JEECS (Journal of Electrical Engineering and Computer Sciences)
We aims to promote high-quality Electrical Engineering and Computer Sciences research among academics and practitioners alike, including power system, electrical engineering, industry automation, mechatronics, computer sciences, informatics, and information system. This journal is dedicated for the author or researcher who has focused in the field of technology and intending on publication and sharing knowledge the novel technology include, but are not limited to, the following topics: Data Mining, Informatics algorithm methodology, Mobile Computing, Automation, Power, Green Technology, Advanced Computer Networks, Image Processing, Computer Vision, Robotics Technology, Decision Support System, Big Data, Data Sciences, Internet of Things, Network Security, Virtual Reality, etc.
Articles
420 Documents
<![CDATA[Structural Analysis Program Using Direct Stiffness Method for The Design of Reinforced Concrete Column ]]>
<![CDATA[Ahmad Faza Azmi]]>
<![CDATA[ JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 2 No. 1 (2017): JEECS (Journal of Electrical Engineering and Computer Sciences) ]]>
Publisher : <![CDATA[Fakultas Teknik Universitas Bhayangkara ]]>
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DOI: 10.54732/jeecs.v2i1.161
<![CDATA[Most of the analyzes and calculations in civil engineering have been using computer. But many commercial structuralanalysis programs are relatively expensive. Hence one of the alternative way is using a self developed structuralanalysis program. The computer program is constructed using Visual Basic 6 programming language. Using directstiffness method and theory of ACI 318-02, a numerical procedure along with a computer program was developed forthe structural analysis and design of reinforced concrete member. From the direct stiffness method,in terms ofstructural analysis, the output that obtained from the program are internal element forces and support reactions nodedisplacements. From ACI 318-02 codes, in terms of reinforced concrete member analysis, the program generate theamount of longitudinal and lateral reinforcement of concrete member based on the output in the previous structureanalysis program. The program also reveals the biaxial bending-axial interaction diagrams in each direction ofrectangular and circular column. The interaction diagram of the columns is a visual representation to determine themaximum axial load and moment exceeded the capacity of the column.]]>
<![CDATA[Implementation of Naive Bayes Method in Classification of Breast Cancer Disease ]]>
<![CDATA[Alamsyah]]>;
<![CDATA[Eko Prasetyo]]>;
<![CDATA[R Dimas Prasetyo]]>
<![CDATA[ JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 2 No. 1 (2017): JEECS (Journal of Electrical Engineering and Computer Sciences) ]]>
Publisher : <![CDATA[Fakultas Teknik Universitas Bhayangkara ]]>
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DOI: 10.54732/jeecs.v2i1.162
<![CDATA[Less knowledge of early symptoms of breast cancer and how to deal with it early and the number of specialist doctorswho are still limited is one factor contributors because of the increasing number of people affected by breast cancerdisease. The development of breast cancer disease classification system aims to predict the early diagnosis of breastcancer disease in users or patients into two categories of malignant or benign. The initial diagnoses of this systemprediction variable include Clump Thickness, Uniformity of Cell Size, Uniformity of Cell Shape, Marginal Adhesion,Single Epithelial Cell Size (Single Epithelial Cell) Size), Bare nuclei, Bland Chromatin, Normal nucleoli, Mitosis Usingthe naive bayes method to process diagnostic data in patients, the results of this system test show that the system isable to predict and classify breast cancer disease into two categories (malignant or benign) with the amount of datatesting of 500 data. With the output of malignant or YA and benign or NO, the system is able to predict with an accuracyvalue of 98%.]]>
<![CDATA[Application of Cloud Computing for The Development of Knowledge Management System Web Based Network ]]>
<![CDATA[Chusnul Astri Ch]]>;
<![CDATA[Rani Purbaningtyas]]>;
<![CDATA[R Dimas Prasetyo]]>
<![CDATA[ JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 2 No. 1 (2017): JEECS (Journal of Electrical Engineering and Computer Sciences) ]]>
Publisher : <![CDATA[Fakultas Teknik Universitas Bhayangkara ]]>
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DOI: 10.54732/jeecs.v2i1.163
<![CDATA[Developing Knowledge Management System using cloud computing is a concept that integrates knowledgemanagement (KM), with the process of finding, selecting, seeking, organizing and presenting data or information.KMS Network is a system that provides web-based content (contains data, information, & knowledge) as an increasein knowledge mastery, to help the needs of users or users who have difficulty when looking for sources of information.Kms is developed through the adoption of cloud computing (CC) technology, which has large amounts of data storageusing web servers or cloud servers online. In the research application of cloud computing for the development ofknowledge management system web-based network, has a speed in accessing the average article data 0.7833 seconds/ page, with the average page load memory 2.0 MB, search articles using the method "Sequential Search Or SequentialSearching ".]]>
<![CDATA[Omnet Sales Digital Protection with Box Jenkins and Delphi Method (case Study: PT Media Virtual Indonesia) ]]>
<![CDATA[Sarif Hidayat Tullah]]>
<![CDATA[ JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 2 No. 1 (2017): JEECS (Journal of Electrical Engineering and Computer Sciences) ]]>
Publisher : <![CDATA[Fakultas Teknik Universitas Bhayangkara ]]>
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DOI: 10.54732/jeecs.v2i1.164
<![CDATA[To be able to develop sales turnover digital newspaper Jawa Pos, PT. Media Virtual Indonesia requires an appforecasting a sales turnover. The method used in forecasting the quantitative turnover using ARIMA method (BoxJenkins) while for forecasting the skin using Delphi method. The results showed ARIMA AR method became an optionbecause it has the smallest MSE error that is ARIMA AR 3525.36963, ARIMA MA 3803.33228, while ARIMA ARMA4176.79443. While with the Delphi method, the main problem is the increase in selling power of Digital Java Posnewspaper, while the results obtained at each stage is Phase 1: Which region will be the concentration of sales:Bandung City with points 7. Stage 2 How to introduce the product to the surrounding community? : Held a LocalEvent.]]>
<![CDATA[Decision Supplier Package System Using Fuzzy Subjective and Objective Integrated Weights Method (case Study: PT Garudafood Putra Putri Jaya) ]]>
<![CDATA[Muhammad Saiful Irawan]]>;
<![CDATA[Rifki Fahrial Zainal]]>;
<![CDATA[Syariful Alim]]>
<![CDATA[ JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 2 No. 1 (2017): JEECS (Journal of Electrical Engineering and Computer Sciences) ]]>
Publisher : <![CDATA[Fakultas Teknik Universitas Bhayangkara ]]>
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DOI: 10.54732/jeecs.v2i1.165
<![CDATA[The purchasing department is the part that plays an important and influential role in a company even can be said mostof the business process comes from this section. Because of its nature as a procurement of goods and services then oneof its duties and responsibilities is to choose suppliers of procurement of goods and services for production operationalprocesses within the company. In this case PT Garudafood Putra - Putri Jaya often have difficulty in determining thebest product packaging supplier because of the performance instability of each supplier. For that the company needsa system whose purpose is to help decide the best supplier determination. Decision support system is a computer-basedinformation system that generates various decision alternatives to assist management in handling various structuredor unstructured problems using data or models. There are many methods used in a decision support system such asFuzzy Subjective And Objective Integrated Weights. Fuzzy can solve the problem of uncertainty in determining theweight of each supplier's criteria. The result of the implementation of this decision support system resulted in thesupplier of Mandhara Adhitama Utama as the best supplier. Where the results of calculations with Fuzzy SubjectiveAnd Objective Integrated Weights this supplier obtained the highest value with the number 1.742.]]>
<![CDATA[System Prediction Production PT.Vico Indonesia Using Method Holt Winters ]]>
<![CDATA[Riyan Sukma Sasongko]]>;
<![CDATA[Eko Prasetyo]]>;
<![CDATA[Rani Purbaningtyas]]>
<![CDATA[ JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 2 No. 1 (2017): JEECS (Journal of Electrical Engineering and Computer Sciences) ]]>
Publisher : <![CDATA[Fakultas Teknik Universitas Bhayangkara ]]>
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DOI: 10.54732/jeecs.v2i1.166
<![CDATA[Problem that Taken in this study is the process of forecasting oil and gas production in accordance so that companiescan know the prediction of the amount of oil and gas in the future. The method used to determine production predictionis Holt-Winters forecasting method. In testing the system will do the comparison of alpha, beta and gamma. Using thealpha value = 0.2, beta = 0.1 and gamma 0.5 to get better multiplicative forecast for oil and gas data. And to get thesmaller error difference compared to the smaller alpha (α), beta (β) and gamma (γ) then the smaller the differencewill be. The Multiplexative Spring Method and the Seasonal Additive Method are good enough for oil and gasproduction data]]>
<![CDATA[Analysis and Design of Production Schedulling System for CV. Bulu Nusantara Gresik ]]>
<![CDATA[Emmy Wahyuningtyas]]>
<![CDATA[ JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 2 No. 1 (2017): JEECS (Journal of Electrical Engineering and Computer Sciences) ]]>
Publisher : <![CDATA[Fakultas Teknik Universitas Bhayangkara ]]>
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DOI: 10.54732/jeecs.v2i1.167
<![CDATA[CV. Bulu Nusantara is a company located in Gresik – East Java produces some kinds of flour as animal feedingredients. The flours are come from chicken feathers, chicken bones, fishes and clams. The company has limitedproduction machinery, so as to produce each kind of flour for optimum results, it must be well planned. This study isto analyze and design the information system needed by the company. The system is designed to manage inputs,processing them and resulting some informations like Master Production Schedule, dayly/weekly/monthly productionreport, and so on. The analysis phase produces two algorithms, each for estimating the order finishing time andschedulling calculation. The design phase produces context flow diagram, first level of data flow diagram, theconceptual and physical data model. The study result is showing us that the company needs the information systemwhiches consist of seven interrellated entities, eight main processes and flexible period of detailed reporting or resumereporting in form of chart.]]>
<![CDATA[Grouping of Books Type Based by Time Borrowing (months) Using Fuzzy C-Means Algorithm. (case Study: Surabaya Public Library) ]]>
<![CDATA[Bachtiar Azhari]]>;
<![CDATA[Rifki Fahrial Zainal]]>;
<![CDATA[Rani Purbaningtyas]]>
<![CDATA[ JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 2 No. 1 (2017): JEECS (Journal of Electrical Engineering and Computer Sciences) ]]>
Publisher : <![CDATA[Fakultas Teknik Universitas Bhayangkara ]]>
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DOI: 10.54732/jeecs.v2i1.168
<![CDATA[Book lending transactions are the main activities that take place in the Library. With the method of grouping, it willget what kind of books are most often borrowed. The method used is Fuzzy C-Means. This thesis discusses theapplication of Fuzzy C-Means method to classify book data based on lending per month and measure the effectivenessof the use of methods in the process. This application has been tested by producing 3 clusters and classify the time(month) where the frequency of borrowing done by visitors in the Library.]]>
<![CDATA[3D Simulation of Plant Growth Modeling Using Neuro-Fuzzy, Lindenmayer System, and Turtle Geometry ]]>
<![CDATA[Wiwiet Herulambang]]>;
<![CDATA[Retantyo Wardoyo]]>
<![CDATA[ JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 1 No. 2 (2016): JEECS (Journal of Electrical Engineering and Computer Sciences) ]]>
Publisher : <![CDATA[Fakultas Teknik Universitas Bhayangkara ]]>
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DOI: 10.54732/jeecs.v1i2.169
<![CDATA[Applications that are able to predict plants growth patterns as a function of the nutrients obtained from fertilization pattern, is very useful in agriculture. The purpose of this study was to design and build a system of plants growth simulation models with Neuro-fuzzy method, then visualized by methods Lindenmayer system represented by three-dimensional use of Turtle Geometry. As the object of research is Soybean (Glycine max (L.) Merrill). Modeling parameters is long growth trunk / branches (L), a wide cross section of the leaf (W), and branch growth (B), as a function of changes in the fertilizing elements Nitrogen (N), Phosphate (P) and potassium (K). Modeling done on the vegetative phase of the soybean crop.First step is the modeling output L-W-B as a function of changes in the values of NPK using neurofuzzy (ANFIS). The final step is to combine plant growth pattern parameters (L-W-B) and L-system strings into the visualization process plant structure using Turtle Geometry.The test results on the system to grow plants pattern proves that ANFIS method is quite adaptive to variation of NPK value changes, and able to predict the output value L, W, and B. The final result of string-set of L-system and also it's visualization by Turtle Geometry, has proven to be influenced by variations in the composition of NPK values. Overall, the system has been running as expected.]]>
<![CDATA[Pattern Recognition of Signature Verification Using Cellular Automata Methods ]]>
<![CDATA[Adiananda]]>;
<![CDATA[Retantyo Wardoyo]]>
<![CDATA[ JEECS (Journal of Electrical Engineering and Computer Sciences) Vol. 1 No. 2 (2016): JEECS (Journal of Electrical Engineering and Computer Sciences) ]]>
Publisher : <![CDATA[Fakultas Teknik Universitas Bhayangkara ]]>
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DOI: 10.54732/jeecs.v1i2.170
<![CDATA[A pattern recognition technique in the field of machine learning and can be defined as "the act of taking raw data and act upon data classification". Much research has been done on the topic of pattern recognition using a variety of methods one of which is by using the cellular automata. In this study used cellular automata method for finding and extracting characteristics of an image of the signature and realized in a pattern recognition software that can verify the authenticity of the signature image by using cellular automata method for the extraction process characteristics. In this study used data 57 respondents with 6 signatures used as a reference image. Three pieces of the original signature image and 10 pieces of counterfeit signature image is used as the test images (query). From the testing that has been done precision 88.30%, recall 65.37% and accuracy 71.31%.]]>
