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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 10 Documents
 1 
Search results for , issue "Vol. 17 No. 1: JURNAL TEKNIK INFORMATIKA" : 10 Documents clear
Machine Learning for the Model Prediction of Final Semester Assessment (FSA) using the Multiple Linear Regression Method Rachmawati, Fitria; Jaenudin, Jejen; Ginting, Novita Br; Laksono, Panji
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.v17i1.28652

Abstract

Corona virus (COVID-19) is the reason behind the collapse of the National Assembly. The first is the Final Semester Assessment (FSA) , which is a component of the student's graduation. The aforementioned evaluation process is a crucial consideration for the teacher since it uses several intricate surveys and mark components. A prediction model is employed to assist teachers in providing suitable results for student learning. The method that is used is called the multiple linear regression. This multiple linear regression algorithm yields an accuracy level of approximately 92%. The analysis results using the method are used as a guide to understanding student’s index. This index is a rating that appears based on the Minimum Credit Count (MCC). Therefore, the goal of this study is to determine students' understanding of the FSA prediction value, which will be taken into consideration through the results of the MCC weights in the form of a range in the form of "Grade." Additionally, the research aims to determine the accuracy of the results from the model obtained using multiple linear regression algorithms in predicting students' FSA.
A Comparative Study of Students Graduation Analysis Using Classification Methods in Undergraduate Electrical Engineering Tidar University Wicaksono, Damar; Nisworo, Sapto; Nata, Imam Adi
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.v17i1.32132

Abstract

This research aimed to classify achievement factors for electrical engineering students at Tidar University using K-Means and Agglomerative Clustering classification algorithms. The goal was to understand if any parameters influence high-achieving student performance. The Indonesian government and private sector for university students provide significant education funds. Student scholarships are awarded based primarily on GPA and entry path, overburdening staff and causing confusion during distribution to eligible recipients. A system was needed to accommodate additional eligible criteria. The researcher selected factors to identify engineering student performance, including school origin, entry path, tuition fees, and GPA. These inputs could determine graduation status. The results compared calculation methods based on collected data accuracy, processing times, and characterizing clustered data to determine the best classification method. Agglomerative Hierarchical Clustering performed better. Accuracy testing on 600 training data points yielded 73.94% for improved K-means and 90.42% for AHC. The Average processing time was 674.92 seconds for improved K-means and 554.35 seconds for AHC. Silhouette testing also characterized calculation methods, with improved K-means scoring best at 0.654 and AHC at 0.787 using two clusters.
Use of Ticketing System in Freelancing Platform to Maintaining Client Trust in Product Development Process Sitanggang, Andri Sahata; Hasti, Novrini; Syafariani, R Fenny; Melian, Lusi; Santoso, Bondan Rachmat; Shidiq, Muhammad Daffa
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.v17i1.32228

Abstract

Micro, small, and medium enterprises (MSMEs) are considered to be one of the important components in the economic development of a country, especially Indonesia. However, it has been found that MSMEs are lagging in digitalization, the adoption of information technology, and digital marketing. An information system where MSMEs can have easy access to IT and digital marketing professionals can be a solution to boost and encourage digitalization among local MSMEs. Developing such an information system requires the project to be able to quickly adapt and change based on the user’s needs and current trends. This study proposes an incremental solution to building an accessible information system catered for MSMEs by incorporating the ADDIE model into the development cycle. To understand the feasibility of the system, several group meetings are arranged to demonstrate and try out the system’s capability to the target users. The results indicate that the system is generally able to fit the needs of MSMEs and is quite effective at connecting the MSESs to IT and Digital marketing resources and experts.
Analyzing User Satisfaction of a Study Abroad Guidance Company Website Using the Customer Satisfaction Index (CSI) Method Nispi, Fajrian; Kurniawati, Ana; Wulandari, Lily
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.v17i1.34612

Abstract

XYZ is an education technology company dedicated to assisting Indonesian students in gaining acceptance to universities worldwide through full scholarship, partial, or self-funding. Until 2024, XYZ has a thousand alumni accepted in 46 countries and many universities worldwide. One of the marketing trackers that XYZ has is the website. With this website, the company will deliver the service to customers and receive user feedback to run and improve their services. The measurement of user satisfaction level can be used to improve the quality of service in digital media. The method used in this study to measure user satisfaction level is the Customer Satisfaction Index (CSI), which evaluates satisfaction across five (5) dimensions: usability, information quality, assurance, reliability, and data accessibility. This method's result shows a value of 83.64%, which means the XYZ website performance is in the "Very Satisfied" category. These findings suggest that XYZ Company's website is highly effective and has a "Very Satisfied" result category in meeting user needs, paving the way for continued success in their mission to assist Indonesian students in pursuing global education opportunities
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".
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.

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