Article Per Year (5 Year)
p-Index From 2021 - 2026
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This Author published in this journals
All Journal JURIKOM (Jurnal Riset Komputer) Electronic Integrated Computer Algorithm Journal
Andiharsa Sih Setiarto, Rahardian
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Social Sciences

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Journal : Electronic Integrated Computer Algorithm Journal

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Heart Attack Risk Prediction Using Machine Learning: A Comparative Study of Decision Tree and K-Nearest Neighbors Hizbullah, Fauzi; Noorachmad Muttaqin, Alif; Andiharsa Sih Setiarto, Rahardian; Aulia Hakim, Rizki; Abdulmana, Sahidan
Electronic Integrated Computer Algorithm Journal Vol. 3 No. 1 (2025): VOLUME 3, NO 1: OCTOBER 2025
Publisher : Yayasan Asmin Intelektual Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62123/enigma.v3i1.98

Abstract

Heart disease, particularly heart attacks, is a leading cause of death worldwide, highlighting the importance of early detection and risk prediction. This study develops and evaluates machine learning models to predict heart attack risk using seven health-related attributes: age, marital status, gender, body weight category, cholesterol level, participation in stress management training, and stress level. The dataset, processed with the Orange Data Mining platform, was divided into training (66%) and testing (34%) sets. Two supervised algorithms, Decision Tree and K-Nearest Neighbors (K-NN), were implemented without extensive hyperparameter tuning. Model performance was evaluated using accuracy, precision, recall, and F1 score. The Decision Tree achieved the best results with 84.78% accuracy, 88.52% precision, 79.41% recall, and 83.72% F1 score, indicating its effectiveness in identifying at-risk individuals. Key predictors included age, stress level, and cholesterol, aligning with established medical findings. While the results are promising, limitations include a small dataset and limited algorithm scope. Future research should expand the dataset, include additional clinical features, and explore advanced algorithms to improve accuracy and reduce false negatives, enhancing applicability in preventive healthcare.
The Evaluating Customer Relationship Marketing Strategy on Customer Retention at DMKR Fashion Company Husaini, Galih Rashif; Lubis, Muharman; Andiharsa Sih Setiarto, Rahardian; Fauzan, Ratandi
Electronic Integrated Computer Algorithm Journal Vol. 3 No. 2 (2026): VOLUME 3, NO 2: APRIL 2026
Publisher : Yayasan Asmin Intelektual Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62123/enigma.v3i2.164

Abstract

Building and maintaining strong relationships with customers is essential for business sustainability, especially in an increasingly competitive market where customer loyalty can shift easily. Customer Relationship Management (CRM) has become an important strategic approach that allows companies to manage customer data, strengthen communication, and improve customer experiences. CRM also supports public relations activities by enhancing trust and long-term engagement. During the COVID-19 pandemic, business owners at Dakar, a local MSME in the batik fashion industry, faced significant uncertainty and were required to adapt quickly to changing customer needs and digital consumption patterns. Despite this challenge, the company continued to identify opportunities to strengthen customer loyalty and retention through various CRM-based strategies. This study examines how Dakar implements CRM and evaluates its impact on customer retention using qualitative methods supported by sales and customer behavior data. The results show that CRM contributes to better understanding customer preferences, improving service quality, and encouraging repeat purchases. Furthermore, CRM helps Dakar build emotional bonds with customers through product personalization, social engagement, and the integration of digital platforms. Overall, CRM plays a crucial role in supporting business resilience and customer loyalty in the post-pandemic era.
Co-Authors Abdulmana, Sahidan Ahmad Zainul Fanani Aulia Hakim, Rizki Fauzan, Ratandi Hizbullah, Fauzi Husaini, Galih Rashif Muharman Lubis Noorachmad Muttaqin, Alif