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All Journal Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) JTIULM (Jurnal Teknologi Informasi Universitas Lambung Mangkurat)
Rama Aria Megantara
Universitas Dian Nuswantoro
Computer Science & IT Electrical & Electronics Engineering Engineering

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DIABETES MELLITUS ATTRIBUTE CLASSIFICATION USING THE NAIVE BAYES ALGORITHM BASED ON FORWARD SELECTION Dwi Puji Prabowo; Rama Aria Megantara; Ricardus Anggi Pramunendar; Yuslena Sari
Jurnal Teknologi Informasi Universitas Lambung Mangkurat (JTIULM) Vol. 7 No. 2 (2022)
Publisher : Fakultas Teknik Universitas Lambung Mangkurat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/jtiulm.v7i2.146

Abstract

Diabetes Mellitus is a chronic condition that frequently results in death. Almost every nation has experienced and contributed to this rise in mortality. Consequently, several researchers are motivated to determine this disease's source and prevent the increase in mortality rates. The research was conducted in the field of informatics in partnership with health professionals to determine the causes of this condition. Many informatics researchers employ machine learning techniques to aid in analyzing existing data. This study suggests feature selection based on forward selection and the naive Bayes classification approach to determine this disease's primary aetiology. The results demonstrate that our proposed strategy can increase the classification accuracy of patients. The performance outcomes improved by 169%. According to this theory, it is also known that the primary cause of this disease is its dependence on body mass index and age. Therefore, additional research must explore these two variables' impact on various other disorders.
Implementation of a Supply chain Management System Blockchain-Based in Red Onion Farming Mira Nabila; Farrikh Alzami; Rama Aria Megantara; Fikri Firdaus Tananto; Hasan Aminda Syafrudin; L. Budi Handoko; Chaerul Umam
Jurnal Ilmiah Merpati (Menara Penelitian Akademika Teknologi Informasi) Vol 11 No 1 (2023): Vol. 11, No. 1, April 2023
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Udayana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24843/JIM.2023.v11.i01.p02

Abstract

Red Onions are a horticultural commodity belonging to the spice vegetable group and an important role for economy of the Indonesian people. In red onion farming there have a problem of price fluctuations which result in an uneven and less transparent distribution of red onions yields, thus affecting both consumers and producers. To answer these problems, we designed a system to maintain and store red onion harvest data for farmers, collectors, distributors, and retailers in the form of a blockchain-based supply chain system. This system can maintain the validity of transactions in the supply chain of red onion farming with a private blockchain with Hyperledger Fabric. Then the data on the blockchain system will be displayed through the Hyperledger Explorer website. This system already passed the Black Box Testing system. From the research and testing of the system that has been made, this system can help the red onion farming to maintain the validity of transactions in the supply chain management.
Co-Authors Alzami, Farrikh Chaerul Umam Dwi Puji Prabowo, Dwi Puji Fikri Firdaus Tananto Hasan Aminda Syafrudin L. Budi Handoko Mira Nabila Ricardus Anggi Pramunendar Yuslena Sari, Yuslena