Prediction for Cooperative Credit Eligibility Using Data Mining Classification With C4.5 Algorithm

The problem of nutrition for children is a health problem that must be solved by the government. Malnutrition is a very important problem in the development of children, especially during the growth period. Lack of nutritional intake in children will have a negative impact on resistance to the virus. This will risk death caused by malnutrition. There is direct monitoring from the government, hospitals, and health offices in looking at the classification of nutrition in children in a system. This study aims to classify the nutritional status of children using a machine learning model, which then the final result can show the classification of nutritional vulnerability in each patient at the North Aceh Hospital. The stages of the research include the identification of theories about nutritional problems. Second, data collection is in the form of symptoms and diagnosis of disease classification in machine learning implementation. The third is to analyze the data using the research and development (R&D) method according to the classification of children's nutrition. Finally, the implementation of the patient classification model with decision tree into machine learning The variables included in the system include JK(X1), U (X2), BB(X3), TB (X4), and BB (X3), which are the variables that have the most influence on malnutrition in children. The results of this study for testing weight 16, height 9.7, age 33 months, nutritional value 54,23772 which the program output results are normal. Patient Syafira Nisman, weight 9, height 72, age 21 months, suffered from malnutrition. The results of the research on the application of machine learning for the classification of malnutrition using the decision tree method make it easier for patients and hospitals to classify children's nutrition.

Section: Analisis Masalahunclassified

Application of Machine Learning in Determining the Classification of Children's Nutrition With Decision Tree

Ula

Ulva

Mauliza

et al. 2022

“…Penelitian tentang pembuatan sistem peramalan telah dilakukan oleh Edy Purnomo pada tahun 2018. Hasil peramalan menggunakan Metode Trend Moment pada bulan Desember 2017 mengalami Trend Positif dimana penjualannya adalah 436,17 [2]. Penelitian yang sama juga dilakukan oleh Ayu Nanda Safitri pada tahun 2021.…”

Section: Pendahuluanunclassified

Sales Stock Forecasting System Using Trend Moment Method (Study Case: Warcam Store)

Iriyanti

Kurniawati

Widiastuti

2022

The Warcam store is a store that sells various frozen food products since 2019. The sales process at this Warcam store often experiences a shortage or excess stock of frozen food which causes losses for shop owners. This happens because Warcam Stores have not know how to calculate inventory. This study will discuss how the stages of making a forecasting system using the website-based trend moment method can help to predict frozen food stocks. The data used is data from 2019 to 2020 with in 360 transactions. The stages begin with business understanding, data understanding, and data preparation. Build a model using flowchart and perform a simulation of product forecasting calculations until an evaluation. This system was created using the PHP programming language and MySQL database with the CRISP-DM (Cross Industry Standard Process For Data Mining) approach. From the results of testing the system that has been made, this system can predict frozen food stocks with an error value of 14.52%. This error states that the forecast is still not correct, there are still excess and or lack of stock so that further research needs to be carried out using other methods.

“…Black Box Testing bertujuan untuk menguji apakah aplikasi berjalan sesuai dengan yang diharapkan, yaitu dengan melakukan uji dengan beberapa test case [10]- [12].…”

Section: Pengujian Blackboxunclassified

Mobile-Based Car Booking Service Application at Sriwijaya Berlian Car Repair Shop

Lambardo

Wawan

2022

Current technological developments are needed to help companies face competition, especially in conveying information to many people. Sriwijaya Berlian Car Repair Shop does not yet have a flow in booking service. Therefore, an application is needed to help admins in booking services and make it easier for customers to make reservations. The method in making this application starts from gathering requirements, making prototypes and designing, implementing in the form of applications, and conducting testing. After passing the development stage, a mobile-based application and website for booking services were produced at the Sriwijaya Berlian Car Repair Shop. Based on the results of the blackbox test, it was found that the application was in accordance with what was expected by the application developer, while based on the results of the user acceptance test, the user's average perception was 88.88% with the indicator category "Very Good".