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All Journal BERKALA SAINSTEK Jurnal Sains dan Teknologi INFORMAL: Informatics Journal Sinkron : Jurnal dan Penelitian Teknik Informatika JUTIK : Jurnal Teknologi Informasi dan Komputer Jurnal Infomedia WIDYABHAKTI Jurnal Ilmiah Populer Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Journal of Computer Science and Informatics Engineering (J-Cosine) Jurnal Puan Indonesia Jurnal WIDYA LAKSMI (Jurnal Pengabdian Kepada Masyarakat) Sabangka Abdimas Jurnal Pengabdian Masyarakat Sabangka Journal of Social Work and Empowerment TECHNOVATE KOMET
I Kadek Dwi Gandika Supartha
STMIK STIKOM Indonesia
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Physics Public Health Social Sciences Other

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Journal : informal informatics journal

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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.
Co-Authors Adyana, Andres Andika, I Gede Aniek Suryanti Kusuma Arditya, I Kadek Dito Ariana, Anak Agung Gede Bagus Desak Made Dwi Utami Putra Dewa Made Wiharta Dewa Putu Yudhi Ardiana Dewi, I Gusti Ayu Putu Eka Purnama Dirgayusari, Ayu Manik Eka Dharsika, I Gde I Dewa Ayu Agung Tantri Pramawati I Gede Adnyana I Gede Andika I I Gede Iwan Sudipa I Gusti Ayu Putu Eka Purnama Dewi I Gusti Made Ngurah Desnanjaya I Nyoman Buda Hartawan I Putu Agus Eka Darma Udayana, I Putu Agus Eka I Wayan Sudiarsa Ida Nirmala Sari Iskandar, Adi Panca Saputra Kadek Ayu Ariningsih Kombonglangi, Kaleb Charisma Made Suci Ariantini Made Sudarma Meinarni, Ni Putu Suci Merta, I Kadek Priyana Adi Ni Kadek Bumi Krismentari Ni Ketut Utami Nilawati Ni Putu Ayu Siska Wulantari Nia Maharani Pande, Ni Kadek Nita Noviani Pramawati, I.D.A Tantri Priadinata, I Putu Bramasta Radhitya, I Made Leo Sandhiyasa, I Made Subrata Sandika, I Kadek Budi Sari, Ida Nirmala Welda