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2nd International Conference on Applied Sciences Mathematics and Informatics, ICASMI 2018

作者： Irawan, A. Lestari, M. Rahayu, W. Wulan, R. Program Studi Informatika Universitas Indraprasta PGRI Jl. Raya Tengah No. 80 Kel. Gedong Kec. Pasar Rebo Jakarta Timur13760 Indonesia

Aims of this study is to make an application to detect Balinese batik that has an etnomatematics elements using backpropagation method and to observe etnomatematics elements on Balinese batik. This study using qualitative descriptive methods with ethnographical approach, literature study, and expert study on etnomatematics issues. This paper shows that in typical Balinese batik there are several elements in the transformation of mathematics that are translation, reflection, rotation, while in other batik shows dilation elements In addition from the ethnography there are elements of spiritual and distinctiveness of the Balinese society that upholds local culture values. © Published under licence by IOP Publishing Ltd.

关键词： Mathematical transformations

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Dijkstra's Algorithm to Find Shortest Path of Tourist Destination in Bali 2

Dijkstra's Algorithm to Find Shortest Path of Tourist Destin...

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2nd International Conference on Applied Sciences Mathematics and Informatics, ICASMI 2018

作者： Fitriansyah, A. Parwati, N.W. Wardhani, D.R. Kustian, N. Program Studi Informatika Universitas Indraprasta PGRI Jl. Raya Tengah No.80 Kel. Gedong Kec. Pasar Rebo Jakarta Timur13760 Indonesia

Bali is one of many small island in Indonesia and referred as "The Island of Gods". Bali has varieties of tourist destination e.g. art villages, ecotourism, historical building, spiritual tourism and temples. Dijkstra's algorithm is an algorithm that used to be solution in finding shortest path problem. It can be use to find the shortest route between one tourist destination and all other tourist destinations. Hence, we use dijkstra's algorithm to find shortest path of tourist destination in Bali. There are top ten tourist destinations that has been used in this paper Tanah Lot, Uluwatu, Ulun Danu Beratan, Kebun Raya Eka Karya, Penelokan Batur, Tirta Empul, Taman Ayun, Bali Safari and Marine Park, Goa Gajah and Bali Zoo Park. © Published under licence by IOP Publishing Ltd.

关键词： Parks

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Comparison of argumentation skill in science and non-science undergraduate students

Comparison of argumentation skill in science and non-science...

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International Conference on Mathematics and Science Education (ICMScE)

作者： Hayat, M. S. Djuniadi, D. Prasetyo, A. P. B. Roshayanti, F. Wicaksono, A. G. C. Minarti, I. B. Sumarno, S. Univ PGRI Semarang Program Studi Pendidikan Biol FPMIPATI Sidodadi Timur 24Dr Cipto Semarang Indonesia Univ Negeri Semarang Program Studi Pendidikan Tekn Informatika & Kompu Fak Tekn Gedung E6 Kampus UNNES Sekaran Gunungpati Semarang 50229 Indonesia Univ Negeri Semarang Program Studi Pendidikan Biol Fak MIPA Gedung D6 Lantai 1 Kampus UNNES Sekaran Semarang 50229 Indonesia

This research is aimed to evaluate and compare the argumentation skill in science and non-science students. This research is quantitative research which involved two classes including 30 science students who taught human physiology subject and 30 social and humanities students who taught curriculum development subject. Both classes using blended learning with "argueweb" for online learning and debate for offline learning. The data collected from argumentation score using argumentation observation sheet. The data collected then to analyze descriptively and statistically using t-test. The result showed that there are differences between argumentation skill in science and non-science students. There are differences in quality of argumentation in science and non-science students. Science students showed good and clear backing with so many evidences. While non-science students provide strong and arguable warrant. Thus the quality of both science and non-science students argumentation need improvement to achieve better argument and learning outcomes.

关键词： Students

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Application of Backpropagation Algorithm for Handwriting Recognition

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Journal of Physics: Conference Series 2021年第1期1783卷

作者： Sustin Farlinda Muhammad Yunus Mudafiq Riyan Pratama Bakhtiyar Hadi Prakoso Angga Rahagiyanto Dyah Susilowati Ni Gusti Ayu Dasriani Lukmanul Hakim Khairil Anam Program Studi Rekam Medik Jurusan Kesehatan Politeknik Negeri Jember Program Studi Ilmu Komputer Fakultas Teknik dan Desain Universitas Bumigora Mataram Program Studi Teknik Informatika Fakultas Teknik Universitas Maarif Hasyim Latif Sidoarjo

Handwritten letter recognition is one form of pattern recognition. The introduction of letters looks simple to humans, but it becomes a tough task for computer programs to complete. In recognizing someone's handwriting, a computer program trained first. This study discusses how a computer recognizes a digital image pattern in the form of handwritten letters using the backpropagation algorithm. The backpropagation algorithm used in making this system is backpropagation with momentum. The network architecture used consists of an input screen with 64 neurons, a hidden screen consisting of 46 neurons, and an output screen with five neurons. Before the recognition process, input image with image format (jpg) processed first, which includes scaling, grayscale, and binarization. The trial results show that the system can recognize handwriting with an accuracy of up to 65%.

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The Implementation of the MFEP (Multi Factor Evaluation Process) Method In Determining the Learning Model

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Journal of Physics: Conference Series 2020年第1期1641卷

作者： Ai Ilah Warnilah Dini Silvi Purnia Miftah Farid Adiwisastra Herlan Sutisna Ratningsih Rian Ardianto Program Studi Sistem Informasi Universitas Bina Sarana Informatika Program Studi Sistem Informasi STMIK Nusa Mandiri Program Studi Sistem Informasi Akuntansi Universitas Bina Sarana Informatika Program Studi Teknik Industri Universitas Bina Sarana Informatika

The success of every generation of children is the hope of the success of the education world. The role of educators especially teachers has an important role in achieving the success of their students then a teacher must have a strategy in developing the learning system. A system approach is needed by using specific learning models, in order to help the teacher design the learning system. With the selection of the right learning model is one of the factors that support the success of the learning system. One factor of student achievement is less than the maximum is the application of learning models that are not appropriate, the selection of learning models still using manual systems makes the learning models applied less precise and appropriate. The purpose of this study is to determine the decision support system in determining learning models including cooperative learning models, problem based learning models, contextual learning models, Direct learning models, with the aim to assist teachers in determining the appropriate learning model to be applied in teaching and learning activities. The method applied is using the MFEP (Multi Factor Evaluation Process) method., by determining and giving subjective / intuitive assessments on factors / criteria that are very influential on indicators / alternatives and ranking systems to find out the alternative with the highest value. The results of this study cooperative learning models are highly recommended in the learning process in determining the level of success of students with a value of 6.18

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Wireless Scoreboard Technology Architecture for Athlete Performance Data Warehouse at Multiple Table Sports Games

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Journal of Physics: Conference Series 2021年第1期1764卷

作者： Estiyan Dwipriyoko Widjajani Wahyu Purnama Sari Mujiarto Program Studi Informatika Fakultas Teknik Universitas Langlangbuana Bandung Program Studi Teknik Industri Fakultas Teknik Universitas Langlangbuana Bandung Department of Mechanical Engineering Universitas Muhammadiyah Tasikmalaya Indonesia

The presence of technology brings many new changes that facilitate human life. In the field of information for sports competition results in the form of a scoreboard. Scoreboard is used in sports tournaments as a display of the results of a tournament. So everyone who is in the arena can find out the results of the tournament score. Scoreboard generally displays the value of the tournament, displays the time of the tournament and the number of rounds during the tournament. The majority of scoreboard shows only one result from one tournament, while there are tournaments where several teams compete simultaneously in one room, so the audience has difficulty knowing the score of other tournaments even though they are in one room. For example, in a pool or table tennis tournament, in one arena there are more than one team competing. At that time, usually the scoreboard is only on each table. That causes a limited number of scoreboard that can be seen by the audience, not all tournaments. Meanwhile, the scoreboard used in Indonesia also still uses the remote and cable as the transmission media when inputting scores. The remote is held to a distance according to the length of the cable which is very impractical. The space for the remote holder is also not flexible because the remote is connected by a cable. Therefore, in inputting the score there is no need to use cable anymore, because this application is web-based and connected via a wireless network. The purpose of this research is: to make it easier to record scores of tournaments with multiple tables, and to record performance statistics from athletes. The benefits of this research are: to make it easier to record values because they are connected to a wireless network and display them in real time, and get athlete performance statistics during the competition.

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Knowledge based information system for detecting early eye diseases

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IOP Conference Series: Materials Science and Engineering 2021年第5期1098卷

作者： S Sumarno M A Rosid A Irawan Program Studi Informatika Universitas Muhammadiyah Sidoarjo Jalan Raya Gelam 250 Candi Sidoarjo Jawa Timur Indonesia

The eyes are very important senses in human life. If the eyes experience interference, it will be fatal to human life. Although each type of eye disease has its own specific characteristics and symptoms, early detection with a deeper recognition of eye disease symptoms should be done. Knowledge-based information systems are systems that attempt to convert human knowledge into computers so that computers can solve problems as is usually done by experts. produce conclusions or goals. The aim of this study is to design applications for early detection of fourteen types of eye diseases. This detection uses a knowledge-based system that uses the Forward Chaining method. This study produced an output in the form of the possibility of the disease the user suffered based on fifty-three selected symptoms. This system indicates how much confidence the user has in the symptoms of possible eye diseases.

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K-Means Algorithm for Clustering The Location Of Accident-Prone On The Highway

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Journal of Physics: Conference Series 2020年第1期1641卷

作者： Diah Puspitasari Mochamad Wahyudi Muhammad Rizaldi Acmad Nurhadi Kresna Ramanda Sumanto Program Studi Sistem Informasi Fakultas Teknik dan Informatika Universitas Bina Sarana Informatika Indonesia Program Studi Teknologi Informasi Fakultas Teknik dan Informatika Universitas Bina Sarana Informatika Indonesia Program Studi Sistem Informasi Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri Indonesia Program Studi Teknologi Komputer Fakultas Teknik dan Informatika Universitas Bina Sarana Informatika Indonesia Program Studi Teknik Informatika Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri Indonesia

In Indonesia, there is a highway which connects Jakarta and Bogor, some accidents have occurred at the highway every year. This paper aims to analyze the location of the accident to classify the high and low levels of accident vulnerability in the Jakarta Bogor Highway. First, the extracted data is then grouped based on some of the same characteristics in the dataset namely cause, location, minor injuries, serious injuries and death. Second, the grouping results are visualized in the form of highway maps that can help highway managers in identifying and evaluating several accident-prone points on Jakarta Bogor Highway. The method to be used in data processing in this study is the K-Means clustering algorithm which is expected to produce useful information for Jakarta Bogor Highway managers. The results of this study indicate that accidents that often occur are in cluster 3 with a total of 80 accidents and at least there are in cluster 2 with a total of 57 accidents, the location of accidents that often occurs in cluster 1 is in KM 24, while cluster 2 is in KM 41 and cluster 3 located at KM 10.6.

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Tweet congestion locations identification using natural language processing

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AIP Conference Proceedings 2023年第1期2733卷

作者： Aan Subarkah Geri Kusnanto Syarifah Diana Permai Margaretha Ohyver Samsul Arifin The Audit Board of Indonesia Branch Office South Sulawesi Province Makassar Indonesia 90222 Program Studi Teknik Informatika Fakultas Teknik Universitas 17 Agustus 1945 Surabaya 60118 Indonesia Statistics Department School of Computer Science Bina Nusantara University Jakarta 11480 Indonesia

Natural Language Processing (NLP) is a field of computer science and linguistics that explores how computers interact with human (natural) language. NLP is frequently seen as a subfield of artificial intelligence, and its research area overlaps with computational linguistics. Machine translation, natural language text processing and summarization, user interfaces, speech recognition, and expert systems are all examples of NLP applications. Low-level NLP tasks and higher-level NLP tasks are two types of Natural Language Processing tasks. Tokenization, part-of-speech assignment to individual words (POS tagging), and shallow parsing are examples of low-level NLP activities (chunking). Meanwhile, higher-level NLP tasks, such as spelling/grammatical mistake detection and recovery, named entity recognition (NER), and information extraction, are constructed on top of low-level NLP tasks and used according to the problems found (IE). This study uses natural language processing to extract the location of congestion from tweets (twit). We get the location name and traffic conditions from the tweet by implementing a low-level NLP task in the form of tokenization, POS tagging, and chunking, followed by a higher-level NLP work in the form of named entity recognition. The types of words, such as nouns, verbs, adjectives, and descriptions, are taught at the introductory stage. Following POS tagging, word grouping (chunking) is carried out; if numerous consecutive words are verbs, they are classified as location names, whereas adjectives are grouped as traffic conditions.

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Comparison of Data Mining Algorithms Using Artificial Neural Networks (ANN) and Naive Bayes for Preterm Birth Prediction

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Journal of Physics: Conference Series 2020年第1期1641卷

作者： Diah Puspitasari Kresna Ramanda Adi Supriyatna Mochamad Wahyudi Erma Delima Sikumbang Sulaeman Hadi Sukmana Program Studi Sistem Informasi Fakultas Teknik dan Informatika Universitas Bina Sarana Informatika Indonesia Program Studi Teknik Informatika Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri Indonesia Program Studi Sistem Informasi Akuntansi Fakultas Teknik dan Informatika Universitas Bina Sarana Informatika Indonesia Program Studi Teknologi Informasi Fakultas Teknik dan Informatika Universitas Bina Sarana Informatika Indonesia Program Studi Sistem Informasi Sekolah Tinggi Manajemen Informatika dan Komputer Nusa Mandiri Indonesia

Premature birth is still a big problem in Indonesia, in general, 15 million babies are born prematurely every year, more than 1 million babies die from complications due to premature birth. The main purpose of this study is to compare the Artificial Neural Network and Naive Bayes datamining algorithm models to predict preterm birth so as to obtain clinical evidence in preterm birth long before confinement so that sudden preterm birth can be converted to normal nativity. The model proposed in research on the prediction of preterm birth is by applying an Artificial Neural Network (ANN) algorithm and Naive Bayes algorithm. Where the two algorithms will be compared the level of accuracy and the value of the AUC against the prediction of preterm birth The results obtained that the prediction of preterm birth using the Artificial Neural Network (ANN) algorithm produces an accuracy value of 90.67% and an ROC value of 0.954. While the Naive Bayes algorithm produces an accuracy value of 84.53% and an ROC value of 0.929. For this reason, it can be concluded that the Artificial Neural Network (ANN) algorithm has a superior accuracy of 6.14% and 0.025 for its ROC value in predicting preterm birth.

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