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All Journal International Journal of Health, Engineering and Technology Multidisiplin Pengabdian Kepada Masyarakat (M-PKM) Sevaka: Hasil Kegiatan Layanan Masyarakat
Quratih Adawiyah
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Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Dentistry Economics, Econometrics & Finance Education Engineering Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Mechanical Engineering Medicine & Pharmacology Nursing Public Health Veterinary

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Classification of Heart Disease Risk Factors Using Decision Tree at Rantauprapat Regional Hospital Quratih Adawiyah; Riyan Agus Faisal; Nailatun Nadrah; Juni Purwanto; Baginda Restu Al Ghazali
International Journal of Health Engineering and Technology Vol. 3 No. 4 (2024): IJHESS NOVEMBER 2024
Publisher : CV. AFDIFAL MAJU BERKAH

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55227/ijhet.v3i4.273

Abstract

Heart disease is one of the leading causes of death in Indonesia, so it is important to identify risk factors that contribute to the increasing incidence of heart disease. This study aims to classify risk factors for heart disease using the Decision Tree method with the CART (Classification and Regression Tree) algorithm at Rantauprapat Regional Hospital. The data used includes factors such as Age, High Blood Pressure, High Cholesterol Levels, Body Mass Index (BMI), Family History, Smoking, Unhealthy Diet, and Low Physical Activity. The results of the analysis show that the factors Age, High Blood Pressure, and High Cholesterol Levels have a significant effect on the increased risk of heart disease, with a model accuracy of 80%. Although this model successfully classifies high risk well, there are some errors in identifying low risk, as reflected in the Recall value (0.67).
Penyuluhan Penerapan Metode Naive Bayes Untuk Kalsifikasi Data Pasien Tipus Di RSUD Rantauprapat Intan Nur Fitriyani; Quratih Adawiyah; Rika Handayani; Fitriyani Nasution; Dinda Salsabila Ritonga
Sevaka : Hasil Kegiatan Layanan Masyarakat Vol. 2 No. 4 (2024): November: Sevaka : Hasil Kegiatan Layanan Masyarakat
Publisher : STIKES Columbia Asia Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62027/sevaka.v2i4.524

Abstract

Typhoid fever is an infectious disease caused by the bacterium Salmonella typhi, commonly found in developing countries, including Indonesia. Prompt and accurate treatment is crucial to prevent serious complications in patients. One way to assist in diagnosing typhoid fever is by applying machine learning methods to classify patient data. The Naive Bayes method is one of the machine learning algorithms frequently used in medical data classification due to its strong ability to handle large and complex datasets. This article discusses the application of the Naive Bayes method for classifying typhoid patient data at Rantauprapat General Hospital (RSUD Rantauprapat). By utilizing medical data that includes clinical symptoms, laboratory test results, and patients’ medical histories, the Naive Bayes model can provide fairly accurate predictions regarding the likelihood of a person having typhoid fever. The research findings indicate that Naive Bayes is reliable in predicting typhoid diagnoses with adequate accuracy, thereby supporting healthcare professionals in making faster and more precise decisions. It is expected that the implementation of this method can accelerate the diagnostic process and improve the quality of healthcare services at RSUD Rantauprapat, as well as in other regions.
SOSIALISASI PEMANFAATAN CHATGPT BERBASIS MACHINE LEARNING DALAM MENINGKATKAN PEMASARAN PRODUK UMKM Quratih Adawiyah; Nuraisyah Daulay; Dimas Sudarwanto
Multidisiplin Pengabdian Kepada Masyarakat Vol. 4 No. 03 (2025): Multidisiplin Pengabdian Kepada Masyarakat, 2025
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Pemanfaatan teknologi kecerdasan buatan (Artificial Intelligence) dalam pemasaran digital menjadi peluang strategis bagi pelaku Usaha Mikro, Kecil, dan Menengah (UMKM) di era transformasi digital. Salah satu teknologi yang berkembang pesat adalah ChatGPT berbasis machine learning yang mampu membantu pembuatan konten pemasaran, meningkatkan interaksi pelanggan, serta mendukung personalisasi strategi promosi secara efisien. Namun, keterbatasan literasi digital dan keterampilan teknologi masih menjadi kendala utama UMKM dalam mengoptimalkan pemanfaatan teknologi tersebut. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk mensosialisasikan serta melatih pemanfaatan ChatGPT dalam meningkatkan strategi pemasaran produk UMKM di DHIMAS GRAFIKA. Metode yang digunakan meliputi sosialisasi, demonstrasi, praktik langsung, serta evaluasi melalui observasi, wawancara, dan kuesioner terhadap 10 peserta yang terlibat dalam aktivitas pemasaran. Hasil kegiatan menunjukkan adanya peningkatan pemahaman peserta terhadap pemasaran digital, peningkatan keterampilan teknis dalam pembuatan konten menggunakan ChatGPT, serta perubahan strategi pemasaran yang lebih terstruktur dan berbasis digital. Peserta juga menunjukkan kesiapan dan motivasi tinggi untuk mengimplementasikan teknologi ini dalam pekerjaan sehari-hari. Pemanfaatan ChatGPT terbukti membantu UMKM dalam meningkatkan efisiensi produksi konten, memperbaiki respons terhadap pelanggan, serta memperluas jangkauan pasar dengan biaya yang lebih rendah. Kegiatan ini menunjukkan bahwa pelatihan berbasis teknologi AI dapat menjadi solusi efektif dalam mendorong transformasi digital UMKM.
Co-Authors Baginda Restu Al Ghazali Dimas Sudarwanto Dinda Salsabila Ritonga Fitriyani Nasution Intan nur Fitriyani Juni Purwanto Nailatun Nadrah Nuraisyah Daulay Rika Handayani Riyan Agus Faisal