Fuzzy functional dependencies and linguistic interpretations employed in knowledge discovery tasks from relational databases

Vučetić, Miljan; Hudec, Miroslav; Božilović, Boško

doi:10.1016/j.engappai.2019.103395

Cited by 15 publications

(10 citation statements)

References 48 publications

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“…Systems using rule-based classification achieve explainable and therefore easy interpretable results [7] [16]. Rule-based systems are interpretable, but there is a problem with constructing consistent rule-based systems and when required application in different areas for the same task.…”

Section: Classification Methodsmentioning

confidence: 99%

Criteria for Fuzzy Rule-Based Systems and Its Applicability on Examples

Mináriková

2022

EDAMBA 2021 : COVID-19 Recovery: The Need for Speed : Conference Proceedings

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Classification allows us to handle the large amount of data that is available nowadays. In our work, we use the classification features to divide employees into the several classes and examine the differences between the classical and flexible classification. We also emphasize the advantages of classical classification as well as the disadvantages, and how we can solve them by fuzzy logic. Fuzzy rule-based systems are explainable and therefore interpretable because the rules are defined by linguistic variables. Design of a more complex system is a tedious task. To resolve this, we examine interpretability criteria for fuzzy rule-based systems. We examine this topic on the examples with two classification attributes because it is easily illustrated graphically. To use more attributes is mathematically possible, but it is harder to visualize for users in a three and more dimensional spaces. In our work, we propose how to create an explainable design for classification and propose possibilities how to expand it.

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Section: Classification Methodsmentioning

confidence: 99%

Criteria for Fuzzy Rule-Based Systems and Its Applicability on Examples

Mináriková

2022

EDAMBA 2021 : COVID-19 Recovery: The Need for Speed : Conference Proceedings

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“…Data Mining bertujuan untuk menemukan informasi yang berguna pada database untuk lebih memahami masa lalu, atau bahkan memprediksi masa depan [10]. Data Mining merupakan disiplin penting yang dapat memberikan keuntungan signifikan di bidang penemuan pengetahuan dan analitik bisnis untuk institusi modern [11].…”

Section: Pendahuluanunclassified

Akurasi dalam Analisis Kompetensi Calon Tenaga Keperawatan Menggunakan Algoritma Apriori

Habib-ur-Rahman¹

2022

INFEB

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Setiap lulusan S1 keperawatan (NERS) harus dinyatakan kompeten pada Uji Kompetensi Ners Indonesia (UKNI) yang diadakan Kemdikbud untuk mendapatkan Surat Tanda Registrasi (STR) sebagai syarat bekerja. Tingkat kelulusan mahasiswa keperawatan dalam mengikuti UKNI sangat rendah jika dibandingkan dengan beberapa negara lain. Penelitian ini bertujuan mengidentifikasi faktor-faktor yang perlu dioptimalkan calon tenaga keperawatan dalam persiapan menghadapi UKNI dengan teknologi data mining. Data yang diolah dalam penelitian ini bersumber dari Appskep Indonesia, suatu startup yang bergerak di bidang pendidikan kesehatan, diantaranya try out dan bimbingan belajar UKNI. Appskep memiliki data kelulusan UKNI lebih dari 2000 pesertanya yang tersebar di seluruh Indonesia pada tahun 2021 dan 2022. Data tersebut dianalisis menggunakan Algoritma Apriori untuk menemukan rule-rule asosiasi yang terkait dengan kelulusan calon tenaga perawat dalam UKNI. Hasil dari pengolahan data peserta UKNI ini adalah ditemukannya beberapa set rule asosiasi yang mempengaruhi kompeten atau tidaknya calon tenaga perawat dalam UKNI. Rule asosiasi yang paling dominan adalah jika penguasaan materi keperawatan jiwa lebih dari 60 persen maka seorang perawat akan lulus pada UKNI, dengan support 55% dan confidence 100%.

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“…A relational database is a tabular database in which the data sets are defined so that they can access one another (Vucetic et al , 2020). The entity data for maintenance projects include many attributes, such as cost and contractor; logical connections established between the tables for these attributes allow the generation of specific relational data to analyse usage.…”

Section: E-complaint System Developmentmentioning

confidence: 99%

Exploring e-complaint method: learning from the Malaysian Polytechnic institutions

Ismail

2021

JFM

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Purpose The conventional e-complaint method provides a platform that contains multiple data sources of an infrastructure project, including building facilities, associated asset documentation of the asset. However, the conventional e-complaint method practised by the Development and Facilities Management Unit (UPPF) faces issues due to management deficiencies and negligent staff to handle operations and maintenance processes within facilities management at Malaysian Polytechnic. This paper aims to identify the different maintenance management system (MMS) approaches using information and communication technology that is equipped with decision-making processes. Design/methodology/approach This research presents eight cases of the use of e-complaint in major facilities management platforms in Malaysian Polytechnic, identifying the major problems using the conventional e-complaint method, the current technologies realised, as well as the procedures for learning and improving e-complaint to the Polytechnic institution. The major conclusion drawn from the interview results was that there is a lack of comprehensive MMSs that integrate operations and maintenance processes within facilities management and software programming to provide guidelines for decision-making processes. Findings The findings demonstrate that the conventional e-complaint method cannot be used effectively to support the defect diagnosis process during maintenance assessment and development. The case studies further demonstrated that the conventional e-complaint method will be particularly led to inadequate strategic decision-making to analyse information to improve the maintenance project outcomes for Malaysian Polytechnic’s buildings, thereby, ignoring the accuracy and reliability of information for operations and maintenance. New MMS tools are suggested from the findings and lessons learned as a good practice to reduce defect repetition on the design specifications used and construction methods practised. Originality/value Due to the increasingly complex nature of projects in terms of size and information technology, realising these current technologies would require a learning process for all stakeholders involved in financial and managing assets. This research proposes stepped change and learning opportunity for maintenance value maximisation and delivery, management and operation efficiency using MMS. The new MMS can potentially transform operational and maintenance processes within facilities management into one of the most sophisticated technologies by accommodating data recordings, such as complaints and specific items needed for maintenance through the internet and intranet to facilitate improved execution of Polytechnic’s building activities.

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Fuzzy functional dependencies and linguistic interpretations employed in knowledge discovery tasks from relational databases

Cited by 15 publications

References 48 publications

Criteria for Fuzzy Rule-Based Systems and Its Applicability on Examples

Criteria for Fuzzy Rule-Based Systems and Its Applicability on Examples

Akurasi dalam Analisis Kompetensi Calon Tenaga Keperawatan Menggunakan Algoritma Apriori

Exploring e-complaint method: learning from the Malaysian Polytechnic institutions

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