All Outputs (36)

Prediction of Violence Against Women Using Ensemble Learning Models: A Comparative Study of LightGBM, XGBoost, and Others (2025)
Journal Article

Violence against women and the possibility of its occurrence among children is a very serious issue that negatively impacts the physical, psychological, and emotional aspects of the victims and those around them. Various efforts have been made to red... Read More about Prediction of Violence Against Women Using Ensemble Learning Models: A Comparative Study of LightGBM, XGBoost, and Others.

Revitalizing Pastoral Care: Leveraging Stupa Learning Management System in Diocese of Maumere (2025)
Journal Article

The Catholic Church of the Diocese of Maumere is developing a learning management system (LMS) for its pastoral training program called the Weekend Pastoral Study, which is also abbreviated in Indonesian as Stupa. The aim of this LMS development is t... Read More about Revitalizing Pastoral Care: Leveraging Stupa Learning Management System in Diocese of Maumere.

Ship Movement Analysis Based on Automatic Identification System (AIS) Data Using Convolutional Neural Network and Multiple Thread Processing (2024)
Journal Article

Automatic Identification System (AIS) data is one of the most common and widely used datasets in the maritime industry.
This dataset is a useful source of information regarding maritime traffic for both individuals and businesses. The reliability o... Read More about Ship Movement Analysis Based on Automatic Identification System (AIS) Data Using Convolutional Neural Network and Multiple Thread Processing.

Attention is Everything You Need: Case on Face Mask Classification (2023)
Journal Article

Automated face mask classification has surfaced recently following the COVID-19 mask wearing regulations. The current State-of-The-Art of this problem uses CNN-based methods such as ResNet. However, attention-based models such as Transformers emerged... Read More about Attention is Everything You Need: Case on Face Mask Classification.

Data Warehouse implementation for Mixing Process in Tire Manufacture (2019)
Presentation / Conference Contribution

An energy efficient and resource preserving target tracking approach for wireless sensor networks (2014)
Presentation / Conference Contribution

Efficient object tracking in wireless sensor networks (WSNs) is of importance in many application scenarios such as military and surveillance, health monitoring, etc. In this paper, we propose a target tracking technique from two approaches, dynamic... Read More about An energy efficient and resource preserving target tracking approach for wireless sensor networks.

Knowledge Representation in Agent's Logic with Uncertainty and Agent's Interaction (2014)
Preprint / Working Paper

This paper studies knowledge representation in multi-agent environment. We investigate technique for computation truth-values of statements based at new temporal, agent's-knowledge logic TL KnI,U Dist. A logical language, mathematical symbolic models... Read More about Knowledge Representation in Agent's Logic with Uncertainty and Agent's Interaction.

A Hybrid Approach using Ontology Similarity and Fuzzy Logic for Semantic Question Answering (2014)
Presentation / Conference Contribution

One of the challenges in information retrieval is providing accurate answers to a user’s question often expressed as uncertainty words. Most answers are based on a Syntactic approach rather than a Semantic analysis of the query. In this paper our obj... Read More about A Hybrid Approach using Ontology Similarity and Fuzzy Logic for Semantic Question Answering.

A Fuzzy Algorithm for Mining High Utility Rare Itemsets -FHURI (2014)
Journal Article

Classical frequent itemset mining identifies frequent itemsets in transaction databases using only frequency of item occurrences, without considering utility of items. In many real world situations, utility of itemsets are based upon user's perspecti... Read More about A Fuzzy Algorithm for Mining High Utility Rare Itemsets -FHURI.

Understanding low back pain using fuzzy association rule mining (2013)
Presentation / Conference Contribution

Classifying Mass Spectral Data Using SVM and Wavelet-Based Feature Extraction (2013)
Presentation / Conference Contribution

The paper investigates the use of support vector machines (SVM) in classifying Matrix-Assisted Laser Desorption Ionisation (MALDI) Time Of Flight (TOF) mass spectra. MALDI-TOF screening is a simple and useful technique for rapidly identifying microor... Read More about Classifying Mass Spectral Data Using SVM and Wavelet-Based Feature Extraction.

HURI - A novel algorithm for mining high utility rare itemsets (2013)
Presentation / Conference Contribution

In Data mining field, the primary task is to mine frequent itemsets from a transaction database using Association Rule Mining (ARM). Utility Mining aims to identify itemsets with high utilities by considering profit, quantity, cost or other user pref... Read More about HURI - A novel algorithm for mining high utility rare itemsets.

A hybrid heuristic approach for attribute-oriented mining (2013)
Journal Article

We present a hybrid heuristic algorithm, clusterAOI, that generates a more interesting generalised table than obtained via attribute-oriented induction (AOI). AOI tends to overgeneralise as it uses a fixed global static threshold to cluster and gener... Read More about A hybrid heuristic approach for attribute-oriented mining.

Fuzzy classification in web usage mining using fuzzy quantifiers (2013)
Presentation / Conference Contribution

This paper proposes a new algorithm-FC-WPath, a fuzzy rule-based classification of weighted path traversals using fuzzy quantifiers for web usage mining. Web usage mining usually analyses frequent path traversals or frequent subgraphs where each path... Read More about Fuzzy classification in web usage mining using fuzzy quantifiers.

A framework to mine high-level emerging patterns by attribute-oriented induction (2011)
Presentation / Conference Contribution

This paper presents a framework to mine summary emerging patterns in contrast to the familiar low-level patterns. Generally, growth rate based on low-level data and simple supports are used to measure emerging patterns (EP) from one dataset to anothe... Read More about A framework to mine high-level emerging patterns by attribute-oriented induction.

A hybrid interestingness heuristic approach for attribute-oriented mining (2011)
Presentation / Conference Contribution

A hybrid interestingness heuristic algorithm, clusterAOI, is presented that generates a more interesting generalized final table than traditional attribute-oriented induction (AOI). AOI uses a global static threshold to generalize attributes irrespec... Read More about A hybrid interestingness heuristic approach for attribute-oriented mining.

Finding associations in composite data sets: The CFARM algorithm (2011)
Journal Article

In this paper, a composite fuzzy association rule mining mechanism (CFARM), directed at identifying patterns in datasets comprised of composite attributes, is described. Composite attributes are defined as attributes that can take simultaneously two... Read More about Finding associations in composite data sets: The CFARM algorithm.

Business information query expansion through semantic network (2010)
Journal Article

In this article, we propose a method for business information query expansions. In our approach, hypernym/hyponymy and synonym relations in WordNet are used as the basic expansion rules. Then we use WordNet Lexical Chains and WordNet semantic similar... Read More about Business information query expansion through semantic network.

A framework for mining fuzzy association rules from composite items (2009)
Presentation / Conference Contribution

A novel framework is described for mining fuzzy Association Rules (ARs) relating the properties of composite attributes, i.e. attributes or items that each feature a number of values derived from a common schema. To apply fuzzy Association Rule Minin... Read More about A framework for mining fuzzy association rules from composite items.

Effective mining of weighted fuzzy association rules (2009)
Book Chapter

A novel approach is presented for effectively mining weighted fuzzy association rules (ARs). The authors address the issue of invalidation of downward closure property (DCP) in weighted association rule mining where each item is assigned a weight acc... Read More about Effective mining of weighted fuzzy association rules.