Dynamic Segmentation Of Behavior Patterns Based On Quantity Value Movement Using Fuzzy Subtractive Clustering Method

Sangadji, Iriansyah Bm; Arvio, Yozika; Indrianto,

doi:10.1088/1742-6596/974/1/012009

Cited by 4 publications

(2 citation statements)

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“…In this case, the need for accurate predictions led to a more effective and cheap supply chain, as well as allowed companies to provide quality, quantity, periodical, and lowproduction cost products [11]. Many studies also used other machine learning approaches to map prediction patterns, such as fuzzy subtractive clustering [12].Therefore, this study aims to analyze the patterns by which inventory procurement predictions produce precast products with good quality, using the ereadiness framework concept of the neural network method through appropriate decision-making processes. In this condition, prediction modelling was prepared as part of the application of e-readiness in raw material management.…”

Section: Fig 1 Precast Product Spunpilementioning

confidence: 99%

Raw Material Optimization With Neural Network Method in Concrete Production on Precast Industry

Hidayawanti¹

2023

GEOMATE

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The development of construction is presently experiencing rapid growth in Indonesia, leading to the requirement of the right materials for infrastructural enhancements. From the existing infrastructure, concrete innovations such as precasts are needed with good quality materials, for the quick completion of construction. This is because the need for good quality and smooth material helps to determine the success of a building project, with the use of technology through precast being a problem-solving process. Therefore, this study aims to analyze the patterns by which inventory procurement predictions produce precasts with good quality, using the e-readiness framework concept of the neural network through appropriate decision-making processes. It also focuses on innovating technological products used in the Indonesian precast industry. The Methodology Neural Network was used to produce the best target quality time and precast commodities. The result indicated two outputs from 2 neural network models, using five similar input-value variables. Based on the Adaline neural network, the outputs were observed as the highest sales-cost predictions for precast products, which often occurred in 1, 5, 6 and 9 months. Besides this, production activities were also normally operated at level (1), with profit optimization being highly considered before months 1, 5, 6 and 9. For the LVQ neural network, the result was a predictive classification of class intensity levels, where fast decision-making processes occurred in months 1, 6 and 9. Cost optimization was also carried out by ordering raw materials several months in advance, considering the trend in material prices and logistics.

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Section: Fig 1 Precast Product Spunpilementioning

confidence: 99%

Raw Material Optimization With Neural Network Method in Concrete Production on Precast Industry

Hidayawanti¹

2023

GEOMATE

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“…Salah satu yang dapat diimplementasikan dalam pemanfaatan energi matahari adalah kompor listrik. Penggunaan mikrokontroler pada kompor listrik menjadi sangat membantu dalam mempermudah pengontrolan besarnya api yang diinginkan [19] [20] [21]. Penggunaan kompor Dengan memanfaatkan energi matahari akan menghasilkan beberapa keunggulan dibandingkan dengan penggunaan kompor lain seperti gas, efisiensinya hampir 58% [22].…”

Section: Pendahuluanunclassified

Disain Kompor Listrik Dengan Menggunakan Pembangkit Listrik Tenaga Surya Untuk Kebutuhan Listrik Rumah Tangga

Pahiyanti

Sukmajati

Indrianto

2021

sutet

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Savings in using electric fuel in the use of fossil fuel electricity must be reduced. This research was conducted as an effort to save the use of electricity by using solar power plants as the main source, with the making of this research it is hoped that it can be used for electricity consumption at a more economical cost and the use of electric stoves can be used in daily life. The selection of materials and this research can be seen from the existing literature and field studies. Solar power plants in this study use some equipment such as solar panels that by utilizing solar energy will be a source of initial voltage, a regulator control battery as a regulator of electric power charging to the battery (battery), battery (battery) as a storage of electrical power, and an inverter for convert the dc to ac voltage from the battery (battery). The equipment is the main equipment used to turn on the electric stove which is the main burden in this application. This research is expected to be a reference for the use of solar energy for electric stoves in an effort to save electricity. This equipment also refers to the amount of power used on an electric stove of 300 W, with an observation time of 7 hours a day, so that it will produce a current that flows at 6.8 A, and a voltage of 17.3 Volts which occurs at 11.00 WIB

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Analysis of Electrocardiogram Signal and Ammonia Concentration For Clustering ASD Condition

Marchelliant

Aripin

Wulandari

2021

2021 International Seminar on Application for Technology of Information and Communication (iSemantic)

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Dynamic Segmentation Of Behavior Patterns Based On Quantity Value Movement Using Fuzzy Subtractive Clustering Method

Cited by 4 publications

References 0 publications

Raw Material Optimization With Neural Network Method in Concrete Production on Precast Industry

Raw Material Optimization With Neural Network Method in Concrete Production on Precast Industry

Disain Kompor Listrik Dengan Menggunakan Pembangkit Listrik Tenaga Surya Untuk Kebutuhan Listrik Rumah Tangga

Analysis of Electrocardiogram Signal and Ammonia Concentration For Clustering ASD Condition

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