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Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)

RESTI
Website

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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Seleksi Fitur menggunakan Algoritma Particle Swarm Optimization pada Klasifikasi Kelulusan Mahasiswa dengan Metode Naive Bayes Evi Purnamasari; Dian Palupi Rini; Sukemi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 3 (2020): Juni 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

The study of the classification of student graduation at a university aims to help the university understand the academic development of students and to be able to find solutions in improving the development of student graduation in a timely manner. The Naive Bayes method is a statistical classification method used to predict a student's graduation in this study. The classification accuracy can be improved by selecting the appropriate features. Particle Swarm Optimization is an evolutionary optimization method that can be used in feature selection to produce a better level of accuracy. The testing results of the alumni data using the Naive Bayes method that optimized with the Particle Swarm Optimization algorithm in selecting appropriate features, producing an accuracy value of 86%, 6% higher than the classification without feature selection using the Naive Bayes method.

Komparasi Algoritma Klasifikasi Berbasis Particle Swarm Optimization Pada Analisis Sentimen Ekspedisi Barang Sharazita Dyah Anggita; Ikmah
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 2 (2020): April 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

The needs of the community for freight forwarding are now starting to increase with the marketplace. User opinion about freight forwarding services is currently carried out by the public through many things one of them is social media Twitter. By sentiment analysis, the tendency of an opinion will be able to be seen whether it has a positive or negative tendency. The methods that can be applied to sentiment analysis are the Naive Bayes Algorithm and Support Vector Machine (SVM). This research will implement the two algorithms that are optimized using the PSO algorithms in sentiment analysis. Testing will be done by setting parameters on the PSO in each classifier algorithm. The results of the research that have been done can produce an increase in the accreditation of 15.11% on the optimization of the PSO-based Naive Bayes algorithm. Improved accuracy on the PSO-based SVM algorithm worth 1.74% in the sigmoid kernel.

Optimasi Nilai K pada Algoritma KNN untuk Klasifikasi Spam dan Ham Email Eko Laksono; Achmad Basuki; Fitra Bachtiar
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 2 (2020): April 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

There are many cases of email abuse that have the potential to harm others. This email abuse is commonly known as spam, which contains advertisements, phishing scams, and even malware. This study purpose to know the classification of email spam with ham using the KNN method as an effort to reduce the amount of spam. KNN can classify spam or ham in an email by checking it using a different K value approach. The results of the classification evaluation using confusion matrix resulted in the KNN method with a value of K = 1 having the highest accuracy value of 91.4%. From the results of the study, it is known that the optimization of the K value in KNN using frequency distribution clustering can produce high accuracy of 100%, while k-means clustering produces an accuracy of 99%. So based on the results of the existing accuracy values, the frequency distribution clustering and k-means clustering can be used to optimize the K-optimal value of the KNN in the classification of existing spam emails.

Menentukan Matakuliah yang Efektif Belajar Daring (Belajar dan Ujian) dengan Metode Multi-Attribute Utility Theory (MAUT) Tonni Limbong; Janner Simarmata
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 2 (2020): April 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

The Corona pandemic in Indonesia forced the learning system into a drastic change into online learning. Many campuses that were previously quite comfortable with face-to-face learning were forced to be helpless because they had never prepared a backup plan when something unexpected happened, one of which was when the campus was forced to not be able to face-to-face. If the learning system continues to be done online, it might cause the quality of learners to decrease dramatically compared to face-to-face learning. Moreover, the courses that must be filtered include theories and practice courses. Most assignments given to students are not seriously done because of a lack of significant evaluation and supervision. The Faculty of Computer Science, Santo Thomas Catholic University, Medan supports this government policy by implementing online learning using the Zoom application for face-to-face and Edmodo for supplementary lecture material for online learning media. In one semester apart from studying there is a test period which is the Midterm Examination (UTS) and Final Examination Semester (UAS) where the current leadership must wisely determine the type and nature of the exams to be conducted online. To find out the effectiveness of the form of exam questions in online implementation, a Multi-Attribute Utility Theory (MAUT) method was conducted, the test results found that online learning with Zoom and Edmodo was very effective for theoretical courses with a value of 0.88, then the results of this calculation it is recommended that online tests be conducted in the form of theories such as multiple-choice, essay and analysis

Aplikasi Scheduler Team Meeting Berbasis Mobile Dengan Menggunakan Push Notification Masmur Tarigan; Adven Kristianata
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 3 (2020): Juni 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Each team / individual in a company has its own internal and external meetings. At present PT NTX Solusi Teknologi does not have a system that can schedule meetings and track its employees who carry out meetings, it affects the time management for each individual or team that collaborates with each other. The purpose of making this application is for scheduling, notification of meetings, monitoring the team that is conducting the meeting, and also for data collection by the company admin. Because employees use a variety of devices, applications are created using Web Responsive that can adjust the appearance of employee devices and have the same functionality for all devices. The method used in making this application is the Prototype method for gathering needs, designing and evaluating programs. The problem analysis method uses Fishbone analysis to obtain specific problems. The program will be tested with the Black Box method to ensure the system runs well. With this conclusion the scheduler application can be used to make the schedule, tracking members who carry out external meetings, used by various devices and has a responsive display. And based on testing Black Box the application can run well.

Deteksi Buah untuk Klasifikasi Berdasarkan Jenis dengan Algoritma CNN Berbasis YOLOv3 HR. Wibi Bagas N; Evang Mailoa; Hindriyanto Dwi Purnomo
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 3 (2020): Juni 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

The fruit is part of the flowers in plants that are produced from pollination of the pistils and stamens. The shape and color of many fruits with a variety, with the type of single fruit, double fruit and compound fruit. This study asks for the development of 10 pieces detection applications to help the sensor agriculture sector for 10 pieces detection. The data in this study used the image of 10 fruits namely Mangosteen, Delicious, Star Fruit, Water Guava, Kiwi, Pear, Pineapple, Salak, Dragon Fruit, and Strawberry. Training and testing using CNN algorithms and YOLOv3 machine learning methods with the support of the work of the Darknet53 neural network. The analysis was conducted using 2,333 images of data from 10 classes. The training process is carried out up to 5,000 iterations stored in checkpoints. The implementation of the detection of 10 pieces was carried out on Google Collaboratory through imagery with two tests. Accuracy in the detection of 10 pieces can reach more than 90% in the first test of each fruit and an average of 70% in the second test for images outside the test data.

Evaluasi Buku Interaktif Berbasis Augmented Reality Menggunakan System Usability Scale dan User Experience Questionnaire Dinan Yulianto; Rudy Hartanto; Paulus Insap Santosa
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 3 (2020): Juni 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Nowadays, the implementation of information and communication technology in education is important. In harmony with technological developments, the term mobile learning comes to represent learning that utilizes mobile communication devices. The implementation of augmented reality in education provides a new learning model in the form of a combination of technology-based conventional learning media. This research aimed to evaluate augmented reality-based books as media for learning Cirebon mask dance. As many as 15 respondents were involved in the evaluation process, including testing the usability using the System Usability Scale (SUS) and User Experience Questionnaire (UEQ). The evaluation using SUS found a value of 77.67, meaning that the Acceptability Ranges category was “Acceptable”; the Grade Scale category was “C”; and the Adjective Rating category was “Excellent”, while that using UEQ found that each category, namely Attractiveness, Perspicuity, Efficiency, Dependability, Stimulation, Dependability, and Novelty got a value greater than the impression value (0.8), namely 2.122; 2.117; 1.983; 1.750; 1.950 and 1,867, respectively. Overall, all of the evaluation results show that augmented reality-based books are acceptable to be used as media for learning Cirebon mask dance.

A Simple Vehicle Counting System Using Deep Learning with YOLOv3 Model Muhammad Fachrie
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 3 (2020): Juni 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Deep Learning is a popular Machine Learning algorithm that is widely used in many areas in current daily life. Its robust performance and ready-to-use frameworks and architectures enables many people to develop various Deep Learning-based software or systems to support human tasks and activities. Traffic monitoring is one area that utilizes Deep Learning for several purposes. By using cameras installed in some spots on the roads, many tasks such as vehicle counting, vehicle identification, traffic violation monitoring, vehicle speed monitoring, etc. can be realized. In this paper, we discuss a Deep Learning implementation to create a vehicle counting system without having to track the vehicles movements. To enhance the system performance and to reduce time in deploying Deep Learning architecture, hence pretrained model of YOLOv3 is used in this research due to its good performance and moderate computational time in object detection. This research aims to create a simple vehicle counting system to help human in classify and counting the vehicles that cross the street. The counting is based on four types of vehicle, i.e. car, motorcycle, bus, and truck, while previous research counts the car only. As the result, our proposed system capable to count the vehicles crossing the road based on video captured by camera with the highest accuracy of 97.72%.

Implementasi Algoritma Playfair Cipher dan Least Significant Bit pada Citra Digital Hermansa; Rusydi Umar; Anton Yudhana
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 3 (2020): Juni 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Message security is very important now. Because security is part of the privacy of someone who wants to protect messages from those who do not have the right to read or receive them. The method used for securing information messages with message encryption and decryption techniques is the Playfair Cipher algorithm combined with the Least Significant Bit (LSB) method. In this study it was found that the Playfair Cipher algorithm is quite safe in implementing cryptographic encryption or ciphertext because the playfair cipher has a level of appearance of letters that is so difficult to predict so that the ciphertext becomes a randomized collection of data. For the Least Significant Bit (LSB) steganography method in the insertion of a secret or embedded message it is difficult to guess in plain view the changes that occur between before and after the image is inserted are not too significant. Also see the value of the Peak-Signal-to-Noise ratio or PSNR can still be considered good quality due to> 30 decibels (dB). So the final result of the combination of the Playfair Cipher algorithm with the Least Significant Bit (LSB) method is quite good in securing messages.

Augmented Reality Untuk Media Promosi Hasil Penelitian Andrian Wikayanto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 3 (2020): Juni 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Science & Technopark (STP) was built to accelerate the process of transfer technology of research findings that have been discovered by LIPI. The research findings not only in the form of patents or products but also in the form of tools and buildings. To facilitate the understanding of stakeholders in the research findings an innovative media for the promotion of LIPI research findings was made using Augmented Reality (AR) media. This study uses a linear strategy method that combines text, posters, and videos into AR media. The AR application was tested on 25 LIPI stakeholders by distributing questionnaires using a Likert measurement scale. The results obtained are that AR not only effective in promoting commercial products but also very effective in promoting research products that have been found by LIPI at STP and making promotional activities more interesting and interactive.

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Yuhefizar

Contact Email
jurnal.resti@gmail.com

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+628126777956

Journal Mail Official
ephi.lintau@gmail.com

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

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INDONESIA

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

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