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All Journal Jurnal Pilar Nusa Mandiri PROJECT (Professional Journal of English Education)
Roviani, Roviani
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Computer Science & IT Languange, Linguistic, Communication & Media

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PREDICTION OF COOPERATIVE LOAN FEASIBILITY USING THE K-NEAREST NEIGHBOR ALGORITHM Roviani, Roviani; Supriadi, Deddy; Iskandar, Iqbal Dzulfiqar
Jurnal Pilar Nusa Mandiri Vol 17 No 1 (2021): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v17i1.2183

Abstract

Approval of credit lending to cooperative members without proper feasibility analysis can cause credit problems, cooperatives such as late payment of installments, and an increase in bad credit which can threaten the survival of the cooperative as a provider of lending services. As a solution to minimize the creditworthiness assessment errors for loan funds, research is carried out to analyze the feasibility of loan funds from the data of cooperative members using the data mining method approach and the algorithm used using the K-Nearest Neighbor. The purpose of this research is to predict the feasibility of granting credit with the right decision and to find out the level of evaluation, accuracy, and validation of the effectiveness of the k-NN algorithm on processing creditworthiness application data classifications. After the prediction research was carried out, the data on the eligibility of credit lending applications were conducted at the Bakti Berkah Sukaraja Savings and Loan Cooperative, The data obtained from the accuracy value of the k-nearest neighbor algorithm before being validated has an accuracy of 87.78% with AUC 0.95, after validation with split validation the accuracy decreased slightly by 2% to be 85.71%, while the AUC value in the ROC Curve was 0.836%. Even though there was a decline, it can still be categorized as a good classification. The impact of this research is that besides the accuracy of the k-NN algorithm being validated, the Bakti Berkah Sukaraja Savings and Loan cooperative can predict the feasibility of applying for credit funds, as an effort to reduce the threat of bad credit risk
Exploring Wordwall.Net Implementation in Vocabulary Learning at Junior High School Roviani, Roviani; Mobit, Mobit; Srisudarso, Mansyur
PROJECT (Professional Journal of English Education) Vol. 8 No. 1 (2025): VOLUME 8 NUMBER 1, JANUARY 2025
Publisher : IKIP Siliwangi

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Abstract

This study explores the implementation of Wordwall.net in vocabulary learning for junior high school students. Vocabulary is fundamental in language acquisition, but traditional methods often fail to engage students, leading to poor outcomes. This research employs a qualitative case study approach to examine how Wordwall.net enhances vocabulary learning by making the process more interactive and enjoyable. Conducted in a junior high school in Karawang, the study involved four grade VIII students and used interviews, observations, and document analysis as data collection methods. The findings reveal that Wordwall.net significantly improves student engagement and vocabulary retention. Teachers played a crucial role in selecting appropriate activities, preparing lessons, and addressing challenges post-learning. Students responded positively to the platform, citing increased interaction, ease of use, and a more enjoyable learning experience. Despite its advantages, challenges remain, including the need for appropriate selection criteria and effective post-learning reinforcement. The study concludes that Wordwall.net is an effective tool in enhancing vocabulary learning, fostering a more dynamic and interactive classroom environment. Additionally, it highlights the importance of ongoing teacher support and training to maximize the platform's potential and address any limitations that may arise during its use, particularly in different educational contexts.
Co-Authors Deddy Supriadi Iskandar, Iqbal Dzulfiqar Mansyur Srisudarso Mobit, Mobit