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Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)

RESTI
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Published by Ikatan Ahli Informatika Indonesia

ISSN : 25800760 EISSN : 25800760 DOI : https://doi.org/10.29207/resti.v2i3.606

Core Subject : Science, Engineering,

Computer Science & IT Engineering

Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) dimaksudkan sebagai media kajian ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai penelitian Rekayasa Sistem, Teknik Informatika/Teknologi Informasi, Manajemen Informatika dan Sistem Informasi. Sebagai bagian dari semangat menyebarluaskan ilmu pengetahuan hasil dari penelitian dan pemikiran untuk pengabdian pada Masyarakat luas dan sebagai sumber referensi akademisi di bidang Teknologi dan Informasi. Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) menerima artikel ilmiah dengan lingkup penelitian pada: Rekayasa Perangkat Lunak Rekayasa Perangkat Keras Keamanan Informasi Rekayasa Sistem Sistem Pakar Sistem Penunjang Keputusan Data Mining Sistem Kecerdasan Buatan/Artificial Intelligent System Jaringan Komputer Teknik Komputer Pengolahan Citra Algoritma Genetik Sistem Informasi Business Intelligence and Knowledge Management Database System Big Data Internet of Things Enterprise Computing Machine Learning Topik kajian lainnya yang relevan

Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)

Articles 1,046 Documents

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Sistem Tertanam Berbasis PLC pada Simulator Pemberian Label dan Pemisahan Botol Danang Adi Nugroho; Arief Goeritno; Anang Dwi Purnomo
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 5 (2021): Oktober2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Utilization of photoelectric and fiberoptic sensors equipped with a number of actuators have been integrated into an embedded system based on a programmable logic controller (PLC). The labeling mechanism is based on the detection of the photoelectric sensor due to the photoelectric effect, while the bottle separation process is based on the detection of the fiberoptic sensor for two different colors. The objectives of this research includes three things, namely (i) produce a simulator controlled by a PLC system with assisted the help of sensors and actuators, (ii) create a ladder-based program structure, and (iii) measure the performance of the embedded system based on the performance of sensors and actuators. The research methods are conducted based on the research objectives through three stages, namely (i) the assembly of the conveyor frame, installation of the entire device, and integrated wiring; (ii) providing a 64-bit CX-Programmer, determining algorithms, compiling ladder, and compiling and uploading the entire program structure; and (iii) synchronization conditions and readings of on-board sensors for activation of all devices in the output line, and measurement of the processing time of stamping and bottle separation assisted by a pneumatic system. The results of the system performance during the labeling process for green and red bottles were fifteen times each, as was the case with the bottle separation process for green and red bottles, fifteen times each. The performance of the system is based on the success rate during the labeling process of 100%, while the success rate during the bottle separation process is 73.33%. The unsuccessful separation of bottles by 26.67% occurred in green bottles. The general conclusion is that a fabricated embedded system can be used as a simulator for a mechanical system of labeling and separating bottles based on bottle color.

Sentiment Analysis of Work from Home Activity using SVM with Randomized Search Optimization Fatihah Rahmadayana; Yuliant Sibaroni
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 5 (2021): Oktober2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Government policy on a problematic topic can lead to pros and cons, including the implementation of work from home during the COVID-19 pandemic in Indonesia. Lots of social media users express their opinions through social media, such as Twitter. Using Twitter API, data on Twitter can be obtained freely, so it can be utilized for sentiment analysis. Therefore, this study contains an analysis of public sentiment on the work from home policy using various preprocessing methods and Support Vector Machine with randomized search optimization. The result shows that the use of the acronym expansion method, slang word translation, and emoji translation in the preprocessing stage can increase the F1 Score value. The best F1 score results obtained were 83.362%. The results of the preprocessing method are used to predict unlabeled data. Prediction results show that 62.35% of tweets have positive sentiments, on the contrary, 37.65% of tweets have negative sentiments. So, it can conclude that most netizens support the policy of work from home.

Temu Kembali Kemiripan Motif Citra Tenun Menggunakan Transformasi Wavelet Diskrit Dan GLCM Anderias Bai Seran; Aviv Yuniar Rahman; Istiadi Istiadi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 5 (2021): Oktober2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Indonesia is a country with cultural diversity. One of the famous cultural heritages in Indonesia is Woven Fabrics. East Nusa Tenggara Province, especially South Central Timor, is an area that also produces weaving. There are 3 types of woven fabric motifs, namely the Buna, Lotis, and Futus motifs which were inherited from their ancestors. Woven cloth is unique because it is made through a ritual process and is used for traditional ceremonies, weddings, funerals, and so on. However, along with the development of technology, ordinary people increasingly forget the motifs of woven fabrics and have difficulty distinguishing the motifs. The function of this research is to improve the performance of previous studies in the process of finding the similarity of weaving image motifs using discrete wavelet transforms and GLCM. The results are known, calculations using a confusion matrix on discrete wavelet transformation feature extraction and GLCM, comparisons on discrete wavelet transformations produce an accuracy rate of 70% Minkowski matrix, 60% Manhattan matrix, 60% Canberra matrix, 20% Euclidean matrix. Comparison of feature extraction calculations on GLCM produces an average quality of the Minkowski matrix of 90% and the lowest level of accuracy on the Euclidean, Manhattan, and Canberra matrices of 80%.

The Hybrid Recommender System of the Indonesian Online Market Products using IMDb weight rating and TF-IDF Muhammad Johari; Arif Laksito
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 5 (2021): Oktober2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Today, consumers are faced with an abundance of information on the internet; accordingly, it is hard for them to reach the vital information they need. One of the reasonable solutions in modern society is implementing information filtering. Some researchers implemented a recommender system as filtering to increase customers’ experience in social media and e-commerce. This research focuses on the combination of two methods in the recommender system, that is, demographic and content-based filtering, commonly it is called hybrid filtering. In this research, item products are collected using the data crawling method from the big three e-commerce in Indonesia (Shopee, Tokopedia, and Bukalapak). This experiment has been implemented in the web application using the Flask framework to generate products’ recommended items. This research employs the IMDb weight rating formula to get the best score lists and TF-IDF with Cosine similarity to create the similarity between products to produce related items.

Rancang Bangun Perangkat Komunikasi Adaptif Untuk Pengembangan QoS (Quality of Service) Infrastruktur Internet of Vehicle (IoV) Nizirwan Anwar; Dewanto Rosian Adhy; Rudi Hermawan; Budi Tjahjono; Muhammad Abdullah Hadi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 5 (2021): Oktober2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

The communication network is an important and vital component in the implementation of the Internet of Vehicle (IoV). The characteristics of IoV related to mobility, load, coverage area is very complex. The movement of connected nodes, communication load and wide coverage require reliable infrastructure support. Coupled with a high level of Quality of Service (QoS) for Internet of Vehicle (IoV) implementation which has a high risk if a communication system failure occurs. In this research, a system that has adaptive capability has been built in choosing a good connection infrastructure at the point where the unit is connected. Created a system that has the ability to connect to several communication network infrastructure. The system can switch to another provider when there is a connection that decreases its QoS level. The tests carried out resulted in better connection dynamics because there was an infrastructure backup. Although there are still many weaknesses because the distribution of network availability is still problematic. Anticipation of network overload can be anticipated with this system. The test results show that there is an increase in the percentage of lines connected to the new system. There is an increase in the percentage of connectivity around 10% to 20% compared to systems without connection backups.

Analisis Metode Representasi Teks Untuk Deteksi Interelasi Kitab Hadis: Systematic Literature Review Amelia Devi Putri Ariyanto; Chastine fatichah; Agus Zainal Arifin
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 5 (2021): Oktober2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Hadith is the second source of reference for Islamic law after the Qur'an, which explains the sentences in the Qur'an which are still global by referring to the provisions of the Prophet Muhammad SAW. Classification of text documents can also be used to overcome the problem of interrelation between the Qur'an and hadith. The problem of interrelation between books of hadith needs to be done because some hadiths in certain hadith books have the same meaning as other hadith books. This study aims to analyze the development of text representation and classification methods suitable to overcome similarity meaning problems in detecting interrelationships between hadith books. The research method used is Systematic Literature Review (SLR) sourced from Google Scholar, Science Direct, and IEEE. There are 42 pieces of literature that have been studied successfully. The results showed that contextual embedding as the newest text representation method considered word context and sentence meaning better than static embedding. As a classification method, the ensemble method has better performance in classifying text documents than using only a single classifier model. Thus, future research can consider using a combination of contextual embedding and ensemble methods to detect interrelationships between books of hadith.

Sistem Monitoring dan Deteksi Stres Pada Anak Berbasis Wearable Device Phie Chyan; Yudi Kasmara
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 5 (2021): Oktober2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

The need for monitoring of children today is very important, especially for children under five, whose physical and verbal abilities are still inadequate to be able to communicate effectively with their parents or caregivers about the conditions they are experiencing. Previous studies related to child safety that were studied generally focused on responses to events that could potentially harm children.This study aims to design a prototype child monitoring system consisting of a wearable device that is used on a child's wrist equipped with sensors and connected to a server via a wireless network. Monitoring software that runs on the server will collect all data parameters from wearable devices with built-in audio signal, temperature, and heart rate sensor then with machine learning algorithm implemented in software will allow the system to predict if stress conditions happen on children and then system can give warnings to child-caregiver through monitoring applications or SMS messages. Using the Decision Tree and Naive Bayes classification methods the system can effectively predict stress conditions in children with an accuracy of 82.8 percent using audio, temperature, and heart rate parameters. This shows that the system has the capability to contribute to increasing child safety in the supervision environment.

Analisis Perbandingan SVM, XGBoost dan Neural Network pada Klasifikasi Ujaran Kebencian Suwarno Liang
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 5 (2021): Oktober2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

In social media, it is found that hate speech is conveyed in the form of text, images and videos, as a result it can provoke certain people to do things that are against the law and harm other person. Therefore, it is necessary to make early detection of hate speech by utilizing machine learning algorithms. This study is to analyze the level of accuracy, precision, recall and F1-Score of 3 kinds of algorithms (SVM, XGBoost, and Neural Network) in the classification of hate speech, using datasets sourced from public hate speech on Twitter in Indonesian. The results of the analysis show that the SVM algorithm has a level of accuracy (83.2%), precision (83%), recall (83%) and F1-score (83%), SVM occupies the highest level compared to XGBoost and Neural Network, so the SVM algorithm can be considered for use in hate speech classification

Sistem Keamanan Helm Berbasis Internet of Things dengan Fitur Pelacakan Menggunakan Android Panji Wiratama Santoso; I Nyoman Piarsa; Ni Made Ika Marini Mandenni
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 5 (2021): Oktober2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Helmet theft is a problem that is of concern to the public. Information Technology provides may resolve any problems, like Internet of Things-based system that can detect helmet theft and track the location of the helmet if it's stolen. This system is designed using a microcontroller device, namely Arduino which is attached to the helmet and motorbike with the help of the SIM800L v2, GPS Neo-6m, buzzer, and Bluetooth HC-05 which is connected to the master slave as an indicator of the safety of the helmet. The hardware on the helmet is connected to Firebase Realtime Database server so it can be connected with the user's Android application to monitor the state and location of the helmet. Android application displays maps to determine the position of the helmet, and can display notifications when the helmet is being stolen. The conclusion is this system can detect helmet theft with a maximum distance from the master and slave bluetooth connections of 10 meters, and the average data transmission from hardware to Firebase is 1,1 seconds, and can monitor status of the helmet and track the position of the helmet through the Android application with Android Jelly Bean (v4.3) operating system.

Pengembangan Karakterisasi Gelembung Mikro Menggunakan Metode PIV beserta Pemantauan dengan IOT Taufik Ibnu Salim; Endang Juliastuti; Vebi Nadhira
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 5 (2021): Oktober2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

The development of microbubble technology has been widely used in various fields. One of these areas is sterilization technology using microbubbles to speed up and increase the effectiveness of the sterilization process. One example is room sterilization using vaporized ozone gas microbubbles which can minimize the spread of the Covid-19 virus. However, research and development of microbubbles are still not much related to the characterization of their size and hydrodynamic properties. In this study, we propose the development of a continuous characterization of the size of microbubbles using the image analysis method. Image analysis aims to find the displacement vector using particle image velocimetry (PIV) techniques. The Hadamard-Rybczynski equation was used to calculate the size of the microbubbles based on the rising velocity vector of the microbubbles. The image capture process uses an LED light shadow technique to get a brighter and more stable image. The template matching algorithm is used to speed up the displacement vector analysis process used in the PIV technique. The analysis process is carried out in-situ in parallel processing using the python program on the raspberry pi4 unit. The analysis process uses three program services that run parallel, namely recording, pre-processing, and processing services. The measurement process uses three validations, namely pixel validation, template matching algorithm validation, and interrogation window. Bubble size data is displayed in the form of real-time graphs and size distribution histograms online using IoT. The test results show the size distribution of the microbubbles produced has an average of 14.60 µm with a deviation value of 0.11µm.

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Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Yuhefizar

Contact Email jurnal.resti@gmail.com

Phone +628126777956

Journal Mail Official ephi.lintau@gmail.com

Editorial Address Politeknik Negeri Padang, Kampus Limau Manis, Padang, Indonesia.

Location , INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Contact Name
Yuhefizar

Contact Email
jurnal.resti@gmail.com

Phone
+628126777956

Journal Mail Official
ephi.lintau@gmail.com

Editorial Address
Politeknik Negeri Padang, Kampus Limau Manis, Padang, Indonesia.

Location
,

INDONESIA