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All Journal Jurnal Sistem Komputer & Kecerdasan Buatan International Journal of Biology Education Towards Sustainable Development
Prabowo, Abram Setyo
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Social Sciences

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Analisis Perbandingan Kinerja Algoritma Klasifikasi dalam Mendeteksi Penyakit Jantung Prabowo, Abram Setyo; Kurniadi, Felix Indra
Jurnal SISKOM-KB (Sistem Komputer dan Kecerdasan Buatan) Vol. 7 No. 1 (2023): Volume VII - Nomor 1 - September 2023
Publisher : Teknik Informatika, Sistem Informasi dan Teknik Elektro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47970/siskom-kb.v7i1.468

Abstract

Abstract— Deteksi penyakit jantung secara dini dan akurat memiliki dampak signifikan terhadap prognosis pasien serta mengurangi beban penyakit secara keseluruhan. Dalam upaya meningkatkan efektivitas deteksi penyakit jantung, teknik pembelajaran mesin dan algoritma klasifikasi telah muncul sebagai alat yang berpotensi ampuh dalam mendiagnosis kondisi ini dengan tingkat akurasi yang tinggi. Penelitian ini bertujuan untuk memprediksi penyakit jantung dengan menggunakan perbandingan Support Vector Machine (SVM), Random Forest, Logistic Regression, dan AdaBoost. Pada penelitian ini algoritma Random Forest mempunyai model base score untuk training test dengan nilai 1, nilai tersebut merupakan nilai terbaik dibandingkan dengan 3 algoritma yang diusulkan pada penelitian ini. Selama pengujian, hasil yang diperoleh adalah algoritma random forest, SVM, dan AdaBoost merupakan algoritma yang mempunyai nilai terbaik dan nilai yang sama pada hasil pengujian. Untuk nilai akurasi 0.985366, presisi 0.985714, recall 0.985437, dan f1-score 0.985364.. Keywords — Heart Disease, Machine Learning, SVM, AdaBoost, Random Forest, Linear Regression
The Perceptions of the Pre-service and In-service Biology Teachers on Artificial Intelligence in Biology Learning Kurniawan, Aditya; Hariyadi, Slamet; Prabowo, Abram Setyo; Savira, Nadyatul Ilma Indah
International Journal of Biology Education Towards Sustainable Development Vol 4, No 1 (2024)
Publisher : Gemilang Maju Publikasi Ilmiah (GMPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53889/ijbetsd.v4i1.432

Abstract

This study aimed to determine the perceptions of pre-service biology teachers and in-service biology teachers on artificial intelligence in Biology learning. AI has recently become a new trend and has changed many aspects of life. Artificial intelligence allows machines to learn from experience, adapt to new inputs, and perform human-like tasks like ChatGPT, launched in Q4 of 2022. The survey method used in this study. We used a questionnaire from 42 respondents of in-service teachers and pre-service teachers, respectively. Selected teachers were senior high school biology teachers who have used the independent curriculum in their schools. This study showed that the pre-service biology teachers (69%) had higher perceptions than in-service biology teachers (40.5%). This result followed by AI usage; 28.6% of pre-service biology teachers and 7.1% of in-service biology teachers used AI daily. However, the pre-service and in-service biology teachers believed that AI could be implemented in the new curriculum to increase student achievement on biology subject. This study concluded that the perceptions of to use AI is still low. So, AI must be introduced to the pre-service and in-service biology teachers.
Co-Authors Aditya Kurniawan Kurniadi, Felix Indra Nadyatul Ilma Indah Savira Slamet Hariyadi