Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal Jurnal Krisnadana
Ida Bagus Gede Anandita
Program Studi Informatika, Institut Bisnis Dan Teknologi Indonesia, Denpasar, Bali, Indonesia
Computer Science & IT Control & Systems Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
A Binary Particle Swarm Optimization–Based Association Rule Mining Model for Retail Transactions Ni Kadek Bumi Krismentari; I Made Dwi Putra Asana; I Kayan Herdiana; Ida Bagus Gede Anandita; Nabila Fitri Syarifah
Jurnal Krisnadana Vol 5 No 2 (2026): Jurnal Krisnadana- January 2026
Publisher : Yayasan Sinergi Widya Nusantara (Sidyanusa)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58982/krisnadana.v5i2.1064

Abstract

This study aims to optimize the association rule mining process on retail transaction data by applying the Binary Particle Swarm Optimization (BPSO) algorithm. Classical methods such as Apriori and FP-Growth often face efficiency limitations, particularly when dealing with large-scale datasets, due to repeated candidate generation processes and high memory requirements. BPSO is employed as a metaheuristic approach capable of adaptively exploring the search space through binary itemset representation and a fitness function based on support, confidence, and lift values. This research follows the CRISP-DM framework, encompassing the stages of data understanding, data preparation, modeling, and evaluation. Based on retail transaction data from KLM, the BPSO process produced the best particle containing 16 potential itemsets. The calculation of support and confidence resulted in seven item combinations that met the minimum threshold and generated eighteen association rules. Evaluation using the lift ratio showed that all rules have lift values greater than one, indicating strong and meaningful relationships among products. These findings demonstrate that BPSO is effective in discovering relevant association patterns and can support retail decision-making, such as product arrangement, cross-selling strategies, and the development of recommendation systems.
Real-time Data Visualization of Inventory Lending Services using Metabase: A Case Study Ida Bagus Gede Anandita; Ni Putu Anggi Karolina; I Made Dwi Putra Asana
Jurnal Krisnadana Vol 5 No 2 (2026): Jurnal Krisnadana- January 2026
Publisher : Yayasan Sinergi Widya Nusantara (Sidyanusa)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58982/krisnadana.v5i2.1079

Abstract

Effective inventory management is critical in higher education but is often constrained by rigid reporting mechanisms. At the Institut Bisnis dan Teknologi Indonesia (INSTIKI), substantial asset volumes are currently presented in static tabular formats, resulting in suboptimal information availability. This impedes the Bureau of General Affairs from extracting rapid strategic insights regarding asset conditions and maintenance. This study addresses these inefficiencies by developing a real-time data visualization system utilizing Metabase as an open-source Business Intelligence (BI) tool. The system integrates directly with operational databases to transform raw data into interactive visual insights without complex ETL processes. The implementation yielded 14 comprehensive dashboard menus, covering metrics such as asset distribution, depreciation analysis, lending trends, and infrastructure quality control. User Acceptance Testing (UAT) indicated a 96% approval rate within the "Strongly Agree" category. These results demonstrate that the system successfully simplifies inventory data complexity, accelerates managerial decision-making, and provides an accurate foundation for budget planning and facility maintenance.
Co-Authors I Kayan Herdiana I Made Dwi Putra Asana Nabila Fitri Syarifah Ni Kadek Bumi Krismentari Ni Putu Anggi Karolina