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Results in Journal SinkrOn: 130

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Besus Maulana Shulton, Eva Zuraidah
Published: 1 October 2020
SinkrOn, Volume 5, pp 152-163; doi:10.33395/sinkron.v5i1.10570

Abstract:
In recent years the existence of web-based information systems in Indonesia has increasingly felt its presence in supporting daily activities, both economic and non-economic. Manually processing data certainly cannot keep up with the need for fast, precise, and accurate presentation of information. Currently, manual data processing is considered less effective for providing reports and information for companies that are developing and have diverse transactions. The importance of Trouble Ticket Desktop Support is to make equalization of workloads that are fair and balanced besides that it is also a tool for assessment on each a technician. So with this, the author tries to examine the application of web-based technology that can be applied to problems that exist in one activity so that it can integrate the activities concerned. Ticket Desktop Support as a process to collect data from various existing sources and Desktop Support is required to be active monitor and treat user needs. With Trouble Ticket Desktop Support that is well integrated so that accessing data on Desktop Support can be done easily and quickly in order to measure the level of problems and access reports by the Head of IT Operations, as well as problems can be handled well within the scope of problem boundaries that produce the right solution to manage resources the power available, with this application it will be clear what problems are faced by the customer.
Arie Satia Dharma, Lily Andayani Tampubolon, Daniel Somanta Purba
Published: 13 September 2020
SinkrOn, Volume 5, pp 26-34; doi:10.33395/sinkron.v5i1.10529

Abstract:
Currently the purchases of drugs at Instalasi Farmasi RSU (IFRS) HKBP Balige are based on the examination of the amount of drugs usage. The purchases of drugs based on the examination of the amount of drugs usage cause frequent unplanned drugs purchases that must be hastened (cito) and purchases to other pharmacies. The purchases of cito and purchases to other pharmacies will inflict a financial loss to the patients, because when IFRS makes drugs purchases of cito or to other pharmacies, the cost of the drugs will be more expensive. Therefore, in this research, a prediction of drugs stock in IFRS HKBP Balige using Adaptive Neuro Fuzzy Inference System (ANFIS) will be carried out. ANFIS is a combination of Least Square Estimator (LSE) and Error Back Propagation (EBP) algorithms. ANFIS consists of forward pass and the backward pass learning. The sample data used to predict drugs stock in this research is data of drugs sales at the IFRS HKBP Balige from 2013 to 2015. From the results of drugs stock prediction research with ANFIS, obtained that number of errors of ANFIS model is 5.52%. Based on MAPE accuracy level evaluation, number of errors have an excellent rate so that it can be concluded that the predicted results of the drugs stock are good.
Published: 1 October 2020
SinkrOn, Volume 5, pp 107-115; doi:10.33395/sinkron.v5i1.10564

Abstract:
Sentiment analysis is an important and emerging research topic today. Sentiment analysis is done to see opinion or tendency of opinion to a problem or object by someone, whether it tends to have a negative or positive view. The main purpose of this study is to find out public sentiment on Full Day school's policy comment from Facebook Page of Kemendikbud RI and to find out the performance of the Naïve Bayes Classifier Algorithm. In this study, the authors used the Naïve Bayes Classifier algorithm with trigram and quad ram character feature selection with two different training data models and labeling of training data using Lexicon Based method in the classification of public sentiment toward the Full day school policy. The result of this research shows that public negative sentiment toward Full Day School policy is more than positive or neutral sentiment. The highest accuracy value is the Naïve Bayes Classifier algorithm with trigram feature selection of 300 data training models with a value of 80%. The greater of training data and feature selection used on the Naïve Bayes Classifier Algorithm affected the accurate result.
Published: 1 October 2020
SinkrOn, Volume 5, pp 92-99; doi:10.33395/sinkron.v5i1.10611

Abstract:
Automatic cocoa fermentation design is expected to facilitate the work of cocoa farmers during the process of reversing and stirring cocoa fermentation based on the right temperature. Fermentation process is of course done in a box or sack so that chocolate quickly produces heat and is cemented. However, in certain conditions, especially when in sacks there are often obstacles in the stirring process. Often the fermented chocolate experiences weathering or moldyness due to the uneven reversal that causes chocolate to clot, causing weathering or moldiness and produce an unpleasant odor and unattractive color on the cocoa beans. To overcome this problem a tool that automatically can turn or stir the cocoa beans evenly. This device is controlled by Arduino Uno R3 with a sensor that is an LM35 temperature sensor and has an LCD output and DC motor. This tool uses Relay to adjust the delay when driving a DC motor. The working principle of this tool, when the LM35 temperature sensor receives heat conditions on the cocoa beans, the LCD will display the condition of the temperature while the relay will instruct the DC motor to move the Cocoa Fermentation rail rotating left or right. The purpose of making this tool is to create a tool that can help alleviate the work of cocoa farmers in cocoa bean stirring activities at the time of cocoa bean fermentation controlled by Arduino.
Published: 8 October 2020
SinkrOn, Volume 5, pp 129-137; doi:10.33395/sinkron.v5i1.10610

Abstract:
This study discusses the infusion detection device in a hospital room. This tool is designed to help hospital nurses to cope more quickly to avoid problems due to the infusion. Load cell sensors are used as heavy detectors that send notifications to the nurses through the telegram application that has been installed. The nurse will get a notification message sent to the telegram if the sensor has read the weight. The tool is made using a load cell sensor and NodeMCU Wi-FiESP866 which functions to send notification of the results of sensor data input to the Internet of Things (IOT) platform namely Telegram. Nurses need to be connected to the internet network to get notifications on the telegram. Test results show that the time needed to send and receive notifications on Telegram takes about 2-5 seconds. The message will be sent 3 times, first the infusion WARNING is almost exhausted (alert), second the infusion WARNING is almost exhausted (standby) and the infusion WARNING is almost exhausted (please replace). If the infusion is not replaced by the nurse, it will be warned by Buzzer. However, time can be influenced by the available internet network connectivity. However, time can be affected by the available internet network.
Tri Retna Sari, Eva Rahmawati, Hani Harafani
Published: 4 April 2019
SinkrOn, Volume 3, pp 280-287; doi:10.33395/sinkron.v3i2.10108

The publisher has not yet granted permission to display this abstract.
Rudi Arif Candra, Arie Budiansyah, Taufiq Abdul Gani, Dirja Nur Ilham, Siti Rusdiana
Published: 28 October 2019
SinkrOn, Volume 4, pp 256-259; doi:10.33395/sinkron.v4i1.10394

Abstract:
A map is one of the cartographic scientific products that is used as a guide to access locations or places. The use of information technology and computer systems in cartography can increase the value of map products to be interactive and can be accessed online via the internet. This interactive map of the Unsyiah Director Office building is the development of an interactive map product of the author with the addition of an animated pathway from the reference point to the location point. With these additions, it will be easier for visitors to access the location
Published: 7 March 2020
SinkrOn, Volume 4, pp 34-41; doi:10.33395/sinkron.v4i2.10502

Abstract:
Pears is a fruit that is widely available in tropical climates such as in western Europe, Asia, Africa and one of them is Indonesia. There are many types of pears in Indonesia. Types of pears can be distinguished from the color, size, and shape. But it is still difficult for ordinary people to get to know the types of pears. This is what gave rise to the idea to conduct research related to image processing to classify three types of pears namely abate, red and william pears in order to help determine the type of pears. The pear type classification process is done by verify the image of pears based on existing training data. The research method used consisted of preprocessing image segmentation with morphological operations and feature extraction into Principal Component Analysis (PCA). The classification algorithm used is K-Nearest Neighbor (KNN). The use of adequate training data will further improve the classification of types of pears. The final results of this study amounted to 87.5%.
Amir Mahmud Husein, Muhammad Arsyal, Sutrisno Sinaga, Hendra Syahputa
Published: 13 March 2019
SinkrOn, Volume 3, pp 112-118; doi:10.33395/sinkron.v3i2.10044

The publisher has not yet granted permission to display this abstract.
Rudi Arif Candra, Dirja Nur Ilham, Hardisal Hardisal, Sriwahyuni Sriwahyuni
Published: 18 March 2019
SinkrOn, Volume 3, pp 200-204; doi:10.33395/sinkron.v3i2.10094

The publisher has not yet granted permission to display this abstract.
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