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Sinkron : Jurnal dan Penelitian Teknik Informatika
Published by Politeknik Ganesha Medan
ISSN : 2541044X     EISSN : 25412019     DOI : 10.33395/sinkron.v8i3.12656
Core Subject : Science,
Computer Science & IT
Scope of SinkrOns Scientific Discussion 1. Machine Learning 2. Cryptography 3. Steganography 4. Digital Image Processing 5. Networking 6. Security 7. Algorithm and Programming 8. Computer Vision 9. Troubleshooting 10. Internet and E-Commerce 11. Artificial Intelligence 12. Data Mining 13. Artificial Neural Network 14. Fuzzy Logic 15. Robotic
Arjuna Subject : Ilmu Komputer (semua kategori) - Visi Komputer dan Pengenalan Pola
Articles 1,196 Documents
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Data Mining using K-means method for feasibility selection of Non-cash food Assistance recipients in the Era of Covid-19 Rusdiansyah, Rusdiansyah; Supendar, Hendra; Tuslaela, Tuslaela
Sinkron : jurnal dan penelitian teknik informatika Vol. 5 No. 2B (2021): Article Research October 2021
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v6i1.11101

Abstract

All countries in the world are currently experiencing a severe economic crisis following the outbreak of the COVID-19 outbreak. In Indonesia, the Large-Scale Social Restriction (PSBB) policy is reported to have increased the number of poor people. Social assistance is a government program to improve the social welfare of the lower economic community. In carrying out the program, the central government and local governments coordinate with each other so that the program is right on target without any element of fraud. In the neighbourhood of Rukun Warga 001, Kelapa Dua Village, there are still obstacles in selecting the eligibility for social assistance recipients, namely Non-Cash Food Aid. The data on the poor are not in accordance with the actual conditions. In this study, to implementing data mining with the K-Means Algorithm. The K-Means Clustering algorithm is used to classify people who are classified as eligible to receive social assistance and those who are not entitled to receive social assistance. The data sample used is the data of Rukun Warga 001, Kelapa Dua Village. The results of this study indicate that cluster 1 with the appropriate category of receiving social assistance according to government programs in the Rukun Warga 001 neighbourhood of Kelapa Dua sub-district amounted to 13 families. And cluster 2 in the category of not eligible to receive social assistance amounted to 97 heads of families out of a total of 110 heads of families in RW 001.
Application of the C4.5 Algorithm on the Effect of Watching Youtube Videos On the Development of Early Childhood Creativity Sintawati, Ita Dewi; Widiarina, Widiarina; Mariskhana, Kartika
Sinkron : jurnal dan penelitian teknik informatika Vol. 5 No. 2B (2021): Article Research October 2021
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v6i1.11116

Abstract

Youtube media is one of the social media for communication used by the community, not out of reach of children. The rapid development of information technology, of course, this has an influence on human life. Talking about life in humans, it cannot be separated from human behavior. Some psychologists say that children tend to fully absorb what they see, and children will learn from what they see. This can trigger creativity for young children. The creativity of each individual can be seen in terms of how he makes something he thinks of because he sees an object that already exists and then he innovates it into a new form. This attracted the attention of the author to identify and describe the impact of watching YouTube videos on the development of early childhood creativity. This type of research is based on developing phenomena, how much influence is brought about by technological advances on YouTube social media in the formation of children's behavior. The process of completing the goals to be achieved in this study is to provide information about recommendations for child development with positive creativity, making it easier to determine early childhood development by using the Decision Tree Algorithm C4,5 method. The problem in this study is that early childhood imaginations are higher and will be affected by streaming video ads on YouTube. The results showed that children aged 3 and 4 years often watched, while children aged 5 and 6 years did not watch often, so the role of parents was more dominant in supervising children aged 3 and 4 years.
Bot to Monitor Student Activities On E-Learning System Based On Robotic Process Automation (RPA) Munawar, Ghifari
Sinkron : jurnal dan penelitian teknik informatika Vol. 5 No. 2B (2021): Article Research October 2021
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v6i1.11128

Abstract

Student activities in the e-learning system need to be monitored regularly by lecturers to observe their learning achievements. The monitoring process carried out is monitoring student attendance, collecting assignments, and taking quizzes. This will be a burden if it is done regularly, especially if the lecturer teaches many subjects. Robotic process automation (RPA) is a technology that uses software agents (bots) to imitate human work processes to be automated. The objectives of this research are (1) applying RPA technology as bots that can monitor student activity on the e-learning system (Moodle), and (2) measuring the time efficiency of RPA bots in processing their work. The research stages are divided into three, namely: the preparation stage, the RPA implementation stage, and the evaluation stage. The preparation stage is carried out to define the problem to be handled, the RPA implementation stage to develop bots using the UiPath platform, and the evaluation stage to compare the efficiency of work time between bots and manually (by humans). The RPA bot was developed on four work focuses, namely (1) attendance monitoring, (2) task collection monitoring, (3) quiz processing monitoring, and (4) email delivery automation. Efficiency testing was carried out on four test scenarios (FR1, FR2, FR3, FR4), where FR2 had the highest percentage of work time efficiency at 754%, and the lowest was in FR1 with a percentage of 165%, with an overall average efficiency percentage of 444%. Thus, through RPA technology, monitoring work becomes faster and saves effort.
Solo City Batik Design Security System (SiKemTi Solo) During the Pandemic Covid-19: Inggris Kusanti, Jani; Sudalyo, Ramadhian Agus Triono
Sinkron : jurnal dan penelitian teknik informatika Vol. 5 No. 2B (2021): Article Research October 2021
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v6i1.11141

Abstract

Safeguarding copyright on traditional batik works is very important to prevent duplication of Indonesian cultural products. The ease of duplicating, especially in batik designs, causes frequent violations of the design's copyright. Especially with the rise of online commerce today, it is easier for everyone to use other people's products and copy other people's products. This will not happen if there is already a system that can be used to secure the design work. For this reason, it is important to develop methods that can be used to secure traditional batik works, especially Surakarta. Based on these problems, a research was conducted on the application of image watermarking techniques that are resistant to changes generated by image processing in the form of compression. The method used to secure Surakarta batik works is compression using wavelet transformation. The aim is to develop a batik design security system method using the watermarking method. The steps taken started with taking photos of batik designs and the designer's name, photos in the form of images followed by the embedding process using the watermarking method. The watermarking method used is the DWT method. After encryption, identification is carried out to determine the level of errors that occur. The results of testing 323 batik image data in this study obtained an average mse level = 0.00000065 and an average psnr result = 188.471186102179. From the results of this study, it was found that the development of methods that can be used to secure batik products by using the watermarking method.
Bayesian Pixel Density Estimation Modeling to Detect Human Sperm Sample Image Based on Sperm Head Shape Zonyfar, Candra; Baihaqi, Kiki Ahmad
Sinkron : jurnal dan penelitian teknik informatika Vol. 5 No. 2B (2021): Article Research October 2021
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v6i1.11148

Abstract

Currently, there is a problem of the difficulty in classifying human sperm head sample images using different databases and measuring the accuracy of several different datasets. This study proposes a Bayesian Density Estimation-based model for detecting human sperm heads with four classification labels, namely, normal, tapered, pyriform, and small or amorphous. This model was applied to three kinds of datasets to detect the level of pixel density in images containing normal human sperm head samples. Experimental results and computational accuracy are also presented. As a method, this study labeled each human sperm head based on three shape descriptors using the formulas of Hu moment, Zernike moment, and Fourier descriptor. Each descriptor was also tested in the experiment. There was an increased accuracy that reached 90% after the model was applied to the three datasets. The Bayesian Density Estimation model could classify images containing human sperm head samples. The correct classification level was obtained when the human sperm head was detected by combining Bayesian + Hu moment with an accuracy rate of up to 90% which could detect normal human sperm heads. It is concluded that the proposed model can detect and classify images containing human sperm head objects. This model can increase accuracy, so it is very appropriate to be applied in the medical field
ALGORITMA C4.5 DALAM PEMETAAN POLA PENERIMAAN MAHASISWA BARU DI TEKNIK KOMPUTER: Data Mining Siregar, Yunita Sari; Sembiring, Boni Oktaviana; Hasdiana, Hasdiana; Dewi, Arie Rafika; Harahap, Herlina
Sinkron : jurnal dan penelitian teknik informatika Vol. 5 No. 2B (2021): Article Research October 2021
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v6i1.11154

Abstract

University of Harapan Medan is one of the private universities in North Sumatra which has computer-based study programs such as Informatics Engineering and Information Systems. Every year this college receives many registrations from students who have completed their education at the school stage. The large number of incoming student data makes it difficult for the admin to select new students who will register. In this study using the C4.5 algorithm data mining method to map the pattern of student admissions selection in the field of Engineering and computers. The attributes used are the average value of report cards (high, enough, low), basic academic ability tests (very high, high, medium, low, very low), basic computer knowledge tests (very high, high, enough, low, very low) and interviews (good, bad). Data mining is a mathematical calculation process that uses algorithms and requires large data. While the C4.5 algorithm is an algorithm that processes data by calculating entrophy and information gain, where after the calculation process is carried out, those who get the largest information gain value will become nodes and branches. This C4.5 algorithm will describe a decision tree that will form a pattern in student selection. The results of this study indicate that in mapping the selection pattern of interview attributes into level 1 nodes, the attributes of the basic computer knowledge test become the level 1 branch, the attributes of the basic academic ability test become the level 2 branch and the attribute average value of report cards becomes the level 3 branch.
Design and Build a Multilevel Mace Nutmeg Dryer to Improve the People's Economy Ihsan, Ihsan; Ilham, Dirja Nur; Putra, Reza Ade; Candra, Rudi Arif; Budiansyah, Arie
Sinkron : jurnal dan penelitian teknik informatika Vol. 5 No. 2B (2021): Article Research October 2021
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v6i1.11171

Abstract

Nutmeg is a source of income for some people in South Aceh, and some types of nutmeg, like mace nutmeg, are of better quality. Mace nutmeg is also an agricultural community with great economic value and benefits for humans, as it can be processed into spices and herbs. A range of products includes nutmeg oil and medicines. The harvesting and drying of mace nutmeg, which is still considered a problem by nutmeg growers, cannot be isolated from the processing of the basic ingredients. The natural process of drying mace nutmeg involves the use of sunshine, which necessitates a considerable drying time. Therefore nutmeg farmers frequently complain of erratic weather, especially during the wet season. The constant rain can cause the mace to rot, causing the nutmeg farming community's revenue to become unstable. Methods and steps of research work starting from the study of literature, determination of design specifications, hardware design, software design, toolmaking, tool testing.Good results were reached with the dryness of the mace nutmeg, which can be adjusted, and without putting into account the weather in the drying process, which is usually done with the heat of the sun, per the results of the testing of the designed tools.The average dryness of mace nutmeg is at a temperature of 45 percent with a time of 4 hours and a capacity of 100 grams; according to the test results of the automatic mace drying machine, it produces 50 grams of dry mace.  
Classification of the Human Development Index in Indonesia Using the Bootstrap Aggregating Method Goldameir, Noor Ell; Yolanda, Anne Mudya; Adnan, Arisman; Febrianti, Lusi
Sinkron : jurnal dan penelitian teknik informatika Vol. 5 No. 2B (2021): Article Research October 2021
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v6i1.11173

Abstract

Successful development of the quality of human life in a region is determined by the Human Development Index (HDI). Human development performance based on the HDI can be measured: long and healthy life, knowledge, and a decent standard of living. The HDI is usually grouped into several categories to facilitate the classification of the HDI level of each region. This study aimed to determine the ability of the bootstrap aggregating (bagging) method to classify the HDI by district/city. Bagging is a stochastic machine learning approach that can eliminate the variance of the classifier by producing a bootstrap ensemble to obtain better accuracy results. The dependent variable in this study was the HDI by district/city in 2020. In contrast, life expectancy at birth, expected years of schooling, mean years of schooling, and real expenditure per capita are adjusted as independent variables. Bagging was applied to the high and low categories of HDI data. The bagging method demonstrated good classification performance due to only eight classification errors, namely the HDI data which should be in the high category but classified into the low category by the bagging method. Based on the results of calculations with 25 replications, it can be concluded that the bagging method has a very good performance, with an accuracy value of 92.3%, the sensitivity of 100%, and specificity of 83.33%. The bagging method is considered very good for the classifying the HDI by district/city in Indonesia in 2020 because it has a balanced accuracy of 91.67%.
TF-IDF Method and Vector Space Model Regarding the Covid-19 Vaccine on Online News Zen, Bita Parga; Susanto, Irwan; Finaliamartha, Dian
Sinkron : jurnal dan penelitian teknik informatika Vol. 5 No. 2B (2021): Article Research October 2021
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v6i1.11179

Abstract

Advances in information and technology have caused the use of the internet to be a concern of the general public. Online news sites are one of the technologies that have developed as a means of disseminating the latest information in the world. When viewed in terms of numbers, newsreaders are very sufficient to get the desired information. However, with this, the amount of information collected will result in an explosion of information and the possibility of information redundancy. The search system is one of the solutions which expected to help in finding the desired or relevant information by the input query. The methods commonly used in this case are TF-IDF and VSM (Vector Space Model) which are used in weighting to measure statistics from a collection of documents on the search for some information about the Covid 19 vaccine on kompas.com news then tokenizing it to separate the text, stopword removal or filtering to remove unnecessary words which usually consist of conjunctions and others. The next step is sentence stemming which aims to eliminate word inflection to its basic form. Then the TF-IDF and VSM calculations were carried out and the final result are news documents 3 (DOC 3) with a weight of 5.914226424; news documents 2 (DOC 2) with a weight of 1.767692186; news documents 5 (DOC 5) with weights 1.550165096; news document 4 (DOC 4) with a weight of 1.17141223;, and the last is news document 1 (DOC 1) with a weight of 0.5244103739.
Identification of Face Mask With YOLOv4 Based on Outdoor Video Harahap, Mawaddah; Kusuma, Leonardo; Suryani, Melva; Situmeang, Candra Ebenezer; Purba, Juniven Francisco
Sinkron : jurnal dan penelitian teknik informatika Vol. 5 No. 2B (2021): Article Research October 2021
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v6i1.11190

Abstract

The use of face masks in the current era is one of the special regulations in many countries including Indonesia to prevent the spread of coronavirus. However, not all people strongly agree to wear masks because they feel uncomfortable to wear even in crowded places require the use of masks such as shopping malls, hospitals, factories, stations and others by checking manually. Therefore, in the study proposed automatic detection of masks with YOLOv4 with the stage of data collection recording community activities in crowded places, labeling images of masks and non masks. The labelling results were conducted in training that resulted in 90.3% accuracy in the 2000 ierasi, the last of which was video testing in three different crowd locations: taxes, city parks and highways. Based on the test results, YOLOv4 can detect masks and non masks on videos with different obstruction conditions such as people wearing helmets, hand obstacles. However, for the detection of people with tissue obstruction conditions and improper position of wearing masks has not resulted in good detection.

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