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Enrichment: Journal of Multidisciplinary Research and Development
ISSN : -     EISSN : 29873398     DOI : https://doi.org/10.55324
Enrichment: Journal of Multidisciplinary Research and Development is a double-blind, peer-reviewed journal covering multidisciplinary issues. Monthly published by International Journal Labs, the journal serves as a means of relevant discussion that fall within its focus and scopes. This journal publishes research articles covering multidisciplinary sciences, including humanities and social sciences, education, religious sciences, philosophy, economics, engineering sciences, and health sciences.
Arjuna Subject : Umum - Umum
Articles 5 Documents
Search results for , issue "Vol. 1 No. 8 (2023): Enrichment: Journal of Multidisciplinary Research and Development" : 5 Documents clear
The Difference In Qirâ'ât Al-Qur'an Is Seen From The Rules Of Arabic According To Abduh Al-Rajihi In The Book Al-Lahjât Al-'Arabiyyah Fi Al-Qirâ'ât Al-Qur'âniyyah Ekawati, Ekawati; Ivada, Putra Dian Kharisma
Enrichment: Journal of Multidisciplinary Research and Development Vol. 1 No. 8 (2023): Enrichment: Journal of Multidisciplinary Research and Development
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/enrichment.v1i8.50

Abstract

The aim of this research is to analyze and describe analitically the difference in " qirâ’ât al-Qur’an" from the point of view of Arabic language structure. The writer applies qualitative method. In discussing the problems of this research, she applies library research by using comprehensive and comparative approaches. The result shows that the difference in "qirâ’ât al-Qur’an" analyzed by " qawâ`id" aspects in Arabic language can be classified into "mustawâ sharfî" (morphological aspects), and " mustawâ nahw" (syntactic aspects).
Analysis of Misuse of Eyd in Elementary School Students of SD Negeri Sangiang Jaya Oktavia, Putri; Sa’odah, Sa’odah; Ginanjar, Romi Ramdon
Enrichment: Journal of Multidisciplinary Research and Development Vol. 1 No. 8 (2023): Enrichment: Journal of Multidisciplinary Research and Development
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/enrichment.v1i8.67

Abstract

Education is a process, namely the process of maturing students. This process is carried out by educators consciously and responsibly. Children who have difficulty in one or more of these difficulties usually have low achievement and grades in certain subjects. Research Focus, determining what factors cause students to have difficulty writing EYD, especially the use of capital letters, periods and commas, students' problems in using EYD (capital letters, periods, commas), problem formulation based on the background of the problem So the formulation of the problem in the research is, what difficulties do students have in using EYD, how many mistakes do students make in writing narrative essays in accordance with EYD, research objectives In accordance with the problem formulation that has been determined, the objectives to be achieved in this research namely, describing what factors cause students to have difficulty writing EYD, describing what mistakes students make in using EYD.
Implementation of Random Forest Using Smote and Smoteenn in Customer Churn Classification in E-Commerce Mubarak, Muhammad Munzir Rizkya; Chrisnanto, Yulison Herry; Sabrina, Puspita Nurul
Enrichment: Journal of Multidisciplinary Research and Development Vol. 1 No. 8 (2023): Enrichment: Journal of Multidisciplinary Research and Development
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/enrichment.v1i8.69

Abstract

The rapid development of the internet is one of the driving factors behind the growth of e-commerce. This has led to the emergence of many e-commerce companies, resulting in intense competition among them. Customers have the right to choose the e-commerce platforms that suit their needs and can switch to competing e-commerce platforms, a phenomenon known as customer churn. This issue can be addressed by classifying customer behavior based on existing data. This study utilizes the Random Forest Classifier method, employing the SMOTE and SMOTEENN resampling techniques to handle data imbalance. From the conducted research, the best results were achieved using the SMOTE implementation, with an accuracy of 96.3%, precision of 87.8%, recall of 87.1%, f1-score of 87.4%, and an AUC score of 93%. These results successfully strike a balance between recognizing the positive class (churn) and controlling false positives. On the other hand, the SMOTEENN implementation yields the best recall value and an increase in AUC score, but it comes with a significant decrease in precision, indicating a challenge in controlling false positives.
Consumer segmentation using K-Medians algorithm on transaction data based on LRFMP (length, recency, frequency, monetary, periodecity) Maulana, Akbar Dena; Ningsih, Ade Kania; Abdillah, Gunawan
Enrichment: Journal of Multidisciplinary Research and Development Vol. 1 No. 8 (2023): Enrichment: Journal of Multidisciplinary Research and Development
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/enrichment.v1i8.70

Abstract

Consumer loyalty has a crucial role for companies, especially in conditions of competition between companies. Success in retaining loyal customers is crucial. For this reason, customer loyalty analysis is needed to identify the level of consumer compliance with the company. In this case, consumer segmentation is also an important step to group consumers with similar characteristics to facilitate the management process. One of the analysis methods used is the LRFMP (Length, Recency, Frequency, Monetary, Periodecity) model, which examines consumer purchasing patterns based on various factors such as relationship length, last transaction time span, number of transactions, total money spent, and purchase regularity. The K-Medians grouping method was also used in this study. The data used is the history of purchase transactions in e-commerce for 373 days. From the application of LRFMP analysis and the K-Medians method, 4 clusters were obtained. The number of consumers in cluster 1 is 1183, cluster 2 is 1221, cluster 3 is 1206, and cluster 4 is 1102. The interpretation of the LRFMP model shows that 25.1% of consumers have high loyalty potential, 25.9% of consumers have low loyalty potential, 25.6% of consumers have high loyalty potential, and 23.4% of consumers have medium loyalty potential.
Classification of Sentiment Towards BPJS Services Using the C50 Algorithm Cahyaningrum, Amellia Fahezha; Chrisnanto, Yulison Herry; Ningsih, Ade Kania
Enrichment: Journal of Multidisciplinary Research and Development Vol. 1 No. 8 (2023): Enrichment: Journal of Multidisciplinary Research and Development
Publisher : International Journal Labs

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55324/enrichment.v1i8.71

Abstract

This public health insurance program for all Indonesian people is supervised by the Social Security Administering Body (BPJS) for Health, an Air-Owned Enterprise. Thus, it will be easier for the public to find information about what policies the government has implemented to regulate BPJS. One of them is that people can find information on the social network Twitter. Due to its ease and simplicity of use, the number of tweets can easily grow quickly, which is why Twitter is more popular among Indonesians for communicating. Twitter is widely used as a promotional medium as well as a means of expressing opinions regarding criticism, suggestions, issues, and opinions of a public nature such as the views of netizens on new government policies and so on. One of them is in BPJS services, the large number of BPJS users causes BPJS to provide feedback services to users to find out how many good and bad responses to BPJS services. Sentiment classification is a branch of text mining. Sentiment classification is very basic in the evaluation process of a topic problem. Then the sentiment classification has the main objective of finding out the polarity of positive, and negative sentiment. The c50 algorithm method is one of the methods that can be used in the classification of BPJS service sentiment. In this research, the classification of BPJS service sentiment through Twitter media was carried out using the C50 algorithm method.

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