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INDONESIA
Journal of Informatics and Computer Engineering Research
Published by Politeknik Negeri Ujung Pandang
ISSN : -     EISSN : 30896320     DOI : https://doi.org/10.31963
Core Subject : Science,
Computer Science & IT
Journal of Informatics and Computer Engineering Research PNUP is research journal as a forum for scientific communication between academics, researchers and practitioners in disseminating research results in the fields of Information System, Networking, Mobile Applications, Software Engineering, Web Programming Mobile Computing, Science Application, Virtual Reality, Multimedia.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 5 Documents
 1 
Search results for , issue "Vol. 1 No. 2 (2024)" : 5 Documents clear
EVALUASI KINERJA LOAD BALANCING DENGAN ALGORITMA SCHEDULLING NEVER QUEUE Zulfianndari; Irmawati,; Nur , Rini
Journal of Informatics and Computer Engineering Research Vol. 1 No. 2 (2024)
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/jicer.v1i2.5176

Abstract

Load balancing is used as a technique to handle large loads that cannot be carried out by a single server, so that the server does not experience overload. In handling load sharing, Load balancing uses a scheduling algorithm (Scheduling). The scheduling algorithm that is generally used is Round Robin which works by dividing requests evenly and then creating a queue for the server so that unfinished processes wait in the queue for quite a long time. In the Load balancing system there is an algorithm that adopts two speed models, which works by looking at the server status and the smallest connection delay, namely the Never Queue Algorithm. This study aims to determine the performance of Load balancing when the Schedulling Never Queue Algorithm is applied, based on predetermined scenarios and parameters. This study succeeded in implementing the Never Queue Algorithm in a Load balancing system for the Apache web server where the Time Per Request value will be lower if the Request received is larger when compared to using the Round Robin Algorithm. The Request Per Second value increases when the Requests sent are getting bigger. In terms of sharing server connections, the load balancer will share the load on the number of Requests based on the Shortest Expected Delay (SED) Algorithm, so several web servers receive different numbers of connections, so that processes don't stay in queues for a long time.
ANALISIS POLA PENYAKIT DENGAN METODE ASSOCIATION RULE (STUDI KASUS : RSUD LABUANG BAJI) Mintu, Yupita Febriani; Yusri, Iin Karmila; Saharuna , Zawiyah
Journal of Informatics and Computer Engineering Research Vol. 1 No. 2 (2024)
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/jicer.v1i2.5177

Abstract

RSUD Labuang Baji has a lot of medical record data, but this medical record data has not been used optimally and has not been processed to produce useful information for Laburan Baji Hospital. In this study the data used were outpatient medical record data in 2019, by analyzing three attributes, namely disease diagnosis (ICD), gender, and age group. The method for conducting data analysis is the association rule method using the Apriori algorithm and Tools R. The results of this study are disease patterns using a minimum support value of 0.01 and a minimum confidence value of 0.6, and the disease pattern formed is an associative rule with a combination of 2k-itemset and 3k item set of 25 associative rules where the rules for this disease pattern have a lift ratio value of > 1, so this disease pattern can be used as a recommendation to improve hospital services.
PENERAPAN ALGORITMA OPPOSITION-BASED WHALE DALAM KLASIFIKASI SVM UNTUK ANALISIS SENTIMEN TERHADAP KEBIJAKAN PPKM Said, Asrul; Tungadi, Eddy; Olivya , Meylanie
Journal of Informatics and Computer Engineering Research Vol. 1 No. 2 (2024)
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/jicer.v1i2.5178

Abstract

Corona Virus Disease 2019 (COVID-19) has had a serious impact, forcing the Indonesian government to establish various policies to deal with the spread of COVID-19. One of these policies is the Implementation of Restricting Community Activities (PPKM). During its implementation, this policy raised pros and cons in the community, especially on Twitter social media. The existence of this public opinion, can be used as an effective source of information to assist the government in taking and evaluating policies. The purpose of this study was to determine public sentiment towards PPKM policies based on the classification of tweets or public opinion on Twitter. This process is carried out by applying the OBWOA method for selecting appropriate and optimal SVM parameters and feature selection to select the best features thereby reducing computation time and producing good classification performance. The results of the optimization of the SVM parameters obtained C = 4.99522643 and gamma = 1.4236435 with an average accuracy of 75.20%, precision of 79.73%, recall of 71.65%, and f measure of 70.88%. The feature selection results obtained an average accuracy of 82.40%, precision of 84.23%, recall of 79.63%, and f-measure of 78.96%. In addition, the sentiment classification of 1,389,481 public tweet data in the period January to December 2021 obtained 53% of tweets with Negative sentiment, 25% of Tweets with Neutral sentiment, and 22% of tweets with Positive sentiment.
IMPLEMENTASI DEEP LEARNING UNTUK PENDETEKSIAN PENGGUNA MASKER PADA CCTV: STUDI KASUS PUSKESMAS SUDIANG RAYA Trisnaningrun, Ainun; Tungadi, Eddy; Syamsuddin, Irfan
Journal of Informatics and Computer Engineering Research Vol. 1 No. 2 (2024)
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/jicer.v1i2.5184

Abstract

The use of mask is one of the things that needs attention when you want to leave the house to implement health protocols to avoid diseases that are currently troubling people in the world or commonly known as Covid-19. Currently, people are reluctant to come to the hospital for fear of being exposed to the Covid-19 virus, so people who need treatment prefer to visit the puskesmas near their home. However, there are still many people who do not use masks on the grounds that the intended location is close to home. To overcome this can be done by detecting visitors' faces using the camera. So a system is proposed, namely the detection of mask users with the Convolutional Neural Network (CNN) method. One of the widely applied CNN methods for processing image data is YOLO. YOLO (You Only Look Once) is a deep learning-based model developed to detect an object in real-time. YOLO works by looking at the image as a whole, then using a neural network and automatically detecting existing objects. So that in this study the YOLO model, namely YOLOv4, was used as an object detection model in a mask detection system with CCTV video media whose data is sent in real-time.
INOVASI APLIKASI ASESMEN NASIONAL MENGGUNAKAN TEKNOLOGI PROGRESSIVE WEB APP Muhamad Aslan, La Ode; Yusri, Iin Karmila; Raharjo , Muh. Fajri
Journal of Informatics and Computer Engineering Research Vol. 1 No. 2 (2024)
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/jicer.v1i2.5185

Abstract

The national assessment is a program for assessing the quality of each school, madrasah and equality program at the primary and secondary levels. The national assessment application utilizes network connectivity to send national assessment results data from the application to the server. However, the lack of equal distribution of network facilities and infrastructure is an obstacle in the use of national assessment applications. Therefore, to build a national assessment application system that can be accessed without having to depend on network connectivity, the system will be built using the Progressive Web App (PWA) concept. Meanwhile, by using the web app manifest, the website can bring up a pop-up add to homescreen which is useful for installing the system on the user's homescreen so that applications can be accessed quickly via the homescreen icon. By using indexedDB, even though in an offline state the user can still send data and the data will be saved to indexedDB and when the network returns online the data will be automatically synchronized with the server. From the results of testing the quality of PWA using Lighthouse, there is a decrease in the performance of the progressive web app application each time the number of users is added, this indicates that the number of users can affect the performance of a computer-based national assessment application using a progressive web app.

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