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Coreid Journal
Published by Generasi Intelektual Digital
ISSN : -     EISSN : 29876990     DOI : https://doi.org/10.60005/coreid.v1i2.14
Core Subject : Science,
Computer Science & IT
CoreID is a scientific journal that contains scientific papers from Academics, Researchers, and Practitioners about research on informatics and Computer. CoreID is published 3 times a year in March, July, and November. The paper is an original script and has a research base on Informatics. The scope of the paper includes several studies but is not limited to the following study. 1. Computer Sciences 2. Software Engineering 3. Information Technology 4. Digital Innovation
Arjuna Subject : Ilmu Komputer (semua kategori) - Sistem Informasi
Articles 5 Documents
 1 
Search results for , issue "Vol. 1 No. 2 (2023): July 2023" : 5 Documents clear
Classification of Health and Nutritional Status of Toddlers Using the Naïve Bayes Classification Saputra, Yogi; Khoirunisa, Nurfitria; Arinal Haqq, Syauqi
CoreID Journal Vol. 1 No. 2 (2023): July 2023
Publisher : CV. Generasi Intelektual Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60005/coreid.v1i2.8

Abstract

Life is characterized by the presence of symptoms of growth and development. The growth and development of the degree of health of each individual are different. In this case, one of the efforts to improve health status is to improve nutritional status. Nutritional status is the state of the body related to food consumption patterns and the use of nutrients that are tailored to the body's needs. Improving nutritional status is useful for increasing body resistance and promoting normal growth. In the daily actualization of the nutritional status of toddlers at the posyandu, it is usually obtained through anthropometric measurements, namely by using the weight/age index or weight-for-age to determine nutritional status. However, in measuring with anthropometry, there was confusion in determining nutritional quality, so to get accurate results, a data mining method is needed, namely the Naive Bayes Classification (NBC) Algorithm, which will be implemented in research. With this research, it is hoped that it can help posyandu cadres in the Baros sub-district, Cimahi sub-district, and Cimahi city determine the level of health and nutritional status of toddlers better and more accurately.
Attendance System Implementation Existing Android Platform Using React Native Framework Bakti Nugraha, Arif; Rizcky Hikmawan, Muhammad
CoreID Journal Vol. 1 No. 2 (2023): July 2023
Publisher : CV. Generasi Intelektual Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60005/coreid.v1i2.9

Abstract

In a school that has hundreds of students, the attendance system or attendance recording is a problem in terms of practicality and data capture. Especially during a pandemic like this, learning is carried out online or in a network, commonly called distance learning (PJJ). Currently, various applications of technological advances have been created and begun to replace conventional systems. One of them is an Android-based attendance application system. The purpose of this study is to analyze and design an application that can help manage attendance data more easily and accurately. System modeling uses Unified Modelling Language (UML) to describe visually, then implemented with PHP and JavaScript programming languages, React Native Framework, and MySQL database as a database. With the mobile-based attendance system, it can make it easier for teachers to conduct attendance effectively and efficiently.
Classification of Non-Civil Servant Performance Appraisal Using Naïve Bayes Classifier Algorithm Dewi, Sofia
CoreID Journal Vol. 1 No. 2 (2023): July 2023
Publisher : CV. Generasi Intelektual Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60005/coreid.v1i2.10

Abstract

Employee performance assessment is a way to measure the level of employee productivity. In the process of assessing the performance of Non-Civil Servants (non-PNS) employees at the Regional Technical Implementation Unit of Education and Training of Cooperatives and Entrepreneurs (UPTD P3W) at this time, it is required to classify data based on several factors to find out whether the employee fits into the eligible category or not as the best employee to become a civil servant (PNS) candidate. The purpose of this research is to make it easier to determine the classification of the performance assessment of non-PNS employees at UPTD P3W using the Naïve Bayes Classifier Algorithm and to determine the level of accuracy in the classification of the performance assessment. In this study, the authors used 498 data as training data and 105 data as testing data for manual testing in Excel and for testing using RapidMiner tools. Based on the analysis in the study, the result of the predictions determines the best employees to become candidates for civil servants quickly and accurately, while from the tests performed by comparing training data and with data testing using RapidMiner tools, the accuracy rate is 84.76%.
Optimizing Bank Marketing Strategies Through Analysis Using Lightgbm Diaz Aditya, Erindra Reynaldi; Yudha Satria, Dhian Kartika
CoreID Journal Vol. 1 No. 2 (2023): July 2023
Publisher : CV. Generasi Intelektual Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60005/coreid.v1i2.11

Abstract

Marketing campaigns in a bank are one of the ways for the bank to achieve its organizational goals. Optimal marketing is a crucial factor for a bank's success in attracting and retaining customers. Therefore, if a bank's marketing campaigns are carried out suboptimally, it will be challenging to achieve the goals of those campaigns. In this case study, it can be observed that the number of customers who subscribe to fixed-term deposits is lower, with a proportion of 5289 customers making deposits and 5873 customers not making deposits. This research aims to optimize bank marketing strategies by applying analysis using the LightGBM algorithm, which is a highly effective and efficient Gradient Boosting Decision Tree algorithm. This approach facilitates the design of more optimal marketing strategies. The accuracy score of the predictive model generated is 0.8584, with an F1 score of 0.8564, including 974 true negatives and 943 true positives.
Sentiment Analysis on Twitter Social Media Regarding Depression Disorder Using the Naive Bayes Method Lavenia, Nur Lickha; Permatasari, Reisa
CoreID Journal Vol. 1 No. 2 (2023): July 2023
Publisher : CV. Generasi Intelektual Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60005/coreid.v1i2.14

Abstract

Depression disorder is a serious issue in mental health that affects many individuals worldwide. This research analyzes the sentiments related to depression disorder on Twitter using the Naïve Bayes method. Depression-related tweet data was collected through snscrape and processed to eliminate irrelevant information. Three Naïve Bayes methods, namely Multinomial, Gaussian, and Bernoulli, were compared to classify positive, negative, or neutral sentiments in each tweet. The results of the study indicate that Multinomial Naïve Bayes exhibited the best performance with an accuracy rate of 90.13%, followed by Gaussian Naïve Bayes (88.38%), and Bernoulli Naïve Bayes (85.37%).

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