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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 26 Documents

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Search results for , issue "Vol 4 No 6 (2020): Desember 2020" : 26 Documents clear

Implementation of Convolutional Neural Network and Multilayer Perceptron in Predicting Air Temperature in Padang Isman Kurniawan; Lusi Sofiana Silaban; Devi Munandar
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Weather prediction is usually performed for a reference in planning future activity. The prediction is performed by considering several parameters, such as temperature, air pressure, humidity, wind, rainfall, and others. In this study, the temperature, as one of weather parameters, is predicted by using time series from January 2015 to December 2017. The data was obtained from Lembaga Ilmu Pengetahuan Indonesia (LIPI) weather measurement station in Muaro Anai, Padang. The predictions were carried out by using Convolutional Neural Network (CNN), Multilayer Perceptron (MLP), and the hybrid of CNN-MLP methods. The parameters used in the CNN method, such as the number of filters and kernel size, and used in the MLP method, such as the number of hidden layers and number of neurons, were selected by performing the hyperparameter tuning procedure. After obtaining the best parameters for both methods, the performance of both methods was evaluated by calculating the value of Root Mean Square Error (RMSE) and R2. Based on the results, we found that the prediction by CNN is more accurate than other method. This is indicated by the highest value of R2 of the prediction obtained by CNN method.

Advanced Encryption Standard (AES) 128 Bit untuk Keamanan Data Internet of Things (IoT) Tanaman Hidroponik Roiya Ravida; Heru Agus Santoso
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

One method of growing vegetables is to use hydroponics by utilizing water as the medium used. In this era of rapidly developing technology, one of which is Internet of Things (IoT) is a system between computers or objects that can connect and exchange data without requiring interaction, because the data sent is public data, a security system is needed to secure the data sent. Advanced Encryption Standard (AES) 128 bits are used to secure data sent by users or data received by users, using a private key so that data security is maintained. The process of encryption and decryption was carried out through the website using an Arduino Uno microcontroller, SoC version ESP 8266. To adjust the rules for controlling plant needs such as Total Dissolve Solid (TDS), Potential Hydrogen (PH), temperature, and distance, this study uses Sensor2. Database in the research used to facilitate computerized access to assist the process of caring for IoT-based hydroponic plants. The final results have been tested in the encryption decryption process, Avalanche Effect (AE), entropy and Bit Error Ratio (BER). The AE yield 58.01% as highest score, the highest entropy was 6.3566 while all data resulted in BER = 0.

EPDSAp: Aplikasi Skrining Baby Blues Berbasis Android dengan Uji Sensitivitas dan Spesifisitas Novinaldi Novinaldi; Feiby Edwardi; Imam Gunawan; Desi Sarli
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Baby Blues Syndrome is depression that occurs in mothers within a few hours after giving birth, until a few days after delivery, and then it will disappear by itself if given good psychological care. One method to detect postpartum Baby Blues Syndrome is to use the EPDS (Edinburgh postnatal depression scale). However, currently, EPDS can only be done by health workers. Mothers cannot carry out their screening using this method. The purpose of this research is to produce an Android-based EPDS application that will be able to detect the symptoms of baby blues syndrome early after childbirth. Where the detection of the symptoms of baby blues syndrome can be carried out by postpartum mothers themselves quickly and easily, which in turn will reduce the negative impact of this syndrome. This study uses the System Development Life Cycle (SDLC) research method, where the stages of the activity plan are System / Information Engineering and Modeling, Software Requirements Analysis, Systems Analysis and Design, Code Generation, Testing, Implementation, and Maintenance. This EPDS application was built using Android Studio programming which can detect a postpartum mother experiencing the baby blues. This android-based EPDS design has a home screen form design, a questionnaire form design, and a result form design. This application displays results based on a score above 10, so the mother experiences depression or baby blues, while the score between 5 and 9 requires supervision of the mother and re-evaluation using the EPDS application.

Uji Validasi Algoritme Self-Organizing Map (SOM) dan K-Means untuk Pengelompokan Pegawai Titik Susilowati; Dedy Sugiarto; Is Mardianto
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Managing employee work discipline needs to be done to support the development of an organization. One way to make it easier to manage employee work discipline is to group employees based on their level of discipline. This study aims to group employees based on their level of discipline using the Self Organizing Map (SOM) and K-Means algorithm. This grouping begins with collecting employee attendance data, then processing attendance data where one of them is determining the parameters to be used, then ending by implementing the clustering algorithm using the SOM and K-Means algorithms. The results of grouping that have been obtained from the implementation of the SOM and K-Means algorithms are then validated using an internal validation test consisting of the Dunn Index, the Silhouette Index and the Connectivity Index to obtain the best number of clusters and algorithms. The results of the validation test obtained 3 best clusters for the level of discipline, namely the disciplinary cluster, the moderate cluster and the undisciplined cluster.

Literature Review: Legalisasi Dokumen Elektronik Menggunakan Tanda Tangan Digital sebagai Alternatif Pengesahan Dokumen di Masa Pandemi Trihastuti Yuniati; Muhammad Fajar Sidiq
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

With a pandemic that has hit almost all over the world, the government has issued policies for doing physical distancing and work from home (WFH). That policies made a very significant change in the way people work and interact. WFH applies in most fields of work, one of them is in education. WFH and online learning require every student, lecturer and employee to work online from home. In fact, there are many activities that require validation in the form of a signature, both for academic and non-academic matters. Digital signature is a technology that can be applied to overcome this problem. There are various algorithms and schemes that users can implement. This paper will present the results of a review of several literature related to the implementation of digital signatures. The results of this literature review are expected to provide the readers with an insight of the implementation of digital signatures in various fields, as well as their strengths and weaknesses.

Sistem Pengecekan Toko Online Asli atau Dropship pada Shopee Menggunakan Algoritma Breadth First Search Nurdin; Muhammad Hutomi; Mukti Qamal; Bustami Bustami
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

The abundance of online shops on web ecommerce Shopee's makes it difficult for consumers to detect the genuineness of an online store. Online store detection app is an application to detect genuine online shop, good rating online shop, and fake online shop, which is useful as a recommendation to consumers in buying a product against an online shop. Detection by implementing the Breadth First Search (BFS) algorithm with Web Scraping techniques against Web e-commerce Shopee with the keyword "Kemeja Pria" with a search number of 5000, generate 1389 online shops data with the detection results of genuine online shop, good rating online shop, and fake online shop respectively as many as 90 online shops (6.5%), 948 online shops (68.3%), and 351 online shops (25.3%). The time it takes for the system to visit each node, from the first node to the 1389 node by applying the Breadth First Search algorithm takes about 2,690,021 second, or about 44.833683333 minutes, with the queue formation process, node browsing, online shop detection, and test results. The results reveal that the Breadth First Search algorithm is a simple algorithm that can be used to perform online store detection with good performance.

Prototype Pendeteksi Daerah Rawan Kecelakaan Berbasis Internet of Things Yankotinu Al Qod'r Jonnata; Fahrudin Mukti Wibowo; Iqsyahiro Kresna A
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

The high number of deaths due to traffic accidents is still a problem for every country where Indonesia ranks third in Asia with 38,279 deaths according to the 2015 Global Status Report on Road Safety. Blackspots scattered in Indonesia has a role in contributing to the death rate, however not all blackspots are equipped with warning signs. Based on these problems then developed a prototype in the form of a device for detecting and website as the central information system of blackspots based Internet of Things. The prototype is designed using an Arduino Uno Rev 3 microcontroller equipped with a GPS module to measure vehicle speed and distance from the setpoint before arriving on blackspots, a GSM module to download blackspots data and upload speed and distance data to the database, and LED components, speakers/buzzer, OLED display to provide notification every time crossing the setpoint of blackspots. The usability testing performance measurement method is used to measure the performance of the device prototype and the black box testing method is used to validate each function of the website system. The results of this research obtained the success rate of the prototype device was 60% with the highest error rate of 19.09% at the 1500m setpoint for speed and 57.98% at 10m setpoint for the distance.

Implementation of JSON Web Token based on the SHA-512 Algorithm for Authentication on BatikKita Applications Andi Setiawan; Ade Irma Purnamasari
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Batikkita is an android based application and web framework laravel web service architecture that is used to bring together between craftsmen and consumers of batik Trusmi and batikkita application with the e-commerce model used is business to customer. The backend system interface used is a web framework while the frontend system interface used is android. The problem that arises from the Batikkita application is that the security of users, both as sellers and consumers, is very vulnerable to being hacked, so it is very detrimental to both sellers and buyers. This study aims to implement the JSON Web Token based on the HMAC SHA-512 algorithm in the Batikkita application in order to provide a sense of security for both the seller and the buyer before entering the sales transaction page. The application development method used is Rapid Application Development because the cycle used to develop our batik application is very short so it is very helpful in this research. While the implementation of JSON Web Token with the HMAC SHA-512 algorithm in the Batikkita application is used to improve user security when logging in to the Batikkita application in the form of a token and the password used by the user is wrapped in a token given by the Batikkita application. As a comparison, the HMAC SHA-256 algorithm and the HMAC SHA-384 algorithm are used. The results obtained from testing the implementation of JSON Web Token with the SHA-512 algorithm in our batik application, for an average increase of speed between 138.8 milliseconds for SOAP and 122.7 milliseconds for REST compared to the HMAC SHA-256 algorithm and the HMAC SHA-algorithm. 384. While the required token size is greater between 2.13 kb for SOAP and 2.11 kb for REST compared to the HMAC SHA-256 algorithm and the HMAC SHA-384 algorithm.

Pengelolaan Data Terintegrasi Berdasarkan Instrumen Akreditasi Perguruan Tinggi 3.0 Menggunakan Zachman Framework Ardhin Primadewi; Mukhtar Hanafi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Higher education in Indonesia is regulated by the government with the Higher Education Accreditation (APT). In APT 3.0, Higher Education is required to be able to present performance data in the form of a Higher Education Performance Report (LKPT) as a reference in making a Self-Evaluation Report (LED). However, it is necessary to have an in-depth analysis to determine the gaps in the data required by Higher Education according to the APT 3.0 standard. The process of integrating the samples refer to the Zachman Framework (ZF). The results of this simplification that the data is available in support of APT 3.0 approximately 79% of the total data both inside and outside the core business of Higher Education and is well managed in an integrated database. The remaining 21% of the data that are not available is spread across several information systems, especially SIMMawa, SIMHumas and Cooperation, and SIMAKU. This shows that the change in accreditation standards that have been in effect since April 2019 has created a significant data gap for Higher Education. This research also produced an alternative model of integrated data management that can be used as input for Information System developers in the Higher Education scope.

Comparison of Clustering Methods in Grouping Puskesmas Data on Complete Basic Immunization Coverage Pelsri Ramadar Noor Saputra; Ahmad Chusyairi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

The coverage of Health Care Center toward UCI (Universal Child Immunization) at Banyuwangi Regency in 2018 met the target 91%. Onfortunately with a high amount of immunization, the number of infant deaths reached 138 infants. Total number increased 111 from the previous year. A review of the complete basic immunization data needs to be done. In this research, a clustering method was proposed by comparing the K-Means and Fuzzy C-Means (FCM) algorithm in grouping Health Care Center data. Silhouette Coefficient and Standart Deviation were used to evaluate clusters that were perfomed to find out the accuracy in grouping data. The result showed that the FCM algorithm was better than K-Means based on Silhouette Coefficient results that were close to good, and the calculation of Standart Deviation had a smaller result that was 0.0918 than K-Means with the results of 0.0942. The Grouping of Heath Care Center data can be considered by the Health Department of Banyuwangi Regency in evaluating complete basic immunization services, especially in groups with poor immunization services to reduce infant and child mortality, so a disease that can be prevented with immunization become lower.

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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

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Abstract

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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