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Irmayani, Decy
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Computer Science & IT

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ANALYZE THE ADVANTAGES AND COSTS OF PROCESSING DIRTY SWALLOW'S NESTS TO FINISHED PRODUCTS USING THE C5.0 ALGORITHM Pasaribu, Milwan; Irmayani, Decy; Nasution, Fitri Aini
INFOKUM Vol. 10 No. 5 (2022): December, Computer and Communication
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/infokum.v10i5.1529

Abstract

Swallow's nest is a very popular health product nowadays. This can happen due to swallow's nest has many health benefits such as antioxidant, anti-inflammatory, antiaging, anticancer, immune-boosting and accelerating wound healing. However, the production of swallow's nest is difficult to do so that the product of swallow's nest becomes expensive. This study aims to analyze the costs and benefits required to produce swallow nests. The method used is the C5.0 algorithm which uses a decision tree. The results showed that the root node was obtained, namely the drying stage of the swallow's nest. If the costs required at this stage were equivalent to the existing capital, the company would get benefit. Conversely, if the required cost exceeds the existing capital, the company will experience a loss. Through the decision tree, it can be determined that the determinant or root node of the swallow's nest production process is the stage of the swallow's nest drying process. If the capital is within the budget (budget) then the company will generate profits. Meanwhile, if the existing capital is insufficient (pass) then the company will suffer losses. Based on the results of this study, it can be suggested to use the C5.0 algorithm method in analyzing the costs and profits generated from a production process that produces finished products for sale.
CLUSTERING OF ALGORTIMA K-MEANS BASED NATIONAL EXAM SCORE DATA WITH ELBOW AND SILHOUETTE OPTIMIZATION Rahman NST, Arief; Irmayani, Decy; Putra Juledi, Angga
INFOKUM Vol. 10 No. 5 (2022): December, Computer and Communication
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58471/infokum.v10i5.1530

Abstract

The national examination is a system of evaluating basic education standards that supports student graduation. In accordance with the regulations of the Government of the Republic of Indonesia, the evaluation of learning outcomes aims to evaluate the achievements of national postgraduate students. The research methods carried out in this study start from problem analysis, data analysis, application design and data implementation. As the data obtained by the author, namely the National Vocational Examination Score Data for Vocational High Schools in Central Java Province for the class of 2019. But the data displayed is still random and uninformed. Then data mining techniques are needed to classify which schools are carried out using the k-means clustering method and using elbow and silhouette optimization, with the optimum k obtained K = 3 and K = 2 by calculation using the RStudio tool. It is expected to produce the best cluster for clustering. The overall average of K = 3 UN values Indonesian is 72.79906. The average score of UN English is 45,941. The average score of UN Mathematics is 41,324. Average UN Competency score 48.1947. The overall average of K = 2 UN values Indonesian 76.95. The average score of UN English is 33,425. The average score of UN Mathematics is 45.65. The average un competency score is 52.54. From the data on national test scores at the VOCATIONAL level, 3 groups were obtained using the k-means cluster with the elbow optimization method. On cluster 1 it has 707 members, the cluster has 152 members. Cluster 3 has 675 members
Co-Authors Nasution, Fitri Aini Pasaribu, Milwan Putra Juledi, Angga Rahman NST, Arief