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

Implementation of the Weighted Aggregated Sum Product Assessment Method in Determining the Best Rice for Serabi Cake Making

This study explains the implementation using the Weighted Aggregated Sum Product Assessment method in determining the best rice to be used for making Serabi cakes, the case was taken from a Serabi cake seller in Tegal City, Central Java with the aim of providing knowledge to Serabi cake traders to be more detailed in determining the rice that is used. suitable for use in making Serabi not just rice is cheap, but it is necessary to see the shape and characteristics of the whole rice. The steps taken to determine the best rice which will then be used as the basis for making Serabi cakes using the Weighted Aggregated Sum Product Assessment method are: (1) Prepare a matrix in which is the value of each set of criteria, (2) Normalize matrix data x becomes normalized data, (3) Calculates alternative values using Weighted Aggregated Sum Product Assessment formula so that the ranking value is found. After these steps are carried out, in this study the best rice that is right to be used as a material for making Serabi is Pelita rice with a yield of 7.12 by occupying the first rank

An Alternative in Determining the Best Wood for Guitar Materials Using MOORA Method

This study aims to assist wood craftsmen in Dongkelan, Krapyak, Yogyakarta in determining the best wood to be used as guitar material, because there are frequent complaints from buyers that the materials used as guitar materials are rotten quickly and are dull in terms of color. Based on these problems, a solution is sought using the Multi Objective Optimization on the basis of Ratio Analysis (MOORA) decision support system method, and is assisted by experts in determining the right criteria related to determining the best wood used in making guitar materials, after a long time discussing the correct criteria were found based on the problem, in the form of criteria for wood strength, wood grain, texture, and wood weight. All of these criteria are then processed using the MOORA decision support system method. After processing, the best results are obtained. The right wood for guitar making is ebony with 23.6831 results occupying the first rank. Proving the results of the MOORA decision support system method, a questionnaire was carried out directly to several guitar makers with a total of 14 people, resulting in an accuracy of 85.71% which means that it has significant verification, that ebony wood is best used as a guitar-making materia

The WASPAS Method in Determining BSM Recipients Objectively

This research was conducted due to complaints from several parents regarding the determination of BSM at SDN Karanganyar 02 which still contains subjectivity in its selection so that some students are less fortunate. SDN Karanganyar 02, once a year always carries out activities related to determining the selection of BSM recipients. With this activity, it is hoped that students who are underprivileged but have fairly good achievements can receive this BSM so that the activities they carry out do not feel burdened with financial needs. The fact is that in institutions there are still many students who do not get BSM, even though according to the requirements these students should be eligible to get BSM. So in the selection that occurs there is a very irrational subjectivity. To solve this problem, the researcher tries to make a solution through an application that applies the Weight Aggregated Sum Product Assessment (WASPAS) method, which is a method of determining with predetermined criteria. The criteria in question are activities, achievements, report cards, parental income, home conditions, and parental dependents. After analyzing and implementing the WASPAS Decision Support System, it was found that the results were detrimental to students where the criteria scores and final determination were lower than some other students, but the SD carried out an assessment by obtaining BSM. To prevent this incident from recurring, WASPAS is very capable of answering objective determinations with the results obtained at 79.88% and the previous subjective determination at 20.12%

Forecasting Roof Tiles Production with Comparison of SMA and DMA Methods Based on n-th Ordo 2 and 4

This research aims to predict roof tile production trends at one of the roof tile companies in Kebumen to assist company management in determining and providing management recommendations for the tile production that occurs. A comparison of Single Moving Average (SMA) and Double Moving Average (DMA) Forecasting methods was used to better accommodate trends in roof tile production data optimally. Where the forecast is presented for several steps ahead, and is equipped with a value measuring the accuracy of the forecast using Mean Absolute Percentage Error (MAPE), on roof tile production transaction data over 60 months, namely January-December 2019 to January-December 2023 to produce a monthly forecast for predicting roof tile production with n-th ordo 2 and 4. The total sample of training data processed was 1,415,987 records which were roof tile production transaction data, as well as data in January 2024 as test data (to test the accuracy of the forecast). The results of testing the forecast results produced a MAPE calculation of 6.6% for SMA with n-th ordo 2, while for n-th ordo 4 it was 7.2%. The MAPE value for DMA is 6.3% for n-th ordo 2, while for n-th ordo 4 it is 8.2%, which means the accuracy level is very good, namely above 90%. Based on the MAPE results obtained, the DMA method with n-th ordo 2 is a suitable method for carrying out periodic forecasting for roof tile companies in carrying out the production process to maintain stability and avoid unexpected events

Application of the Fuzzy Inference System Method to Predict the Number of Weaving Fabric Production

In this study discusses the application of fuzzy logic in solving production problems using the Tsukamoto method and the Sugeno method. The problem that is solved is how to determine the production of woven fabric when using three variables as input data, namely: stock, demand and inventory of production costs. The first step is to solve the problem of woven fabric production using the Tsukamoto method which is to determine the input variables and output variables which are firm sets, the second step is to change the input variable into a fuzzy set with the fuzzification process, then the third step is processing the fuzzy set data with the maximum method. And the last or fourth step is to change the output into a firm set with the defuzzification process with a weighted average method, so that the desired results will be obtained in the output variable. The solution to the production problem using the Sugeno method is almost the same as using the Tsukamoto method, it\u27s just that the system output is not a fuzzy set, but rather a constant or a linear equation. The difference between the Tsukamoto Method and the Sugeno Method is in consequence. The Sugeno method uses constants or mathematical functions of the input variables