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All Journal Journal of Soft Computing Exploration Recursive Journal of Informatics
Saputro, Meidika Bagus
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Computer Science & IT

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Journal : Journal of Soft Computing Exploration

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Accuracy of classification poisonous or edible of mushroom using naïve bayes and k-nearest neighbors Hamonangan, Roni; Saputro, Meidika Bagus; Atmaja, Cecep Bagus Surya Dinata Karta
Journal of Soft Computing Exploration Vol. 2 No. 1 (2021): March 2021
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v2i1.26

Abstract

Mushrooms are plants that are widely consumed by the general public, but not all mushrooms can be consumed directly, because the types of mushrooms are feasible and it is still too difficult to distinguish, then there are several ways to identify fungi, namely by means of morphology. The morphology referred to in this paper is the morphology of fungi which includes color, habitat, class, and others. We got the morphology of this mushroom from a datasets we get from UCI Machine Learning with the 23 atribut that we use in the program. In determining the classification of this fungus we use the Naive Bayes algorithm which produces an accuracy of around 90,2% which we then improve again so that it reaches 100% accuracy using the K-Nearest Neighbors algorithm. Furthermore, in this case to prove accuracy that we had before, we use calculation accuracy with confusion matrix to show it the accuracy of classification poisonous or edible mushroom.
Classification of potential customers using C4.5 and k-means algorithms to determine customer service priorities to maintain loyalty Syani, Nur Hazimah; Amirullah, Afif; Saputro, Meidika Bagus; Tamaroh, Ilham Alzahdi
Journal of Soft Computing Exploration Vol. 3 No. 2 (2022): September 2022
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v3i2.89

Abstract

The increasing competition among Middle-Class Micro Enterprises (MSMEs) is a problem because business actors must improve techniques and strategies to maintain customer satisfaction, and the number of customers continues to increase. Customers are an essential asset for the company. To maintain customer loyalty with promising prospects for the company, a strategy is needed to support this. Strategies such as service prioritization can be used to maintain customer loyalty. This research was conducted to classify customers who are estimated to have good prospects for the company so that service priorities are not mistargeted by utilizing 1683 data from store By.SIRR, a fashion store in Semarang, Indonesia contains five attributes, and customers are classified and are estimated to have promising prospects for the company. Data mining methods use the C4.5 and K-Means algorithms to classify the classification process. The research resulted in the grouping of customers into four categories: potential lover, flirting, faithful lover, and spiritual friend. From the validation test conducted using the Confusion Matrix Validation method, the classification results get an Accuracy of 97.70%.
Co-Authors Alamsyah - Amirullah, Afif Atmaja, Cecep Bagus Surya Dinata Karta Hamonangan, Roni Syani, Nur Hazimah Tamaroh, Ilham Alzahdi