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Yuhefizar
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jurnal.resti@gmail.com
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+628126777956
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Politeknik Negeri Padang, Kampus Limau Manis, Padang, Indonesia.
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INDONESIA
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
ISSN : 25800760     EISSN : 25800760     DOI : https://doi.org/10.29207/resti.v2i3.606
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
Articles 462 Documents
Identifikasi Citra Beras Menggunakan Algoritma Multi-SVM Dan Neural Network Pada Segmentasi K-Means Nurfalah, Ridan; Dwiza Riana; Anton
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 1 (2021): Februari 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v5i1.2721

Abstract

Indonesia is a country with high rice needs because it is a staple food for more than 90% of populations. High demand requires high stock so imports are carried out in accordance with Permendagri Number 19/M-DAG/PER/3/2014 which explains rice import standards. There are many types of rice imported into Indonesia with various quality, color and import requirements such as for health or price stabilization. In terms of colors, imported white rice is the most consumed rice by Indonesians. One example is jasmine rice from Thailand. Meanwhile, in terms of imports, both for health and stabilizing the price of japonica rice (Japan) and Basmati (Pakistan) are the most imported to Indonesia. But there are still many who are not familiar with those three rices. In this research, the three types of rice were identified by comparing the Multi-SVM algorithm and Neural Network algorithm. Image acquisition is done using a flatbed scanner which produces 90 images divided into 63 training images and 27 testing images. K-Means becomes an image segmentation method and image binary converts. Feature extraction using morphological features with the regionprop method combined with the Gray Level Co-Occence Matrix (GLCM) produces 9 features that can produce 96.296% accuracy for Multi-SVM and 88.89% Neural Network
Hate Speech Classification on Twitter Using Support Vector Machine Oryza Habibie Rahman; Gunawan Abdillah; Agus Komarudin
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 1 (2021): Februari 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v5i1.2700

Abstract

Nowadays social media has become a place for peoples to express their opinions, there are many ways that can be done to express both positive and negative opinions. Hate speech is one of the problems that we find quite a lot in cyberspace, that things can be detrimental to many parties. Twitter as one of social media, can be used as a source of analysis about people's behavior in cyberspace. Many of our society that unconsciously act of hate speech on social media, therefore this study finds out how people's behavior patterns in cyberspace and the main issue of hate speech on a particular topic and time period by classify it into five classes, namely ethnicity, religion, race, inter-groups and neutral using Support Vector Machine. In this study also compares three kernel that common to use and the result is the system can classify hate speech by using RBF kernel and got the highest result with 93% accuracy on 700 data train and 300 data test.
Sistem Rekomendasi Produk Menggunakan Model RFM, AHP dan Ranked Clustering Monalisa, Siti; Asrori, Achmad Harpin; Kurnia, Fitra
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 3 No 2 (2019): Agustus 2019
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v3i2.810

Abstract

Monstreation is a business engaged in clothing convection, these business products are marketed online such as jackets and shirts for class, shirt and community clothing. The problem that occurs in this convection is the lack of product recommendation services to customers. Another problem is that if there are customers who order products that are not in accordance with their needs, the customer will rarely order products at Monstreation. The solution used is to provide services that match the characteristics of the customer, for example by giving product recommendations. Product recommendations are also needed considering this type of business is a business that has many business rivals. The steps taken in this study begin by collecting customer transaction data, then the data is transformed into RFM criteria data. After being transformed, the data is weighted using AHP, after that the RFM data is weighted then grouped / clustered. The grouping results are validated with DBI. From the experiments conducted it is known that the number of cluster 3 is the optimal number of clusters in product grouping. After it is ranked based on the value of the total weight. From the experiments conducted, it is known that the results of the 3 customer clusters, the customers who have the highest weight value are customers in cluster 1. The results of this study are a product recommendation that is an association of product history of customers who have a cluster similarity and a product recommendation information system.
Performance Testing of Five Back-End JavaScript Frameworks Using GET and POST Methods Eka Pratama, I Putu Agus
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v4i6.2675

Abstract

Currently, JavaScript is widely used in server-side (Back-End) website development. There are five choices of Back-End JavaScript frameworks that are commonly used: Koa, Express, Plumier, Loopback, Nest. Developers need to choose which framework has the best performance in order to produce a website with the best performance. For this reason, in this research, a comparsion of performance of the five Back-End JavaScript frameworks on the HTTP protocol was carried out using the GET and POST methods. Performance measurement uses two assessment parameters: 1.) The framework's ability to handle requests per second (req/s), 2.) Decrease in data processing speed (%) related to parsing, validation, routing, requests. Each tested framework is equipped with a router, body-parser, validator, NPM. Tests were carried out ten times on GET and POST, then obtain the average performance value of each framework. The test results show that Koa has the best performance and Loopback has the worst. From the results, it is recommended that Koa, Express, Plumier, be chosen by the developer, compared to Nest and Loopback.
Penggunaan Virtual Machine untuk Mengoptimalkan Server pada Cloud Gaming dengan GamingAnywhere Prabowo, Tiko Hadi; Hertiana, Sofia Naning; Sussi, Sussi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v4i6.2679

Abstract

The development of the game industry is increasingly advanced until the emergence of cloud gaming network technology. Cloud gaming allows low-spec clients to play high-spec games. An open-source cloud gaming platform is GamingAnywhere. In this study, we will implement a cloud gaming server using GamingAnywhere and combine it with a virtual machine. The virtual machines that will be used are VirtualBox and VMware. This research is aimed at providing information about resource usage on servers and clients as well as Quality of Service (QoS) and Frames Per Second (FPS) from GamingAnywhere running on virtual machines. From the results of server measurements it only takes 12-21% CPU usage, 5-7% GPU usage, and 75-77% memory usage for VirtualBox and 17-26% CPU usage, 26-35% GPU usage, and 64-65% memory usage for VMware. From the FPS measurement results obtained on the client, it has an average of more than 59 fps for the three test games when GamingAnywhere is running on VirtualBox, VMware, and without using a virtual machine. From the measurement results, to get optimal QoS in accessing games with GamingAnywhere, a minimum bandwidth of 5 Mbps is needed and the distance between the client and the router is a maximum of 7 meters. If the bandwidth is less than 5 Mbps, the system experiences a delay of ± 0.003 seconds and the packet loss is more than 10%.
Simulator Berbasis PLC untuk Pengaturan Lalu-lintas Jalan Raya pada Perlintasan Jalur Kapal Goeritno, Arief; Tirta, Sandi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v4i6.2668

Abstract

A PLC based simulator has been assembled for controlling road traffic at ship line crossings. The objectives of this study include (i) assembling a miniature bridge body, a lift-drop back mechanism for highway traffic at ship crossings, and an operating system based on a programmable logic controller (PLC) and (ii) measuring the performance of the operating system through its presence input-output signal. Assembly with the following stages: (i) implementation of miniature bridge construction; (ii) selection and placement of sensors; (iii) installation of pumps for hydraulic systems; (iv) installation of servo motor assisted latches; (v) installation of traffic control lights and indicators; and (vi) manufacture of operation panels, wiring, and installation of PLC systems. Mitsubishi PLC system programming is based on compiling algorithms and ladder diagrams with GX Works-2 32 bit. Performance measurement includes (i) when synchronization between the operating system and control on the PLC in the form of input from the operation panel and sensors on the input line are processed in the PLC program to produce an output in the form of appropriate and precise control, (ii) when the sensors installed in the system operation has functioned as programmed into the PLC, and (iii) during the process of lifting and lowering the miniature of the bridge body, there is a time difference of 26 seconds with the condition that the lifting time is longer than the time of lowering the miniature bridge body. The general conclusion is that the miniature of the bridge body and the operating system that has been built can be used as a simulator for the existence of a bridge that can be lifted and lowered again as a highway traffic lane at a ship crossing.
Analisis Data Sistem Informasi Geografis Rumah Tidak Layak Huni (RTLH) Menggunakan Metode Fuzzy Logic Hamdi, Khairil
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v4i6.2658

Abstract

Houses and other types of housing are things that cannot be separated from the needs of human life. The house function as a place to refuge, a place to live, and to gather with family. Proper housing is the basic need of all people who will strengthen the family, as the main pillar of the nation's strength, at the same time acting as a bastion against various health risks. The properness of a house for family housing becomes the basis for the growth and development of a better family life. Roofs, floors, and walls (aladin) are indicator data of whether a house is proper or not at the time of the survey. An adaptive, flexible and interactive computer-based system is used to solve unstructured problems so the more valuable decisions can be produced. This study describes how to process data using fuzzy logic methods. The expected result is to support the decision whether or not a house is feasible are in accordance with the facts and location data in the field. To determine which housing are categorized as severely damaged, moderate and lightly damaged by using the fuzzy logica method with roof, floor and wall variables as input variables so that local governments will find it easier to sort work priorities in the short, medium and long term
Pengambilan Keputusan Multi Hesitant N-Soft Sets Fatia Fatimah
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v4i6.2662

Abstract

In this article, we introduce a new hybrid model of -soft sets called multi hesitant -soft sets (MHNSS). The multi hesitant -soft sets is extention of -soft sets theory which is needed for multicriteria from some group decision makers. We propose the decision making algorithm of MHNSS dan apply it with real life data of distance education especially online learning using webinar tutorial. The population are tutors of Universitas Terbuka Padang that using webinar tutorial between April until May 2020. We use random sampling and spread questionnaires online to collect the data. As a result, by using the MHNSS algorithm, we conclude that webinar tutorial is effective for conceptual subjects.
99 / 5000 Hasil terjemahan JWT Implementation in Attendance Applications with Fingerprint Validation, Geotagging and Device Checker Arief Umarjati; Wibowo, Arief
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v4i6.2650

Abstract

During the Covid-19 pandemic the government implement the imposition of Large-Scale Social Restrictions (PSBB). This PSBB also has an impact on companies in Jabodetabek including PT Akses Digital Indonesia. In order to comply with regulations given by the government, PT Akses Digital Indonesia has implemented a Work From Home (WFH) policy for its employees. During the implementation of the WFH policy, had difficulty monitoring the performance of its employees. Attendance is one measure of the level of performance, especially employee discipline. Based on the identification of the problem, an employee presence web service application is needed. Of course, this application should be as effective as conventional fingerprint machines in offices. This application is accompanied by a validation feature using geotagging, fingerprint and device checkers to minimize fraud when employees make attendance. This study implements the RESTful API security feature on web services using JSON Web Token (JWT) based on the HMAC SHA-256 algorithm. All implementation stages are tested using the Black Box method and show that JWT can secure the authentication process and secure data. The validation feature is able to provide attendance data with an accuracy of 90,9%.
Implementasi Convolutional Neural Network untuk Klasifikasi Variasi Intensitas Emosi pada Dynamic Image Sequence Lia Farokhah
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v4i6.2644

Abstract

Facial emotion recognition (FER) is a research topic that focuses on the analysis of human facial expressions. There are many FER research has been conducted on single images or photo. Emotion analysis on single images has many disadvantages compared to dynamic image sequences or videos. This is due to human emotions or expressions within a certain time. The classification of emotions becomes complicated when considering different emotions. There are some people who are very expressive, there are some people who have low or moderate expressions. Predictions of emotion with variety intensities has decresed error due to data sets that provide only a few emotions intensities. Data annotation is a major problem in recognition fields that require a lot of time and effort to annotate new data. This study aims to find information about facial emotions with emotional intensity from subtle to sharp in a sequence images or videos. The dataset will be trained using Convolutional neural network by augmentation to add data annotations. The proposed method was evaluated using the public BP4D-Spontaneous dataset. The evaluation results show that the average emotion recognition in video sequences using the holdout method is 18%. Evaluation of the loss function parameter shows overfitting where the curve generalization gap is too high. The last evaluation is the evaluation of the emotion class between the real class and the prediction class in 14.28%. This shows that the classification of emotion recognition in dynamic image sequences is quite low.

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