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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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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

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 Saputra, Ramadhana; Cahyono, Ari; Al Badawi, M. Abu Amar
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%.
PERBANDINGAN METODE DECISION TREE DAN NAIVE BAYES CLASSIFIER PADA ANALISIS SENTIMEN PENGGUNA LAYANAN PT PERUSAHAAN LISTRIK NEGARA (PLN) BAGUS MUSTRIYANTO, ABIYOGA; Muhammad Habibi; Subekti, Dayat; Syahruddin, Fajar
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) 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

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.
Analisis Pola Konsumen Dalam Bertransaksi Bisnis di Bengkel Resmi AHASS Total Honda Motor Wardoyo, Budi; Cahyo, Puji Winar; Habibi, Muhammad; Al Badawi, M. Abu Amar
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.v16i1.1133

Abstract

The accumulated data, which consists of facts and transaction events in a business, should be processed and utilized for the progress of business development. Currently, the data owned by AHASS THM has not been optimized and further processed to provide broader benefits, such as promotion and forming loyal AHASS customers. The objective of this research is to analyze the existing transaction data to identify consumer transaction patterns at AHASS THM. The research methodology used is Market Basket Analysis (MBA), a method for analyzing consumer transaction data by finding associative relationships between different items in the consumer's shopping cart. By applying a minimum parameter limitation of support = 0.001, confidence = 0.8, and sorting based on the magnitude of the confidence parameter, 62 associative rules of consumer transaction patterns in AHASS THM business were obtained. By selecting the top 10 associative rules based on the highest confidence values, generally, these associative rules have a confidence parameter greater than 0.95 or 95%. Additionally, there are 3 associative rules with a confidence value of 1 or 100%, indicating that consumers will purchase Bearing Needle 20x29x218 after buying Bearing Ball 6902U, or a combination of Bearing Ball 6902U with CVT Grease 10 gr or Oli MPX2 0.8 lt.
APLIKASI MONITORING DATA KETERSEDIAAN SOAL BERBASIS WEB PADA SITUS TANYA JAWAB BRAINLY Prasetyo, Moch. Adji; Bayu Saputra, Andika; Priadana, Adri; Syahruddin, Fajar
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

Abstract

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.
RANCANG BANGUN SISTEM PENYIRAMAN OTOMATIS MENGGUNAKAN SENSOR KELEMBABAN TANAH PADA TANAMAN SELEDRI BERBASIS NodeMCU ESP8266 Muhammad Chanafi; Sudarmana, Landung; Syahruddin, Fajar
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.v13i2.1136

Abstract

Celery is the one of the vegeTabels that has several benefits, it can be used as a complement for cooking and it has medical function. Several factors that influence the growth of celery are soil and air conditions. These conditions must be always monitored so that the growth of celery becomes fertile. The design of automatic watering monitor system use soil’s moisture sensor, it can help the farmers and celery cultivators to increase the productivity and quality of celery cultivation. By using the NodelMCU ESP8266, which is equipped by a soil’s moisture sensor and DHT11 sensor. Thus, it can monitor the condition of soil’s moisture, air temperature, humidity, and record the data that can be stored in database and displayed on a web page by using Tabel form. This research produces a prototype system that can be able to monitor soil’s moisture conditions, air temperature and humidity in celery cultivation, it can be used to monitor soil conditions in order to maintain the humidity.
ANALISIS KOMPARATIF UX DESIGN PADA PLATFORM EDUKASI ONLINE Agus Setiawan, Hendry; Ma’arif, Muhammad Rifqi; Budi Setiawan, Chanief; Syahruddin, Fajar
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.v13i1.1138

Abstract

User experience is the result of what the user feels and thinks when using a product or service, and makes the user experience subjective, therefore the user experience (user experience) can be tested in conjunction with other tests to get an objective assessment of the user when can be done directly with the product. This study will discuss the user experience using the User Experience Questionnaire and Focus Group Discussion methods. The process to be carried out is by using the Brainly and Quora applications obtained from the UEQ and FGD test questionnaires through interviews and data interviews from questionnaires. Based on the results of this study, the results of the analysis and comparisons with UEQ and FGD were obtained. The first test objectively used direct testing to respondents using the UEQ questionnaire which has 6 scales, namely: attractiveness, efficiency, perspective, dependability, stimulation and novelty, which are given to 11 respondents. Second, subjective testing using Focus Group Discussion for perceptions and more detailed user problems with interviews. From the second test conducted, it can be denied that the Brainly application is superior to Quora.
PEMODELAN TOPIK TERKAIT BANJIR PADA TWITTER DENGAN MENGGUNAKAN LATENT DIRICHLET ALLOCATION IRWANSYAH, MUHAMMAD SUTAN; Muhammad Habibi; Syahruddin, Fajar
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.v16i1.1139

Abstract

In this background discusses the topic of tweet about Flooding on Twitter using the keyword "Flood". Tweet data was taken from June 1, 2021 to June 2, 2021 with the number of tweet data obtained, which was 2000 tweets. The number of tweets related to flooding has not been analyzed so that the topics contained in it are not yet known. Research . Modeling topics related to floods in Indonesia on Twitter social media with the LDA method. Research. This study uses experimental methods with several variables to test hypotheses. Then the data is processed with stages, namely web data extraction, preprocessing, feature extraction, topic modeling using latent dirichlet allocation algorithms, visualization, and analysis. Research. The results of the topic coherence stage were carried out a search for the most optimal topic from the 20 topics that had been determined at the beginning. The results of topic coherence for 20 topics concluded that for topic 10 it has a total topic value of 0.41 and has an ideal topic modeling result and is in accordance with the provisions. Conclusion : Based on the results of the discussion of topic coherence, it can be concluded that the most ideal number of topics is topic 10 because it has the highest value compared to other topics. The advice here is to be able to display or get flood information in Indonesia in real time and accurately.
Metode Hybrid Menggunakan Pendekatan Lexicon Based dan Naive Bayes Classifier Untuk Analisis Sentimen Terkait Jaminan Hari Tua Fauzi Akbar, Rizky; Habibi, Muhammad; Winar Cahyo, Puji; Alfi Sa'diya, Nafisa
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.v16i2.1247

Abstract

Badan Penyelenggara Jaminan Sosial (BPJS) Ketenagakerjaan adalah badan aturan publik yang dibuat melalui Undang-Undang No 24 Tahun 2011 Tentang Badan Penyelenggaran Jaminan Sosial menggunakan tujuan untuk mewujudkan terselenggaranya pemberian jaminan terpenuhinya kebutuhan dasar yang layak bagi setiap peserta atau anggota keluarganya. Dalam pelaksanaannya terdapat informasi yang tersebar khususnya pada tweet di Twitter mengenai keputusan Kementrian Kesehatan yaitu mengenai Jaminan Hari Tua (JHT) yang hanya bisa dicairkan/diambil setelah peserta (BPJS) Ketenagakerjaan menginjak usia 56 tahun, menyebabkan adanya pro dan kontra yang ada dikalangan masyarakat. Berdasarkan tweet-tweet pada Twitter yang belum dianalisis maka perlu di analisis secara mendalam untuk mendapatkan informasi yang sesuai berdasarkan opini netizen. Berdasarkan hasil penelitian ini diperoleh nilai akurasi data testing sebesar 92% untuk metode Lexicon Based dan 95% untuk data testing pada metode Naïve Bayes Classifier lalu untuk data training Naïve Bayes Classifier mendapatkan akurasi 82%. Penelitian ini mendapatkan kesimpulan bahwa jaminan hari tua (JHT) pada (BPJS) Ketenagakerjaan mendapat sentimen negatif dari netizen yang banyak membahas mengenai penolakan peraturan baru dimana jaminan hari tua (JHT) pada (BPJS) Ketenagakerjaan, hanya bisa dicairkan atau diambil ketika peserta BPJS Ketenagakerjaan menginjak usia 56 tahun.

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