cover
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
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 21 Documents
Search results for , issue "Vol 4 No 4 (2020): Agustus 2020" : 21 Documents clear
Emotion Classification of Song Lyrics using Bidirectional LSTM Method with GloVe Word Representation Weighting Jiddy Abdillah; Ibnu Asror; Yanuar Firdaus Arie Wibowo
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 4 (2020): Agustus 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v4i4.2156

Abstract

The rapid change of the music market from analog to digital has caused a rapid increase in the amount of music that is spread throughout the world as well because music is easier to make and sell. The amount of music available has changed the way people find music, one of which is based on the emotion of the song. The existence of music emotion recognition and recommendation helps music listeners find songs in accordance with their emotions. Therefore, the classification of emotions is needed to determine the emotions of a song. The emotional classification of a song is largely based on feature extraction and learning from the available data sets. Various learning algorithms have been used to classify song emotions and produce different accuracy. In this study, the Bidirectional Long-short Term Memory (Bi-LSTM) deep learning method with weighting words using GloVe is used to classify the song's emotions using the lyrics of the song. The result shows that the Bi-LSTM model with dropout layer and activity regularization can produce an accuracy of 91.08%. Dropout, activity regularization and learning rate decay parameters can reduce the difference between training loss and validation loss by 0.15.
Penilaian Tata Kelola dan Manajemen Layanan Teknologi Informasi dengan Cobit 2019 dan ITIL 4 Nachrowi, Erika; Yani Nurhadryani; Heru Sukoco
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 4 (2020): Agustus 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v4i4.2265

Abstract

The implementation of E-government evaluation is already a necessity to know the level of process of governance and management of service and provide improvement suggestions for quality improvement. Evaluation of the governance and management of services at the Directorate Institutional, Directorate General of Higher Education using the COBIT 2019, by measuring the capability process level based on the design factor which recommends improvement priorities in the 11 domain COBIT 2019 and the level of user satisfaction of service applications using the E-govqual model. IT capability level assessment results have 3 levels 0 processes or no existing approaches, 6 levels 1 processes or incomplete approaches, 1 level 2 process or initial approach fulfils the intent of the practice area and 1 Process level 3 or achievement of objectives is much more organized. Service Satisfaction rate measurement get 3 criteria in Quadrant A or priority improvement, 13 criteria in quadrant B or maintained, 12 criteria in quadrant C or less priority and 3 criteria in Quadrant D or less expected. Repair recommendations are compiled based on the SWOT model, referring to COBIT 2019 and ITIL 4. The results of the recommendation include increased competency of human resources and integrate services with PDDIKTI.
Implementasi Golang dan New Simple Queue pada Sistem Sandbox Pihak Ketiga Berbasis REST API Albertus Ari Kristanto; Harjoseputro, Yulius; Joseph Eric Samodra
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 4 (2020): Agustus 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v4i4.2218

Abstract

A good application development requires a testing phase to ensure there are no errors before it’s released to public. But testing phase becomes difficult if the application development involves features from third parties. The idea to resolve the problem for Dhanapala application under the auspices of PT. Semangat Gotong Royong is to make the Sandbox system which is a system designed to resemble the characteristics of a third party. The Sandbox system will be developed into a REST API and written using the Golang programming language. In conducting communications with other systems New Simple Queue (NSQ) is also used that can support concurrency and prevent data transmission failures. As a result, the Sandbox system can receive requests and will process responses that are similar to functions from third parties. All forms of feature calls to third parties can be transferred to the Sandbox system so that all the data needs on some functions involving third parties can be fulfilled and the Dhanapala application can be run without its dependence on third parties
Implementasi Anti Forensik pada Harddisk Menggunakan Metode DoD 5220.22 M dan British HMG IS5 E Hasa, Muh Fadli; Anton Yudhana; Abdul Fadlil
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 4 (2020): Agustus 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v4i4.2165

Abstract

The process of securing data is related to anti-forensic science, one of the anti-forensic techniques that can be used to safeguard data security, namely by deleting data on storage media. This study examines the implementation of data deletion using the DoD 5220.22 M and British HMG IS5 E methods, then compares these methods. The comparison of the two methods includes performance tests, forensic tests, and data recovery tests. The results of the performance test show that the two methods are strongly influenced by the anti-forensic tools used and do not provide a significant difference when applied using one of the tools. The results of the implementation of data deletion using both methods on the hard disk drive are declared safe to delete data, as evidenced by the extraction results in the forensic test using the Autopsy tool found files on the partition :F with the number of 252 files and on the partition :I with the number of 1 file and the extraction results from the test Forensics using the Recover My File tool managed to find files with the number of 102 files on different partitions, but all the files found in the forensic test process cannot be accessed. The results of the recovery test show that the safest method in the process of deleting data is the British HMG IS5 E method using the Active @ Kill Disk tool, as evidenced by all the results of the recovery process using three tools that do not find any files. Meanwhile, the application of the deletion method that is generally carried out by users, namely the shift + delete method, is declared unsafe, as evidenced by the results of the recovery tests conducted showing that the deleted files can be recovered 100% and can be reaccessed using recovery tools.
Investigasi Cyberbullying pada WhatsApp Menggunakan Digital Forensics Research Workshop Imam Riadi; Sunardi; Widiandana, Panggah
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 4 (2020): Agustus 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v4i4.2161

Abstract

Cyberbullying in group conversations in one of the instant messaging applications is one of the conflicts that occur due to social media, specifically WhatsApp. This study conducted digital forensics to find evidence of cyberbullying by obtaining work in the Digital Forensic Research Workshop (DFRWS). The evidence was investigated using the MOBILedit Forensic Express tool as an application for evidence submission and the Cosine Similarity method to approve the purchase of cyberbullying cases. This research has been able to conduct procurement to reveal digital evidence on the agreement in the Group's features using text using MOBILedit. Identification using the Cosine method. Similarities have supported actions that lead to cyberbullying with different levels Improved Sqrt-Cosine (ISC) value, the largest 0.05 and the lowest 0.02 based on conversations against requests.
Evaluasi Pemanfaatan Teknologi Informasi Pada Matakuliah Jaringan Komputer di Era Pandemi Covid-19 Elfizar, Elfizar
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 4 (2020): Agustus 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v4i4.2153

Abstract

The Covid-19 pandemic makes massive use of information technology (IT) in various fields. This study aims to evaluate the use of IT in Computer Networks lectures at the Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Riau in the era of Covid-19 Pandemic. This causal comparative study uses data from the results of student achievement in the Even Semester Academic Year 2019/2020. There are two lecture models given to students namely synchronous and asynchronous models. The use of the model is based on the type of lecture material provided. Furthermore, the results of student achievement obtained at the end of the semester are compared with the results of student achievement in the previous year that used physical face-to-face lectures. The results of this study indicate that there was an increase of 7.17% in the student achievement during the use of IT in lectures during the Covid-19 Pandemic with the effective synchronous lectures duration from 60 to 100 minutes.
Pencitraan Digital Nyala Lampu Hemat Energi Berbasis Single Board Computer Hadid Tunas Bangsawan; Lukman Hanafi; Deny Suryana
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 4 (2020): Agustus 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v4i4.2146

Abstract

Computer Vision (CV) is an interdisciplinary scientific field that discusses how computers can gain a high-level understanding of digital images or video. A system has been created that is capable of detecting a compact fluoresence lamp (CFL) light. However, in previous research there is no justification that the lamp is only a part that can glow on the lamp alone and has not been done in multi-lamp testing. This study aims to compare the lamp segmentation when it goes OFF and ON so that it could be justified the accuracy of this system and does multi-lamp testing. The method used is an experiment with collecting data by direct observation of the results of the system made. The system consists of a single board computer and a common webcam. The result is the difference between the lamp segmentation when it goes OFF and ON is small with the appropriate threshold setting. So that lamp light imaging had been made could function with good reability.
Optimasi Model Transfer Learning Convolutional Neural Network Untuk Klasifikasi Citra CIFAR-10 Rastri Prathivi
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 4 (2020): Agustus 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v4i4.2131

Abstract

The low accuracy when performing the image classification process is a problem that often occurs. The image classification process requires the completeness of the features of the image which form an informative image pattern so that information from the image can be displayed. The purpose of this study is to classify images in the CIFAR-10 image dataset using the CNN method. Initially the CNN method gave an accuracy of 79.4% but had a long computation time of 12 hours with 10,000 iterations. The optimization process for the CNN method is carried out by combining the CNN method, the PCA algorithm and the t-SNE algorithm. The algorithm is used to reduce the length of the image matrix in the initial transfer of learning without reducing the information in the image so that the classification process can be done correctly. The final result obtained from the optimization has an accuracy of 90.5%. With an optimization rate of 11%. The resulting time is more efficient, namely 3 hours for the feature transfer-value process and 6 minutes for the testing process with 10,000 iterations.
Identifikasi Berita Palsu (Hoax) pada Media Sosial Twitter dengan Metode Decision Tree C4.5 Irena, Brenda; Erwin Budi Setiawan
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 4 (2020): Agustus 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v4i4.2125

Abstract

Social media is a means to communicate and exchange information between people, and Twitter is one of them. But the information disseminated is not entirely true, but there is some news that is not in accordance with the truth or often called hoaxes. There have been many cases of spreading hoaxes that cause concern and often harm a particular individual or group. So in this research, the authors build a system to identify hoax news on social media Twitter using the Decision Tree C4.5 classification method to the 50,610 tweet data. What distinguishes this research from some researches before is the existence of several test scenarios, classification only, classification using weighting feature, and also classification using weighting feature and feature selection. The weighting method used is TF-IDF, and the feature selection uses Information Gain. The features used are also generated using n-grams consisting of unigram, bigram, and also trigrams. The final results show that the classification test that uses weighting feature and feature selection produces the best accuracy of 72.91% with a ratio of 90% training data and 10% test data (90:10) and the number of features used is 5000 in unigram features.
Pemanfaatan Optical Character Recognition Dan Text Feature Extraction Untuk Membangun Basisdata Pengaduan Tenaga Kerja Yan Puspitarani; Yenie Syukriyah
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 4 (2020): Agustus 2020
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v4i4.2107

Abstract

The examination of complaints of labor violations is part of the main activity of the labor inspection section within the Department of Manpower. Monitors will examine companies that are considered to have violated labor laws based on a letter of complaint sent by the relevant union organization or legal aid agency. The easy way to communicate at this time, making the submission of complaint letters can be directly sent in the form of images through electronic media such as whatsapp or email. This makes it difficult for administrative staff to recapitulate incoming complaints because they have to read and enter data manually into the system. Therefore, this research was conducted to create a system that utilizes OCR technology and text feature extraction to be able to input complaints data automatically. This research resulted in a prototype of letter input and a database of letter storage that can be further utilized for Data Mining and Business Intelligent. OCR implementation is done by using the Tesseract library while the text feature selection utilizes the Natural Language Toolkit (NLTK) library. The results of testing of the prototype showed an accuracy of 66.7% of the OCR results and 91.67% of the manually typed letters.

Page 1 of 3 | Total Record : 21