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All Journal Informasi Interaktif Jurnal Riset Sistem dan Teknologi Informasi
Muhammad Misbahul Munir
Universitas AMIKOM Yogyakarta
Computer Science & IT Decision Sciences, Operations Research & Management

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SISTEM PAKAR DIAGNOSA PENYAKIT TANAMAN BUAH NAGA MENGGUNAKAN TEOREMA BAYES Muhammad Misbahul Munir
Informasi Interaktif Vol 5, No 3 (2020): Jurnal Informasi Interaktif
Publisher : Universitas Janabadra

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Abstract

Dragon fruit is a plant that has a lot of benefits and special appeal in society. Currently dragon fruit plantations in Indonesia are growing very rapidly. Dragon fruit grows and is cultivated in almost all parts of the archipelago, whether it is individual property or company property. This plant contains many properties that make dragon fruit demand high.Expert system itself is artificial intelligence that uses specific knowledge to map problems at the expert level. One application of the expert system is in the field of plantations to diagnose diseases in plants. In this study, the design and manufacture of an expert system used to help diagnose a disease in dragon fruit and determine suggestions or treatment solutions for dragon fruit.The result of this paper is an expert system to diagnose dragon fruit plant diseases along with the probability value of the diagnosed disease which shows the level of system confidence in the disease and suggestions or treatment solutions for the dragon fruit. Keywords : Expert system, Dragon Fruit, diagnostics
Optimisasi Algoritma Genetika dengan Particle Swarm Optimization (PSO) untuk Sistem Rekomendasi Diet Gizi bagi Penderita Diabetes Muhammad Misbahul Munir; Ade Pujianto; Haechal Aulia Muhali Lamuru
Jurnal Riset Sistem dan Teknologi Informasi Vol. 1 No. 2 (2023): Jurnal Riset Sistem dan Teknologi Informasi (RESTIA) Vol. 1 No. 2
Publisher : Universitas Aisyiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30787/restia.v1i2.1289

Abstract

Diabetes, especially diabetic nephropathy, is a global health problem that is increasing in prevalence. This disease can cause various serious complications and even death. Despite the high cure rate associated with diabetes, it is important to improve the human body's immune system to reduce the risk of developing diabetes or diabetic nephropathy. One approach that can help is maintaining a diet with good nutritional coverage. This research aims to develop an artificial intelligence (AI) system that can provide recommendations for a good nutritional diet menu for diabetes sufferers. We propose the use of well-known genetic algorithms in decision making. However, to improve the accuracy and efficiency of the genetic algorithm, we will optimize it using the Particle Swarm Optimization (PSO) algorithm. The research method used is an experimental method, where we will conduct experiments to test the performance of the optimized genetic algorithm. It is hoped that the results of this research can be used as a basis for making scientific publications in accredited national journals as well as product patents for food menu recommendation systems for diabetes sufferers. The main contribution of this research is improving the performance of the genetic algorithm through the use of the PSO algorithm, which will help increase the accuracy of the nutritional diet recommendation system. In this way, it is hoped that the results of this research can provide significant benefits in efforts to prevent and manage diabetes and improve the quality of life of diabetes sufferers.
Co-Authors Ade Pujianto Haechal Aulia Muhali Lamuru