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Journal : JOMLAI: Journal of Machine Learning and Artificial Intelligence

Identification of Rice Plant Diseases Through Leaf Image Using DenseNet 201: Identifikasi Penyakit Tanaman Padi Melalui Citra Daun Menggunakan DenseNet 201 Primatua Sitompul; Harly Okprana; Annas Prasetio
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 2 (2022): June
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (570.449 KB) | DOI: 10.55123/jomlai.v1i2.889

Abstract

Indonesia as an agrarian country with the largest population uses rice as a staple food is depending on rice production. The lack of quantity and quality of production that often occurs is caused by disease attacks on plants that are detected too late. This is due to the lack of agricultural extension workers who help farmers in dealing with plant diseases. This study conducted an experiment on rice plant diseases based on leaf imagery using a dataset that has four classifications of leaf conditions of rice plants, namely healthy, brown spot, hispa, and leaf blast. The results obtained are quite good, namely, the accuracy value of the training data is 88.4% and 82.99% in data testing using the Densely Connected Convolutional Networks (DenseNet)-201 architecture as. From the results of the key research, DenseNet201 is quite suitable to be used to carry out diseases in rice plants so that the types of diseases that attack can be identified and given early. Thus food security can be maintained and not cause losses due to crop failures that harm farmers.
Selection Analysis of Pre-Employment Card Recipients Using the Simple Additive Weighting (SAW) Method Tri Ayu Lestari; Harly Okprana; Rizky Khairunnisa Sormin
JOMLAI: Journal of Machine Learning and Artificial Intelligence Vol. 1 No. 2 (2022): June
Publisher : Yayasan Literasi Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (424.73 KB) | DOI: 10.55123/jomlai.v1i2.964

Abstract

The Pre-Employment Card Program is a work and business capability development program that focuses on job seekers, laborers or workers who have finished their working period, and workers or workers who need to improve their skills, including those who have macro and micro businesses. One of these government programs aims to reduce unemployment due to the economic impact of the Covid-19 virus outbreak. Decision Support System is an effective system used to produce calculations with the output in the form of ranking. And the purpose of this research is to build a decision support system by analyzing the selection of Pre-Recipients of Pre-Employment Cards with the Simple Additive Weighting (SAW) Method. The data source of this study was obtained from the distribution of questionnaires/questionnaires which were distributed randomly to the people of Tempel Village, Kerasaan Rejo Village, Pematang Bandar. This study uses 50 alternatives and 7 criteria.