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Irfan Syamsuddin
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jurnaljicer@poliupg.ac.id
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+6281242117575
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jurnaljicer@poliupg.ac.id
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Jl. Tamalanrea raya (BTP) Moncongloe, Kampus 2 Politekik Negeri Ujung Pandang, Makassar
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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. 1 (2024)" : 5 Documents clear
KINERJA HYBRID MONGODB-ELASTICSEARCH PADA APLIKASI SOCIAL NETWORK ANALYSIS Jaury, Muhammad; Olivya, Meylanie; Nur, Rini
Journal of Informatics and Computer Engineering Research Vol. 1 No. 1 (2024)
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/jicer.v1i1.4916

Abstract

Social media data is growing rapidly in size, variety and complexity. Social media data stores various potential information such as sentiment analysis, trend predictions etc. Potential information can be extracted through Social Network Analysis. SNA has a major challenge which is to process very large datasets in a reasonable time. One of the efforts that can be done is create hybrid system of MongoDB and Elasticsearch using social media datasets from Twitter. The results of this study that the highest response time in insert process starting from 26.2s on 1K data to 19520.45s on 1M data. The replication process with 1K tweet data is 6.25s to 1M tweets is 2817,146s. The select process has under 0.1s and relatively constant due to the Inverted Index on Elasticsearch. Highest CPU performance in process of selecting data from Elasticsearch. Highest RAM performance in the insert process to MongoDB and data replication to Elasticsearch.
INOVASI SISTEM PEMERIKSAAN UJIAN SELEKSI CALON MAHASISWA BARU DI POLITEKNIK NEGERI UJUNG PANDANG Dzulmukmin, Andi Abdul; Tungadi, Eddy; Abduh , Ibrahim
Journal of Informatics and Computer Engineering Research Vol. 1 No. 1 (2024)
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/jicer.v1i1.4918

Abstract

The inspection system for the entrance exam to the state polytechnic in Ujung Pandang is a process for checking participant computer answer sheets (LJK) to obtain the scores of participants who took the exam so that it becomes a benchmark for participants' graduation of the desired study program. The previous UMPN inspection system had drawbacks, namely the program inspection system still needed to be developed in terms of accuracy and effectiveness. Designing an FSI inspection program that has high accuracy requires data collection such as FSI along with references to similar inspection programs. The LJK inspection program uses the python language with the image processing library, namely openCV. LJK will be scanned and produce 100dpi and 200dpi LJK images which will be tested in the FSI inspection program. Based on the program testing conducted, it is recommended to use a 15x15 pixel resolution of 100dpi with an average accuracy of 99.31% and for a 200dpi resolution it is recommended to use 30x30 pixels with an average accuracy of 99.98%.
PENGEMBANGAN SISTEM BIG DATA: RANCANG BANGUN INFRASTRUKTUR DENGAN FRAMEWORK HADOOP Sudirman , Ahmad; Irawan; Saharuna , Zawiyah
Journal of Informatics and Computer Engineering Research Vol. 1 No. 1 (2024)
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/jicer.v1i1.4919

Abstract

Hadoop is a distributed data storage platform that provides a parallel processing framework. HDFS (Hadoop Distributed File System) and Map Reduce are two very important parts of Hadoop, HDFS is a distributed storage system built on java, while Map Reduce is a program for managing large data in parallel and distributed. The research focused on testing the data transfer speed on HDFS, testing using 3 types of data, namely video, ISO Image, and text with a total of 512 MB, 1 GB, and 2 GB of data. Testing will be carried out by entering data into HDFS using the Hadoop command and changing the size of the block size with parameters 128 MB, 256 MB and 384 MB. Hadoop's performance on a large block size of 384 MB has better speed than block sizes of 128 MB and 256 MB because the data will be divided into 384 MB so that data mapping will be less than on block sizes of 128 MB and 256 MB.
PENERAPAN MACHINE LEARNING UNTUK MENGATASI KETIMPANGAN DATA DALAM MENENTUKAN KLASIFIKASI UANG KULIAH TUNGGAL (UKT) Syam, Nurul Tarizya; Irmawati; Saharuna , Zawiyah
Journal of Informatics and Computer Engineering Research Vol. 1 No. 1 (2024)
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/jicer.v1i1.4921

Abstract

Single Tuition Fee or UKT is a tuition fee borne by students every semester. Payment is made every time students enter a new semester while studying at tertiary institutions. One of the state universities in Indonesia that has implemented the UKT payment system is Politeknik Negeri Ujung Pandang. Based on observations, the purchase of UKT is still done manually, so it has the potential to produce decisions that are not on target. This study was classified based on the amount of single student tuition fees using the smote method and without smote. The algorithm used in classifying is SVM, Decision Tree, Random Forest. The data used is 985 UKT data in 2021. Based on experiments that have been carried out with the Random Forest algorithm, it has the best performance compared to the SVM and Decision Tree algorithms. The proportion of results obtained before being hit is accuracy of 84.75%, precision of 79.22%, recall of 81.15% and F1 score of 80.17%. Whereas after applying smote it increased with an accuracy proportion of 98.9%. So it can be interpreted that the best algorithm used in classification is the Random Forest algorithm by applying smote.
PENERAPAN TEKNOLOGI BLOCK STORAGE DALAM SISTEM VIRTUALISASI BERBASIS OPENSTACK Putri , Oka Karma; Irawan; Saharuna , Zawiyah
Journal of Informatics and Computer Engineering Research Vol. 1 No. 1 (2024)
Publisher : Politeknik Negeri Ujung Pandang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31963/jicer.v1i1.4922

Abstract

In agriculture, the drip irrigation system is still using a manual system, so it is necessary to develop an automatic irrigation system that can make it easier for farmers to control water supply. network The use of wireless sensors in agriculture is a field that is experiencing an increase. Using a wireless network helps farmers when they have to carry out cable maintenance and repairs in areas that are difficult to reach. This study aims to implement a wireless sensor network based on ESP8266 for drip irrigation system automation that monitors changes in soil moisture and plant temperature, as well as automatic drip irrigation control. The method used in this study is the Waterfall Method, this model develops systematically from one stage to the next. The maximum range distance that can be achieved by the router node to send data to the sink node is 140 meters at the Line Of Sight (LOS) position. At the same time, the router node also controls drip irrigation automatically by sending commands to the actuator node (drip controller) to open or close the solenoid valve connected to the water reservoir which will circulate air by gravity. To implement it, you need ESP8266, YL-

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