industri Kecil dan Menengah (IKM) terhadap keuntungan usaha, omzet penjualan dan biaya usaha IKM Klaster makanan dan minuman yang tersebar di Kota Cimahi dengan menggunakan data primer pada bulan juli 2018 dengan jumlah responden 41 IKM . Penelitian ini menggunakan metode kuantitatif primer dengan menggunakan teknik analisis uji beda independent t-test. Dari survey para pelaku IKM klaster makanan dan minuman sebanyak 41 IKM rata rata mengatakan bahwa keuntungan usaha, omzet penjualan dan total biaya produksi meningkat hampir duakali lipat dan untuk biaya usaha pada rata rata biaya produ...

Tujuan pengabdian kepada masyarakat ini adalah: (1) mengeksplorasi dan menciptakan desain-desain alas kaki yang up to date sesuai dengan keinginan dan kebutuhan konsumen berbasis kearifan lokal, dan (2) membuat prototipe alas kaki untuk mendukung sektor Alas Kaki sebagai Industri Prioritas (Nawa Cita). Pemberdayaan masyarakat di Kelurahan Kemasan Kecamatan Krian sangat perlu mendapat perhatian khusus baik dari pemerintah maupun swasta serta dari civitas akademisi, karena masyarakat yang ada sudah mempunyai budaya kerja dibidang alas kaki. Oleh karena itu perlu upaya peningkatan dalam pemberdayaan masyarakat yang ada sesuai dengan kebutuhan dari masyarakat. Jumlah industri kecil khususnya dibidang alas kali ada 39 IKM dengan jumlah tenaga kerja sudah sangat besar totalnya yaitu 245 orang. Metode pelaksanaan yang akan diterapkan ini adalah benchmarking, design by drawing dan teknologi konstruksi alas kaki. Diberikan pembelajaran design by drawing adalah kegiatan yang melibatkan penala...

Industri kreatif merupakan bentuk pemanfaatan kreatifitas, ketrampilan serta bakat individu dengan cara menghasilkan dan mengeksploitasi daya kreasi dan daya cipta individu (Sumotarto, 2010). Menurut Departemen Perdagangan Republik Indonesia dalam Pengembangan Industri Kreatif Menuju Visi Ekonomi Kreatif 2025 menelompokkan jenis industri kreatif menjadi empat belas sektor antara lain ; 1). Periklanan, 2) Arsitektur, 3) Pasara Barang Seni, 4) Kerajinan, 5) Desain, 6) Fesyen, 7) Video, Film dan Fotografi, 8) Permainan Interaktif, 9) Musik, 10) Seni Pertunjukan, 11) Penerbitan dan Percetakan, 12) Layanan Komputer dan Piranti Lunak, 13) Televisi dan Radio, 14) Riset dan Pengembangan. Pemilihan kompetensi inti daerah pada multi-variabel berupa produk domestik bruto (PDB), jumlah ketenagakerjaan, perdagangan internasional dan jumlah perusahaan berdasarkan pemetaan industri kreatif di Kabupaten Bangkalan adalah tujuan yang ingin dicapai pada penelitian ini. Aplikasi Multi Criteria Decision...

Tracking damaged roads and damage level assessment after earthquake is vital in finding optimal paths and conducting rescue missions. In this study, a new approach is proposed for the semi-automatic detection and assessment of damaged roads in urban areas using preevent vector map and both pre and post-earthquake QuickBird images. In this research, damage is defined as debris of damaged buildings, presence of parked cars and collapsed limbs of trees on the road surface. Various texture and spectral features are considered and a genetic algorithm is used to find the optimal features. Subsequently, a support vector machine classification is applied to the optimal features to detect damages. The proposed method was tested on QuickBird pan-sharpened images from the Bam earthquake and the results indicate that an overall accuracy of 93% and a kappa coefficient of 0.91 were achieved for the damage detection step. Finally, an appropriate fuzzy inference system (FIS) and also an ''Adaptive Neuro-Fuzzy Inference System'' are proposed for the road damage level assessment. These results show that ANFIS has achieved overall accuracy of 94% in comparison with 88% of FIS. The obtained results indicate the efficiency and accuracy of the Neuro-Fuzzy systems for road damage assessment. Keywords Road damage assessment Á Adaptive neurofuzzy inference system (ANFIS) Á QuickBird images Á Support vector machine (SVM) Á Genetic algorithm (GA)

Penelitian dilakukan pada sentra kerajinan kulit di kelurahan Selosari Magetan, Jawa Timur untuk mengetahui tiga hal, yaitu (1) Pendapatan dan efisiensi penggunaan biaya produksi industri alas kaki, (2) Nilai tambah produk, dan (3) strategi pengembangan industri. Data dikumpulkan dari 10 pelaku usaha dan 5 tenaga ahli yang mewakili instansi dan pihak terkait. Data terkumpul diolah menggunakan tiga kategori; analisa R/C ratio, analisis nilai tambah Hayami, dan AHP (Analytical Hierarcy Process). Hasil penelitian menunjukkan (1) rata-rata R/C ratio 1,23; (2) produk alas kaki dari kulit memiliki nilai tambah sebagai berikut; sepatu wanita Rp 30.707,71; sepatu laki-laki Rp 30.129,60; sandal laki-laki Rp 25.281,98; dan sandal wanita Rp 23.475,61; dan (3) strategi yang relatif tepat adalah pada kriteria pengembangan produksi dengan bobot 0,490.

Essay ini berisi Gambaran Umum mengenai Desa Ketajen, Kecamatan Gedangan, Kabupaten Sidoarjo yang di analisa menggunakan Analisis SWOT untuk mengetahui bagaimana Potensi Desa sehingga dapat menentukan Tujuan Desa yang meliputi Perencanaan Desa dan Rencana Strategis yang di capai.

Small and Medium Industry (SMI) have an important role in economic development to increase the value of products and providing employment as an industry. The purposes of this research are to determine the leading sector of food small-industry in Jambi City, and to measure the contribution rate of it in absorb labors within the city. The result showed that in Jambi City, the leading sector of food small-industry was a group of nut-processing industry and plantation product-processing industry. That leading sector contributed 18.65 percent to the absorption of labor.  

tertinggi sub-kriteria ekonomi adalah ketersediaan spare part (KSP), nilai preferensi tertinggi sub-kriteria teknis adalah losis minyak (LM). Hasil analisis tahap ketiga AHP adalah dekanter Merek B berada pada peringkat pertama, dengan nilai preferensi ekonomi 0,148 dan teknis 0,130. Hasil ini menunjukkan bahwa nilai preferensi dapat berubah jika melibatkan analisis yang kompleks antara kriteria, sub-kriteria dan merek dekanter. Hasil analisis sensitifitas menunjukkan bahwa dekanter Merek B dan Merek E menjadi peringkat pertama preferensi, dimana Merek E berada pada rangking ketiga sebelum analisis sensitifitas. Kata kunci: dekanter 3 fasa, pabrik kelapa sawit, merek, analytic hierarchy process, kriteria dan subkriteria pemilihan dekanter Abstract Decanter is used to separate oil phase from underflow sludge of continuous settling tank (CST) in Palm Oil Mills (POM). The most commonly type of decanter is 3-phase decanter. This paper describes the brand preferences in 3-phase decanter selection by using the Analytical Hierarchy Process (AHP) method. Before the AHP was done, expert correspondent prepared a list of criteria and sub-criteria for 3-phase decanter brand selection. AHP was conducted in 3 steps, which were: i) criteria classification, ii) pair-wise comparison of criteria and sub-criteria, that did by user correspondent, and iii) evaluation on the 3-phase decanter selection based on the brand comparison, that did by user correspondent. AHP simulation was carried out using Expertchoice® version 11. The first step of AHP generated: i) a question list arranged in questionnaire form, regarding criteria and sub-criteria concerning the brand of the decanter, and ii) weight value for each question. The second step of AHP

Generalized adaptive resonance theory (GART) is a neural network model that is capable of online learning and is effective in tackling pattern classification tasks. In this paper, we propose an improved GART model (IGART), and demonstrate its applicability to power systems. IGART enhances the dynamics of GART in several aspects, which include the use of the Laplacian likelihood function, a new vigilance function, a new matchtracking mechanism, an ordering algorithm for determining the sequence of training data, and a rule extraction capability to elicit if-then rules from the network. To assess the effectiveness of IGART and to compare its performances with those from other methods, three datasets that are related to power systems are employed. The experimental results demonstrate the usefulness of IGART with the rule extraction capability in undertaking classification problems in power systems engineering.

Damage in structures can negatively affect their functionality and safety and leads to failure. Thus it is very important to monitor structures for occurrence, location and severity of damage. Structural health monitoring techniques provide information on the life expectancy of structures simultaneously detects and locates structural damage. Damage identification of structures based on vibration has always been important subjects and are being rapidly used to damage and location of structures. Artificial Neural Networks (ANNs) as a soft computing method using dynamic parameters of structures have been utilized increasingly for structural damage detection due to their excellent pattern recognition capability. Dynamic parameters of structure are easy to implement for damage identification and can directly linked to the topology of structure. This study presents the application of ANN for damage identification in steel beams using dynamic parameters. For identification of severity and location of damage, at first, five individual neural networks corresponding to mode 1 to mode 5 are considered. At the second step, a method based on neural network ensemble is proposed to combine the outcomes of the individual neural networks to a single network. Ensemble results were evaluated and discussed according to the differences between predicted output by ANN and desire data (target data) obtained from experimental modal analysis of structure.

Penyakit Diabetes Melitus Gestasional (DMG) merupakan salah satu penyebab kematian pada ibu hamil. Penyakit ini penyebab kematian wanita tertinggi nomor 9 di dunia. Frekuensi penyakit DMG yang tidak terdeteksi 10-25%. Kurangnya pengetahuan ibu hamil tentang faktor-faktor penyebab penyakit DMG membuat Angka Kematian Ibu masih tinggi. Penelitian ini menggunakan logika fuzzy khususnya fuzzy Mamdani untuk mendeteksi penyakit DMG. Logika fuzzy mengandung nilai yang kabur atau samar di antara dua nilai yaitu benar atau salah. Penentuan rule atau aturan fuzzy berdasarkan pakar. Pengetahuan pakar yang digunakan dalam sistem ini berupa kumpulan aturan diagnosis (rule) berupa hubungan antara gejala-gejala dengan jenis penyakit yang dialami. Pakar mengevaluasi aturanaturan tersebut dan menetukan himpunan Fuzzy untuk setiap gejala. Gejala yang diiput diubah ke dalam bentuk himpunan Fuzzy (Fuzzifikasi), kemudian dimasukan ke dalam fungsi implikasi serta disesuaikan dengan aturan diagnosis yang telah dievaluasi oleh pakar. Karena hasil perhitungan yang di dapat masih dalam bentuk Fuzzy maka harus dilakukan proses Defuzzifikasi (penegasan), sehingga dapat ditentukan hasil diagnosis ibu hamil dengan kehamilan normal atau terkena penyakit DMG.

As data become an increasingly important asset for organizations, so does the access control policies that protect aforesaid data. Many subjects (public, researchers, etc.) are interested in accessing these data, leading to the desire for simple access control. However, some scenarios use vague concepts, such as the "researcher's expertise", when making access control decisions. Therefore, access control models based on fuzzy logic have been proposed to handle these scenarios. However, subject attributes can change between access requests and are processed in non-trivial ways by these models to reach a decision. This makes it difficult to audit the capabilities of subjects and their permissions over resources, and consequently, the number of application scenarios naturally suffers. Hence, the contribution of this paper lies in proposing an optimized auditing algorithm that allows fuzzy policies to be validated before being used. An assessment is also carried out to validate the method and its effectiveness.

This research was conducted in the area of Pekanbaru City which includes 12 subdistricts in Pekanbaru City, in the period 2010 to 2015. This study aims to identify and examine small industries that are the leading small industries in Pekanbaru City, where are small industries in Pekanbaru City concentrated spatially. This study uses secondary data, namely data on labor absorption in the small industry sub-sector in each sub-district in Pekanbaru City. Data analysis used descriptive analysis method, to explain/describe the problem in accordance with the research objectives. While the quantitative analysis method with the location quotient (LQ) analysis tool and spatial concentration, is to determine the basic economic sector and the leading small industry sector in Pekanbaru City. The results of the study using location quotient (LQ) analysis of labor absorption showed that in 2010-2015 the leading small and small industries in Pekanbaru City were small handicraft industries, where the absorption of small handicraft industries in the sub-districts of Pekanbaru City was greater than the absorption other business sector workers in Pekanbaru City. Small handicraft industries in the Pekanbaru City area excel in: (i) Tampan District, (ii) Bukit Raya District, (iii) Marpoyan Damai District, (iv) Tenayan Raya District, (v) Lima Puluh District, (vi) Sail District, (vii) Pekanbaru City District, (viii) Sukajadi District, (ix) Rumbai District, and (x) Rumbai Pesisir District. Based on the calculation of spatial concentration, the presence of small industries in Pekanbaru City is concentrated in Payung Sekaki and Tenayan Raya Districts with the mainstay small industry being the metal small industry branch.

Penyakit jantung koroner (PJK) merupakan penyakit yang apabila sudah terdiagnosa perlu sekali diawasi karena beresiko tinggi terhadap kematian. Resiko kematian tersebut perlu diminimalisasi dengan membuat sebuah media konsultasi dan monitoring terhadap penderita sesuai gejala yang dialami. Dokter dan paramedis adalah pakar yang berkompeten untuk mediagnosa tingkat resiko penyakit jantung koroner, namun dalam pengambilan keputusan yang sulit terdapat keragaman opini pakar (inter-expert) dan seiring waktu opini pakar pun berubah (intra-expert) karena pengetahuannya terus bertambah berdasarkan adanya gejala baru dari penelitian yang dilakukan, kebiasaan baru, atau dipengaruhi keadaan emosi. Model fuzzy mengatasi permasalahan ketidakpastian. Model fuzzy yang menggunakan himpunan fuzzy non-stationary (FNIS) mereplikasi keragaman pada manusia sehingga mampu mengatasi permasalahan kegaraman opini pada pakar baik inter-expert maupun intra-expert. Sistem yang dibangun menggunakan model fuzzy non-stationary untuk mendiagnosa tingkat resiko jantung koroner berdasarkan 5 input yakni umur, tekanan darah, gula darah, status BMI, dan kolesterol. Fuzzy sistem pada penelitian ini menggunakan mamdani inferensi. Dua fungsi perturbation function yang digunakan sistem adalah fungsi distribusi acak normal pada variabel input dan fungsi sinusoidal pada variabel output untuk meng-generate membership function untuk 5 kali perulangan. Hasil perbandingan diagnosa antara pakar, FIS, dan FNIS didapati bahwa FNIS lebih tepat dibandingkan FIS sesuai diagnosa pakar secara manual.

The current trend of increasing quality and demands of the final product is affected by time analysis of the entire manufacturing process. The primary requirement of manufacturing is to produce as many products as soon as possible, at the lowest possible cost, but of course with the highest quality. Such requirements may be satisfied only if all the elements entering and affecting the production cycle are in a fully functional condition. These elements consist of sensory equipment and intelligent control elements that are essential for building intelligent manufacturing systems. Intelligent manufacturing system itself should be a system that can flexibly respond to changes in entering and exiting the process in interaction with the surroundings. In this paper a concept of designing and building intelligent decision support systems in production management is introduced. The new approach to the design of intelligent management systems is proposed based on integration of artificial intelligence technologies (fuzzy logic, artificial neural networks ,expert systems and genetic algorithms) with exact methods and models of decisions search and simulation techniques. The proposed approach allows for creating intelligent decision support systems of complex, unstructured management problems in fuzzy conditions. The systems learn based on accumulated data and adapt to changes in operation conditions.

In this paper is presented ANFIS (Adaptive Network based Fuzzy Inference System) method of modeling of pH neutralisator. Data that has been used for training of ANFIS are obtained by performing experiments on a real pH neutralisator. The mathematical model of the pH neutralisator is strongly nonlinear so it is advisable to use ANFIS, since ANFIS is an universal approximator. Inputs of the process (control variables) are flow of acid and hydroxide. The working temperature of the process is 128 0 C, with instaled pH meter of operating range 2-12 pH with combined glass electrode in the upper part of the neutralizer, 20 cm bellow the surface. Then using Genetic Algorithms (GA) parameters of PID controller of pH value has been adjusted in optimal way. Since GA is method of search of global optimum, achieved solution is optimal according to integral criterion of performance. Simulation results show utility of the proposed methodology.

In this paper is presented ANFIS (Adaptive Network based Fuzzy Inference System) method of modeling of pH neutralisator. Data that has been used for training of ANFIS are obtained by performing experiments on a real pH neutralisator. The mathematical model of the pH neutralisator is strongly nonlinear so it is advisable to use ANFIS, since ANFIS is an universal approximator. Inputs of the process (control variables) are flow of acid and hydroxide. The working temperature of the process is 128C, with instaled pH meter of operating range 2-12 pH with combined glass electrode in the upper part of the neutralizer, 20 cm bellow the surface. Then using Genetic Algorithms (GA) parameters of PID controller of pH value has been adjusted in optimal way. Since GA is method of search of global optimum, achieved solution is optimal according to integral criterion of performance. Simulation results show utility of the proposed methodology.

Program desa Vokasi dilatarbelakangi beberapa permasalahan di pedesaan, seperti: kurang berkembang akses masyarakat pedesaan pada sumber daya produktif, dan masih terbatasnya kapasitas kelembagaan pemerintahan di tingkat lokal. Artikel ini memaparkan hasil studi identifikasi potensi wilayah desa vokasi Sojokerto Kecamatan Leksono Kabupaten Wonosobo. Hasil studi menyimpulkan terdapat 4 usaha/industri kecil utama yang layak dikembangkan di Desa Vokasi Sojokerto yaitu Industri Konveksi, Industri Boga/Makanan Ringan, Usaha Penggemukan Ternak, dan Usaha Pertanian. Hasil analisis dengan analytical hierarchy process AHP menyimpulkan bahwa nilai ekonomi dan modal usaha menjadi kriteria terpenting untuk menentukan skala prioritas pengembangan industri kecil. Sementar itu, ketersediaan bahan baku dan penyerapan tenaga kerja belum menjadi perhatian utama karena tidak ada kendala selama ini. Hasil penelitian juga menyimpulkan bahwa untuk usaha di luar usaha tradisional, industri/usaha konveksi menjadi prioritas utama untuk dikembangkan lebih lanjut di desa vokasi.

Nowadays, the threats caused by aerial targets are among the most critical challenges. Two main components in threat management are visualization and decision-making based on compiled pictures. In this process, the decisions are made based on threat evaluation and resource allocation modelling. To do so, the sequential nature of resource allocation is considered to provide a more accurately visualized situation. Here, a multi-stage multi-objective model is constructed based on the fuzzy inference system and the decision tree. Also, NSGA-II and SPEA-II are used to find Pareto solutions. Both Algorithms have been compared based on generational distance as a convergence measure, spread as a diversity measure, and the actual computational time. Ultimately, the TOPSIS method is used to make the final decision while the results are reported using a simulated scenario. The simulation results show that the SPEA-II has better convergence and spread, while NSGA-II is faster and has less standard deviation in the execution time. We believe that the fuzzy inference system is more suitable than the decision tree in practical applications. Nevertheless, when facing data shortage or incompatibility, the decision tree would be the preferred choice.

The Hidden Markov Modeling (HMM) methodology has been successfully employed in the modeling and analysis of sequence data, for example, continuous speech recognition in the temporal domain and analysis of protein structures in the sequencing domain. However, these domains assume that the model structure has been provided by human experts. In a number of other domains, such as physiology, economics, and social sciences, model structures of dynamic phenomena are not not readily available. In this context, this paper develops a clustering methodology to automatically partition temporal data into homogeneous groups, and to construct HMM models for each group. when the model structure is unknown. Our methodology makes two new contributions to data clustering using HMM models. First, an explicit HMM model size selection procedure is incorporated into the clustering process, i.e., the sizes of the individual HMMs are dynamically determined for each cluster. This improves the interpretability of cluster models, and the quality of the final clustering partition results. Second, a partition selection method is developed to ensure an objective, data-driven selection of the number of clusters in the partition. The result is a heuristic sequential search control algorithm that is computationally feasible. Experiments with artificially generated data show that the HMM model size selection algorithm is effective in rediscovering the structure of the generating HMMs, and the HMM clustering with model size selection significantly outperforms HMM clustering using uniform HMM model sizes for rediscovering clustering partition structures. Experiments with real world ecological data show interesting results.

Tarik Krian Sidoarjo is one of the areas of agricultural technology and the result pemroduk carpentry most reliable and most turnover compared with other regions. Products produced are tools such as the hoe, trowel, sickles, shovels, machetes, bendo and others. However, these efforts have not seen a sign - a sign of progress and development, which means, it is necessary to increase output menajamen improvement.The method used was a demonstration and practice. Demonstrations conducted at the stage of the introduction of tools to etalworkers, while the practice is performed immediately after the target is considered to use a tool that is prepared to increase production.Activity Results: Effectiveness and efficiency of technology tools / lathe versatile mechanical system seen from the large expenses associated with the manufacture of the benefits calculated by financially. (1) Changes in the behavior of workers before and after using the technology tools / lathe versatile mechanical sy...

This research aims at woven bamboo handicrafts which are one of the superior products of Magetan Regency. The problem that occurs is that innovation is not optimal, because the quality of the workforce is still low. Bamboo woven handicraft products cannot yet have an export market. The lack of coordination between craftsmen, distributors and the government resulted in a weak institutional structure. The purpose of this research is to determine the strategy for increasing the competitiveness of the small bamboo woven handicraft industry in the Ringinagung area, Magetan district. The method used is analytical descriptive. The instrument in the form of a questionnaire given to 5 key respondents. The research used the Process Hierarchy Analysis (AHP) technique. The results of the study show that there are five areas of strategy including 1). Innovation 2). HR, 3). Production , 4). Marketing, and 5) Institutional

Bridges as an important part of the transportation system have a role in spurring economic growth and regional development. For this reason, the government is obliged to build bridge infrastructure in a stable condition so that connectivity between regions can be realized. Given the many infrastructure development activities that have been delayed since 2019 as a result refocusing as well as the limitations of the APBD, it is necessary to select the order of priority for the bridge implementation program. This study aims to analyze the dominant criteria and sub-criteria that need to be considered so that the order of priority for the construction of a truss bridge in Deli Serdang Regency can be compiled. The method used is AHP with a quantitative approach through a questionnaire. The criteria considered are economic (cost), technical (sub-criteria for bridge age, length, width, and implementation time), land use (sub-criteria for agriculture/plantation, tourism, fisheries, and minin...

Avant Propos Les travaux présentés dans cette thèse sont le résultat des recherches réalisées dans le Laboratoire d'Analyse et d'Architecture des Systèmes du Centre National de la Recherche Scientifique, LAAS-CNRS, dans les groupes de recherche Diagnostic, Supervision et Conduite qualitatifs, DISCO, et Microsystèmes et Intégration des Systèmes, MIS. Je remercie à Monsieur Jean-Claude LAPRIE et à Monsieur Malik GHALLAB, ancien et actuel directeur du LAAS, de m'avoir accueilli dans cet établissement. J'exprime toute ma gratitude et reconnaissance à mon directeur de thèse Monsieur André TITLI, Professeur à l'Institut National des Sciences Appliquées de Toulouse, INSA, et cadre Scientifique au LAAS-CNRS, pour sa confiance et son amitié toute au long de ces années de travail. Sa forme très particulière d'écouter, de discuter et de proposer des idées claires et précises, a su diriger sagement les mouvements de ce jeune chercheur, en me donnant, en même temps, un grand niveau d'autonomie et une manière plus élargie d'apprécier le monde. Je lui remercie également de m'avoir maintenu sur la voie de la représentation à partir de la connaissance, notamment sur les systèmes d'inférence flous, pour lesquels je voyais moins d'intérêt que pour la représentation à partir des données. Au LAAS j'exprime ma reconnaissance envers : Monsieur Joseph AGUILAR-MARTIN, directeur du Laboratoire Européen LEA-SICA et ancien directeur du groupe DISCO, de m'avoir toujours aidé et supporté pour réaliser les séjours en Catalogne et participer aux différentes conférences. Son grand enthousiasme, bonne humeur et disponibilité a crée une bonne ambiance entre nos camarades. Madame Anne-Marie GUE, directeur du groupe MIS, pour m'avoir toujours aidé à effectuer les missions au cours de ces années pour les projets. Madame Louise TRAVE-MASSUYES, directeur du groupe DISCO, de m'avoir également soutenue lors des différentes missions et de m'avoir invité à participer au réseau MONET. Je lui remercie également pour sa disponibilité et ces commentaires par rapport au diagnostic. Monsieur Alfredo SANTANA DIAZ, pour nos collaborations sur la détection de la baisse de la vigilance du conducteur et pour m'avoir introduit au monde des ondelettes. Monsieur Sébastien BEYOU, stagiaire de DEA, pour sa contribution à ce travail de thèse. Mes collègues du groupe DISCO et MIS qui ont contribué, avec son bon humeur à rendre plus convivial mon séjour au LAAS :