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All Journal International Journal of Integrative Sciences AMMA : Jurnal Pengabdian Masyarakat JRIIN :Jurnal Riset Informatika dan Inovasi
Ashari, Idpan
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Humanities Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing Social Sciences

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Klasifikasi Penyakit Liver Menggunakan Algoritma Decision Tree Dan Random Forest Stiady Syah, Farhan; Salsabila Putri, Firda; Ashari, Idpan; Sofian, Kurnain; Rosyani, Perani
Jurnal Riset Informatika dan Inovasi Vol 2 No 8 (2025): JRIIN: Jurnal Riset Informatika dan Inovasi
Publisher : shofanah Media Berkah

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Abstract

Penyakit liver merupakan salah satu masalah kesehatan yang sering kali memerlukan deteksi dini agar penanganan dapat dilakukan secara optimal. Machine learning berperan penting dalam klasifikasi penyakit ini melalui pemanfaatan algoritma seperti Decision Tree dan Random Forest, yang mampu mengolah data medis dan memberikan hasil klasifikasi yang akurat. Tujuan dari penelitian ini adalah untuk mengevaluasi kinerja kedua algoritma tersebut dalam klasifikasi penyakit liver dan menentukan algoritma yang lebih efektif. Dengan menggunakan studi literatur, penelitian ini memberikan pemahaman komparatif mengenai efektivitas Decision Tree dan Random Forest dalam mendeteksi penyakit liver, diharapkan dapat memberikan solusi yang lebih baik bagi sistem deteksi penyakit liver berbasis machine learning.
Pengembangan Sistem Pakar Untuk Diagnosa Penyakit Pernafasan Pada Hewan Dengan Metode: Bayesian Network Dan Rule-Based System Stiady Syah, Farhan; Salsabila Putri, Firda; Ashari, Idpan; Sofian, Kurnain; Rosyani, Perani
Jurnal Riset Informatika dan Inovasi Vol 2 No 9 (2025): JRIIN: Jurnal Riset Informatika dan Inovasi
Publisher : shofanah Media Berkah

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Abstract

Masalah kesehatan pada hewan, terutama penyakit pernapasan, merupakan salah satu tantangan yang memerlukan diagnosa yang cepat dan akurat untuk mencegah penyebaran dan meningkatkan kualitas kesehatan hewan. Penelitian ini bertujuan mengembangkan sistem pakar berbasis metode Bayesian Network dan Rule-Based System untuk mendukung diagnosa penyakit pernapasan pada hewan secara otomatis. Metode Bayesian Network digunakan untuk memodelkan ketidakpastian dalam proses diagnosa, sedangkan Rule-Based System diterapkan untuk menangani aturan-aturan medis yang telah ada. Hasil yang diharapkan dari penelitian ini adalah sistem pakar yang mampu mendiagnosa penyakit pernapasan dengan akurat, serta memberikan rekomendasi penanganan yang efektif.
Sosialisasi Teknologi Keamanan Digital: Strategi Menghindari Ancaman Siber bagi Pelajar Di SMPN 2 Tangerang Selatan Sri Rahayu, Eka; Masayu Lintang, Ananda; Rayhan Sanjaya, Bayu; Stiady Syah, Farhan; Ashari, Idpan; Sofian, Kurnain; Arfiola Suci, Meta; Abdul Sahid, Rahmat; Dwi Irawan, Ryan; Aziz, Tanzilal; Salsabila Putri, Firda
AMMA : Jurnal Pengabdian Masyarakat Vol. 3 No. 11 : Desember (2024): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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An This community service activity in the field of digital security technology aims to raise awareness and understanding among middle school students about the importance of protecting themselves from cyber threats. In an increasingly digital world, cyberattacks have become a real threat that can damage personal data, steal important information, or even cause financial losses. Unfortunately, many students lack sufficient knowledge about preventive measures against cyberattacks, making them more vulnerable to such risks. Therefore, this activity aims to provide an understanding of how to avoid cyberattacks through socialization, training, and simulations that can be applied in daily life. The steps taught include using strong passwords, managing privacy settings on social media, being cautious of suspicious emails and links, as well as the importance of security tools like antivirus software and firewalls. It is expected that through this activity, middle school students will be able to reduce the risk of falling victim to cyberattacks and become more cautious in using digital technology. The expected outcome of this community service activity is to enhance students' knowledge and skills in safeguarding personal data, as well as positively impacting safer digital behaviors.
Development of an Expert System for Diagnosing Respiratory Diseases in Animals Using the Bayesian Network and Rule-Based System Methods Farhan Stiady Syah; Rosyani, Perani; Suryaningrat; Putri, Firda Salsabila; Ashari, Idpan; Sofian, Kurnain
International Journal of Integrative Sciences Vol. 4 No. 1 (2025): January 2025
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ijis.v4i1.13481

Abstract

Respiratory diseases in animals are a common health issue affecting both livestock and pets. These conditions can lead to significant economic losses in the livestock sector and reduce the quality of life for pets if left untreated. Early and accurate diagnosis is crucial to identify diseases promptly, prevent further spread, and minimize negative impacts on animals and their owners. Therefore, a system capable of providing fast, accurate, and data-driven diagnoses is essential. This study aims to develop an expert system specifically designed to diagnose respiratory diseases in animals using two main approaches: Bayesian Network and Rule-Based System. The Bayesian Network models uncertainties by analyzing probabilistic relationships between observed symptoms and potential diseases, while the Rule-Based System supports decision-making based on predefined rules. The combination of these methods is expected to yield more accurate and informative diagnostic results. Symptom data for this study were obtained from various sources, including relevant medical literature and animal health databases. The system was developed using Python programming language, leveraging libraries such as pgmpy for constructing Bayesian Network models and experta for implementing the Rule-Based System. The development and testing processes were conducted on the Google Colab platform, enabling efficient data processing, simulation, and visualization. The expert system was evaluated using simulated symptom data, with performance parameters including diagnosis probability and overall accuracy. The results indicate that the expert system effectively provides diagnoses based on user-input symptoms. The probability information included in the diagnostic results aids veterinarians and livestock owners in making more precise, data-driven medical decisions
Liver Disease Classification Using Decision Tree and Random Forest Algorithms Cahyono, Yoyo; Rosyani, Perani; Syah, Farhan Stiady; Putri, Firda Salsabila; Ashari, Idpan; Sofian, Kurnain
International Journal of Integrative Sciences Vol. 4 No. 1 (2025): January 2025
Publisher : PT FORMOSA CENDEKIA GLOBAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55927/ijis.v4i1.13509

Abstract

Diagnosing diseases using technology is no longer uncommon. With advancements in healthcare technology, decision-making, particularly in detecting liver diseases, has become more efficient. Liver, an essential human organ, sees its functionality decline in patients with liver diseases. According to WHO data (2013), 28 million individuals in Indonesia suffer from liver diseases, marking it as one of the ten deadliest diseases. Early detection is crucial for effective treatment. This study aims to predict liver diseases using the Random Forest algorithm. Feature selection and classifier choice are pivotal for improving accuracy and computational efficiency. Using the Liver Disease Patient Dataset, the study involved data analysis, preprocessing, algorithm modeling, and visualization. Results show the Random Forest algorithm achieved an accuracy of 0.713326 with an F1 score of 81%
Co-Authors Abdul Sahid, Rahmat Arfiola Suci, Meta Aziz, Tanzilal Cahyono, Yoyo Dwi Irawan, Ryan Farhan Stiady Syah Masayu Lintang, Ananda Perani Rosyani Putri, Firda Salsabila Rayhan Sanjaya, Bayu Salsabila Putri, Firda Sofian, Kurnain Sri Rahayu, Eka Stiady Syah, Farhan Suryaningrat Syah, Farhan Stiady