Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi)
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi), e-ISSN: 2580-1643 is a free and open-access journal published by the Research Division, KITA Institute, Indonesia. JTIK Journal provides media to publish scientific articles from scholars and experts around the world related to Hardware Products, Software Products, IT Security, Mobile, Storage, Networking, and Review An application service. All published article URLs will have a digital object identifier (DOI).
Articles
801 Documents
<![CDATA[Klasifikasi Data Penderita Skizofrenia Menggunakan CNN-LSTM dan Cnn-Gru pada Data Sinyal EEG 2D ]]>
<![CDATA[Firmansyah]]>;
<![CDATA[Rini, Dian Palupi]]>;
<![CDATA[Sukemi]]>
<![CDATA[ Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 7 No 4 (2023): OCTOBER-DECEMBER 2023 ]]>
Publisher : <![CDATA[Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35870/jtik.v7i4.1072
<![CDATA[Schizophrenia (SZ) is a brain disease with a chronic condition that affects the ability to think. Common symptoms that are often seen in SZ patients are hallucinations, delusions, abnormal behavior, speech disorders, and mood disorders. SZ patients can be diagnosed using electroencephalographic (EEG) signals. This study conducted a comparative analysis of the best method in EEG classification using the Deep Learning (DL) method. The author uses the 2D Convolutional Neural Network (2D-CNN) method with different layers. The first 2D-CNN uses a layer of Long Short Term memory(LSTM) and Gate Recurrent Unit(GRU). The dataset used consists of two types of EEG signals obtained from 39 healthy individuals and 45 schizophrenic patients during a resting state. Test results for the accuracy of the F1-score from 5 times testing the CNN method using the LSTM layer has the best accuracy value of 94.12% and 5 times testing the CNN method using the GRU layer has the best accuracy value of 94.12%.]]>
<![CDATA[Penerapan Metode Market Basket Analysis (MBA) dengan Algoritma Apriori Untuk Menganalisis Pembelian Jajanan Khas Lebaran Pada Warung Sembako di Toko Win ]]>
<![CDATA[Nugraheni, Wahyu]]>;
<![CDATA[Nugroho, Adi]]>
<![CDATA[ Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 7 No 4 (2023): OCTOBER-DECEMBER 2023 ]]>
Publisher : <![CDATA[Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35870/jtik.v7i4.1083
<![CDATA[Market Basket Analysis is determining marketing strategies to meet products that will be purchased simultaneously by consumers who are frequently used and most useful for marketing environments that apply an "if-then" pattern. The aim is to identify which can be used as a reference in determining the layout of items with a combination of items that are frequently purchased and interconnected in order to increase sales with the right marketing strategy Research was conducted at the Win Store where so far there is a lot of data accumulate that is only used as archives or bookkeeping, so as to help increase sales by making sales transaction data as new information by processing it using the Basket Analysis Method and the Apriori Algorithm using Rapid Miner Studio.Here using 7 data atribut namely Astor, Kastangel, Spinach Chips, Seblak Chips, Intestine Chips, Monde, and Nastar, and 50 data records, with a minimum support limit = 0.4 and minimum confidence = 0.6 which produces 14 rules. And the highest item set combination pattern obtained in this study is [NASTAR, MONDE] => [KASTANGEL] yielding a confidence of 85.7%.]]>
<![CDATA[Perancangan Kriptografi Blok Cipher Berbasis Pola Gambar Rumah Adat Joglo ]]>
<![CDATA[Bramantya, Samuel Dwi]]>;
<![CDATA[Pakereng, Magdalena A. Ineke]]>
<![CDATA[ Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 7 No 4 (2023): OCTOBER-DECEMBER 2023 ]]>
Publisher : <![CDATA[Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35870/jtik.v7i4.1085
<![CDATA[Cryptography is a scientific discipline used to maintain data security. To increase the level of security, cryptographic development is needed by implementing 64 bit Block Cipher Cryptography based on the Joglo traditional house image pattern. This approach produces random ciphertext, which is useful in changing data in the form of clear messages (plaintext) into messages that cannot be understood (ciphertext). The designed pattern is 64 bits long and then converted back into plaintext. This cryptographic design is based on the description of the Joglo traditional house, using encryption and decryption processes combined with XOR operations. The S-Box substitution table is used for byte transposition, which aims to obtain Ciphertext. The research results show that the 64 bit block cipher cryptographic system by applying the avalanche effect to the Joglo traditional house image pattern can be considered an effective cryptographic system. The correlation value achieved reached 53.125%, validating its ability to maintain data security.]]>
<![CDATA[Implementasi Artificial Neural Network dalam Identifikasi Fatalitas Kecelakaan Lalu Lintas (Studi Kasus: Kota Leeds-Inggris) ]]>
<![CDATA[Aryatama, Andrew Ananta]]>;
<![CDATA[Wowor, Alz Danny]]>
<![CDATA[ Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 7 No 4 (2023): OCTOBER-DECEMBER 2023 ]]>
Publisher : <![CDATA[Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35870/jtik.v7i4.1102
<![CDATA[Traffic accidents are a serious worldwide problem, including in Leeds, England. The high fatality rate of traffic accidents is a significant challenge in improving road safety. Therefore, this research aims to implement artificial neural networks in analyzing the factors contributing to traffic accident fatalities in Leeds. The method used in this research involves collecting data of traffic accidents from 2009 to 2018 in the town of Leeds. This method was chosen because artificial neural networks can perform complex and in-depth analyses of large and complex data. This research concludes that artificial neural networks can be used as an effective tool in analyzing traffic accident data and helping policymakers improve road safety in Leeds and possibly elsewhere.]]>
<![CDATA[Implementasi Metode Imputasi Mean dan Single Center Imputation Chained Equation (SICE) Terhadap Hasil Prediksi Linear Regression pada Data Numerik ]]>
<![CDATA[Baihaqi, Mario Rangga]]>;
<![CDATA[Padilah, Tesa Nur]]>;
<![CDATA[Jajuli, Mohamad]]>
<![CDATA[ Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 7 No 4 (2023): OCTOBER-DECEMBER 2023 ]]>
Publisher : <![CDATA[Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35870/jtik.v7i4.1169
<![CDATA[Data and information play an important role in all aspects of science, so data must be processed well through the process of data excavation or data mining. The excavation of patterns from data can be done using machine learning algorithms such as linear regression. However, in the process of extracting information from data, it can be less effective if there is a loss of value in a data. The purpose of this research is to implement the mean imputation and single center imputation chained equation (SICE) techniques against the linear regression algorithm. The data used in this research is numerical data. The root mean squared error (RMSE) value shows that the implementation of linear regression algorithm using the mean imputation technique results in better performance compared to the SICE imputation technique.]]>
<![CDATA[Penerapan Metode User Centered Design dan WebQual 4.0 dalam Pengembangan Sistem Informasi Desa Wisata Punden Gunung Cigrek ]]>
<![CDATA[Christine]]>;
<![CDATA[Riyadi , Teguh]]>
<![CDATA[ Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 7 No 4 (2023): OCTOBER-DECEMBER 2023 ]]>
Publisher : <![CDATA[Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35870/jtik.v7i4.1187
<![CDATA[User-centered design (UCD) and WebQual 4.0 are two methods that are commonly used to develop high-quality information systems. This research applied these methods in the context of developing a tourism information system for Punden Gunung Cigrek village in Indonesia. UCD was used to collect user needs and preferences through interviews and observations, while WebQual 4.0 was used to evaluate the quality of the system based on six dimensions: usability, usefulness, information quality, service interaction, trust, and loyalty. The study found that the application of UCD and WebQual 4.0 was effective in improving the quality of the tourism information system for Punden Gunung Cigrek village. UCD helped researchers to obtain user needs and preferences, which were then implemented in the information system. Meanwhile, WebQual 4.0 allowed for a holistic evaluation of the system's quality based on six dimensions. This research demonstrates the effectiveness of using UCD and WebQual 4.0 in developing high-quality information systems for tourism. In future research, these methods could be applied in other locations to improve tourism information systems.]]>
<![CDATA[Perancangan Aplikasi Manajemen Pengelolaan Data Jemaat Berbasis Microservices Website ]]>
<![CDATA[Septiadi, Michael]]>;
<![CDATA[Purnamasari, Intan]]>;
<![CDATA[Carudin]]>
<![CDATA[ Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 7 No 4 (2023): OCTOBER-DECEMBER 2023 ]]>
Publisher : <![CDATA[Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35870/jtik.v7i4.1195
<![CDATA[Data management that is still done manually at God's DNA Cut Mutiah Church makes the data team have to do data collection manually as well. Hence, this makes the data team have to work extra by collecting new data needed directly. Errors such as inputting data incorrectly and the like may occur. This study aims to solve these problems by designing microservices-based data management application websites. Using the SDLC waterfall methodology can help facilitate the design of this application. The SDLC waterfall methodology has five stages: analysis, design, implementation, testing, and maintenance. In its implementation, to build microservices-based applications, this website is designed using MongoDB for databases, ReactJS at the front, and FastAPI Python at the back. This application has been tested using the white-box testing method, and the results of the test run according to the design and needs determined.]]>
<![CDATA[Perbandingan Algoritma Support Vector Machine dan Random Forest untuk Analisis Sentimen Terhadap Kebijakan Pemerintah Indonesia Terkait Kenaikan Harga BBM Tahun 2022 ]]>
<![CDATA[Samantri, Muhamad]]>;
<![CDATA[Afiyati]]>
<![CDATA[ Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 8 No 1 (2024): JANUARY-MARCH 2024 ]]>
Publisher : <![CDATA[Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35870/jtik.v8i1.1202
<![CDATA[The commodity of fuel oil (BBM) is the main commodity and the driving force of business. The increase in world oil prices is a threat to countries around the world, one of which is Indonesia. With the turbulent conditions in several countries, the Indonesian government decided to cut fuel subsidies which had an impact on price increases. The policy invited all Indonesian people and criticized it on various social media. The purpose of this research is to find out which algorithm has a better accuracy rate and to provide input to the government about public opinion regarding the increase in fuel prices in Indonesia. From the test results both work well, this is evidenced by the accuracy value obtained, where the support vector machine algorithm produces an accuracy value of 77%, while the Random Forest algorithm produces an accuracy value of 76%. So it can be concluded that the support vector machine algorithm has a fairly good accuracy rate compared to the Random Forest algorithm.]]>
<![CDATA[Perancangan Sistem Informasi Akuntansi Penerimaan Dan Pengeluaran Kas di PT. Koprima Sandysejahtera Bandung ]]>
<![CDATA[Putri, Syifa Nur Alya]]>;
<![CDATA[Muthmainnah]]>;
<![CDATA[Sufyana, Candra Mecca]]>
<![CDATA[ Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 7 No 4 (2023): OCTOBER-DECEMBER 2023 ]]>
Publisher : <![CDATA[Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35870/jtik.v7i4.1224
<![CDATA[This research aims to create an accounting information system for receipts and disbursements. The data collection methods used are observation, interviews, documentation and literature related to the problem. The results of research conducted at PT. Koprima Sandysejahtera showed that the processing of receipts and disbursements data was still done manually, so it was necessary to design an accounting information system to facilitate these activities. The Waterfall method is used for software development. The models used are Flowmap, Data Flow Diagrams and Entity Relationship Diagrams which are then implemented using web programming language and MySQL as the database. This research resulted in the creation of an accounting information system for cash receipts and disbursements at PT. Koprima Sandysejahtera by facilitating the process of data entry, data processing and reporting. By making this system capable of producing reports more efficiently, quickly, easily and accurately.]]>
<![CDATA[Penerapan Metode Extreme Learning Machine (ELM) untuk Memprediksi Hasil Sensor EWS Trafo ]]>
<![CDATA[Apalem, Rolisa]]>
<![CDATA[ Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 8 No 1 (2024): JANUARY-MARCH 2024 ]]>
Publisher : <![CDATA[Lembaga Otonom Lembaga Informasi dan Riset Indonesia (KITA INFO dan RISET) ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.35870/jtik.v8i1.1243
<![CDATA[The Early Warning System (EWS) Trafo is a continuous monitoring tool for transformers that provides warnings when anomalies are detected, aiming to prevent explosions. This device applies artificial intelligence and machine learning technologies to monitor and predict the real-time condition of transformers using sensor data collected by the tool. This research aims to predict the condition of transformers based on the EWS Trafo sensor results using the Extreme Learning Machine (ELM) method. The study investigates the effectiveness of the ELM method in predicting transformer conditions. Based on the research results obtained from several combinations of data training: testing with different numbers of hidden layers, the lowest Mean Absolute Percentage Error (MAPE) value was found in the combination of 40% training data and 60% testing data, out of a total of 470 data points, with 20 hidden layers, at 23.1125%. Thus, it can be concluded that the Extreme Learning Machine (ELM) method is effective in predicting the condition of transformers.]]>
