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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

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%.

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

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.

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

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.

APLIKASI MONITORING DATA KETERSEDIAAN SOAL BERBASIS WEB PADA SITUS TANYA JAWAB BRAINLY Moch. Adji Prasetyo; Andika Bayu Saputra; Adri Priadana; Fajar Syahruddin
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.v14i1.1134

Brainly is a website that allows users to ask each other and answer questions related to school lessons openly to other users. On the site, you must first create an account as a questioner or answerer. Brainly harness the power Freelance to answer questions on the Brainly website. In working on the questions carried out by the Brainly Freelancer, there are often delays in updating questions at the Uniform Resource address Locator (URL) assigned to Freelancers. This results in Freelancers often being hampered in their work meet the target of working on the questions because the questions that have been answered are still not replaced with a new question. Therefore, the researcher designed and built an Application for Monitoring Data Availability of Web-Based Questions on the Tanya Site Answer on the Brainly site which aims to make it easier for Brainly Freelancers to meet their target for working on questions. This application is built using the Python programming language by utilizing the Flask framework. The results of this study state that the process contained in the application has been running smoothly as evidenced by the results of black box testing. User testing is done with Brainly Freelancers opening the application and viewing the availability of unanswered questions on the Brainly URL with a table view.

Implementasi Penggunaan Algoritma Weighted Product untuk Sistem Pendukung Keputusan Bantuan Lansia Ferlinda Yuyung Kusumaningrum; Andika Bayu Saputra; Agung Priyanto; Nurul Fatimah
Jurnal Teknomatika Vol 16 No 2 (2023): 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.v16i2.1249

Lansia merupakan suatu siklus hidup yang pasti dialami oleh manusia dan hampir setiap orang. Terdapat permasalahan yang dihadapi oleh lansia dari menurunnya kondisi fisik sampai tidak dapat bekerja, Pemerintah mengeluarkan program untuk mendukung lansia. Bantuan lansia yang dapat diterima setiap tiga bulan atau sesuai informasi dari pemerintah. Namun saat ini program yang ada masih belum efektif karena terdapat kendala seperti belum ada sebuah sistem yang dapat menginputkan data, sehingga pendataan bantuan lansia masih secara manual menggunakan pencatatan di buku yang dapat menghambat waktu pendataan dan perhitungan data. Penelitian ini bertujuan untuk membangun sebuah sistem pendukung keputusan dalam menentukan penerima bantuan lansia guna membantu dalam proses pengambilan keputusan. Algoritma weighted product yang merupakan suatu algoritma yang sering digunakan untuk menganalisa sebuah keputusan. Hasil penelitian ini berupa sebuah Implementasi Penggunaan Algoritma Weighted Product untuk Sistem Pendukung Keputusan Penerima Bantuan Lansia. Sistem diharapkan membantu dalam menentukan keputusan dari barbagai pilihan yang mempertimbangkan beberapa macam kriteria dan dapat diterapkan untuk membantu menyelesaikan permasalahan mengidentifikasi penerima bantuan lansia secara cepat, tepat dan efektif.

Sistem Prediksi Kasus Covid-19 di Indonesia Menggunakan Algoritma Linear Regression Mufidah, Yusriyah Isnaini; Saputra, Andika Bayu; Kusumaningtyas, Netania Indi
Jurnal Teknomatika Vol 16 No 1 (2023): 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.v16i1.1099

The Coronavirus disease outbreak caused by severe acute respiratory syndrome by coronavirus 2 was first reported in Wuhan, Hubei province, China in December 2019, until March 2, 2020, President Joko Widodo announced the first case of an Indonesian citizen who was confirmed positive for COVID-19. The development of new cases of COVID-19 patients in Indonesia is still being reported even though the pandemic has lasted for almost two years. Then need a way to determine predictions or predict the number of increases in Indonesia’s COVID-19 cases in the future using machine learning technology with the Linear Regression algorithm. Estimating the number of active cases adding positive COVID-19 cases in Indonesia over the next 3 months using the machine learning method using the Linear Regression algorithm. This study predicts COVID-19 cases using machine learning with the Linear Regression algorithm. The model results have a linear coefficient, so the model predicts very well for linear data on days 0 – 300, and on the day after that, the number of positive cases of the national COVID-19 virus does not continue to show a linear relationship, the model becomes inaccurate again. The results of the parameter evaluation show that the level of accuracy is low, but this model can be used as a reference for case predictions for the next month with the results of comparison of predicted data and actual data not much different.

MONITORING PEMAKAIAN ARUS DAN PENGENDALI INTENSITAS CAHAYA PADA LAMPU BERBASIS INTERNET OF THINGS MENGGUNAKAN ANDROID Fatta Shofa Hasani; Choerun Asnawi; Andika Bayu Saputra; Alfun Roehatul Jannah
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.v14i1.1100

The switch on and off of a light takes time when it has to be done in a lot of space. Not to mention in a multistoried building that had to turn the lights on and off on each floor of the building and in each room. Not only that, the omission in turning on and off lights would be very dangerous if left unchecked. Besides electrical waste, a fire starter will occur when lights will run continuously. To make it easier for users to engage in daily activities in turn off lights especially in many areas, it is suggested in this study that a prototype of the current monitoring system and light intensity control for lights based on the Internet of things which the design would be integrated with wi-fi and android. The prototype was built to provide the solution by turning off and turning on the lights without having to move from place to place. Designed by simple looks, the user can control it via the android. With the prototypes and created systems it is expected to make user activity easier and minimise the user negligence factor in turning on and off lights that can overload electricity to fire triggers.

PURWARUPA ALAT PENDETEKSI OTOMATIS KETINGGIAN AIR UNTUK MENGATUR BUKA TUTUP PINTU AIR BERBASIS ARDUINO M Roykhul Jinan; Agung Priyanto; Andika Bayu Saputra; Alfun Roehatul Jannah
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.v15i2.1102

With the increasing population and the reduction of water catchment areas due to numerous development projects that disregard green open spaces, coupled with a lack of public awareness regarding the importance of water flow, many individuals continue to consciously dispose of garbage into rivers, including river areas, dams, and reservoirs. This behavior leads to river blockages, resulting in flooding in those areas and other low-lying regions. The traditional method of monitoring water levels heavily relies on human operators, which can introduce errors when interpreting water indicators. To address these challenges, this research adopts a design-oriented methodology to develop an automated system for real-time maintenance and monitoring of water levels. The study begins with a comprehensive analysis of the existing issues and the underlying processes involved. Subsequently, the research focuses on designing and implementing a prototype system using appropriate materials, system development tools, and methodologies. The proposed system consists of a water level detection device integrated with a servo-controlled dam opener. Experimental tests demonstrate the device's effectiveness in accurately detecting changes in water levels, with an average accuracy of 10 cm from the sensor point. Additionally, the servo-controlled dam opener plays a significant role in regulating water flow within the system. The proposed system aims to facilitate efficient monitoring and decision-making processes, thereby reducing the occurrence of human errors in determining water levels.

Portal Masjid “Mosque Wanted” Solusi Pencarian Lokasi Masjid, Info Kajian & Berita Seputar Masjid di Yogyakarta Puji Santoso, Imam; Saputra, Andika Bayu; Al Badawi, M. Abu Amar
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

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.

Analisis Sentimen Opini Masyarakat Tentang Penggunaan Aplikasi Bimbingan Belajar Online di Masa Pandemi Covid-19 Menggunakan Metode Support Vector Machine (SVM) Gunawan, Albet; Saputra, Andika Bayu; Al Badawi, M. Abu Amar
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

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.

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