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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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Predict stock prices using the Generative Adversarial Networks Mohammad, Saiful Azhari; Santoso, Handri
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11405

Abstract

Predicting the price of a stock is very difficult. Due to very volatile prices. Many traders incorrectly predict stock prices, forex or trading commodities. It takes an analysis of each price movement. The purpose of the analysis is to predict price movements. One of them is the use of indicators that seek to help predict prices. Currently the development of Artificial Intelligence (AI) has grown very rapidly. Machine learning which is part of AI is also used to predict prices. Stocks are data that are related to time. Just like the weather. If the stock is analyzed then the suitable method is the time series method. The method used is Deep Learning, namely Recurrent Neural Network (RNN). A recurrent Neural Network is the same as Artificial Neural Network (ANN). ANN performs the processing of sequential data. RNN does not discard past problem data information, but will also enter past information as input. This is what distinguishes RNN and ANN. In the Recurrent Neural Network, there is a Long Short Term Memory Algorithm, Gated Recurrent Unit (GRU). One of the algorithms that can be used to predict stock prices is the Generative Adversarial Network. This algorithm was modified before being used. In the GAN algorithm, there are Generators and Discriminators. Because stock is a process that is carried out in the presence of time or time series, the Generative is modified with Long Short Term Memory and Discriminator uses Long Short Term Memory
Design of Pond Water Temperature Monitoring Built Using NodeMCU ESP8266 Muhammad, Saiful Azhari; Haryono, Haryono
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11406

Abstract

Freshwater fish farming is currently booming in Indonesia, and many use small ponds for efficiency or due to limited location, this can be a problem due to Indonesia's hot climate. Small ponds with not much water volume will cause the water temperature to rise more easily on hot days, of course this is not good for the fish colonies in it. To prevent temperature rise, farmers generally irrigate ponds with fresh water to stabilize the water temperature. Due to the unpredictable weather in Indonesia lately, it will be difficult for farmers to monitor their ponds manually, so a tool is needed that can detect the heat of pond water and turn on the water pump to irrigate ponds. This research is expected to make it easier for farmers to regulate pond temperatures more easily. The use of a microcontroller in Internet of Thing devices is very much needed, considering that the microcontroller is able to carry out the task of controlling the existing sensors. The sensor used in this study uses a temperature sensor that is used to control the pool water. The prototype for detecting pool water temperature and increasing water flow is used to reduce heat in pool water and increase water flow that is reduced due to evaporation of water during the day. The purpose of this research is to make a prototype to detect pond water temperature and increase pond water discharge which is useful for reducing pond water temperature to be cooler and reducing the risk of fish death. The prototype developed is a NodeMCU ESP 8266 micro-controller, a temperature detection sensor in water, a relay as a switch and a mini pump
Implementation of Enterprise Architecture in Cloud Computing Companies Michael, Dennis; Indrajit, Richardus Eko; Dazki, Erick
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11407

Abstract

In the current era of digitalization, the cloud computing industry market is increasingly shining along with the birth of a number of renewable technologies in this industry. A good and well-planned architectural design for the cloud industry is a major factor in the success of cloud computing companies in competing in a market that has a very broad market share. By conducting research on enterprise architecture, a cloud computing company is expected to provide a different approach to exploring and planning a cloud computing company according to market needs so that it can help or provide different methods and designs that allow us to enter the business world. and business. cloud industry competition. in this digital age. Architectural design planning for companies engaged in the cloud computing industry can use several approaches and tools available in the field so as to simplify, save time and encourage new ideas and initiatives. To be able to achieve the expected goals, it is necessary to conduct several studies and research that is quite intensive so that it can provide significant results and impacts. This research is expected to be one of the means to present a cloud computing architecture that is able to compete in the market and as a whole becomes the concern of all users or researchers. This study aims to discuss Enterprise Architecture related to Cloud Computing companies as providers of modern technology services. Provide information that the technology used is effective and cost-effective for industrial cloud service users. This study uses the TOGAF ADM method in conducting Enterprise Architecture.
Implementation of Support Vector Machine Algorithm for Shopee Customer Sentiment Anlysis Sitepu, Melda Betaria; Munthe, Ibnu Rasyid; Harahap, Syaiful Zuhri
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11408

Abstract

As the number one largest marketplace in Indonesia based on the criteria for the origin of international stores, Shopee must always improve the quality of its products and services based on reviews from users. Given the huge number of user reviews, it is not effective to identify them by reading one by one. For this reason, an automated system is needed that can read and identify reviews better. Sentiment analysis has proven to do the job. This study aims to conduct a sentiment analysis of shopee product reviews from users who use English. This study applies the Support Vector Machine algorithm to classify the Shopee user review data. To solve this problem, the research was carried out by going through several stages, namely: pre-processing the text of the dataset, performing feature extraction, after that the word weighting was carried out using the TF-IDF method, after clean data was obtained, the SVM algorithm was implemented, for further evaluation of the model. In the results of the study, it was found that the word that most represented the positive opinion of Shopee customers was "Good" with a total of 4684 words. While the word that represents the most negative opinion is "Seller" with 68 words. From the five sentiment analysis models tested, the average value of the confusion matrix is ​​obtained, which are precision=1, recall=0.97, and f1-score=0.98. From this research, it can be concluded that the SVM algorithm is proven to be applicable in conducting sentiment analysis on user reviews of Shopee products with an average accuracy rate of 97.3%.
Content-Based Image Retrieval for Songket Motifs using Graph Matching Yullyana, Yullyana; Irmayani, Deci; Hasibuan, Mila Nirmala Sari
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11411

Abstract

Indonesia is a country that has abundant cultural wealth. One of the characteristics of Indonesian culture is Songket. Songket is a typical Malay woven cloth that has many variants of motifs, each of which represents a different meaning and philosophy. Songket is often found in Sumatra Island with different motifs in each region. With so many types of songket motifs, not everyone can recognize and distinguish between one songket motif and another, even Indonesian citizens themselves. With the help of computers, it is easier to find information about a songket motif or to find a similar songket motif. The field that can play a role in solving this problem is Content-Based Image Retrieval (CBIR). This study aims to carry out a content retrieval process on the songket core motif using graph matching-based processing. In this study, the method used is felzenzswalb segmentation, and graph matching through the VF2 isomorphism algorithm and graph edit distance. The number of songket core motif images used as data is 180 data in the form of color images measuring 64 x 64 pixels. Based on the results of the study, it was found that the optimal graph matching algorithm and parameters in this study were the VF2 algorithm for artificial images with an f-1 score of 91.05%, and Graph Edit Distance with GED≤8 parameters for songket motif images with an f1-score. by 53.36%.
Zakat Fitrah Application based on Web Framework using Waterfall Method Friyansyah, Karsan; Yanris, Gomal Juni; Muti’ah, Rahma
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11412

Abstract

Zakat Fitrah is an obligation for every Muslim. In the management of zakat fitrah, the Amil Zakat Agency has a very vital function, namely managing the receipt and distribution of zakat to groups of people who are entitled to receive it (Mustahik). If the amil zakat is negligent and not careful in managing zakat, then the distribution of zakat is not right on target. The Buyung Rahimah Rantauprapat Mosque has the Amil Zakat Fitrah Agency, but in the management process it still uses the manual method so that the zakat management process takes a long time and the data stored is inaccurate. To solve these problems, an orderly, neat and good recording system is needed. This study aims to create an application for the management of Zakat Fitrah at the Buyung Rahimah Rantauprapat Mosque based on the Web Framework. The application development method uses the Waterfall model which divides into four stages, namely: analysis, design, program code generation, and system testing. This research has produced a zakat fitrah application with the main menus, namely: login menu, amil agency, types of zakat, zakat payment, zakat distribution, user management. This application also manages to display zakat fitrah data and zakat fitrah distribution history data. With the application of a web-based framework, making this application user friendly, making it easier for the Amil Agency to manage zakat fitrah. A web framework with the MVC concept and a complete library makes zakat fitrah data management accurate and fast.
Prototype of movement monitoring Objects using Arduino Nano and SMS Notifications Lupitha, Mariska; Haryono, Haryono
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11413

Abstract

Currently, the development of information technology is very rapid, coupled with the development of the internet of things which is also very fast. This encourages many researchers to use information technology devices and internet of things devices to solve problems in the field. The Internet of things is a device that can communicate between one device and another. Currently, there are many internets of things devices that have been used in everything, including Smart Home, Smart Office, Smart Campus, and others. There is a problem, where currently there is a lot of theft of goods or the transfer of goods that are not known by the owner. This problem encourages researchers to conduct research, by making prototypes to be able to find out about objects that have moved. So that the owner of the goods will know, that the goods have moved without notifying the owner. This research is to detect motion sensors using MPU6050. Where the sensor has two functions, namely accelerometer, and gyroscope. Both sensors are able to find the coordinates of the x-axis, y-axis, and z-axis. The most widely used and affordable microcontroller is the Arduino Nano or Arduino Uno. The purpose of this study is to detect motion with the MPU6050 sensor, then the detection results of the x-axis, y-axis, and z-axis are sent via SMS media with the SIM900A device. The use of a prototype has many functions, it can be used to detect falling objects, detect falling motorcycles, and others. This device is equipped with a SIM900A module which functions to transmit coordinate data via Short Message Service (SMS).
Measurement of Photosynthetic Pigment Content using Convolutional Neural Network Rezeki, Imam Dwi; Nasution, Fitri Aini; Juledi, Angga Putra
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11414

Abstract

Estimation of photosynthetic pigment levels from leaves can be done using conventional methods using laboratory equipment such as spectrophotometers and using digital image processing from leaf images with a computational model. In digital image processing methods, various models are used, such as neural network, CNN, and linear regression. Measurement of photosynthetic pigment levels using image processing methods uses color value data from image data as input to the model used. In this study, we will analyze the effect of various types of color space and inpaint preprocessing settings on the accuracy of the CNN model in measuring leaf photosynthetic pigment levels. The color space types being tested are 4 single color spaces RGB, HSV, LAB, and YCbCr, as well as 6 color combination spaces RGB+HSV, RGB+LAB, RGB+YCbCr, HSV+LAB, HSV+YCbCr, and LAB+YCbCr. The choice of the type of color space takes into account the phenomenon of color constancy and the characteristics of the color space on the lighting elements. In addition, image data is divided into two types, namely through inpaint preprocessing and not, so that in total there are 20 types of input data. After the CNN model training process with various types of color spaces and different preprocessing settings as input data, observations were made on the accuracy values, namely the training MAE and the validation MAE for each model. From 20 types of input data, 3 types of input data are obtained which are recommended as input data that provide the best model accuracy value based on MAE validation with values ​​of 0.08761, 0.09252, and 0.09288. The three recommended input data from the sequence of accuracy values ​​are RGB+LAB without inpaint, RGB with inpaint, and LAB+YCbCr without inpaint.
Forecasting Health Sector Stock Prices using ARIMAX Method Aprilianto, Muhammad; Hasibuan, Mila Nirmala Sari; Harahap, Syaiful Zuhri
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11418

Abstract

In daily stock trading activities, stock prices can experience ups and downs. The rise and fall of stock prices occurs due to changes in supply and demand for these shares. The COVID-19 pandemic did not have a negative effect, instead it had a positive impact on stock prices in health companies. companies in the health sector experienced a fairly good profit of 10.46% in the fourth quarter of 2021. This fact made investors interested in buying shares in companies in the health sector in the hope of selling them when demand increased, resulting in doubled profits. Stock conditions continue to fluctuate every day, making investors need to pay attention and study the past data of the health sector company that will be selected before deciding to invest. Therefore, it is necessary to forecast stock prices in the health sector for the next several periods as a step in making investment decisions. The health sector companies that will be modeled are PT Kimia Farma (Persero) Tbk and PT Kalbe Farma Tbk. The method used in this study is the ARIMAX model. The test and analysis results show that based on the RMSE and MAPE values, the best model is ARIMAX(5,13) for PT Kalbe Farma Tbk shares with a MAPE value of 1% in in-sample data and 0.6% in out-sample data.
Design and Build Inventory System using EOQ and ROP Methods (Case Study: CV. Ziefa Karya) Lubis, Rapida Hanim; Nasution, Fitri Aini; Juledi, Angga Putra
Sinkron : jurnal dan penelitian teknik informatika Vol. 6 No. 2 (2022): Articles Research Volume 6 Issue 2, April 2022
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v7i2.11419

Abstract

As a construction company that manages large quantities of incoming and outgoing goods, CV. Ziefa Karya must carry out an inventory control process, to determine the number of products to be re-supplied in a fast and accurate manner. But what happened was the opposite, with the inventory control process that was still manual, the owner of the company experienced various losses because he did not record goods and went out regularly. Based on these problems, this study tries to provide a solution in order to facilitate the management of inventory. CV. Ziefa Karya must have an inventory system that can manage the supply of goods properly. This study aims to build an inventory system based on information systems on CV. Ziefa Karya by applying the Economic Order Quantity (EOQ) and Reorder Point (ROP) methods. The system development method used is Model Driven Development (MDD) which includes: interviews, observations, literature studies, problem analysis, needs analysis, design, construction, and implementation. From the results of implementation and testing, it is found that the implementation of EOP and ROP in the application has succeeded in making the inventory system function properly. From these results it can be concluded that to build an inventory system on CV. Ziefa Karya uses the EOQ and ROP methods which can provide fast, precise, and accurate information, so the Model Driven Development (MDD) method must be used.

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