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All Journal International Journal of Ethno-Sciences and Education Research Jurnal Dimamu Jurnal AbdiMU INTERNAL (Information System Journal)
Aryanti, Utami
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Religion Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Economics, Econometrics & Finance Education Languange, Linguistic, Communication & Media Mathematics Transportation Other

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Journal : INTERNAL (Information System Journal)

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Penerapan Data Mining untuk Menganalisis Kepuasan Nasabah BPRS Al-Ma’soem Menggunakan Algoritma C4.5 Dewi, Sofia; Salsabila, Jihan Salma; Aryanti, Utami
INTERNAL (Information System Journal) Vol. 8 No. 1 (2025)
Publisher : Masoem University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32627/internal.v8i1.1388

Abstract

Customer satisfaction levels with the services provided by BPRS Al Ma’soem Bandung using the C4.5 Customer satisfaction is an important factor in influencing the running of a bank. To understand the indicators that influence customer satisfaction, it is necessary to evaluate the level of customer satisfaction with a service. This article explains the use of the classification method with the C4.5 algorithm at BPRS Al Ma'soem Bandung. Data were obtained from 406 respondents through a questionnaire covering variables such as service, facilities, ease of access, products, and trust. The results of the analysis show that the attributes of trust and suitability have the greatest influence on customer satisfaction. The resulting model has an accuracy level of 96.31%, indicating the effectiveness of the C4.5 algorithm in analyzing data. This study provides recommendations to BPRS Al Ma'soem to improve service quality, adjust facilities, and products to customer needs to maintain competitiveness in the Islamic banking sector.
Penerapan Data Mining Algoritma Apriori untuk Menemukan Pola Hubungan Status Gizi Balita Nurmalasari, Evi; Aryanti, Utami; Rachman, Tonton Taufik
INTERNAL (Information System Journal) Vol. 6 No. 2 (2023)
Publisher : Masoem University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32627/internal.v6i2.885

Abstract

Malnutrition of toddlers can cause severely health problems, growth retardation, and decreased intelligence. Therefore, it is important to know the pattern of the relationship between the nutritional status of toddlers, especially against the condition of malnutrition to get information about the possible risk of nutritional coexistence problems. The purpose of this research is to apply data mining using the apriori algorithm in finding patterns of relationships betweennutritional status and to produce an accuracy level of association rules based on the value of support, confidence, and validation with the lift ratio. The results of this study are expected to generate information that can help prevent and treat malnutrition, as well as appropriate nutrition interventions. Analysis and implementation of data using the a priori algorithm method. Manual calculations are carried out using Microsoft Excell and accurate calculations with python programming. Data on the nutritional status of children under five, especially undernourished conditions will be processed to find patterns of association relationships. Determined the minimum support value of 0.1 or 10% and the minimum confidence of 0.5 or 50%. The research produces association rules in the form of association relationship patterns of nutritional status specifically malnutrition conditions (Underweight?Stunting ) with a support of 0.25 or 25% and confidence 0.57 or 57%. The rules have met the minimum support and minimum confidence values and have been validated by the lift ratio with a value > 1.
Co-Authors Anwar, M. Taufan Anwar Anwar, Moch. Taufan Anwar, Moh. Taufan Atmoko, Dwi Dewi, Sofia Lusiana, Novita Naasyiah, Rifdah Nurmalasari, Evi Rachman, Tonton Taufik Ramdhani, M. Rizki Ramdhani Rifasya, Pramadika Salsabila, Jihan Salma Tina Rahmawati