Claim Missing Document
Check
Articles

Found 2 Documents
Search
Journal : INFORMAL: Informatics Journal

Analisis Kinerja Fuzzy C-Means (FCM) dan Fuzzy Subtractive (FS) dalam Clustering Data Alumni STMIK STIKOM Indonesia I Kadek Dwi Gandika Supartha; Adi Panca Saputra Iskandar
INFORMAL: Informatics Journal Vol 6 No 1 (2021): Informatics Journal (INFORMAL)
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v6i1.22077

Abstract

In this study, clustering data on STMIK STIKOM Indonesia alumni using the Fuzzy C-Means and Fuzzy Subtractive methods. The method used to test the validity of the cluster is the Modified Partition Coefficient (MPC) and Classification Entropy (CE) index. Clustering is carried out with the aim of finding hidden patterns or information from a fairly large data set, considering that so far the alumni data at STMIK STIKOM Indonesia have not undergone a data mining process. The results of measuring cluster validity using the Modified Partition Coefficient (MPC) and Classification Entropy (CE) index, the Fuzzy C-Means Clustering algorithm has a higher level of validity than the Fuzzy Subtractive Clustering algorithm so it can be said that the Fuzzy C-Means algorithm performs the cluster process better than with the Fuzzy Subtractive method in clustering alumni data. The number of clusters that have the best fitness value / the most optimal number of clusters based on the CE and MPC validity index is 5 clusters. The cluster that has the best characteristics is the 1st cluster which has 514 members (36.82% of the total alumni). With the characteristics of having an average GPA of 3.3617, the average study period is 7.8102 semesters and an average TA work period of 4.9596 months.
Restructuring Arsitektur Backend Aplikasi XYZ Berbasis Microservice Merta, I Kadek Priyana Adi; Andika, I Gede; Supartha, I Kadek Dwi Gandika; Ariana, Anak Agung Gede Bagus; Adnyana, I Gede
INFORMAL: Informatics Journal Vol 9 No 2 (2024): Informatics Journal (INFORMAL)
Publisher : Faculty of Computer Science, University of Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19184/isj.v9i2.48699

Abstract

This research aimed to restructure the backend architecture of the XYZ application prototype using Microservice architecture. Load testing was conducted to compare the performance of the initial prototype backend and microservice architecture on response-time, throughput, and latency metrics. The restructuring method used was arranged in 4 stages with a total of 7 activities. In the first stage, system analysis was conducted on the XYZ application prototype. In the second stage, architecture decomposition, consisting of 3 activities, which were identifying system operations, identifying services using domain-driven design decomposition, and defining services and collaboration, was performed. In the third stage, database requirements analysis was performed on the microservice architecture that had been formed. In the fourth stage, the database design and microservice backend were implemented and tested using 3 different amounts of data, which were 56, 112, and 210, against 14 endpoints on both the prototype backend and the microservice backend. Based on the test results taken from the Apache JMeter Listener, it showed that the prototype backend showed superior performance in testing per endpoint, but in the overall test, the microservice backend showed better performance with a 2,4% faster response time, 1,8% higher throughput, and 2,4% lower latency. There is a pattern that shows the dominant microservice backend excels in tests with the last data, Data 210, in all metrics measured.