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All Journal ComEngApp : Computer Engineering and Applications Journal INTECOMS: Journal of Information Technology and Computer Science JURNAL CEMERLANG: Pengabdian pada Masyarakat Jurnal Teknik Industri Terintegrasi (JUTIN) PKM Linggau: Jurnal Pengabdian dan Pemberdayaan Masyarakat
M. Nejatullah Sidqi
Universitas PGRI Silampari
Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Mechanical Engineering Other

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Journal : ComEngApp : Computer Engineering and Applications Journal

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Optimization of Deep Neural Networks with Particle Swarm Optimization Algorithm for Liver Disease Classification Muhammad Nejatullah Sidqi; Dian Palupi Rini; Samsuryadi Samsuryadi
Computer Engineering and Applications Journal Vol 12 No 1 (2023)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/comengapp.v12i1.432

Abstract

Liver disease has affected more than one million new patients in the world. which is where the liver organ has an important role function for the body's metabolism in channeling several vital functions. Liver disease has symptoms including jaundice, abdominal pain, fatigue, nausea, vomiting, back pain, abdominal swelling, weight loss, enlarged spleen and gallbladder and has abnormalities that are very difficult to detect because the liver works as usual even though some liver functions have been damaged. Diagnosis of liver disease through Deep Neural Network classification, optimizing the weight value of neural networks with the Particle Swarm Optimization algorithm. The results of optimizing the PSO weight value get the best accuracy of 92.97% of the Hepatitis dataset, 79.21%, Hepatitis 91.89%, and Hepatocellular 92.97% which is greater than just using a Deep Neural Network.
Optimization of Deep Neural Networks with Particle Swarm Optimization Algorithm for Liver Disease Classification Sidqi, Muhammad Nejatullah; Rini, Dian Palupi; Samsuryadi
Computer Engineering and Applications Journal (ComEngApp) Vol. 12 No. 1 (2023)
Publisher : Universitas Sriwijaya

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

Abstract

Liver disease has affected more than one million new patients in the world. which is where the liver organ has an important role function for the body's metabolism in channeling several vital functions. Liver disease has symptoms including jaundice, abdominal pain, fatigue, nausea, vomiting, back pain, abdominal swelling, weight loss, enlarged spleen and gallbladder and has abnormalities that are very difficult to detect because the liver works as usual even though some liver functions have been damaged. Diagnosis of liver disease through Deep Neural Network classification, optimizing the weight value of neural networks with the Particle Swarm Optimization algorithm. The results of optimizing the PSO weight value get the best accuracy of 92.97% of the Hepatitis dataset, 79.21%, Hepatitis 91.89%, and Hepatocellular 92.97% which is greater than just using a Deep Neural Network.
Co-Authors Ahmad Marsehan Aprilisa, Shinta AULIA, RIZKA Dian Palupi Rini Dian Palupi Rini Felani, Rani Okta Ira Primalasari M Rusni Eka Putra Muhamad Fadli Rani Okta Felani Rio Rio, Rio Samsuryadi Samsuryadi Samsuryadi Syabawaihi Vera Octalia Widya Analisa