Production Time Optimization using Campbell Dudek Smith (CDS) Algorithm for Production Scheduling

Mashuri, Chamdan; Mujianto, Ahmad Heru; Sucipto, Hadi; Arsam, Rinaldo Yudianto; Permadi, Ginanjar Setyo

doi:10.1051/e3sconf/201912523009

Cited by 6 publications

(3 citation statements)

References 5 publications

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“…K-means is a data method with a non-hierarchical method that aims to partition data into one or more clusters [22]. The purpose of this data clustering method is to minimize the objective function set in the clustering process [23]. Following the stages of data clustering using the K-Means method is commonly done with the basic algorithm as follows [24]: a) There are 3 classes which will then be determined by K-means namely classes a, b and c, where one of these classes becomes the selected cluster point.…”

Section: K-means Methodsmentioning

confidence: 99%

K-means method for clustering learning classes

Indriyanti

Prehanto

Vitadiar³

2021

IJEECS

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<span>Learning class is a collection of several students in an educational institution. Every beginning of the school year the educational institution conducts a grouping class test. However, sometimes class grouping is not in accordance with the ability of students. For this reason, a system is needed to be able to see the ability of students according to the desired parameters. Determination of the weight of test scores is done using the K-Means method as a grouping method. Iteration or repetition process in the K-Means method is very important because the weight value is still very possible to change. Therefore, the repetition process is carried out to produce a value that does not change and is used to determine the ability level of students. The results of the class grouping test scores affect the ability of students. Application of K-Means method is used in building an information system grouping student admissions in an educational institution. Acceptance of students will be grouped into 3 groups of learning classes. The results of testing the system that applies K-Means method and based on data on the admission of prospective students from educational institutions have very high accuracy with an error rate of 0.074. </span>

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Section: K-means Methodsmentioning

confidence: 99%

K-means method for clustering learning classes

Indriyanti

Prehanto

Vitadiar³

2021

IJEECS

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“…Penjadwalan perlu dirancang sesuai dengan karakteristik jalur produksi. Pekerjaan dasar penjadwalan adalah untuk memproses tugas sesuai dengan proses pengolahan untuk mengatur produksi dan pemrosesan (Mashuri et al, 2019).…”

Section: Pendahuluanunclassified

Sistem Optimasi Penjadwalan Mesin Produksi Menggunakan Metode GUPTA Berbasis Android

Mashuri

Mujianto

Sucipto

et al. 2020

J. Sistem Info. Bisnis

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Research has been carried out by developing an optimization information system for scheduling production machines by applying the Android-based GUPTA method. This android-based application is able to optimize production time, because in the android application it implements the GUPTA algorithm which uses the calculation of the comparative processing time on every machine in the company by prioritizing the smallest processing time for scheduling which aims to optimize production scheduling time, by paying attention to the value of makespan to produce product size 12 griddle, size 14 griddle, 16 size griddle, 18 size griddle and 20 size griddle so that an optimal makespan value is obtained. The GUPTA method can be used in problems with more than two machines, because this method combines the time of each process on the first and subsequent machines to find the minimum value and can only be used in pure flow shop scheduling. The advantage of this method is that it determines scheduling only on one machine group. This research resulted in an Android-based application that can schedule products to be produced by machines automatically. From the results of testing with a total of 12 pieces of production in each product with a total of 5 different sizes, the minimum value of makespan is obtained, namely 2054569 minutes with the sequence of product processing with work order 12 griddle, griddle 18, griddle 20, griddle 16, and griddle 14 The accuracy of the application test results shows 98.87% for the first time and 98.84% for the second time when compared with manual calculations.

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“…The goal of XP is a team formed between small to medium sized courses, no need to use a large team. It is intended to address unclear requirements and requirements change very quickly [6].…”

Section: Xpmentioning

confidence: 99%

Development Of Mapping Area Software For Dismissal People Affected By Covid-19

Indriyanti

Putra

Prehanto

et al. 2020

2020 Third International Conference on Vocational Education and Electrical Engineering (ICVEE)

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The spread of the Covid-19 Virus which has a major impact on various sectors of human life, from health problems that have caused many deaths and also economic impacts. The decline in people's purchasing power has caused the industry to experience a decrease in sales turnover, causing business actors to carry out budget efficiency by terminating employment. In terms of assisting government programs in assisting victims of layoffs, a system for mapping the locations of these victims is needed. In building a mapping system for the location of victims of layoffs using the XP method which is part of agille. The system can display the location area down to the districts level. By using a system of mapping the locations of dismissed communities, it can assist in data collection and distribution of assistance.

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Production Time Optimization using Campbell Dudek Smith (CDS) Algorithm for Production Scheduling

Cited by 6 publications

References 5 publications

K-means method for clustering learning classes

K-means method for clustering learning classes

Sistem Optimasi Penjadwalan Mesin Produksi Menggunakan Metode GUPTA Berbasis Android

Development Of Mapping Area Software For Dismissal People Affected By Covid-19

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