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2018 Workshop on Multidisciplinary and Its Applications: Applied Mathematics, computer science, Information Systems, and Information Technology, WMA-Mathcomtech 2018

作者： Achmad Daengs, G.S. Ratnadewi Alpha, Christian Dio Napitupulu, Darmawan Nurdiyanto, Heri Kurniasih, Nuning Hasibuan, Abdurrozaq Daengs, Achmad Manurung, Rosida Tiurma Mulyaningsih, Indrya Rahim, Robbi Sugianto, Castaka Agus Abdullah, Dahlan Department of Electrical Engineering Universitas Kristen Maranatha Bandung Indonesia Research Center for Quality System and Testing Technology Indonesian Institute of Sciences Banten Indonesia STMIK Dharma Wacana Indonesia Faculty of Communication Sciences Library and Information Science Program Universitas Padjadjaran Bandung Indonesia Universitas Islam Sumatera Utara Indonesia University of 45 Surabaya Indonesia Graduate Program in Scientific Psychology Universitas Kristen Maranatha Bandung Indonesia Department of Education Institut Agama Islam Negeri Syekh Nurjati Cirebon Indonesia School of Computer and Communication Engineering Universiti Malaysia Perlis Kubang Gajah Malaysia Politeknik TEDC Bandung Indonesia Department of Informatics Universitas Malikussaleh Aceh Utara Indonesia

Nowadays, messaging technology in digital data form more often used and not less messages that confidentially wanted. Then it should be modified so that can be understood only by the sender and the intended recipients. All of this system can be realization by using cryptography. LUC algorithms are introduced by Smith and Lennon in 1993. LUC algorithm is an algorithm that based on the use of Lucas sequence (specific arithmetic operations derived from Lucas row) that rarely used to enhance the security of the messages. In this research, LUC algorithm is combined with visual cryptography to process the encryption and the description of a colored image. Four different images were used in the trial here. The performance of the system is assessed using Structural similarity (SSIM) which has an assessment similar to human eye. If the image quality is the same as the original image, then the SSIM value is one. Whereas if the quality of decryption image is very different from the original image then the value of SSIM is zero. © Published under licence by IOP Publishing Ltd.

关键词： Information systems

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Improved accuracy of long short term memory (LSTM) algorithm in chili price prediction

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AIP Conference Proceedings 2024年第1期3222卷

作者： Rizki Ramadhansyah Benny Benyamin Nasution Ade Candra Informatics Engineering Master Program Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia Computer Engineering Program Computer Engineering and Informatics Politeknik Negeri Medan Medan Indonesia

The unstable price of chili is still a serious problem in society. Many previous studies have created systems that can predict chili prices. However, there are no chili price prediction results that are considered quite accurate and consistent. So the problem is overcome by processing chili price data using interpolation and dropna on missing values in order to maintain data quality and using the Long Short Term Memory (LSTM) algorithm development in predicting chili prices. This LSTM development was carried out to improve the inconsistent chili price prediction results due to the high error value. LSTM development is carried out in the cell state (ct) and hidden state (ht) with the aim of obtaining better prediction results. Then the accuracy of the error value obtained from the LSTM development in Labuhanbatu district is MAE = 2.589, RMSE = 3.419, and MSE = 11.695.900. This value is lower than using the original LSTM and only using dropna in processing missing value data, namely MAE = 5.517, RMSE = 7.930, and MSE = 62.900.289. Then the difference in percentage error value from the comparison is MAE = 53.07%, RMSE = 56.88%, and MSE = 81.41%. Therefore, it is expected that the low error value results from the development of LSTM can be an indicator of increasing the accuracy of chili price prediction results and making the results more consistent.

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The Concept and Implementation of Smart Room using Internet of things (IoT) for Cost Efficiency and Room Security

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Journal of Physics: Conference Series 2019年第1期1381卷

作者： R Y Endra A Cucus F N Affandi Informatics Study Program-Faculty of Computer Science Universitas Bandar Lampung (UBL) Jl. Zainal Abidin Pagar Alam no 26 Bandar Lampung Informatics Study Program-School of information and computer management Bandar Lampung

The Internet of Things (IoT) is a concept where internet connectivity can exchange information with each other with objects around it. The essence of IoT is interconnected devices that produce and exchange observation data, facts, and other data, so that it is available to anyone. In this paper we present how the smart room model is designed using sensors and micro-controllers to automate the use of electronic devices and the security of a room using the concept of the Internet of Things. Implementation of the smart room concept from the results of this study, we hope that the concept in this smart room can be implemented and the automation process in this smart room can have a major impact on the efficiency of operational costs, especially electricity payments and improve home security because there is automatic control.

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Psychological Stress Classification Using Extreme Gradient Boosting Algorithm

Psychological Stress Classification Using Extreme Gradient B...

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International Conference on Information and Communication Technology Convergence (ICTC)

作者： Maria Mahardini Sakanti Viacheslav Siniaev Aurelia Amaris Win-Jet Luo Suhartono C. Bambang Dwi Kuncoro Graduate Institute of Precision Manufacturing National Chin-Yi University of Technology Taichung Taichung Taiwan Institute of Applied Computer Science ITMO University St. Petersburg Russian Federation Department of Informatics Engineering Faculty of Computer Science Universitas Brawijaya Malang Indonesia Ph.D. Program Prospective Technology of Electrical Engineering and Computer Science National Chin-Yi University of Technology Taichung Taichung Taiwan Department of Refrigeration Air Conditioning and Energy Engineering National Chin-Yi University of Technology Taichung Taiwan

ISBN: (数字)9798350364637

ISBN: (纸本)9798350364644

Stress, as a reaction to threatening situations, can raise heart rate and result in serious conditions that might cause significant damage or even be life-threatening. Traditional methods for evaluating stress, which rely on subjective self-reporting and clinical assessments, often suffer from biases and inconsistencies. Artificial intelligence models have been explored to predict stress levels more accurately. This paper investigates the application of Extreme Gradient Boosting in classifying psychological stress using the WESAD dataset, which includes parameters such as acceleration, electrocardiogram, electromyography, electrodermal activity, temperature, and respiration. The dataset was balanced and sampled to create a manageable subset for experimental. Extreme Gradient Boosting was chosen for its efficiency and scalability in handling complex datasets. The model was trained and validated, achieving a 95% accuracy in predicting stress levels. This study highlights the potential of integrating Extreme Gradient Boosting models into wearable devices for real-time stress monitoring. Future work involves optimizing the model to utilize fewer sensors without decreasing accuracy, ensuring it can be integrated into portable/wearable systems using tiny microcontrollers.

关键词： Accuracy Microcontrollers Psychology Human factors Predictive models Boosting Prediction algorithms Real-time systems Sensors Wearable devices

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Performance LoRa Technology for Autonomous Vehicles

Performance LoRa Technology for Autonomous Vehicles

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International Seminar on Intelligent Technology and Its Applications (ISITIA)

作者： Puput Dani Prasetyo Adi Iwan Purnama Arfanda Anugrah Siregar Angga Putra Juledi Firman Edi Abdul Karim Yuyu Wahyu Fairuz Iqbal Maulana Suhardi Atmoko Budi Susilo Toni Ilham Maliki Harahap Lintang Patria National Research and Innovation Agency (BRIN) Bandung Indonesia Faculty of Science and Technology Labuhanbatu University Labuhanbatu North Sumatra Indonesia Telecommunication Engineering Study Program Politeknik Negeri Medan Medan City North Sumatra Indonesia Department of Engineering Management Faculty of Industrial Technology Batam Institute of Technology Batam City Riau Islands Indonesia Department of Information Technology Budi Darma University Medan North Sumatra Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Faculty of Teacher Training and Education Labuhanbatu University Labuhanbatu North Sumatra Indonesia Faculty of Engineering Universitas Terbuka Jakarta Indonesia

This research is an approach to intelligent vehicles with a LoRa communication system, LoRaWAN compatible for Long-Range and Outdoor Communication, but in this paper, we will test the ability of LoRa to handle autonomous vehicles, a Blind-Adaptive Data method will be tried on vehicles systems. The system offered is when the vehicle is running, the sensor will send position data in real-time, the number of vehicles is four, and GPS data is sent alternately using the Blind Adaptive Data Rate principle to avoid data collisions, and when the GPS shows a certain position, the value of SF is ascertained, which affects the data rate and ToA, and the output given is RSSI on each car, speed of a car, power consumption of sensor nodes, signal power, SNR, Bit rate or data rate, and sensitivity. With the Blind ADR principle, it is ensured that there is no data collision between car position data that causes packet loss.

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Dynamic programming Algorithm using Furniture Industry 0/1 Knapsack Problem

Dynamic Programming Algorithm using Furniture Industry 0/1 K...

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Mietha Anditta Natashya Amartya Laurens Spits Warnars Harco Leslie Hendric Spits Warnars Arief Ramadhan Teddy Siswanto Teddy Mantoro Nurulhuda Noordin Computer Science Departement School of Computer Science Bina Nusantara University Jakarta Indonesia Information Systems Departement School of Information Systems Bina Nusantara University Jakarta Indonesia Computer Science Departement BINUS Graduate Program - Computer Science Bina Nusantara University Jakarta Indonesia PJJ Informatika Telkom University Bandung Indonesia Information Systems Department Trisakti University Jakarta Indonesia Faculty of Engineering and Technology Sampoerna University Jakarta Indonesia School of Computing Sciences College of Computing Informatics and Mathematics Universiti Teknologi MARA Selangor Malaysia

Dynamic programming is a fundamental algorithm that can be found in our daily lives easily. One of the dynamic programming algorithm implementations consists of solving the 0/1 knapsack problem. A 0/1 knapsack problem can be seen from industrial production cost. It is prevalent that a production cost has to be as efficient as possible, but the expectation is to get the proceeds of the products higher. Thus, the dynamic programming algorithm can be implemented to solve the diverse knapsack problem, one of which is the 0/1 knapsack problem, which would be the main focus of this paper. The implementation was implemented using C language. This paper was created as an early implementation algorithm using a Dynamic program algorithm applied to an Automatic Identification System (AIS) dataset.

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Integration of Artificial Intelligence in Software Defined Networking Technology through Developing Machine Learning Algorithms

Integration of Artificial Intelligence in Software Defined N...

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Advance Computing and Innovative Technologies in engineering (ICACITE), International Conference on

作者： Lamhot Naibaho Pulkit Raj Saxena Kuldeep Sharma Badria Sulaiman Alfurhood L. Pallavi Bhasker Pant English Language Education Study Program Faculty of Letters and Languages Christian University of Indonesia College of Computing Science and Information Technology Teer Thanker Mahaveer University Moradabad Uttar Pradesh India Department of Computer Science and Engineering Lovely Professional University Phagwara Jalandhar Punjab India Department of Computer Sciences College of Computer Information Sciences Princess Nourah Bint Abdulrahman University Saudi Arabia CSE B V Raju Institute of Technology Narsapur Telangana India Computer Science & Engineering Graphic Era Deemed to be University Dehradun Uttarakhand India

A future networking design called "software-defined networking" combines network programmability with centralized administration (SDN). Network administration is currently handled by SDN, which, at the regulator, which acts as the cable network processor and divides the data plane into a control plane and a data aircraft. Recent breakthroughs in artificial intelligence (Al) have shown a stronger inclination for the science community to benefit from their ability to give learning capabilities and enhance Indicator. The author of this research provides a comprehensive analysis of initiatives underway to incorporate Al with SDN. The study concluded that the three primary Al thread where scientific research was centered were computer science, conceptual, and fuzzy reasoning systems. The authors of this paper explore the several fields in which these approaches may be used, their potential future applications, and the innovations made possible by the integration of AI-based methods into the SDN paradigm. By choosing the right SDN controller, any large organization may lower network complexity, implementation expenses, and maintenance costs. The focus of this article is software defined networking's benefits and downsides (SDN). Following is a basic explanation of artificial intelligence and a list of some of its most significant applications in SDN.

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Diabetes Prediction Model for Better Clarification by using Machine Learning

Diabetes Prediction Model for Better Clarification by using ...

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International Conference on Inventive Computation Technologies (ICICT)

作者： J. Lysa Eben R. Jayasudha S. Ramya S. Kaliappan Shobha Aswal Khalid Ali Salem Al-Salehi Department of Computer Applications School of Computing Sciences Vels Institute of Science Technology and Advanced Studies Chennai Tamilnadu India Department of Mathematics Dr.N.G.P.Institute of Technology Coimbatore India Department of Computer Science and Engineering Kongu Engineering College Erode Tamilnadu India Division of Research and Development Lovely Professional University Phagwara Punjab India School of Computing Graphic Era Hill University Dehradun India Biomedical engineering study program faculty of science and technology Airlangga University Surabaya Indonesia

Diabetes mellitus is one of the most pressing health concerns because so many people are afflicted by its disabling symptoms. Factors such as age, excess body fat, insufficient physical activity, a history of diabetes in one's family, a sedentary lifestyle, an unhealthy diet, hypertension, etc., all increase the likelihood of developing diabetes mellitus. Health complications are more common in people with diabetes, including cardiovascular disease, renal failure, stroke, blindness, and nerve injury. To validate a diagnosis of diabetes, hospitals typically perform a battery of procedures on the patient. Big data analytics has many vital applications in the healthcare sector. Numerous large computer systems are used in the healthcare sector. With the help of big data analytics, researchers can sift through mountains of data in search of previously unseen patterns and insights. Current techniques have a poor degree of precision in classification and forecast. While previous research has focused on factors such as glucose, body mass index, age, insulin, etc., the proposed model takes these into account and also the other factors that may be more relevant to the development of diabetes. The newer sample is superior to the older one based on categorization accuracy. A workflow algorithm for diabetes prognosis is also required to improve the accuracy.

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Exploring Tourist Feedback on Riau Attractions Through Indonesian Language YouTube Opinion Using Naïve Bayes Algorithm

Exploring Tourist Feedback on Riau Attractions Through Indon...

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IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)

作者： Rahmad Kurniawan Iwan Iskandar Fitra Lestari Habibi Al Rasyid Harpizon Ilyas Husti Department of Computer Science Faculty of Mathematics and Natural Sciences Universitas Riau Pekanbaru Indonesia Department of Informatics Engineering Universitas Islam Negeri Sultan Syarif Kasim Riau Pekanbaru Indonesia Department of Industrial Engineering Universitas Islam Negeri Sultan Syarif Kasim Riau Pekanbaru Indonesia Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Selangor Malaysia Graduate Program Universitas Islam Negeri Sultan Syarif Kasim Riau Pekanbaru Indonesia

YouTube is a widely-used platform in Indonesia, with 93.8% of its users. As such, it presents a valuable opportunity for marketing tourist destinations, particularly in Riau province, which aims to become Indonesia’s top Halal travel destination. Tourism is a vital contributor to the economic growth of regions, and each province in Indonesia competes to promote its tourist attractions to attract more visitors every year. However, the large volume of data can challenge the manual analysis of feedback from YouTube’s features, such as likes, dislikes, and comments. A literature review suggests that the Naive Bayes algorithm, which uses machine learning, is helpful for sentiment analysis. Therefore, this study aims to analyze public sentiment toward tourist destinations in Riau province by analyzing YouTube comments using the Naïve Bayes algorithm. The study used 1680 opinions collected from 10 YouTube videos showcasing tourist destinations in Riau. The Naive Bayes algorithm classified 60% of the comments as positive, 32% as neutral, and 8% as negative. The experimental results indicated an accuracy and precision of 73%, a recall of 94%, and an F-1 Score of 82%. The study used the word frequency technique to reveal that Riau could become a popular halal tourist destination based on several frequently occurring words in the comments.

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Remote Chlorophyll-a and SST to Determination of Fish Potential Area in Makassar Strait Waters Using MODIS Satellite Data

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IOP Conference Series: Earth and Environmental science 2019年第1期270卷

作者： A Selao A A Malik F I Yani A Mallawa Safruddin Informatics Faculty of Engineering Muhammadiyah University of Parepare Study Program of Aquaculture Faculty of Agriculture Animal Husbandry and Fishery Muhammadiyah University of Parepare Study Program of Aquatic Resource Utilization Faculty of Marine Science and Fishery Hasanuddin University

The objective of this research was to analyze integrated geospatial data using MODIS Satellite data and field data observation to the determination of potential fish area. This study applied in Makassar Strait 118° 0' 0' E-119° 37' 0' E, 3°0'0' S – 4°45'0' S. The methods of this research was conducted using MODIS combine the depth of map waters survey direct interviews and people who participate in fishing activities monthly in January, February, March, April, May, and June. Data were analyzed by using software: Statistics, SeaDas, ENVI, and GIS. The result showed that the horizontal distribution of sea surface temperature (SST) spread evenly or divergent. The distribution of sea temperature in the coastal area was relatively warm in the sea around Barru and Pangkep was ranged 31 to 32 °C. Sea surface temperature dominates in the range of 30 - 31°C. SST correlation coefficient was 0.79 between MODIS and value of observation field data.

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