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Helmy, S.T., M.Eng
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Program Studi Teknik Telekomunikasi Jurusan Teknik Elektro Politeknik Negeri Semarang Jl. Prof. H. Soedarto, S.H. Semarang
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Journal of Applied Information, Communication and Technology (JAICT)
Published by Politeknik Negeri Semarang
ISSN : 25416340     EISSN : 25416359     DOI : https://doi.org/10.32497/jaict
Core Subject : Engineering,
Engineering
Focus of JAICT: Journal of Applied Information and Communication Technologies is published twice per year and is committed to publishing high-quality articles that advance the practical applications of communication and information technologies. JAICT scope covers all aspects of theory, application and design of communication and information technologies, including (but not limited): Communication and Information Theory. Mobile and Wireless Communication, Cognitive Radio Networks. Ad Hoc, Mesh, Wireless Sensor Network, Distributed System and cloud computing Computer networking and IoT Optimization Algorithms, Artificial intelligence, Machine Learning, and Adaptive System.
Arjuna Subject : Teknik (semua kategori) - Teknik Listrik dan Elektro
Articles 4 Documents
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Search results for , issue "Vol 5, No 2 (2020)" : 4 Documents clear
IMPROVING COMMUNICATION CAPABILITY ASK FOR AUTISM CHILDREN THROUGH MEDIA PECS BASED ANIMATED PICTURE Sattriedi Wahyu Binabar; Taryadi Taryadi; Dicke JSH. Siregar
JAICT Vol 5, No 2 (2020)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v5i2.1974

Abstract

The number of children suffering from autism from year to year is increasing. Autism Spectrum Disorders (ASD) is autism that occurs in childhood in the form of disorders characterized by disorders that affect language and communication, imagination and flexibility of thought and socialism. One way to improve communication skills, especially the ability to ask is to use the help of computer software. In this study, the PECS (Picture Exchange Communication System) method with the help of animation to attract the attention of ASD children. The results obtained were an increase of 70% communication ability to request from ASD children who were the object of research.
Analysis of Tuberculosis (TB) on X-ray Image Using SURF Feature Extraction and the K-Nearest Neighbor (KNN) Classification Method Reyhan Achmad Rizal; Nurlela Octavia Purba; Lidya Aprilla Siregar; Kristina Sinaga; Nur Azizah
JAICT Vol 5, No 2 (2020)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v5i2.1979

Abstract

With current technological developments, machine learning has become one of the most popular methods, one of the popular machine learning algorithms is k-nearest neighbors (KNN). Machine learning has been widely used in the medical field to analyze medical datasets, in this study the k-nearest neighbors (KNN) machine learning algorithm will be used because of its good level of accuracy in recognition and is included in the supervised learning algorithm group. The results showed the k-nearest neighbors (KNN) method in recognizing x-ray images of tuberculosis (TB) using SURF feature extraction with an average accuracy of 73%.
Fuzzy Integration to Standard Calculation of K-Nearest Neighbour Attributes M Adib Al Karomi; Ivandari Ivandari
JAICT Vol 5, No 2 (2020)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v5i2.1984

Abstract

The development of information and data in the era of the industrial revolution 4.0 is very fast. Researchers, institutions and even industry are competing to find and utilize methods in data processing that are more effective and efficient. In data mining classification, there are several best methods and are widely used by researchers. One of them is K-Nearest Neighbor (KNN). The calculation process in the KNN algorithm is carried out by comparing the testing data to all existing training data. This comparison is generally symbolized by the value of closeness or similarity between attribute records. The KNN method is proven to be good for handling large datasets and datasets with many attributes. One of the drawbacks in calculating the similarity of the KNN is that if there are attributes with a large range value, the similarity value will also be large. Conversely, if the range in an attribute is small, the similarity is also small. This condition is clearly unfair considering the types of attributes in the current data vary widely. One solution to this problem is to use standardization for all existing data attributes. Fuzzy is a model introduced by Prof. Zadeh which allows a faint value to be a value between 1 and 0. In this study the fuzzy model will be integrated in the KNN similarity calculation to obtain standardization of all data attributes. The results show that the use of the KNN algorithm in the classification of credit approval has an accuracy rate of 91.83%.
Design of a Water Sprinkler System and Monitoring of Soil Moisture in Potato Cultivation of the Kledung Horticulture Seed Center based on the Internet of Things (IoT) Eko Supriyanto; Endro Wasito; Abu Hasan; Dhea Ernanda; Karenza Balqis
JAICT Vol 5, No 2 (2020)
Publisher : Politeknik Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32497/jaict.v5i2.2023

Abstract

Potato is one of horticultural commodities that plays an important role to assure food security, mostly upper place such as plateau. Monitoring soil’s moisture and soil’s pH in potato plant tendance is the key point for good growth and development of potatoes. Soil moisture in a land is affected by the level of water contain in the soil. For that reason automatic monitoring system is needed to observe the land condition where the potato seedling is planted and a moisture control system that can ease the work. 40% to 70% of soil moisture is ideal for potatoes plant. The development of this design make use of wireless fidelity (wifi). This device keep the dampnes know less than 40%. If it’s less than 40%, the sensor will detected so the watering system will running and system will stop if reaching 70%. This design can monitor pH, temperature and humidity through the android application. With an accuracy level of the pH sensor for measuring 95.85% of acidity, the capacitive sensor for measuring soil moisture is 96.6% and DHT11 for measuring temperature and humidity at 99.75%.

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