Pemetaan untuk Strategi Dakwah di Kota Semarang Menggunakan Pendekatan Data Mining (Mapping for Da'wah Strategy in Semarang City Using Data Mining Approach)

This paper aims to explore the potential of da'wah in the city of Semarang with a data mining approach. The data mining approach is carried out by implementing the fuzzy c-means (FCM) algorithm in order to obtain the optimum number of clusters in the potential clustering of da'wah in the city of Semarang. The data used in this study from the Ministry of Religion of the Republic of Indonesia and the Central Statistics Agency (BPS) of Semarang City. The results of the FCM analysis show that the optimum number of clusters is two clusters, where the sub-district in the second cluster is an area with a high potential for da'wah. This study provides information that in effective da'wah activities, certainty and clarity is needed regarding the targets of da'wah through mapping of da'wah in the form of clustering potential da'wah. This can be a consideration of dakwah strategies for the successful implementation of da'wah studies so that an increase in the target behavior of da'wah can be achieved. The application of FCM to get the optimum cluster of potential da'wah in order to produce da'wah mapping is novelty in the field of Islamic studies, especially the science of da'wah.

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Temporal Analysis for Epileptic Seizure Detection by Using Data Mining Approach

2020 IEEE 22nd International Conference on High Performance Computing and Communications; IEEE 18th International Conference on Smart City; IEEE 6th International Conference on Data Science and Systems (HPCC/SmartCity/DSS) ◽

10.1109/hpcc-smartcity-dss50907.2020.00175 ◽

2020 ◽

Author(s):

Francesca Pafferi ◽

Gaetano Zazzaro ◽

Angelo Martone ◽

Paolo Bifulco ◽

Luigi Pavone

Keyword(s):

Data Mining ◽

Epileptic Seizure ◽

Temporal Analysis ◽

Seizure Detection ◽

Epileptic Seizure Detection ◽

Data Mining Approach ◽

Using Data

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Predicting car purchase intent using data mining approach

2011 Eighth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) ◽

10.1109/fskd.2011.6019863 ◽

2011 ◽

Cited By ~ 1

Author(s):

Yap Bee Wah ◽

Nor Huwaina Ismail ◽

Simon Fong

Keyword(s):

Data Mining ◽

Purchase Intent ◽

Data Mining Approach ◽

Using Data

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A Data Mining Approach to Forming Generic Bills of Materials in Support of Variant Design Activities

Journal of Computing and Information Science in Engineering ◽

10.1115/1.1812556 ◽

2004 ◽

Vol 4 (4) ◽

pp. 316-328 ◽

Cited By ~ 34

Author(s):

Carol J. Romanowski , ◽

Rakesh Nagi

Keyword(s):

Data Mining ◽

Product Family ◽

Research Direction ◽

Design Constraints ◽

Variant Design ◽

Data Mining Approach ◽

Design Activities ◽

Using Data ◽

New Research

In variant design, the proliferation of bills of materials makes it difficult for designers to find previous designs that would aid in completing a new design task. This research presents a novel, data mining approach to forming generic bills of materials (GBOMs), entities that represent the different variants in a product family and facilitate the search for similar designs and configuration of new variants. The technical difficulties include: (i) developing families or categories for products, assemblies, and component parts; (ii) generalizing purchased parts and quantifying their similarity; (iii) performing tree union; and (iv) establishing design constraints. These challenges are met through data mining methods such as text and tree mining, a new tree union procedure, and embodying the GBOM and design constraints in constrained XML. The paper concludes with a case study, using data from a manufacturer of nurse call devices, and identifies a new research direction for data mining motivated by the domains of engineering design and information.

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