Jurnal Komtika (Komputasi dan Informatika)
Aims Jurnal Komtika (Komputasi dan Informatika) is a scientific journal published by the Faculty of Engineering, Universitas Muhammadiyah Magelang and is Accredited by the Ministry for Research, Technology, and Higher Education (RISTEKDIKTI)(No:200/M/KPT/2020). It is a medium for researchers, academics, and practitioners interested in Computer Science and wish to channel their thoughts and findings. Our concept of Informatics includes technologies of information and communication as well as results of research, critical, and comprehensive scientific study which are relevant and current issues covered by the journals. Jurnal Komtika publishes regular research articles. We encourage researchers to publish their theoretical and empirical results in as much detail as possible. For theoretical papers, full details of proofs must be provided so that the results can be checked; for experimental papers, full experimental details must be given so that the results can be reproduced. Additionally, electronic files or software regarding the full details of the calculations, experimental procedure, etc., can be deposited along with the publication as “Supplementary Material”. Scope Jurnal Komputasi dan Informatika (Komtika) focuses on various issues, but not limited in the field of: Software Development: Software development process, Requirements analysis, Software design, Software construction, Software deployment, Software maintenance, Programming team, Open-source model Mathematics of Computing: Discrete mathematics, Mathematical software, Information theory Theory of computation: Model of computation, Computational complexity Human Computer Interaction: Interaction design, Social computing, Ubiquitous computing, Visualization, Accessibility, User Interface Study, User Experience Study Applied Computing: E-commerce, Enterprise software, Electronic publishing, Cyberwarfare, Electronic voting, Video game, Word processing, Operations research, Educational technology, Document management. Machine Learning: upervised learning, Unsupervised learning, Reinforcement learning, Multi-task learning Graphics: Animation, Rendering, Image manipulation, Graphics processing unit, Mixed reality, Virtual reality, Image compression, Solid modeling Information System: Database management system, Information storage systems, Enterprise information system, Social information systems, Geographic information system, Decision support system, Process control system, Multimedia information system, Data mining, Digital library, Computing platform, Digital marketing, World Wide Web, Information retrieval
Articles
144 Documents
<![CDATA[Identifikasi Penyakit Tanaman Ubi Kayu Berdasarkan Citra Daun Menggunakan Metode Probabilistic Neural Network (PNN) ]]>
<![CDATA[Sari, Yuslena]]>;
<![CDATA[Alkaff, Muhammad]]>;
<![CDATA[Arif Rahman, Muhammad]]>
<![CDATA[ Jurnal Komtika (Komputasi dan Informatika) Vol 5 No 1 (2021) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Magelang ]]>
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DOI: 10.31603/komtika.v5i1.4605
<![CDATA[Cassava or better known as cassava is one of the staples of rice which is popular in Indonesia. Cassava plants can flourish in almost all regions of Indonesia. However, cassava is a plant that is susceptible to plant disease, which attacks the disease resulting in a decrease in the amount of productivity of tubers produced by cassava plants. The application of identifying cassava disease based on leaf image is expected to be useful as a support for cassava farming in easily detecting cassava disease, so that it can be dealt with more quickly. This study uses the Gray Level Co-occurrence Matrix (GLCM) method as an extraction feature and the Probabilistic Neural Network (PNN) method for identification processes. Based on the results of tests on 6 types of cassava leaf images, obtained an accuracy of 83.33%.]]>
<![CDATA[Implementasi Aplikasi Monitoring Nilai dan Kegiatan Siswa Berbasis Android dengan Metode Prototype ]]>
<![CDATA[Juniawan, Fransiskus Panca]]>;
<![CDATA[Sylfania, Dwi Yuny]]>;
<![CDATA[Rian Chrisna Putra, Rendy]]>;
<![CDATA[Sulaiman, Rahmat]]>
<![CDATA[ Jurnal Komtika (Komputasi dan Informatika) Vol 5 No 1 (2021) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Magelang ]]>
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DOI: 10.31603/komtika.v5i1.5119
<![CDATA[The number of smartphone and internet users in Indonesia is currently very large. This is become the basis for the use and development of mobile-based applications for the advantage of education. However, not all High Schools in Indonesia have a mobile-based system. Another problem is that most of them still use conventional methods in implementing teaching and learning activities, and reporting learning outcomes to parents. This is also still the case at SMA Negeri 1 Pangkalanbaru, Bangka Tengah. This problem is what we want to raise and solve by developing applications that can solve these problems. The research was developed using the Prototype method which consists of stages of Data Collection, Rapid Planning, Prototype Design, and Prototype Testing. By using the UML tool, results are obtained in the form of parents who can monitor grades, school information, and school announcements. In addition, students can take attendance online, register for extracurricular activities, and view announcements. From the testing results it is known that the system performance is running well as it should.]]>
<![CDATA[Analisis Keamanan Sistem Informasi Menggunakan Sudomy dan OWASP ZAP di Universitas Duta Bangsa Surakarta ]]>
<![CDATA[Hariyadi, Dedy]]>;
<![CDATA[Nastiti, Faulinda Ely]]>
<![CDATA[ Jurnal Komtika (Komputasi dan Informatika) Vol 5 No 1 (2021) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Magelang ]]>
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DOI: 10.31603/komtika.v5i1.5134
<![CDATA[Peretas saat ini tidak hanya menyerang instansi pemerintah seperti pada tahun 2019 melainkan sudah melakukan serangan ke instansi pendidikan. Hal ini sesuai dengan pantauan dan identifikasi Badan Siber dan Sandi Negara bahwa instansi pendidikan telah diserang sebanyak 38% pada tahun 2020. Sebagai wujud tindakan preventif terkait dengan serangan siber pada instansi pendidikan perlu dilakukan sebuah tindakan analisis keamanan informasi terhadap sistem-sistem yang terpasang. Pada artikel ini diusulkan tahapan teknis melakukan analisis keamanan informasi menggunakan perangkat lunak dengan lisensi Free Open Source Software, yaitu Sudomy dan OWASP ZAP. Menggunakan kedua perangkat lunak tersebut didapatkan hasil analisis potensi-potensi celah keamanan pada sistem informasi yang terpasang pada Universitas Duta Bangsa.]]>
<![CDATA[Prediksi Perubahan Penggunaan Lahan dan Pola Berdasarkan Citra Landsat Multi Waktu dengan Land Change Modeler (LCM) ]]>
<![CDATA[Herlawati, Herlawati]]>;
<![CDATA[Nidaul Khasanah, Fata]]>;
<![CDATA[Dina Atika, Prima]]>;
<![CDATA[Sari, Rafika]]>;
<![CDATA[Handayanto, Rahmadya Trias]]>
<![CDATA[ Jurnal Komtika (Komputasi dan Informatika) Vol 5 No 1 (2021) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Magelang ]]>
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DOI: 10.31603/komtika.v5i1.5139
<![CDATA[Land use/cover greatly affect the quality of an area. Therefore, many regional planners need assistance byother fields, such as geoinformatics, computer science, environment, and others. Although prediction and forecasting have been widely studied, in regardto real conditions (geospatial)itstill needmoredevelopment, especially thoseinvolving a combination of regional types, such as urban and suburban areas. This study uses a remote sensing base and geographic information system in predicting land in the city and district of Bekasi, West Java, Indonesia. With two scenarios compared (business as usual and vegetation conservation), the model that has been created and validated (with an AUC accuracy result of 0.828) is used to predict land use change until 2030. Scenarios with vegetation conservation are able to keep green areas to switch to land types others, such as buildings and industry]]>
<![CDATA[Komparasi Algoritma Naive Bayes dan K-Nearest Neighbor untuk Membangun Pengetahuan Diagnosa Penyakit Diabetes ]]>
<![CDATA[Nurmalasari, Maulidya Dwi]]>;
<![CDATA[Kusrini, Kusrini]]>;
<![CDATA[Sudarmawan, Sudarmawan]]>
<![CDATA[ Jurnal Komtika (Komputasi dan Informatika) Vol 5 No 1 (2021) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Magelang ]]>
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DOI: 10.31603/komtika.v5i1.5140
<![CDATA[Diabetes is caused by a deficiency of the hormone insulin, which is secreted by the pancreas to lower blood sugar levels. The factors that trigger the occurrence of diabetes are derived from various factors such as a combination of genetic and environmental factors. The phenomenon of the emergence of various beverage brand outlets can be one of the triggers for blood sugar levels in humans. Normal blood sugar levels in the body range from 70-130 mg/dL before eating, less than 180 mg/dL two hours after eating, less than 100 mg/dL after not eating or surviving for eight hours, and 100-140 mg/dL at bedtime. This research aims to determine which algorithm is suitable for building knowledge about diabetes using the Naïve Bayes and K-Nearest Neighbor (KNN) algorithm. The accuracy results from Naïve Bayes are 85.60% and K- Nearest Neighbor of 91.61%. The results showed that K-Nearest Neighbor proved to have the best accuracy.]]>
<![CDATA[Analisis Sentimen Opini Terhadap Vaksin Covid - 19 pada Media Sosial Twitter Menggunakan Support Vector Machine dan Naive Bayes ]]>
<![CDATA[Fitriana, Frizka]]>;
<![CDATA[Utami, Ema]]>;
<![CDATA[Al Fatta, Hanif]]>
<![CDATA[ Jurnal Komtika (Komputasi dan Informatika) Vol 5 No 1 (2021) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Magelang ]]>
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DOI: 10.31603/komtika.v5i1.5185
<![CDATA[The corona virus outbreak, commonly referred to as COVID-19, has been officially designated a global pandemic by the World Health Organization (WHO). To minimize the impact caused by the virus, one of the right steps is to develop a vaccine, however, with the vaccination for the Indonesian people, it is controversial so that it invites many people to give an opinion assessment, but the limited space makes it difficult for the public to express their opinion, because Therefore, people choose social media as a place to channel public opinion. Support vector machine algorithm has better performance in terms of accuracy, precision and recall with values of 90.47%, 90.23%, 90.78% with performance values on the Bayes algorithm, namely 88.64%, 87.32%, 88, 13%, with a difference of 1.83% accuracy, 2.91% precision and 2.65% recall, while for time the Naive Bayes algorithm has a better performance level with a value of 8.1 seconds and the Support vector machine algorithm gets a time speed of 11 seconds with a difference of 2, 9 seconds. With the results of sentiment analysis neutral 8.76%, negative 42.92% and positive 48.32% for Bayes and neutral 10.56%, negative 41.28% and positive 48.16% for SVM.]]>
<![CDATA[Sentimen Analisis Terhadap Aplikasi pada Google Playstore Menggunakan Algoritma Naïve Bayes dan Algoritma Genetika ]]>
<![CDATA[Rahman, Arif]]>;
<![CDATA[Utami, Ema]]>;
<![CDATA[Sudarmawan, Sudarmawan]]>
<![CDATA[ Jurnal Komtika (Komputasi dan Informatika) Vol 5 No 1 (2021) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Magelang ]]>
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DOI: 10.31603/komtika.v5i1.5188
<![CDATA[Sentiment analysis is a science to extract text to get someone's emotions for that. The benefits of sentiment analysis have many benefits, one of which is to see whether or not customers have a good response to the product and this can be an input for the development of the product's business in the future. The weakness of previous studies in research sentiment analysis is that the authors conduct research to improve the results of previous studies using the naïve Bayes algorithm that is optimized with a genetic algorithm. From the results of the research that has been done, the average value in this study is on average better than previous studies, no applications have been identified as underfitting or overfitting and finally the naïve Bayes algorithm that has been optimized by the genetic algorithm can be a classification solution for sentiment analysis.]]>
<![CDATA[Analisis Sentimen Twitter Kuliah Online Pasca Covid-19 Menggunakan Algoritma Support Vector Machine dan Naive Bayes ]]>
<![CDATA[Setiawan, Hendrik]]>;
<![CDATA[Utami, Ema]]>;
<![CDATA[Sudarmawan, Sudarmawan]]>
<![CDATA[ Jurnal Komtika (Komputasi dan Informatika) Vol 5 No 1 (2021) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Magelang ]]>
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DOI: 10.31603/komtika.v5i1.5189
<![CDATA[The World Health Organization (WHO) COVID-19 is an infectious disease caused by the Coronavirus which originally came from an outbreak in the city of Wuhan, China in December 2019 which later became a pandemic that occurred in many countries around the world. This disease has caused the government to give a regional lockdown status to give students the status of "at home" for students to enforce online or online lectures, this has caused various sentiments given by students in responding to online lectures via social media twitter. For sentiment analysis, the researcher applies the nave Bayes algorithm and support vector machine (SVM) with the performance results obtained on the Bayes algorithm with an accuracy of 81.20%, time 9.00 seconds, recall 79.60% and precision 79.40% while for the SVM algorithm get an accuracy value of 85%, time 31.60 seconds, recall 84% and precision 83.60%, the performance results are obtained in the 1st iteration for nave Bayes and the 423th iteration for the SVM algorithm]]>
<![CDATA[Sistem Pakar Diagnosa Penyakit pada Hewan Kucing Berbasis Web ]]>
<![CDATA[Ramadhan, Faiz Zaki]]>;
<![CDATA[Aditya, Gilang]]>;
<![CDATA[Nainggolan, Purnama Dileon Yamora]]>;
<![CDATA[Adhinata, Faisal Dharma]]>
<![CDATA[ Jurnal Komtika (Komputasi dan Informatika) Vol 5 No 2 (2021) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Magelang ]]>
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DOI: 10.31603/komtika.v5i2.5301
<![CDATA[Tahun 2018 Rakuten Insight menyurvei hewan jinak di Asia. Survei diikuti 97.000 responden dari benua asia timur dan asia tenggara. bahwa 59% orang memiliki binatang peliharaan. Dari banyaknya peliharaan, kucing menjadi pilihan, terutama diIndonesia. sebanyak 47% orang memelihara kucing. Kucing terkadang sering terkena penyakit, dan kita suka bingung apa yang terjadi dengan hewan kita, dan bagaimana cara kita bisa mengobatinya, terutama kota yang tidak memiliki rumah perawatan hewan. Untuk mengetahui penyakit apa yang diderita kucing, diperlukan informasi medis untuk mengetahui itu, sedangkan yang kita tahu masih sangat terbatas. akibatnya dibutuhkan sistem guna menyampaikan pengetahuan seperti seseorang pakar, penulis membuat sistem dimana berisi pengetahuan seseorang ahli penyakit pada kucing, agar masyarakat yang awam dapat mengetahui jenis penyakit serta penyembuhanya, rancangan sistem pakar menggunakan metode Naïve Bayes dimana pengklasifikasian probabilitasnya sederhana. keuntunganya naïve bayes hanya membutuhkan data kecil pelatihan untuk proses klasifikasi yang diperlukkan untuk parameter dalam membantu membuat sistem identifikasi penyakit. hasil contoh, kita menginputkan gejala-gejala seperti bulu rontok, lingkaran merah pada kulit, serta bercak putih seperti ketombe, dimana merupakan gejala pernyakit kadas seperti yang ada disystem. Hasil penelitian menunjukkan diagnosa penyakit kucing menggunakan naïve bayes dapat menghasilkan akurasi 93%.]]>
<![CDATA[Sistem Pendukung Keputusan Penilaian Kinerja Tenaga Kependidikan (TENDIK) Dengan Menggunakan Metode SMARTER ]]>
<![CDATA[Utomo, Dito Putro]]>;
<![CDATA[Purba, Bister]]>
<![CDATA[ Jurnal Komtika (Komputasi dan Informatika) Vol 5 No 2 (2021) ]]>
Publisher : <![CDATA[Universitas Muhammadiyah Magelang ]]>
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DOI: 10.31603/komtika.v5i2.5619
<![CDATA[The success of a university is not only seen from the role of Educators (Lecturers) but also the role of Education Personnel (TENDIK). Educational Personnel (TENDIK) includes Administrative Personnel in universities. Work performance is the main factor of the success of higher education performance. The results of good work given will have a good impact on universities. TENDIK who excels are also competent in higher education and contributes to the joint progress of both TENDIK and universities. Apart from lecturers, TENDIK is also an asset owned by universities. Rewards or awards given to TENDIK can be done by assessing the performance results of each TENDIK. The reward given to TENDIK is a form of appreciation for the performance carried out at the university. Giving rewards to TENDIK must be based on a proper and accurate performance assessment. The problem is that there is no definite reference used to evaluate the performance of TENDIK in giving rewards. The performance assessment carried out must be objective, of course, with an objective assessment the results obtained from the TENDIK performance assessment will not be a problem for other TENDIK. Decision Support System is a computer-based information system that is used to assist in decision making by utilizing certain data and models to support a solution in solving a semi-structured and non-structured problem. SMARTER is one of the methods in the Decision Support System that provides recommendations to decision makers based on relevant criteria, which in determining the criteria and sub-criteria and their weight values use ROC (Rank Order Centroid). Of the several criteria used for the selection process using the alternative SMARTER method with the name A4 with a final utility value of 64.25%]]>
