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Teknomatika: Jurnal Informatika dan Komputer
Published by Universitas Jenderal Achmad Yani Yogyakarta
ISSN : 19797656     EISSN : 30310865     DOI : 10.30989
Core Subject : Science,
Computer Science & IT
Teknomatika: Jurnal Informatika dan Komputer ISSN: 3031-0865 (Online), 1979-7656 (Print) is a free and open-access journal published by Fakultas Teknik dan Teknologi Informasi Universitas Jenderal Achmad Yani Yogyakarta, Indonesia. Teknomatika publishes scientific articles from scholars and experts worldwide related to the computer science, informatics, computer systems and information systems. This journal accommodates articles covering: Mathematics and Statistics Algorithms and Programming Intelligent System Artificial Intelligence Software Engineering Computer Architecture Distributed System Cyber Security Electronics and Embedded Systems Data and Information Management Information Systems Enterprise System All published articles will have a Digital Object Identifier (DOI). The Journal publication frequency is twice a year (sixth monthly: Maret and September).
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 271 Documents
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Perancangan Survival Horror Game Out Of Sight Menggunakan Unity 3D Engine Septian Mahendra Dewantoro; Kartikadyota Kusumaningtyas; Andika Bayu Saputra; Nurul Fatimah
Jurnal Teknomatika Vol 15 No 2 (2022): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v15i2.1122

Abstract

A game is the result of the creative expression of a game maker that has an element of entertainment, can be played and has an end goal. In horror games, it is still divided into several more types of games, one of which is a survival horror game that requires players to live against enemy attacks that come their way. This game was created to enrich horror-themed domestically made games. Designing games using the unity 3D engine with the process of applying the MDLC (Media Develpoment Life Cycle) model. A method suitable for game design, starting with the preparation, design, collection of materials, testing and distribution. Out Of Sight game has gameplay with a first-person perspective combined with the survival horror genre. Made with the C# programming language this game is able to run perfectly with various features. There is also a unique feature, namely slowmotion which serves to slow down time to make it easier for players to shoot enemies. This survival horror game has been successfully created and completed. This game conducts testing using black box testing where all features function normally except for the key that serves to open the door. Based on respondents 18.5% said that the door lock had a bug. This game was created to enrich horror-themed domestically made games.
Rancang Bangun Sistem Parkir Menggunakan Kartu Barcode di Pasar Setono Betek Kediri Wenesdy Fajar Ega Roosdwita; Agung Priyanto; Ari Cahyono; Nurul Fatimah
Jurnal Teknomatika Vol 13 No 1 (2020): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v13i1.1123

Abstract

Along with the development of technology and information, human needs are increasing. Especially now that the parking system has experienced rapid development with a level of security for vehicles. One of the important things is the parking problem, the parking problem where the parking lot is large enough but still not supported by an adequate system. The use of a manual parking system has now begun to shift now with an automatic parking system that is integrated with the database as part of the parking system. Barcode card is a code in the form of a line of black or rectangular lines. Each line of the rectangle has a different width. So in this study the barcode card is used as an ID for parking users or parking customers who replace the manual parking system. The parking system data collection starts with Barcode Card user parking which is invincible with the parking user database via Barcode Scan. In a parking system using a Barcode Card, parking users can see the hours of entry and exit of parking congestion. by simply scanning or pasting the Barcode Card on the HC-SR04 sensor. This parking system will work based on existing data on the RFID tag and RFID reader. The data from the RFID tag will read the RFID reader and be processed in the Raspberry pi and servo motor to open and close the bar, then the buzzer will sound after which the ultrasonic sensor closes and opens the bar when the motor passes the sensor. With the parking system using this Barcode Card can provide security, comfort in the parking area is more guaranteed, and the parking area is managed in an orderly manner.
PENERAPAN METODE SURF DAN FLANN UNTUK MENDETEKSI TERBITAN SPAM PADA INSTAGRAM Dwi Sandi Yulianto; Adri Priadana; Andika Bayu Saputra; Fajar Syahruddin
Jurnal Teknomatika Vol 14 No 2 (2021): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v14i2.1125

Abstract

Social media is a new media that utilizes the internet to share information, interact, participate and others, and to be used with each other. Currently there are many social media circulating, one of which is Instagram. At first Instagram was only used to share photos, then along with the development of technology and media, Instagram also developed into being able to share videos and shop on Instagram. Instagram is also one of the social media specifically used to upload images and videos. The growing use of Instagram in supporting promotion makes Instagram faced with various problems, one of which is the emergence of spam issues. For example, the publication of spam on Instagram is published by several sellers of products or the like continuously. It's good to promote a product. But on the other hand, it will interfere with other users if the spam often appears. This is exacerbated by the mass use of popular hashtags, done with the aim of getting more views. Popular hashtags are hashtags that are followed by many Instagram users. Based on these problems, it takes a computer program to detect spam issues based on certain hashtags on Instagram. In this final task, the Speeded-Up Robust Features (SURF) and Fast Library for Approximate Nearest Neighbor (FLANN) methods will be applied to detect spam publications on Instagram. The results of experiments that have been conducted on 12 images that produce 66 comparisons, the application of SURF and FLANN methods can be said to be very good in detecting the similarity of images between Instagram publications that indicate that the same image is a spam issue, which is with a maximum accuracy value of 100%.
Sistem Pendukung Keputusan Pemberian Beasiswa Kurang Mampu di SMA Negeri 2 Kupang Menggunakan Metode Profile Matching Jonia Nova Da Costa; Adri Priadana; M. Abu Amar Al Badawi
Jurnal Teknomatika Vol 13 No 1 (2020): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v13i1.1126

Abstract

At SMAN 2 Kupang, the scholarship program for underprivileged students greatly contributes to their educational attainment. Scholarships at SMAN 2 Kupang are awarded based on parents/guardians' income, number of dependents, possession of smart Indonesian cards, and disabilities. However, there is often an issue of inaccurate scholarship distribution. Some students who do not meet the eligibility criteria receive scholarships, while deserving students who are less fortunate do not receive them. To address this problem, we propose a scholarship decision support system utilizing the profile matching method as the calculation algorithm. The system is developed using the PHP programming language and MySQL database. The primary benefit of this system is to assist in the scholarship selection process based on predetermined criteria. The system includes student registration, profile matching calculation, and the ability to generate registration and calculation reports.
Portal Masjid “Mosque Wanted” Solusi Pencarian Lokasi Masjid, Info Kajian & Berita Seputar Masjid di Yogyakarta Imam Puji Santoso; Andika Bayu Saputra; M. Abu Amar Al Badawi
Jurnal Teknomatika Vol 13 No 2 (2020): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v13i2.1127

Abstract

The dissemination of information and news about mosques in the Yogyakarta area has predominantly relied on social media and the Internet. Most mosques, especially the larger ones, have established their own social media accounts to showcase their activities. However, the information shared is typically limited to text and graphics, such as WhatsApp broadcasts, Instagram posts, Facebook updates, Twitter tweets, or posters displayed within the mosque premises. This text and graphic-based approach restricts accessibility for individuals who are unable to attend mosque activities due to various reasons, including difficulties in navigating to the mosque. This research aims to develop a Web-based Geographical Information System (GIS) that provides a mosque search solution, study information, and news about mosques in Yogyakarta. The system utilizes a responsive web design to enhance the dissemination of information, facilitate navigation, and stimulate public interest in studying Islamic sciences in Yogyakarta. The outcomes of this study offer valuable support to mosque administrators in providing comprehensive information about the mosque, particularly for Islamic da'wah activities. By incorporating detailed information and location data into the system, the dissemination of da'wah information can be improved. Moreover, the system enables the community to easily locate nearby mosques that offer Islamic da'wah activities and access real-time information about these activities.
Penerapan Metode Rabin-Karp untuk Mengukur Kemiripan Kata Dua Dokumen Berbasis Web Ramadhana Saputra; Ari Cahyono; M. Abu Amar Al Badawi
Jurnal Teknomatika Vol 14 No 1 (2021): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v14i1.1128

Abstract

Scientific literature plays a significant role in the academic requirements of colleges, encompassing various types such as papers, reports, journals, and scripts. However, the issue of plagiarism, including the copying and plagiarizing of others' work, remains prevalent in the creation of scientific papers. In particular, digital content plagiarism often involves copy-pasting and quoting from original documents. To address this, measuring the similarity of words between documents becomes essential. In Dhamayanti's research, the recommendation is to enhance the Rabin-Karp algorithm by utilizing a distinct method [1]. This study builds upon previous research employing a string-matching method. Instead of the conventional cosine method, the substitution method employed string-Karp techniques within the Rabin-Karp algorithm, resulting in improved similarity percentages. The manufacturing of the application adopts the string-matching method using the Rabin-Karp algorithm. The algorithm matches 5-gram word sequences converted into hash values, and the similarity percentage is determined based on matching hash values. The presence of identical words indicates similarity. The application is tested using six scientific writing documents from diverse sources with related titles. Through 15 test runs, the accuracy level reached 90%.
Analisis Sentimen Pergerakan Harga Saham Sebuah Perusahaan di Media Sosial Twitter Agung Purwanto Soedarbe; Muhammad Rifqi Ma'arif; Aris Wahyu Murdiyanto; M. Abu Amar Al Badawi
Jurnal Teknomatika Vol 14 No 2 (2021): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v14i2.1129

Abstract

Twitter has become an essential platform for traders and stock investors worldwide, including major countries like America. Traders rely on Twitter to gather information, similar to how they use Bloomberg terminals. While Twitter provides valuable insights, it also contains negative elements such as false information. The sentiment surrounding stocks on Twitter has been growing, and this study aims to analyze the sentiment of Telkom Indonesia's stock price based on tweets. The research involved several stages. First, data was collected from Twitter and labeled manually into positive, neutral, and negative sentiments. The data then underwent pre-processing, including cleaning and dividing it into training and testing datasets using K-Fold Cross Validation. The data was further weighted using the TF-IDF method, and a training process was conducted to develop a model. The final stage involved testing the accuracy of the model. The study successfully implemented the Multinomial Naïve Bayes (MNB) method, achieving an accuracy of 89.0%. The tweet classification results revealed that out of 1000 tweets, 76.5% were classified as positive, 14.3% as negative, and 9.2% as neutral.
Analisis Quality of Service (QOS) pada Akses Game Online Menggunakan Standar Tiphon Bambang Nakulo; Chanief Budi Setiawan; Rama Sahtyawan; M. Abu Amar Al Badawi
Jurnal Teknomatika Vol 15 No 1 (2022): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v15i1.1130

Abstract

The quality of internet service plays a crucial role in online gaming experiences. This study focuses on assessing the quality of internet services provided by 6 cellular cards in Indonesia using the TIPHON standard. The objective is to determine the suitability of these services for online gaming on a website. Data packets generated during online gaming sessions were captured using the Wireshark application in three different locations. The captured data was processed using the TIPHON standard formula to evaluate the quality of internet service provided by the 6 cellular cards. The analysis of the captured data revealed that three cellular cards, namely Telkomsel, XL, and Tri, demonstrated good performance in terms of providing a quality online gaming experience. The results were consistent across the three tested locations. Based on the TIPHON standard, the evaluation of 6 cellular cards in three different locations indicated that three of them (Telkomsel, XL, and Tri) offer suitable internet service for playing online games on the website.
PERBANDINGAN METODE DECISION TREE DAN NAIVE BAYES CLASSIFIER PADA ANALISIS SENTIMEN PENGGUNA LAYANAN PT PERUSAHAAN LISTRIK NEGARA (PLN) ABIYOGA BAGUS MUSTRIYANTO; Muhammad Habibi; Dayat Subekti; Fajar Syahruddin
Jurnal Teknomatika Vol 15 No 2 (2022): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v15i2.1131

Abstract

Background : PLN is a state-owned company that is tasked with supplying electricity to all regions of Indonesia which certainly cannot be separated from the various obstacles experienced, to find out public sentiment on the services that have been provided, an analysis is carried out to determine public sentiment. The results of these sentiments are created in the dashboard using the Flask framework by comparing the Naive Bayes and Decision tree methods. To create a sentiment analysis dashboard for PT. PLN and make a research analysis model using a comparison of the Naive Bayes Classification and Decision tree methods. The method used in this research is Naive Bayes and Decision tree. The data obtained with a total of 40,745 Tweet data taken in the period 1 May 2022 - 4 June 2022 with the keyword "PLN". Making a dashboard that displays the results of the analysis where there is a menu to display the data and each analysis process. The use of 900 training data and 300 testing data resulted in the Naive Bayes method getting an accuracy of 83% on the training data and 80% for the Testing data, while the Decision tree method got an accuracy of 77% on the Training data and 56% on the Testing data. The analysis obtained for the method in this study also shows that the Naive Bayes method is better for classifying large amounts of data than the Decision tree. The sentiment generated by the highest number is negative, with most of the Tweets being complaints about the response to complaints and handling of damage reported by the public.
Analisis Sentimen Opini Masyarakat Tentang Penggunaan Aplikasi Bimbingan Belajar Online di Masa Pandemi Covid-19 Menggunakan Metode Support Vector Machine (SVM) Albet Gunawan; Andika Bayu Saputra; M. Abu Amar Al Badawi
Jurnal Teknomatika Vol 15 No 2 (2022): TEKNOMATIKA
Publisher : Fakultas Teknik dan Teknologi Informasi, Universitas Jenderal Achmad Yani Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30989/teknomatika.v15i2.1132

Abstract

Distance learning has emerged as a response to the Covid-19 pandemic, providing students with a new approach to learning. Online learning platforms, utilizing information technology, have become essential in connecting students and teachers. Online tutoring applications offer valuable supplementary educational materials, with various features to support the learning process. Analyzing sentiment on Twitter regarding these online tutoring applications is crucial in determining the best options for students. This study aims to develop an analytical model using the Support Vector Machine (SVM) for online tutoring applications during the Covid-19 pandemic. The research focuses on analyzing positive and negative sentiments within Twitter data, utilizing the Support Vector Machine (SVM) method. The training phase involved 800 manually labeled tweets, consisting of 400 positive and 400 negative sentiments. For testing, 23,511 labeled data points were used. The training data achieved an accuracy of 91.81%. The research successfully achieved an accuracy rate of 90.62% for training and 91% for testing.

Page 20 of 28 | Total Record : 271

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