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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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PERANCANGAN MOCKUP USER INTERFACE (UI) BERDASARKAN USER EXPERIENCE (UX) APLIKASI BELAJAR BAHASA ARAB MENGGUNAKAN METODE USER CENTERED DESIGN Egia Rosi Subhiyakto; Dian Indah Fajriati
JURNAL TEKNIK INFORMATIKA Vol 14, No 2 (2021): 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.v14i2.21704

Abstract

Arabic and not cause children to get bored or bored quickly when learning. Therefore, it is necessary to design a User interface Mockup based on User experience analysis of Arabic learning applications that focus on children using the User-Centered Design (UCD) method. This method has four stages, namely introduction of user characteristics, collection and alignment of designs, design solutions, and testing of design solutions. The results obtained in the child persona trial as the main subject have an average value of 82 and the results of the parental persona trial as a supporting subject have an average value of 81.16 while the Usability test results obtained a value of 85.46%. And then the design solution that has been made can be categorized as acceptable with grade A and an adjective rating of Excellent based on the System Usability Scale and can be used as a UI/UX design recommendation for the Children's Arabic Learning Application.
Performance Analysis of Support Vector Machine in Sex Classification of The Sacrum Bone in Forensic Anthropology Iis Afrianty; Dewi Nasien; Habibollah Haron
JURNAL TEKNIK INFORMATIKA Vol 15, No 1 (2022): 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.v15i1.25254

Abstract

Sex classification is part of forensic anthropological identification aimed at determining whether the skeleton belongs to a male or a female. This paper exhibits the performance of the Support Vector Machine (SVM) in classifying the sex of the sacrum in forensic anthropology. Bone data was measured by the metric method based on six variables, namely superior breadth, anterior length, mid ventral breadth, real height, diameter the base, and max-transverse diameter of the base. This study shows performance analysis of SVM using the library libSVM with linear, polynomial, and RBF kernel to observe the results of the comparison of the accuracy of the kernel used. According to the results of the trials, the best accuracy was attained in each kernel function, i.e., the RBF kernel is 83.33% with g = 1 and C = 1, the polynomial is 85.56% at γ = 2, C = 2 and d =1, and the linear kernel obtained best accuracy is 84.44 % with C = 2 and C = 3. In conformity with the experimental result, polynomial attained the highest accuracy of 85.56% at γ = 2, C = 2, and d =1.
Development of Color Blindness Test Application Using Ishihara Template at Rumbai Public Health Center Memen Akbar; Warnia Nengsih Sikumbang; Wiwin Styorini
JURNAL TEKNIK INFORMATIKA Vol 15, No 1 (2022): 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.v15i1.24889

Abstract

This research addresses the problem of color blindness testing at Puskesmas Rumbai which serves color blindness checks using printed books. The colors in the book became less clear as time went on. Therefore, this research makes a digital color blindness examination as part of the application for obtaining a certificate of health. The resulting application is named SIP SEHAT which stands for Aplikasi Pelayanan Surat Keterangan Kesehatan. This application was developed using prototyping method approach.  There are 3 categories of users of this application, namely the registration section, doctor or nurse, and administration section. The registration section inputs the identity of the patient who will perform the examination. Meanwhile, doctors or nurses carry out examinations and medical examinations of patients who come. Color blindness test is one of the features found in doctors or nurses. Patients independently answer 24 Ishihara templates that appear on the application. Based on the answers from the patient, the application will display the color blindness test results, whether including total color blindness, partial color blindness, or not color blindness. The administration section prints a certificate of a patient who has performed an examination and gets a recapitulation of health examination reports per month. The application has been tested with 3 types of testing, namely accuracy testing, correctness testing, and usability testing. Based on these three tests, it can be concluded that this application is ready for use by the Puskesmas Rumbai to serve the processing of certificates of health. Based on service process analysis, this application makes the process of managing a health certificate making more efficient by 42.86%.
Hand-Gesture Detection Using Principal Component Analysis (PCA) and Adaptive Neuro-Fuzzy Inference System (ANFIS) Anif Hanifa Setianingrum; Arifa Fauzia; Dzul Fadli Rahman
JURNAL TEKNIK INFORMATIKA Vol 15, No 1 (2022): 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.v15i1.24869

Abstract

Sign language is a non-verbal language that Deaf persons exclusively count on to connect with their social environment.The problem that occurs in two-way communication using sign language is a misunderstanding when learning new terms that need to be taught to deaf and mute people. To minimize these misunderstandings, a system is needed that can assist in correcting hand gestures so that there is no misinterpretation in teaching new terms. Several optimality properties of PCA have been identified namely: variance of extracted features is maximized; the extracted features are uncorrelated; finds best linear approximation in the mean-square sense and maximizes information contained in the extracted feature. The classification uses the Adaptive Neuro-Fuzzy Inference System (ANFIS) method. From the results of experiments with different image size variables, the largest accuracy was obtained with an image size of 449x449 of 76.20%. While the lowest accuracy of 52.38% is obtained through scenarios with image sizes of 57x57 and 45x45. Therefore, differences in the use of image sizes have an influence on the accuracy of hand signal prediction. The smaller the size given, the smaller the accuracy obtained. This is indicated by the decreasing accuracy value when given a smaller size in the four scenarios that have been studied.
Sentiment Analysis of Public Opinion Covid-19 Vaccine Using Naïve Bayes and Random Forest Methods Ines Sholekha; Ahmad Faqih; Agus Bahtiar
JURNAL TEKNIK INFORMATIKA Vol 15, No 1 (2022): 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.v15i1.24847

Abstract

The emergence of COVID-19 or 2019 coronavirus disease has been reported as a problem with a new type of disease caused by SARS-Voc 2. It has spread to 223 countries and 25 areas around the world, including Indonesia. COVID-19 has deeply affected many aspects of our lives, the environment, mental health and the economy. Twitter is one of the media outlets that is busy discussing news regarding the COVID-19 vaccine. Covid-19 has been a major impact. The Government has implemented policies such as large-scale social restrictions to address the spread of COVID-19. The elevated spread of COVID-19 has prompted the Government of Indonesia to encourage the production of a COVID-19 vaccine. The provision of the COVID-19 vaccine has become a boon and a boon to the people of Indonesia. A lot of people don't want to be vaccinated because the news of the impact of vaccination is spreading on social media, even if the news isn't necessarily real. The Government is looking for ways to continue vaccinating the community, including by collaborating with community leaders, influencers and others. The purpose of this study is to identify the community response to the vaccine so that the right strategy can be used. The results of this study yielded 89.79% for Naïve Bayes and 84.62% for Random Forest. Indonesians are giving positive responses to the administration of the COVID-19 vaccine.
Classification of Geometric Batik Motif Typical of Indonesian Using Convolutional Neural Network Muhammad Wahyu Ilahi; Chairu Nisa Apriyani; Anita Desiani; Nuni Gofar; Yuli Andriani; Muhammat Rio Halim
JURNAL TEKNIK INFORMATIKA Vol 15, No 1 (2022): 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.v15i1.24968

Abstract

Batik is a world heritage from Indonesia which is a characteristic of Indonesian culture. On October 2, 2009 batik has been awarded as a cultural heritage from UNESCO. Indonesia has 5.849 batik patterns from Aceh to Papua. The ability to recognize batik cloth patterns is certainly quite difficult and only owned by certain people who have expertise. One way to identify batik patterns is by using a pattern recognition classification method based on quantitative measurements of the main features or characteristics of an object. Deep Learning is one solution to detect batik patterns automatically. One of deep learning methods that can classify patterns of batik patterns is Convolutional Neural Network (CNN). CNN is able to group and detect objects in the image automatically by accepting input data with a size of m×n. CNN uses image input through a convolution layer and be processed according to the specified filter. Each layer produces a pattern from several parts of the image that facilitates the classification process. This study uses the CNN method and obtains the average value of 96% accuracy, 96,78% precision, 96,74% recall, and 96,74%.
Implementation of The Advanced Encryption Standard (AES) Algorithm for Digital Image Security Angga Aditya Permana; Luigi Ajeng Pratiwi
JURNAL TEKNIK INFORMATIKA Vol 15, No 1 (2022): 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.v15i1.25735

Abstract

Nowadays, technological advances have made it increasingly easy to obtain information, especially image data (digital images). Digital image is an interesting thing to look for information. So that misuse of data can be done for personal or public interests. Misuse of data can be avoided by adding data security systems. Cryptography is the science of securing data. Cryptography can be done using the AES (Advanced Encryption Standard) algorithm, which is an algorithm that utilizes symmetric keys. Testing is done by entering the same key in the encryption and decryption process. Encryption is the process of encoding plaintext (original text) into ciphertext (text that has been encoded). While decryption is the process of recovering the plaintext from the ciphertext. Therefore, data security is an important thing to do. This study aims to find out how encryption and decryption on the AES algorithm can be used to secure digital data. The results of this study indicate that the encryption and decryption process on the AES algorithm was successfully carried out so that it can be used to secure data on digital images.
Forecasting Straight Line Methodin The Les Monitoring System Read The Great Children (AHE) in Kudus Aprilia Shanti Setyorini; Tri Listyorini; Endang Supriyati
JURNAL TEKNIK INFORMATIKA Vol 15, No 1 (2022): 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.v15i1.24683

Abstract

The existence of the Covid-19 virus has an impact on almost all fields, one of which is in the field of education. With the Covid-19 virus, the learning process has changed to distance learning or online. Online learning requires parents to be able to accompany their children in learning. However, not all parents can accompany their children to study because of their busy schedule at work, or the parents' low level of education. Therefore, the existence of tutoring or tutoring places is sought to assist parents in educating their children in the midst of a pandemic. Les Baca Anak Hebat (AHE) is a special community tutoring for reading and writing. Its development in Indonesia is increasing from village to village. In Kudus City itself there are many villages that have units. With this significant number of students, the number of existing students also affects the continuation of the unit. To avoid a spike in the number of students, we need a system that can monitor or predict the number of students in the future so that no units are closed. To estimate the number of students can use one of the fields of science such as forecasting. One of the forecasting methods is the Straight Line Method. In developing the system the author uses the waterfall method with the PHP programming language and MySQL database. This web-based system is used to monitor AHE units in Kudus.
Outlier Detection in Inpatient Claims Using DBSCAN and K-Means Panca Oktavia Candra Sari; Suharjito Suharjito
JURNAL TEKNIK INFORMATIKA Vol 15, No 1 (2022): 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.v15i1.25682

Abstract

Health insurance helps people to obtain quality and affordable health services. The claim billing process is manually input code to the system, this can lack of errors and be suspected of being fraudulent. Claims suspected of fraud are traced manually to find incorrect inputs. The increasing volume of claims causes a decrease in the accuracy of tracing claims suspected of fraud and consumes time and energy. As an effort to prevent and reduce the occurrence of fraud, this study aims to determine the pattern of data on the occurrence of fraud based on the formation of data groupings. Data was prepared by combining claims for inpatient bills and patient bills from hospitals in 2020. Two methods were used in this study to form clusters, DBSCAN and KMeans. To find out the outliers in the cluster, Local Outlier Factor (LOF) was added. The results from experiments show that both methods can detect outlier data and distribute outlier data in the formed cluster. Variable that high effect becomes data outlier is the length of stay, claims code, and condition of patient when discharged from the hospital. Accuracy K-Means is 0.391, 0.003 higher than DBSCAN, which is 0.389.
The Development of Telegram Bot Api to Maximize The Dissemination Process of Islamic Knowledge in 4.0 Era William Santoso; Wilda Nurjannah; Mahgrisya Shudhuashar; Asyifa Tasya Fadilah; Muhammad Destamal Junas; Dini Handayani
JURNAL TEKNIK INFORMATIKA Vol 15, No 1 (2022): 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.v15i1.24915

Abstract

Information technology is developing quickly in this era as if the world is in our hands. All forms of information can be accessed quickly, including Islamic information by utilizing internet technology. One of well-known medium to spread information is social media. Telegram, as one of the social media that has various beneficial features and widely used by people, has the potential to be a medium for disseminating Islamic knowledge. To improve the dissemination process of Islamic knowledge, we used one of the services found on Telegram namely chatbot. By utilizing Telegram Bot API, we make a bot that can automatically provide output according to the command given by the user in this case, giving various Islamic knowledges that users need such as Tafsir, hadith, daily prayer, and even Islamic history with a reliable source. Based on the testing result, the bot is showing a good result because it’s displaying the expected output and all features are working fine as they should be. We hoped that this bot can maximize the dissemination process of Islamic knowledge in Indonesia and reach wider audience coverage.

Page 14 of 27 | Total Record : 262

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