PELATIHAN PENGGUNAAN E-DRAW MAX UNTUK MEMBUAT DESAIN SISTEM

Edraw Max is a 2D business technical diagram software that helps create flowcharts, organization charts, mind maps, network diagrams, floor plans, workflow diagrams, business charts and Engineering diagrams, flowcharts, graphs and mappings, besides E- Draw Max is also a vector-based diagramming software, which is usually used to make it easier to make a design. One of them is the design of a production process system in a factory that can use this application. In this training, the E-Draw Max tools will focus on making Data Flow Diagrams (DFD), which are useful for describing the flow of the created system, which consists of Context Diagrams, Level Diagrams, and Level n Diagrams. Data Flow Diagram (DFD) is a diagram that describes the flow of data from a process or information system. In DFD, there is information related to the input and output of each of these processes. DFD also has various functions, such as conveying system design, describing systems, and designing models. This training was held at the ITS NU Pekalongan Institute of Computer Technology. The purpose of this training is to help ITS NU Pekalongan S1 Computer Technology students in making system designs, specifically designing Data Flow Diagrams (DFD) using E-Draw Max tools to make it easier for students to make the flow of the system made in this case DFD on production process in Industry

Fuzzy Inference System Tsukamoto–Decision Tree C 4.5 in Predicting the Amount of Roof Tile Production in Kebumen

Tile is a product that is in great demand by many people. This has become a trigger for producers to improve their management. The company's tile production management is still experiencing problems, namely frequent miscalculations in determining the agreement that must be issued in making tile production from customer requests. One of the efforts made is to predict the production that can be done to get the optimal amount obtained, to get a big profit. In this study, to obtain a prediction of the amount of tile production, computerized calculations were carried out using the Tsukamoto fuzzy logic method. This method uses the concept of rules from the C 4.5 decision tree in the building to make it easier to determine the rules that are built without having to consult an expert because C 4.5 will study existing datasets to serve as a reference in forming these rules according to conditions that often occur. The modeling results produce relevant rules after being compared with the actual results. The results of the comparison of predictions with actual production have an error percentage of 29.34%, with a truth of 70.66% (based on the calculation of the Average Forecasting Error Rate (AFER)). Therefore when implemented in the Tsukamoto Fuzzy Inference System it can produce predictions of tile production that are quite optimum. It is said to be quite optimum because all customer requests are met, either generated by the production prediction itself or the prediction results are added up with inventory data, and all predictions are close to actual production

Subjectivity Tracking System for Poor Scholarship Recipients at Elementary School Using the MOORA Method

This research was conducted because of complaints from several parents at Elementary School regarding recipients of the Poor Student Assistance (PSA) who were still less objective. Elementary School XY regularly conduct screening activities every year to select prospective PSA recipients. This selection is made so that the recipients of this assistance are students entitled to it. Some students should be accepted as a selection committee but do not mistake of choosing some students who have kinship or subjective matters. Therefore, this study aims to explore and create applications that apply the Multi Objective Optimization to the basic  Ratio Analysis (MOORA) method, which is a method for determining students based on predetermined criteria. The criteria used are the value of report cards, student achievement, student activity, parental income, parental dependents, and home conditions. After conducting a search and implementation using the MOORA method in determining PSA recipients, it was found that there were some non-objective results where the student's criteria and final results were lower than some other students. However the Elementary School provided a recommendation to get PSA. If this happens again, then the importance of this system is to help objective selection. The accuracy results explained that 14.39% of PSA recipients were subjective. It was concluded that this research helps an objective decision and facilitates the decision maker in determining the best 3 recipients from each class at Elementary School XY

Fuzzy Inference System Mamdani dalam Prediksi Produksi Kain Tenun Menggunakan Rule Berdasarkan Random Tree

Kain tenun merupakan salah satu produk yang diminati oleh banyak orang. Hal ini menjadi pemicu produsen untuk meningkatkan pengelolahannya. Salah satu usaha yang dilakukan adalah memprediksi produksi yang dapat dilakukan untuk mendapatkan jumlah optimal yang diperoleh, sehingga mendapatkan keuntungan yang besar. Dalam penelitian ini, untuk mendapatkan prediksi jumlah produksi kain tenun dilakukan dengan perhitungan komputerisasi menggunakan metode logika fuzzy Mamdani. Metode ini menggunakan konsep pohon keputusan random tree dalam membentuk rule. Rule yang dibuat berdasarkan pada kriteria dalam penentuan jumlah produksi kain tenun, diantaranya yaitu biaya produksi, permintaan, dan stok. Konsep pohon keputusan random tree dalam penelitian ini digunakan untuk membuat rule secara otomatis berdasarkan data yang tersedia. Pembentukan rule ini berdasarkan data-data kain tenun dan diimplementasikan dalam random tree, sehingga tidak perlu menggunakan pakar. Penelitian ini membuktikan bahwa prediksi yang dilakukan dapat membangun rule dengan nilai akurasi sebesar 100%. Hasil perbandingan prediksi dengan produksi sesungguhnya memiliki persentase error sebesar 3% dengan nilai kebenaran sebesar 97% (berdasarkan perhitungan Average Forecasting Error Rate (AFER)). Oleh karena itu ketika diimplementasikan dalam fuzzy Mamdani dapat menghasilkan prediksi produksi kain tenun yang optimal. AbstractWoven fabric is a product that is in demand by many people. It triggers producers to improve their management. One of the efforts made is to predict the production that can be done to get the optimal amount obtained, to get a significant profit. In this study, to obtain a prediction of the amount of woven fabric production is done by computerized calculations using the Mamdani fuzzy logic method. This method uses the concept of a random tree decision tree in forming rules. The rules are made based on the criteria in determining the amount of woven fabric production, including production costs, demand, and stock. The concept of a random tree decision tree in this study automatically generates rules based on available data. This rule's formation is based on woven fabric data and is implemented in a random tree, so there is no need to use experts. This study shows that the predictions made can build rules with an accuracy value of 100%. The comparison of predictions with actual production has an error percentage of 3% with a truth value of 97% (based on the calculation of the Average Forecasting Error Rate (AFER)). When implemented in Fuzzy Mamdani, it can produce optimal woven fabric production predictions with predicted results less than the actual production

Ripensare la Heimat con la letteratura

This contribution analyzes the new narratives of the Heimat (home-country), the new facets and meanings elaborated by contemporary European literature. It explores in the most recent fiction the different cognitive perspectives and the different sensitivities and experiences fielded by the authors to redefine both the contents of the Heimat and the feelings and emotions it evokes. There is an interesting effort to rethink the traditional concept of Heimat as the founding nucleus of personal, ethnic and cultural identity; to find other ways to describe their idea of home-country, corresponding to the change in lifestyles and cultural priorities. And an expansion of the relative semantic field is evident, which crosses integration, inclusiveness, supranational opening