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INDONESIA
TEKNIK INFORMATIKA
Published by Universitas Islam Negeri Syarif Hidayatullah Jakarta
ISSN : 19799160     EISSN : 25497901     DOI : -
Core Subject : Science,
Computer Science & IT
Jurnal Teknik Informatika merupakan wadah bagi insan peneliti, dosen, praktisi, mahasiswa dan masyarakat ilmiah lainnya untuk mempublikasikan artikel hasil penelitian, rekayasa dan kajian di bidang Teknologi Informasi. Jurnal Teknik Informatika diterbitkan 2 (dua) kali dalam setahun.
Arjuna Subject : -
Articles 262 Documents
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Diversity Balancing in Two-Stage Collaborative Filtering for Book Recommendation Systems Muttaqien, Rifqi Fauzia; Nurjanah, Dade; Nurrahmi, Hani
JURNAL TEKNIK INFORMATIKA Vol. 16 No. 2 (2023): JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v16i2.36580

Abstract

A book recommender system is a system used to provide relevant book recommendations for readers. One approach that is often used in recommender systems is Collaborative Filtering (CF). CF provides book recommendations based on books liked by other similar users. However, CF only provides recommendations for items that are popular, so items that are less popular will be difficult to recommend. Therefore, we propose a book recommendation system based on Two-stages CF using the Diversity Balancing method. Diversity Balancing method in CF is used to balance diversity in the recommendation results by replacing popular items with less popular relevant items. System accuracy is measured using precision and recall, while diversity is measured using personal diversity and aggregate diversity. The test results show that the accuracy of the proposed system increases with the increasing number of recommended items. meanwhile, the diversity of recommended items continues to decrease as more items are included in the recommendation list. In consideration of the trade-off between accuracy and diversity, our system achieves a recall score of 0.301, a precision score of 0.282, a PD score of 0.048, and an AD score of 0.095 with a recommendation list size of 8 items.
Systematic Literature Review: Cybersecurity by Utilizing Cryptography Using the Data Encryption Standard (DES) Algorithm Desianty, Annisa; Imelda, Imelda
JURNAL TEKNIK INFORMATIKA Vol. 17 No. 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v17i1.37256

Abstract

The world of information technology is currently developing very rapidly. This opens up opportunities in the development of computer applications, but it also creates opportunities for threats to alter and steal data or what is often known as cyber-crime. This action is a violation that can cause direct or indirect losses. Therefore, cyber-security is very important to protect user information from cyber-crime. Based on this description, this research will conduct a Systematic Literature Review (SLR) on cyber-security by utilizing cryptography using the DES algorithm. By using the SLR method, literature searches were conducted on Google Scholar or Garuda with the keywords for national journals "Data Encryption Standard Algorithm (DES)" and keywords for international journals "Data Encryption Standard Algorithm (DES)" from both national and international journals, and limiting articles from 2019 to 2023, and obtained selection results as many as 10 articles used from national journals and 10 articles used from international journals. So that this research is expected to increase the understanding of literature that reviews cyber-security by utilizing cryptography using the DES algorithm.
SVM Optimization with Grid Search Cross Validation for Improving Accuracy of Schizophrenia Classification Based on EEG Signal Desiawan, Masdar; Solichin, Achmad
JURNAL TEKNIK INFORMATIKA Vol. 17 No. 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v17i1.37422

Abstract

The advantage of the Support Vector Machine (SVM) is that it can solve classification and regression problems both linearly and non-linearly. SVM also has high accuracy and a relatively low error rate. However, SVM also has weaknesses, namely the difficulty of determining optimal parameter values, even though setting exact parameter values affects the accuracy of SVM classification. Therefore, to overcome the weaknesses of SVM, optimizing and finding optimal parameter values is necessary. The aim of this research is SVM optimization to find optimal parameter values using the Grid Search Cross-Validation method to increase accuracy in schizophrenia classification. Experiments show that optimization parameters always find a nearly optimal combination of parameters within a specific range. The results of this study show that the level of accuracy obtained by SVM with the grid search cross-validation method in the schizophrenia classification increased by 9.5% with the best parameters, namely C = 1000, gamma = scale, and kernel = RBF, the best parameters were applied to the SVM algorithm and obtained an accuracy of 99.75%, previously without optimizing the accuracy reached 90.25%. The optimal parameters of the SVM obtained by the grid search cross-validation method with a high degree of accuracy can be used as a model to overcome the classification of schizophrenia.
Integration of Design Sprint Method into Mobile Development Application Life Cycle to Create MobilePQI Application Prototype Muzayyana Agustin, Fenty Eka; Thahir, Nuriyah; Farida, Ade Rina; Mayastika, Kania
JURNAL TEKNIK INFORMATIKA Vol. 17 No. 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v17i1.37818

Abstract

This study aims to create a mobile-based learning application that can be used to support blended learning. Blended Learning is carried out synchronously, either online using Zoom or Google Meet, or offline in the classroom. asynchronous learning is implemented using MobilePQI Apps. MobilePQI Apps was developed using the Kotlin programming tool and  MADLC methodology (Mobile Application Development Life Cycle). MADLC consists of seven stages: Identification; Design; Development; Prototyping; Testing; Deployment; and Maintenance. We use design sprint method and figma to create design prototype, and Kotlin development kit. The testing method used heuristics evaluation which tests 10 usability principles. The number of questions asked was 115, with 5 respondents consisting of 3 students and 3 lecturers. The results of the heuristics evaluation score were 89% of respondents answered YES. That it can be concluded that the 10 usability  principles of the prototype was acceptable. The SUS results show a score of 74, which means the application's user interface is in the Good and acceptable category.
The Comparison of the Effectiveness and Efficiency of Fine-Tuning Models on Stable Diffusion in Creating Concept Art Qowy, Abdul Bilal; Ihsan, Ahmad Nur; Hartati, Sri
JURNAL TEKNIK INFORMATIKA Vol. 17 No. 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v17i1.37942

Abstract

This research aims to overcome the limitations of the Stable Diffusion model in creating conceptual works of art, focusing on problem identification, research objectives, methodology and research results. Even though Stable Diffusion has been recognized as the best model, especially in the context of creating conceptual artwork, there is still a need to simplify the process of creating concept art and find the most suitable generative model. This research used three methods: Latent Diffusion Model, Dreambooth: fine-tuning Model, and Stable Diffusion. The research results show that the Dreambooth model produces a more real and realistic painting style, while Textual Inversion tends towards a fantasy and cartoonist style. Although the effectiveness of both is relatively high, with minimal differences, the Dreambooth model is proven to be more effective based on the consistency of FID, PSNR, and visual perception scores. The Dreambooth model is more efficient in training time, even though it requires more memory, while the inference time for both is relatively similar. This research makes a significant contribution to the development of artificial intelligence in the creative industries, opens up opportunities to improve the use of generative models in creating conceptual works of art, and can potentially drive positive change in the use of artificial intelligence in the creative industries more broadly. 
Utilization of the FP-Growth Algorithm on MSME Transaction Data:Recommendations for Small Gifts from The Padang Region Hasan, Firman Noor; Ariyansah, Riyan
JURNAL TEKNIK INFORMATIKA Vol. 17 No. 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v17i1.37966

Abstract

The existence of adequate transaction data turns out to have a similar sales transaction pattern for MSMEs, so it would be a shame if it were left like that. Moreover, this data can be used to increase efficiency in MSMEs in the culinary sector, one of which is as a recommendation for small gifts. The study uses the Association Rules technique, whereas fp-growth is used to obtain a combination of elements. The goal is to facilitate MSMEs' ability to suggest small gifts to clients. The fp-growth algorithm calculation was implemented to process 2043 data originating from transaction data in MSMEs, with the specified minimum support value being 15%, while the minimum confidence value determined was 55%. The results of the trial obtained the two best rules, namely, "If a customer buys a list of small gifts from Balado Sanjai Chips, then the customer will buy Jangek Crackers" and "If a customer buys Jangek Crackers, then the customer will buy Sanjai Balado Chips".
Evaluation of Website Performance and Usability Using GTMetrix, Usability Testing, and System Usability Scale (SUS) Methods Puspito, Toto Andri
JURNAL TEKNIK INFORMATIKA Vol. 17 No. 2: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v17i2.38530

Abstract

This study was conducted to measure the performance of IAIN Metro's website in terms of performance and user perception to ensure that the campus website can adequately support visitors' needs. This study aims to determine things that need to be improved to improve the performance of the IAIN Metro website. To get comprehensive results from the performance of the website, this research uses GTMetrix to analyse the technical performance of the IAIN Metro website, and then, to test user perceptions, researchers use Usability Testing and System Usability Scale methods. In usability testing, several aspects will be measured to determine usability problems, namely learnability and efficiency, while the System Usability Scale questionnaire will be used to test the satisfaction level. Based on the test results using GTMetrix, after testing, several aspects of the access speed of the IAIN Metro website need to be improved. Although, in general, from the test results, Usability Testing and System Usability Scale users still consider the performance of the website to be acceptable, the results of the first task on Time Based Efficiency testing show that initial access to the main page metrouniv.ac.id, takes a relatively long time compared to other tasks. This is also evident from the GTMetrix score on the performance aspect, which has a low presentation of 25%. Therefore, optimisation is needed on the main page to improve website performance.
A Comparative Analysis of Random Forest, XGBoost, and LightGBM Algorithms for Emotion Classification in Reddit Comments Anggraini, Nenny; Putra, Syopiansyah Jaya; Wardhani, Luh Kesuma; Arif, Farid Dhiya Ul; Hakiem, Nashrul; Shofi, Imam Marzuki
JURNAL TEKNIK INFORMATIKA Vol. 17 No. 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v17i1.38651

Abstract

This research aims to compare the performance of three classification algorithms, namely Random Forest, XGBoost, and LightGBM, in classifying emotions in Reddit comments. Emotion classification in Reddit comments is a complex classification problem due to its numerous variations and ambiguities. This research utilizes the GoEmotions Fine-Grained dataset, filtered down to 7,325 Reddit comments with 5 different basic emotion labels. In this study, data preprocessing steps, feature extraction using CountVectorizer and TF-IDF, and hyperparameter tuning using GridSearchCV for each algorithm are conducted. Subsequently, model evaluation is performed using Cross-Validation and confusion matrix. The results of the study indicate that Random Forest outperforms the XGBoost and LightGBM algorithm with an accuracy of 75.38% compared to XGBoost with 69.05% accuracy and LightGBM with 66.63% accuracy.
Design and Development of the Koperasi Bintang Tapanuli (KBT) Ticket Ordering System Samosir, Hernawati; Silaban, Monica; Manurung, Resa Halen; Tambunan, Elisabeth Uli; Sitorus, Juan Saut Pandapotan
JURNAL TEKNIK INFORMATIKA Vol. 18 No. 1: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v18i1.38949

Abstract

The transportation industry has undergone a major transformation with the widespread adoption of online ticketing systems. However, Koperasi Bintang Tapanuli (KBT), a major player in regional transport, relies on a traditional manual booking system for its buses. The system suffers from inefficiencies such as long queue times and limited access to information. The project used a rigorous requirements gathering process, including stakeholder interviews to ensure the system met user needs and functionality. Passengers can conveniently search routes, compare timetables, book tickets and manage bookings online without the need for a physical ticket counter. The team built a website consisting of 28 functions. They are: registration, authentication (login and logout),  profile viewing, profile editing, information viewing, adding information, information editing, information deleting, ticket viewing, ticket adding, ticket editing, ticket deleting, vehicle detailed information viewing, dashboard viewing, customer data viewing customer package information viewing, package payment viewing, ticket approval, review viewing, payment viewing, notification viewing, history viewing, ordering method viewing, payment viewing, ticket ordering, package delivery, check ticket order and add review. This website is built using the laravel framework and the waterfall software development methodology. The application we built helps KTB admins in managing ticket orders.
A Case Study: Comparison of LSTM and GRU Methods for Forecasting Oil, Non-Oil, and Gas Export Values in Indonesia Kurniasari, Dian; Nuraini, Maydia Egi; Wamiliana, Wamiliana; Nisa, Rizki Khoirun
JURNAL TEKNIK INFORMATIKA Vol. 17 No. 2: JURNAL TEKNIK INFORMATIKA
Publisher : Department of Informatics, Universitas Islam Negeri Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/jti.v17i2.39098

Abstract

This study explores the forecasting of Indonesia’s oil, non-oil, and gas export values, highlighting its critical role in supporting national economic growth. Given the inherent volatility in export values, accurate forecasting is vital for informed economic decision-making. The research employs Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) models, both well-regarded for their ability to handle sequential data and complex temporal patterns. Model performance was evaluated using Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE). The findings indicate that although both models produced nearly identical MAPE values of 99.99% across the oil, non-oil, and gas sectors, the GRU model outperformed the LSTM model with RMSE values of 0.0655 for oil and gas exports and 0.0697 for non-oil and gas exports. Moreover, the GRU model’s forecasts align closely with data from the Central Bureau of Statistics (BPS), which reported an 11.33% decline in Indonesia’s export values by the end of 2023. These results suggest that the GRU model not only offers greater accuracy but is also applicable to other economic forecasting contexts, such as exchange rate and inflation predictions, thereby enhancing economic policy-making.

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