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Telematika : Jurnal Informatika dan Teknologi Informasi
Published by Universitas Pembangunan Nasional Veteran Yogyakarta
ISSN : 1829667X     EISSN : 24609021     DOI : 10.31315
Core Subject : Engineering,
Electrical & Electronics Engineering
Arjuna Subject : -
Articles 361 Documents
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Retinal Vessel Segmentation to Support Foveal Avascular Zone Detection Dhimas Arief Dharmawan
Telematika Vol 20, No 1 (2023): Edisi Februari 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i1.9645

Abstract

Purpose: This study aims to perform retinal vessel segmentation to support foveal avascular zone detection. Methodology: The proposed approach consists of a multi-stage image processing approach, including preprocessing, image quality enhancementt, and segmentation of retinal blood vessel using matched filter and length filter techniques.Findings: The proposed framework has achieved remarkable results with an average sensitivity, specificity, and accuracy of 77.99%, 86.43%, and 85.24%, respectively.Value: This achievement has the potential to significantly enhance the accuracy and efficiency of detecting and diagnosing medical conditions related to the retina, improving the quality of life for countless individuals.
User Experience Analysis on Student Services Website using User Experience Questionnaire (UEQ) KPI and Importance Performance Analysis (IPA) (Case Study: UPN "Veteran" Yogyakarta) Vivo Putri Wenerda; Yuli Fauziah
Telematika Vol 20, No 2 (2023): Edisi Juni 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i2.10216

Abstract

Purpose: This study aims to obtain an end-user assessment of User Experience on the Student Services website so that it can be used as a priority material for improvement for the Bureau of Academic, Student Affairs, Planning, and Cooperation (AKPK) of the National Development University (UPN) "Veteran" Yogyakarta, when developing a website further.Design/methodology/approach: The User Experience Assessment on the Student Services website refers to 6 aspects of the assessment of the User Experience Questionnaire (UEQ) KPI method. The existing results will be mapped into an IPA (Importance Performance Analysis) diagram.Findings/result: The results of user experience testing on the Student Services website using the UEQ method, get the Good category for the Efficiency (1.56) and Dependability (1.57) aspects, the Above average category for the Attractiveness aspect (1.28), Perspicuity (1.57), and Stimulation (1.15) and the Bad category on Novelty (-0.27). Mapping the results of the UEQ KPI to the IPA quadrant, getting the results of the Attractiveness, Perspicuity, Efficiency, and Dependability aspects are in Quadrant 1, the Stimulation aspect is in Quadrant 2, the Novelty aspect is in Quadrant 3, and no aspect is in Quadrant 4. Based on the results of the study, it can be concluded that the user experience value of the end user is good. Recommendations for improvement priorities for the Student Services website can further prioritize Novelty aspels that are in Quadrant 3 and in Bad condition.Originality/value/state of the art: The focus of this research is the same as previous research, namely analyzing User Experience with reference to the assessment aspects of the KPI User Experience Questionnaire (UEQ) and IPA (Importance Performance Analysis) methods. The difference that can be seen in this study is from the implementation of the method into different case studies with the objectives and urgency and problems described in accordance with the existing research object.
Forecasting Performance of Double Exponential Smoothing Model and ETS Model for Predicting Crude Oil Prices Hari Prapcoyo; Mohamad As'ad; Sujito Sujito; Sigit Setyowibowo; Eni Farida
Telematika Vol 20, No 2 (2023): Edisi Juni 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i2.8104

Abstract

Purpose: This study aims to predict the price of monthly crude oil quickly and accurately by using an easy model and with easily available software.Design/methodology/approach: This study compares the DES-Holts and ETS models to predict price of monthly crude oil.Findings/result: The results of this study recommend the ETS(M,N,N) model to predict the price of monthly crude oil which produces an accuracy value of RMSE and MAPE of 4.385812 and 6.499007 %, respectively.Originality/value/state of the art: This study implements the DES_Holt's and ETS models to predict price of monthly crude oil with an RMSE and MAPE forecasting accuracy that has never been done in previous studies. 
Implementation of Web Scraping on Google Search Engine for Text Collection Into Structured 2D List Tresna Maulana Fahrudin; Prismahardi Aji Riyantoko; Kartika Maulida Hindrayani
Telematika Vol 20, No 2 (2023): Edisi Juni 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i2.9575

Abstract

Purpose: This research proposes the implementation of web scraping on Google Search Engine to collect text into a structured 2D list.Design/methodology/approach: Implementing two important stages in the process of collecting data through web scraping, namely the HTML parsing process to extract links (URL) on Google Search Engine pages, and HTML parsing process to extract the body text from website pages on each link that has been collected.Findings/result: The inputted query is adjusted to the latest issues and news in Indonesia, for example the President's important figures, the month of Ramadan and Idul Fitri, riots tragedy (stadium) and natural disasters, rising prices of basic commodities, oil and gold, as well as other news. The least number of links obtained was 56 links and the most was 151 links, while the processing time to obtain links for each of the fastest queries was 1 minute 6.3 seconds and the longest was 2 minutes 49.1 seconds. The results of scraping links from these queries were obtained from Wikipedia, Detik, Kompas, the Election Supervisory Body (Bawaslu), CNN Indonesia, the General Election Commission (KPU), Pikiran Rakyat, and others.Originality/value/state of the art: Based on previous research, this study provides an alternative to produce optimal collection of links and text from web scraping results in the form of a 2D list structure. Lists in the Python programming language can store character sequences in the form of strings and can be accessed using index keys, and manipulate text efficiently.
Sensitivity Comparison of AHP with The Combination of AHP and SAW for Facial Wash Recommendation System based on Skin Type Novrido Charibaldi; Qurrotu'ain Hanifah; Rifki Indra Perwira
Telematika Vol 20, No 2 (2023): Edisi Juni 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i2.9444

Abstract

Purpose: This research aims to design a facial wash recommendation system based on all skin types, namely normal, dry, oily, combination, and sensitive. This is to tackle the limitation of previous systems that were developed based on limited skin types which are normal, dry, and oily using Promethee II, Fuzzy Logic, and SAW methods.Design/methodology/approach: This research uses the Analytic Hierarchy Process (AHP) method and a combination of AHP and Simple Additive Weighting (SAW) to consider the importance values of each criterion. Four criteria data are used, namely price, rating, content, and availability, along with 70 alternative data of facial wash products.Finding/Result: Sensitivity testing was conducted on both methods, and the combination of AHP and SAW produced a higher sensitivity percentage, which is 67.51%, whereas the AHP method provided a lower sensitivity percentage of 59.26%.Originality/state of the art: The combination of AHP and SAW is an innovation in designing a facial wash recommendation system, and the research results demonstrate that the combination of AHP and SAW is a superior method for recommending facial wash products.
Human Skin Disease Detection using Convolutional Neural Network Method with Hyperparameter Tuning to Determine the Best Parameter Combination Riki Martua Aritonang; Mangaras Yanu Florestiyanto; Bambang Yuwono
Telematika Vol 20, No 2 (2023): Edisi Juni 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i2.9161

Abstract

Purpose: Obtaining the best hyperparameter combination for optimization of the Convolutional Neural Network method, for classifying skin diseases.Design/methodology/approach: Using the CNN method with hyperparameter tuning in determining the best hyperparameter combination. System development is performed with the Python programming language.Findings/result: The best combination of hyperparameter tuning results is RMSprop optimizer, APL dropout value is 0.05, dropout is 0.5 , dense layer is 64, and produces an accuracy of 97,81%.Originality/value/state of the art: This study has differences in terms of the types of skin diseases classified, the architecture of the CNN model, the hyperparameters tested and the combination results obtained compared to previous studies.
Implementation of Penetration testing on Websites to Improve Security of Information Assets UPN "Veteran" Yogyakarta Herry Sofyan; Meilan Sugiarto; Bagus Muhammad Akbar
Telematika Vol 20, No 2 (2023): Edisi Juni 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i2.7757

Abstract

Purpose: This study aims to implement penetration testing on the website https://fit.upnyk.ac.id owned by Telematics UPN "Veteran" Yogyakarta to determine whether there are vulnerabilities or security holes in the web server. Then make an analysis based on the results of penetration testing on the web server using penetration testing tools (penetration testing scanner) so that recommendations for improvements are obtained to close security holes that can be used as a way for hackers to enter the system, as well as provide risk mitigation recommendations.Design/methodology/approach: This study uses the penetration test method which consists of five stages, namely literature study, information gathering, identification of system vulnerabilities, penetration testing and analysis. Penetration tests were carried out using acunetix tools and analysis using the OWASP and ISAAF methods.Findings/result: Based on research conducted on the website https://fit.upnyk.ac.id/ using the OWASP method, several vulnerabilities were found, including one vulnerability with a high level (high), three with a medium level and six with a low level (low), so that it can be it can be concluded that in general the level of vulnerability of the website is at the medium levelOriginality/value/state of the art: Penetration testing on the website can be done by identifying system vulnerabilities, penetration testing and analysis. The OWASP method can be used to find vulnerabilities on a website
Systematic Literature Review on Information Technology Governance in Government Januar Agung Wicaksono; Aris Puji Widodo; Kusworo Adi
Telematika Vol 20, No 2 (2023): Edisi Juni 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i2.9642

Abstract

Purpose: This article aims to assist the government in developing better, more efficient, and sustainable public governance by utilizing information technology and artificial intelligence. The article provides insights on how information technology and artificial intelligence can be applied in public governance to improve the efficiency, effectiveness, and sustainability of public services, as well as to enhance public trust in the government.Design/Method/Approach: The method used in this article is a Systematic Literature Review (SLR), which is a systematic and methodological research method for collecting, evaluating, and synthesizing evidence from previous studies in the field under investigation, through search terms and searching for information in online databases and creating inclusion and exclusion criteria.Results: This article is expected to achieve more efficient, effective, and sustainable public governance and improve the quality of public services and public trust. The article also shows that information technology and artificial intelligence have become an integral part of public governance in various countries, with many countries taking a holistic and sustainable approach.Originality/State of the art: The state-of-the-art of this article is that information technology and artificial intelligence can be effectively used to improve public governance to achieve better, more efficient, and sustainable goals. The article also emphasizes the importance of considering data privacy, cyber security, and unwanted environmental impacts, as well as considering ethical and human rights aspects in the development of artificial intelligence. This will help the government to develop and implement information technology and artificial intelligence in public governance in a responsible and sustainable manner.
Convolutional Neural Network for Identifying Tree Species Using Stem Images Nadia Pramesti; Rianto Rianto
Telematika Vol 20, No 2 (2023): Edisi Juni 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i2.8774

Abstract

Purpose: Identification of tree species based on stem images using programming assistance to design an automation tool to be able to distinguish tree species directly based on stem images from the new data entered.Design/methodology/approach: Identifying tree species is usually done using leaf images, in previous studies related to identifying tree species based on leaf images this resulted in quite high accuracy but was felt to be not optimal. In this study, we used a convolutional neural network to compare the accuracy of bar images.Findings/result: from 1000 tree trunk image data, identification was carried out using the help of python with the CNN method it can be concluded that the test results used the best acuration at epoch 25 with a value reaching 96.80%Originality/value/state of the art: Research with theme identification of tree species based on stem images using the CNN method has never been done by previous researchers. 
Preprocessing Using SMOTE and K-Means for Classification by Logistic Regression on Pima Indian Diabetes Dataset Ahmad Taufiq Akbar; Rochmat Husaini; Hari Prapcoyo
Telematika Vol 20, No 2 (2023): Edisi Juni 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i2.9676

Abstract

Purpose: Our study aims to combine pre-processing methods to develop a training data model from the Indian diabetic Pima dataset so that it can improve the performance of machine learning in recognizing diabetesDesign/methodology/approach: This research was started through several stages such as collecting the Pima indian diabetes dataset, pre-processing including k-means clustering, oversampling using SMOTE, then undersampling the dataset whose cluster is a minority in each class. Furthermore, the dataset is classified using machine learning namely logistic regression through 10 cross validationFindings/result: The results of this classification performance show that the accuracy reaches 99.5% and is higher than the method in previous studies.Originality/value/state of the art:The method in this study uses SMOTE to handle data imbalances and k-means clustering to remove outliers by removing labels that do not match the majority cluster in each class so that clean data is produced and validation using logistic regression is more accurate than previous studies.Tujuan: Penelitian ini bertujuan untuk menerapkan metode pre-processing untuk membentuk model data latih dari dataset Pima Indian diabetes sehingga dapat meningkatkan performa mesin pembelajaran dalam mengenali diabetes.Perancangan/metode/pendekatan: Riset ini dimulai melalui beberapa tahap yakni pengumpulan dataset Pima Indian diabetes, pre-processing meliputi clustering, oversampling menggunakan SMOTE, kemudian undersampling pada dataset pada klaster  minoritas pada setiap kelas. Selanjutnya dataset diklasifikasikan menggunakan machine learning yakni metode regresi logistik melalui 10 cross validationHasil: Hasil dari performa klasifikasi ini menunjukkan akurasi mencapai 99,5% dan lebih tinggi daripada metode pada penelitian sebelumnya.Keaslian/ state of the art: Metode dalam penelitian ini menggunakan SMOTE untuk menangani ketidakseimbangan data dan k-means klastering untuk membuang outlier dengan cara menghapus label yang tidak sesuai dengan klaster mayoritas pada setiap kelas sehingga dihasilkan data yang bersih dan pada validasi menggunakan logistic regression lebih akurat daripada penelitian sebelumnya.

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