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
Articles
1,046 Documents
<![CDATA[Neural Network Backpropagation Identifikasi Pola Harga Saham Jakarta Islamic Index (JII) ]]>
<![CDATA[Musli Yanto]]>;
<![CDATA[Liga Mayola]]>;
<![CDATA[M. Hafizh]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 1 (2020): Februari 2020 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v4i1.1266
<![CDATA[Jakarta Islamic Index (JII) is an organization engaged in the economy with the aim to pay attention to stock movements every day. With the JII, people who do not understand about shares and their movements, will be easy to know and understand the movement of shares that occur at certain times. The problem in this research is that many investors are unable to predict the rise and fall of stock prices. The prediction process can be done with a backpropagation algorithm. The algorithm is a concept of computer science which is widely used in the case of analysis, prediction and pattern determination. The process starts from the analysis of the variables used namely interest rates, exchange rates, inflation rates and stock prices that occurred in the previous period. The variables used are continued in the formation of network patterns and continued in the process of training and testing in order to produce the best network patterns so that they are used as a process of identifying JII stock price movements. The results obtained in the form of the value of stock price movements with an error rate based on the MSE value of 11.85% so that this study provides information in the form of knowledge for making a decision. The purpose of the research is used as input for investors in identifying share prices. In the end, the benefits felt from the results of this study, investors can make an initial estimate before investing in JII.]]>
<![CDATA[Analisis Citra Penyakit Diabetic Retinopathy Berdasarkan Algoritme Jaringan Syaraf Tiruan ]]>
<![CDATA[Tri Astuti]]>;
<![CDATA[Gesha Agus Setiawan]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 2 (2020): April 2020 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v4i2.1269
<![CDATA[Diabetic retinopathy is a complication of diabetes in the form of damage to the retina of the eye. High levels of glucose in the blood are the cause of small capillary blood vessels to rupture and can cause blindness. The signs of this disease can only be seen using retinal fundus images. To identify diabetic retinopathy, a computerized process and analysis are needed, one of which uses artificial neural network methods to determine its performance so that it will help the doctor in analyzing the disease and diagnosing whether a patient suffering from diabetic retinopathy or not. Texture feature extraction method using Gabor filter can represent feature value information that is skewness, kurtosis, mean, entrophy, and variance to be processed at the identification stage using artificial neural network methods. The comparison results of the DIARETDB0 dataset testing with the total of 130 fundus images using the backpropagation ANN method before randomizing the data yielded an accuracy value of 82.30%, a precision value of 71.28%, a recall value of 82.30%, and an f-measure of 76.39%. Whereas after randomizing the data for 30 times, the results of accuracy value were higher than before randomizing the data, namely the accuracy value of 83.07%, the precision value of 71.39%, the recall value of 83.07% and f-measure value of 76.78%. The tests carried out included in good classification.]]>
<![CDATA[Synthetic Minority Oversampling Technique pada Averaged One Dependence Estimators untuk Klasifikasi Credit Scoring ]]>
<![CDATA[Omer Heranova]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 3 No 3 (2019): Desember 2019 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v3i3.1275
<![CDATA[Bank or financial institution is a business entity whose activities are collecting funds from the public in the form of deposits and channeling them to the public in the form of credit and or other forms. In credit financing problems often occur and one of the problems faced in credit assessment is imbalance class data sets or dataset class imbalances. This problem can be overcome by resampling method, namely by using Oversampling, undersampling and hybrids that combine the two sampling approaches. This research proposes the method of applying SMOTE or Synthetic Minority Oversampling Technique on Averaged One Dependence estimators (AODE) to improve the performance of the accuracy of the credit rating classification on German Credit Creditetsets. The results of this experimental study on the GermanCredit dataset with the classification method without the Resampling process on 13 classifiers produce an average performance value of 70%. The results of the classification with classification techniques that apply the SMOTE method on the AODE algorithm can increase the accuracy performance by 5.5% with an accuracy value of 0.817 or 81.69%. While the classification technique that applies the SpreadSubSample + AODE method decreased by 0.041 or 4.1% but still higher than the accuracy value of other methods with an accuracy value of 0.723 or 72.33%. The researcher concludes that by applying the Resampling technique with the SMOTE method on the AODE algorithm can increase the value of accuracy performance effectively on the imbalance class used for credit scoring or credit rating on GermanCredit datasets.]]>
<![CDATA[Implementasi Extreme Programming pada Aplikasi "SIATAP" Sistem Informasi Tanya Apoteker Berbasis Android dan Website ]]>
<![CDATA[Rizki Wahyudi]]>;
<![CDATA[Agus Junadi]]>;
<![CDATA[Haryani]]>;
<![CDATA[Andi Saryoko]]>;
<![CDATA[Donna Setiawati]]>;
<![CDATA[S.M Santi Winarsih]]>;
<![CDATA[Gustin Setyaningsih]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 2 (2020): April 2020 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v4i2.1278
<![CDATA[The pharmacist is a professional degree for someone who has taken the oath of pharmacist position. Pharmacists are expected to be able to improve knowledge, skills, behaviour to be able to interact with patients. The form of interaction is giving information on medicines and counselling. In its service, pharmacists identify, prevent, overcome drug-related problems, and this has the possibility of medication errors. This research aims to build communication media between pharmacists and patients "SIATAP". The application will be developed using the extreme programming method. The advantages of this method can increase client satisfaction due to good communication so that it gets direct input from clients. Android application is designed for communication media between pharmacists and patients, the website application design to manage data for the administrator and pharmacist. To ensure the feasibility of the system, testing is done by using alpha and acceptance testing. The results of the alpha testing of all functional systems can run as expected. The results of the Acceptance Testing, using a questionnaire obtained a percentage of 92.57% with the conclusion that the application can be a good response from users so that the application is feasible to be implemented. The application can be downloaded at the URL: http://bit.ly/2ATy6hT.]]>
<![CDATA[Kematangan Keselarasan Strategis Bisnis dan TI pada Lembaga Edukasi dan Konsultasi TI ]]>
<![CDATA[Clara Hetty Primasari]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 1 (2020): Februari 2020 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v4i1.1279
<![CDATA[The strategic alignment of business and Information Technology (IT) is an important element for an organization so that the organization can realize the benefits of information technology for the business they run. Technological advances, especially in the Industrial Revolution 4.0 era, made all organizations that wanted to win the competition not only implement technology in their business processes, but also had to align the use of information technology with non-IT units in the organization. The impact of the Industrial Revolution was felt in all fields, including education. In the midst of a lot of research on measuring the level of strategic alignment at higher education institutions, this research focuses on measuring the level of strategic alignment that has been carried out by institutions other than tertiary education, namely the IT Education and Consultation Institute in Yogyakarta. The model used in this alignment measurement is the Strategic Alignment Maturity Model (SAMM). From this research it is known that the IT Education and Consultation Institute which actively provides consulting and education services specifically in the IT field, understands the importance of Strategic Alignment in Business and IT and applies them in carrying out its business activities. However, despite implementing IT best practices as what has been taught to its customers, this institution needs to realize and improve the areas of IT human resources, business communication and IT, and measuring the value of benefits and IT competence.]]>
<![CDATA[Klasifikasi Kelompok Usia Melalui Citra Wajah Berbasis Image Texture Analysis pada Sistem Automatic Video Filtering ]]>
<![CDATA[Sudirman S Panna]]>;
<![CDATA[Betrisandi]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 3 No 3 (2019): Desember 2019 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v3i3.1280
<![CDATA[Nowadays information technology makes it easier for everyone to access various information, this easiness harms minors, because it is possible to access adult content from the internet, television or mobile devices. The problem is the unavailability of the system for filtering and authentication to get information by the face. The face contains information related to personal characteristics such as age, etc. feature extraction is an important stage in the face recognition process. This study proposed local binary pattern (LBP) and gray level co-occurrence matrix (GLCM) as feature extraction to describe face feature, and we use artificial neural network to classify the human age, the experiment result after calculation with confusion matrix obtained average acceleration of 94.8%, precision of 93.7% and recall of 92.3%, it’s performance measure obtained proposed method can be described face feature it well, so that, the proposed method can be used as reference material to development video filtering system by age of the users in access information based on video especially pornography and violence content.]]>
<![CDATA[Kerja Sehat: Aplikasi Mobile Untuk Mengurangi Resiko Musculoskeletal Disorders (MSDs) ]]>
<![CDATA[Fikky Aprico]]>;
<![CDATA[Muhammad Syakir Arif]]>;
<![CDATA[Dihin Muriyatmoko]]>;
<![CDATA[Azis Musthafa]]>;
<![CDATA[Ario Ramadhan]]>;
<![CDATA[Sisca Mayang Phuspa]]>;
<![CDATA[Ratih Andhika Akbar Rahma]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 3 No 3 (2019): Desember 2019 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v3i3.1284
<![CDATA[Musculoskeletal Disorders (MSDs) are complaints in the skeletal muscles caused by behavioral errors and work attitudes. If the condition happens every day for long, it can cause permanent pain and damage to muscles, joints, tendons, ligaments and othes. The Occupational Safety and Health Administration (OSHA) recommends ergonomic measures to deal with complaints of MSDs under the Ergonomic Rule of Twenty (ERT) rules. The purpose of this study is applying the method to android application. Work on this application using the steps of waterfall. Testing is done in 5 ways. The first with the blackbox method indicates that the application is running smoothly with no error. The second hardware use with various smartphones and screen size shows that the application is running well on minimum specification 4.3-inch and Android KitKat operating system. The third was carried out to two MSDs expert lecturers indicating that the application was in accordance with the ERT rules and recommended to be used as a media to prevent MSDs complaints. Fourth, by distributing questionnaires to 32 educational staff respondents at University of Darussalam Gontor, actively sitting in front of the computer daily, give good feedback with a score of 82%. Fifth, through users (https://play.google.com/store/apps/details?id=id.amoled.timerapp), 10 users gives rating of 4.6 from March 27 to July 20, 2019. All results show this application complies with ERT rules and helps prevent and reduce complaints of MSDs. This Application is recommended for anyone having a job with the habit of sitting in front of a computer for long time.]]>
<![CDATA[Sistem Pakar Penyakit Menular Menggunakan Dempster Shafer Dengan Rekomendasi Tempat Layanan Kesehatan ]]>
<![CDATA[Istiadi Istiadi]]>;
<![CDATA[Emma Budi Sulistiarini]]>;
<![CDATA[Rudy Joegijantoro]]>;
<![CDATA[Dedi Usman Effendy]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 4 No 1 (2020): Februari 2020 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v4i1.1332
<![CDATA[Delay in the handling of a type of disease can pose a risk for someone who has the surrounding environment. Often the casualties are caused by people's ignorance of the spread of dangerous infectious diseases. People's ignorance as an action that must be done immediately and where to do to get help. Thus it is necessary to build an application of an expert system that can diagnose infectious diseases, provide recommendations for disease management, and provide recommendations for appropriate and acceptable health services. The system was built to diagnose six types of infectious diseases that are of particular concern to Malang City. Various infectious diseases with similar symptoms that appear will lead to the possibility of a diagnosis and many possibilities for diagnosis. The Dempster Shafer method is an approved one that can be used in overcoming these factors. The disease expert consultation system application using the Dempster Shafer method obtained an accuracy test result of 88.5%. While the system usability test obtained results, 76% agreed to system reliability, 85% strongly agreed to system efficiency, 83% strongly agreed to ease for use system, and 79% agreed to accurate system.]]>
<![CDATA[Pemanfaatan Sensor Suhu DHT-22, Ultrasonik HC-SR04 Untuk Mengendalikan Kolam Dengan Notifikasi Email ]]>
<![CDATA[Siswanto]]>;
<![CDATA[Ikin Rojikin]]>;
<![CDATA[Windu Gata]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 3 No 3 (2019): Desember 2019 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v3i3.1334
<![CDATA[In the case of handling rainwater reservoirs, officers are currently overwhelmed, because they have to continue to monitor changes in water level manually. This is ineffective and inefficient because officers must always be present at the location of the water reservoir. While HR is very limited. The purpose of this study is to make an application to monitor and control water levels in rainwater reservoirs with temperature & humidity sensors DHT-22, ultrasonic sensors HC-SR04 and Arduino Uno R3 microcontrollers, so that they can report quickly to staff through email notifications making it easier for staff monitor changes in water level in a rainwater reservoir remotely. This application interface is made using the Arduino programming language, for its web display using the PHP programming language and MySQL database. The results of the trial were obtained as much as 90% of users said the system created was very helpful in controlling the water level of the water reservoir and working in realtime, and as many as 10% of users said the system created was less helpful in controlling the water level of the water reservoir.]]>
<![CDATA[Implementasi Keras Library dan Convolutional Neural Network Pada Konversi Formulir Pendaftaran Siswa ]]>
<![CDATA[Wahyu Andi Saputra -]]>;
<![CDATA[Muhammad Zidny Naf’an]]>;
<![CDATA[Asyhar Nurrochman]]>
<![CDATA[ Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 3 No 3 (2019): Desember 2019 ]]>
Publisher : <![CDATA[Ikatan Ahli Informatika Indonesia (IAII) ]]>
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DOI: 10.29207/resti.v3i3.1338
<![CDATA[Form sheet is an instrument to collect someone’s information and in most cases it is used in a registration or submission process. The challenge being faced by physical form sheet (e.g. paper) is how to convert its content into digital form. As a part of study of computer vision, Optical Character Recognition (OCR) recently utilized to identify hand-written character by learning pattern characteristics of an object. In this research, OCR is implemented to facilitate the conversion of paper-based form sheet's content to be stored properly into digital storage. In order to recognize the character's pattern, this research develops training and testing method in a Convolutional Neural Network (CNN) environment. There are 262.924 images of hand-written character sample and 29 paper-based form sheets from SDN 01 Gumilir Cilacap that implemented in this research. The form sheets also contain various sample of human-based hand-written character. From the early experiment, this research results 92% of accuracy and 23% of loss. However, as the model is implemented to the real form sheets, it obtains average accuracy value of 63%. It is caused by several factors that related to character's morphological feature. From the conducted research, it is expected that conversion of hand-written form sheets become effortless.]]>
