Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
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
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1,046 Documents
<![CDATA[Implementation of JSON Web Token based on the SHA-512 Algorithm for Authentication on BatikKita Applications ]]>
<![CDATA[Andi Setiawan]]>;
<![CDATA[Ade Irma Purnamasari]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v4i6.2533
<![CDATA[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.]]>
<![CDATA[Pengelolaan Data Terintegrasi Berdasarkan Instrumen Akreditasi Perguruan Tinggi 3.0 Menggunakan Zachman Framework ]]>
<![CDATA[Ardhin Primadewi]]>;
<![CDATA[Mukhtar Hanafi]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v4i6.2540
<![CDATA[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.]]>
<![CDATA[Comparison of Clustering Methods in Grouping Puskesmas Data on Complete Basic Immunization Coverage ]]>
<![CDATA[Pelsri Ramadar Noor Saputra]]>;
<![CDATA[Ahmad Chusyairi]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v4i6.2556
<![CDATA[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.]]>
<![CDATA[Peramalan Data Indeks Harga Konsumen Berbasis Time Series Multivariate Menggunakan Deep Learning ]]>
<![CDATA[Soffa Zahara]]>;
<![CDATA[Sugianto]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 1 (2021): Februari 2021 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v5i1.2562
<![CDATA[Multivariate Time Series based forecasting is a type of forecasting that has more than one criterion changes from time to time that it can forecast based on historical patterns of data sequences. The Consumer Price Index (CPI) issued regularly every month by the Statistics Indonesia calculated based on data observations. This study is a development of previous research that only used on type of algorithm to predict CPI value resulting poor of accuracy due to lack of architecture variations testing. This study developed a CPI forecasting model with a new approach about using several types of deep learning algorithms, namely LSTM, Bidirectional LSTM, and Multilayer Perceptron with architectural variations of the number of neurons and epochs. Furthermore, this study adapt ADDIE model of Research and Development method. Based on the results, the best accuracy is obtained from the LSTM Bidirectional with 10 neurons and 2000 epoch resulting 3,519 of RMSE value. Meanwhile, based on the average RMSE value for the whole test, LSTM gets the smallest average of RMSE followed Bidirectional LSTM and Multilayer Perceptron with the RMSE value 4,334, 5,630, 6,304 respectively.]]>
<![CDATA[Classroom Attendance Based on Smiling Face Patterns and Nearby Wifi with Deep Learning ]]>
<![CDATA[Miftakhurrokhmat]]>;
<![CDATA[Rian Adam Rajagede]]>;
<![CDATA[Ridho Rahmadi]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 1 (2021): Februari 2021 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v5i1.2575
<![CDATA[Students' attendance in class is often mandatory in education and becomes a benchmark for assessing students. Sometimes there are still fraudulent practices by students to achieve minimum attendance. From the administrative perspective, a paper-based presence system is potentially wasteful and extends the administrative stage because it requires manual recapitulation. This study aims to design a class attendance application based on facial pattern recognition, smile, and closest Wi-Fi. The method used in this research is a deep learning approach with CNN based architecture, FaceNet, to recognize faces. In addition to facial images, the system will also validate the attendance with location and time data. Location data is obtained from matching SSID from the database, and time data is taken when the user sends attendance data through API. This attendance system consists of three applications: web, mobile, and services installed on a mini-computer, which are integrated to sending attendance data to the academic system automatically. As confirmation, students are required to smile selfies to strengthen the validity of their presence. The testing model's accuracy results are 92.6%, while for live testing accuracy the model obtained 66.7%.]]>
<![CDATA[Causal Modeling of Self Burden, Sosial Support, Spiritual Needs with CRF Using S3C-Latent ]]>
<![CDATA[Putri Mentari Endraswari]]>;
<![CDATA[Ridho Rahmadi]]>;
<![CDATA[Christantie Effendy]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v4i6.2577
<![CDATA[Cancer patients experience cancer-related fatigue (CRF) that are subjective and persistent. CRF can have a negative impact on psychosocial, spiritual, and self-perceived burden. To understand more deeply about CRF, we need to answer one fundamental question: how are the causal mechanisms (cause-effect) of the factors related to CRF. The studies related so far are still limited to correlation analysis between factors and have not focused on the mechanism of a causal relationship. The purpose of this study is to model the causal relationship between CRF and psychosocial, spiritual, and self-perceived burden, using a causal method called the Stable Specification Search for Cross-Sectional Data With Latent Variables (S3C-Latent). The results of this study are in the form of causal modeling between factors where self-burden has a causal relationship with CRF, spiritual need factors (religion) also have a causal relationship with CRF. Meanwhile, the social support factor (friends) with spiritual needs (religion) does not represent a causal relationship, but there is a strong association relationship. Meanwhile, the social support factor (friends) with CRF did not have a causal relationship or an association relationship between the two variables.]]>
<![CDATA[Implementasi Enkripsi dan Otentikasi Transmisi Data pada ZeroMQ Pipeline Menggunakan Enkripsi AES ]]>
<![CDATA[I Made Sukarsa]]>;
<![CDATA[I Made Rama Pradana]]>;
<![CDATA[Putu Wira Buana]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v4i6.2581
<![CDATA[Communication via sockets is used to transmit information between applications or between processes over network or locally. ZeroMQ is a library for sending messages using sockets that are quite well known. Talking about sending data, message security is an important part that needs to be taken into account, especially when sending data over a network. ZeroMQ sends messages openly without securing the messages sent. This is evidenced by research which states that ZeroMQ does not have a security layer for sending messages over the network and direct observation of message packets using the wireshark application. Therefore, this study creates a method of securing and authenticating message delivery using AES (Advanced Encryption Standard) CBC (Cipher Block Chaining) mode combined with an authentication method. The AES CBC mode was chosen because it is faster than other methods and has strong encryption. This encryption and authentication are used so that the sender and recipient of the message are both valid senders and recipients so that no message changes during message delivery and messages can only be opened by the message recipient and the sender of the message. Tests are conducted to measure the effect of encryption and authentication on message delivery performance. Based on the tests conducted, there is an increase of 7% from normal delivery speed and the potential for messages is not up to 0.3% - 1.5%.]]>
<![CDATA[Sistem Referensi Pemilihan Smartphone Android Dengan Metode Fuzzy C-Means dan TOPSIS ]]>
<![CDATA[Giovan Meidy Susanto]]>;
<![CDATA[Sandy Kosasi]]>;
<![CDATA[David David]]>;
<![CDATA[Gat Gat]]>;
<![CDATA[Susanti M. Kuway]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v4i6.2584
<![CDATA[Difficulties faced by STMIK Pontianak students while choosing an Android smartphone are the diversity of brands, types, series and specifications makes it hard to choose which is the best. Determine that matches to needs along with an appropriate budget also difficult. This research aims to design a reference system for selecting an Android smartphone to resolve the problem. This system was developed using the Fuzzy C-Means algorithm and TOPSIS. The research method used is survey. Software design uses agile with extreme programming models also White-Box Testing, cluster center testing, and acceptance testing. This research found a method to get an alternative group that matches to the user from existing cluster by Euclidean Distance. This research produces a system that can clustering smartphone data and provide references in the form of alternatives that matches to the user. The test results using White-Box Testing produce all functions running well. Testing the cluster center using MSE gets the central error values C1: 1.8481, C2: 2.5316, and C3: 1.8214. Acceptance tesing results above 70%. Weaknesses in this system do not discuss lifestyle needs in choosing an Android smartphone. The criteria used in this research is still technical and not use non-technical criteria.]]>
<![CDATA[Analisis Sentimen dan Pemodelan Topik Pariwisata Lombok Menggunakan Algoritma Naive Bayes dan Latent Dirichlet Allocation ]]>
<![CDATA[Ni Luh Putu Merawati Putu]]>;
<![CDATA[Ahmad Zuli Amrullah]]>;
<![CDATA[Ismarmiaty]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 1 (2021): Februari 2021 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v5i1.2587
<![CDATA[Lombok Island is one of the favorite tourist destinations. Various topics and comments about Lombok tourism experience through social media accounts are difficult to manually identify public sentiments and topics. The opinion expressed by tourists through social media is interesting for further research. This study aims to classify tourists' opinions into two classes, positive and negative, and topics modelling by using the Naive Bayes method and modeling the topic by using Latent Dirichlet Allocation (LDA). The stages of this research include data collection, data cleaning, data transformation, data classification. The results performance testing of the classification model using Naive Bayes method is shown with an accuracy value of 92%, precision of 100%, recall of 84% and specificity of 100%. The results of modeling topics using LDA in each positive and negative class from the coherence value shows the highest value for the positive class was obtained on the 8th topic with a value of 0.613 and for the negative class on the 12th topic with a value of 0.528. The use of the Naive Bayes and LDA algorithms is considered effective for analyzing the sentiment and topic modelling for Lombok tourism.]]>
<![CDATA[The Analysis of Dilation Morphology for Quality Improvement of the Edge Detection Imagery on Batik Patterns using Prewitt Operator and Laplacian of Gaussian ]]>
<![CDATA[Muhammad Abrar Masril]]>;
<![CDATA[Refli Noviardi]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 6 (2020): Desember 2020 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v4i6.2601
<![CDATA[The results of the edge detection process using several operators are not yet optimal. Therefore we need a method to improve the quality of edge detection images, the method used in this study is morphology dilation. The results of testing the improvement of image quality using 10 batik patterns, resulting in an accuracy level on Laplacian of Gaussian operators is 80% and for Prewitt operators is 60%. In the process of improving the edge detection quality, Morphology Dilation can connect broken edges using structuring elements. therefore it can improve the quality of edge images.]]>
