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Hadi San, Ahmad Syahrul
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Computer Science & IT

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Classification of Heart (Cardiovascular) Disease using the SVM Method Abidin, Minhajul; Munzir, Misbahul; Imantoyo, Adi; Bintang Grendis, Nuraqilla Waidha; Hadi San, Ahmad Syahrul; Mostfa, Ahmed A.; Furizal, Furizal; Sharkawy, Abdel-Nasser
Indonesian Journal of Modern Science and Technology Vol. 1 No. 1 (2025): January
Publisher : CV. Abhinaya Indo Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64021/ijmst.1.1.9-15.2025

Abstract

Cardiovascular disease is one of the leading causes of death worldwide, with a high mortality rate, especially in developing countries like Indonesia. This highlights the importance of developing systems to identify and detect heart disease at an early stage. In this study, the Support Vector Machine (SVM) algorithm was used to classify cardiovascular diseases by utilizing a dataset consisting of 303 patient records obtained from Kaggle. The dataset was divided into 70% for training and 30% for testing. Before optimization using GridSearchCV, the SVM model achieved an accuracy of 79%, precision of 79%, recall of 73%, and F1-score of 76%. However, after adjusting the hyperparameters with GridSearchCV, the model's accuracy slightly decreased to 77%, with precision remaining at 79%, recall dropping to 66%, and F1-score at 72%. Despite this decline in performance after optimization, the results indicate that although SVM has potential for classifying heart disease, its performance is highly influenced by data quality and the selection of appropriate hyperparameters. Even with the performance decrease postoptimization, the model still provides useful predictions, showing consistent results and a proportional class distribution.
Internet of Things-Based Automatic Trash Can Prototype Using Arduino Mega 2560 Sumarno Wijaya; Ahmad Fatoni Dwi Putra; Yuan Sa'adati; Hadi San, Ahmad Syahrul; Yunus, Muhajir; Talirongan, Florence Jean B.; G. Tangaro, Diana May Glaiza; Grancho, Bernadine
Indonesian Journal of Modern Science and Technology Vol. 1 No. 2 (2025): May
Publisher : CV. Abhinaya Indo Group

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64021/ijmst.1.2.43-49.2025

Abstract

The development of Internet of Things (IoT) technology encourages the creation of various smart device innovations that can be applied in everyday life, one of which is an automatic waste management system. This research aims to design and implement an IoT-based automatic trash can prototype using an Arduino Mega 2560 microcontroller that is able to detect the presence of people who will throw away garbage, open and close the lid of the tub automatically, and provide notification if the trash can is full. This research uses an experimental method by combining ultrasonic sensors, servo motors, and LED indicators as the main components. The test results show that the device works well and in accordance with the researcher's expectations. Ultrasonic sensor 1 can detect the presence of objects in front of the trash can and trigger the servo motor to open and close the lid automatically. Ultrasonic sensors 2 and 3 are also able to detect the height of the garbage and activate the servo motor while the indicator LEDs also function as designed: LED 1 blinks when someone approaches to take out the trash, while LED 2 and LED 3 light up when the sensors detect that the trash has reached a certain height limit. In addition, the system is energy efficient as it only activates when an object is detected, making it suitable for households and educational institutions.
Co-Authors Abidin, Minhajul Ahmad Fatoni Dwi Putra Bintang Grendis, Nuraqilla Waidha Furizal, Furizal G. Tangaro, Diana May Glaiza Grancho, Bernadine Imantoyo, Adi Mostfa, Ahmed A. Muhajir Yunus Munzir, Misbahul Sharkawy, Abdel-Nasser Sumarno Wijaya Talirongan, Florence Jean B. Yuan Sa'adati