Fuzzy Soft Set for Rock Igneous Clasification

Yanto, Iwan Tri Riyadi; Sutoyo, Edi; Apriani, Ani; Verdiansyah, Okki

doi:10.1109/sain.2018.8673383

Cited by 6 publications

(3 citation statements)

References 13 publications

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“…Opinions play an important role as product feedback, services, and other topics. Various text mining and sentiment analysis using classification approaches [19][20][21][22] such as Naïve Bayes classifier [23][24][25], logistic regression [26,27], support vector machine [28,29], and K-nearest neighbor [30] has been applied for finding the best result and accuracy. Therefore, in this study, sentiment analysis will be conducted to find out public opinion about the discourse of relocation of the capital city from Jakarta to Penajam Paser Utara and Kutai Kartanegara.…”

Section: Introductionmentioning

confidence: 99%

Twitter sentiment analysis of the relocation of Indonesia's capital city

Sutoyo

Almaarif

2020

Bulletin EEI

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Indonesia has a capital city which is one of the many big cities in the world called Jakarta. Jakarta's role in the dynamics that occur in Indonesia is very central because it functions as a political and government center, and is a business and economic center that drives the economy. Recently the discourse of the government to relocate the capital city has invited various reactions from the community. Therefore, in this study, sentiment analysis of the relocation of the capital city was carried out. The analysis was performed by doing a classification to describe the public sentiment sourced from twitter data, the data is classified into 2 classes, namely positive and negative sentiments. The algorithms used in this study include Naïve Bayes classifier, logistic regression, support vector machine, and K-nearest neighbor. The results of the performance evaluation algorithm showed that support vector machine outperformed as compared to 3 algorithms with the results of Accuracy, Precision, Recall, and F-measure are 97.72%, 96.01%, 99.18%, and 97.57%, respectively. Sentiment analysis of the discourse of relocation of the capital city is expected to provide an overview to the government of public opinion from the point of view of data coming from social media.

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Section: Introductionmentioning

confidence: 99%

Twitter sentiment analysis of the relocation of Indonesia's capital city

Sutoyo

Almaarif

2020

Bulletin EEI

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“…Logika fuzzy merupakan cara yang tepat untuk memetakan suatu ruang input kedalam suatu ruang output. Titik awal dari konsep modern mengenai ketidakpastian dapat merujuk pada artikel ilmiah yang dibuat oleh Lofti A. Zadeh (1965) [10]. Logika fuzzy adalah peningkatan dari logika Boolean yang berhadapan dengan konsep kebenaran sebagian.…”

Section: A Logika Fuzzyunclassified

Fuzzy Adaptive Clustering Untuk Mengetahui Pengaruh Faktor Lingkungan Hidup Terhadap Tingkat Keluhan Kesehatan

Apriani

Tresnaning

2022

Journal Technology of Civil, Electrical, Mechanical, Geology, M

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Health is something that is very valuable for a person. Along with the development of life, there are more and more various health complaints. The purpose of this study was to determine the effect of environmental factors on the level of health complaints. The data analysis method uses a classification method, namely clustering using Fuzzy Adaptive Clustering (FAC). In this case, the number of clusters is determined, namely 3 clusters. Environmental factors with the largest average percentage value in cluster 1, namely ownership of garden or land infiltration and waste sorting behavior, and environmental factors with the smallest percentage in cluster 1 are porous infiltration holes, presence of perennials, and the habit of using used water for purposes other. Environmental factors with the largest average percentage in cluster 2, namely the presence of perennials and porous infiltration holes and environmental factors with the smallest percentage in cluster 2 are ownership of motorized vehicles, garden/soil infiltration and waste sorting treatment. While environmental factors with the largest average percentage in cluster 3 are infiltration wells, the habit of using used water for other purposes and ownership of motorized vehicles.

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“…In various fields like financial banking, medicine, manufacturing engineering, customer relationship management, web mining, geochemical and e-learning (Saedudin et al 2018(Saedudin et al , 2017(Saedudin et al , 2016Sutoyo et al 2019Sutoyo et al , 2017Yanto et al 2018aYanto et al , 2018bYanto et al , 2016 can apply data mining concepts and methods. The new emerging technique of data mining is educational data mining that can be applied to the data related to the field of education (Romero & Ventura 2007), including students' performance evaluation.…”

Section: Introductionmentioning

confidence: 99%

A Relative Tolerance Relation of Rough Set in Incomplete Information

Saedudin¹,

Kasim²,

Mahdin³

et al. 2019

JSM

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University is an educational institution that has objectives to increase student retention and also to make sure students graduate on time. Student learning performance can be predicted using data mining techniques e.g. the application of finding essential association rules on student learning base on demographic data by the university in order to achieve these objectives. However, the complete data i.e. the dataset without missing values to generate interesting rules for the detection system, is the key requirement for any mining technique. Furthermore, it is problematic to capture complete information from the nature of student data, due to high computational time to scan the datasets. To overcome these problems, this paper introduces a relative tolerance relation of rough set (RTRS). The novelty of RTRS is that, unlike previous rough set approaches that use tolerance relation, non-symmetric similarity relation, and limited tolerance relation, it is based on limited tolerance relation by taking account into consideration the relatively precision between two objects and therefore this is the first work that uses relatively precision. Moreover, this paper presents the mathematical properties of the RTRS approach and compares the performance and the existing approaches by using real-world student dataset for classifying university's student performance. The results show that the proposed approach outperformed the existing approaches in terms of computational time and accuracy.

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Fuzzy Soft Set for Rock Igneous Clasification

Cited by 6 publications

References 13 publications

Twitter sentiment analysis of the relocation of Indonesia's capital city

Twitter sentiment analysis of the relocation of Indonesia's capital city

Fuzzy Adaptive Clustering Untuk Mengetahui Pengaruh Faktor Lingkungan Hidup Terhadap Tingkat Keluhan Kesehatan

A Relative Tolerance Relation of Rough Set in Incomplete Information

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