https://jurnal.polgan.ac.id/index.php/sinkron/issue/feed Sinkron : Jurnal dan Penelitian Teknik Informatika 2020-10-21T15:44:10+07:00 Nurul Khairina sinkron@polgan.ac.id Open Journal Systems <p><strong>Sinkron</strong> <strong>: Jurnal dan Penelitian Teknik Informatika</strong> is<strong> The<a href="http://polgan.ac.id/jurnal/sinkrons3.pdf"> RISTEKBRIN Accredited National Scientific Journal Rank 3 (Sinta 3), Number: 148 / M / KPT / 2020 on August 3, 2020</a></strong>. SinkrOn is published twice in 1 year, namely in April and October. SinkrOn aims to promote research in the field of Informatics Engineering which focuses on publishing quality papers about the latest information about computer science. Submitted papers will be reviewed by the Journal and Association technical committee. All articles submitted must be original reports, previously published research results, experimental or theoretical, and will be reviewed by colleagues. Articles sent to the Sinkron journal may not be published elsewhere. The manuscript must follow the writing style provided by SinkrOn and must be reviewed and edited.</p> <p>Sinkron is published by <strong><span style="text-decoration: underline;"><a href="https://www.polgan.ac.id">Politeknik Ganesha Medan</a></span></strong>, a Higher Education in Medan, North Sumatra, Indonesia. </p> <p><strong>E- ISSN: <a href="http://issn.pdii.lipi.go.id/issn.cgi?daftar&amp;1472194336&amp;1&amp;&amp;">2541-2019</a> </strong>(Indonesian | LIPI)<strong> | </strong><strong>P-ISSN: <a href="http://issn.pdii.lipi.go.id/issn.cgi?daftar&amp;1474367655&amp;1&amp;&amp;">2541-044X</a> </strong>(Indonesian | LIPI)<strong> | </strong><strong>DOI Prefix: 10.33395</strong></p> <p><strong>E- ISSN: <a href="https://portal.issn.org/resource/ISSN/2541-2019">2541-2019</a> </strong>(International)<strong> | </strong><strong>P-ISSN: <a title="International ISSN" href="https://portal.issn.org/resource/ISSN/2541-044X">2541-044X</a> </strong>(International)</p> https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10595 Business Development Management Model at Samo-Samo Recycling House Based on SWOT Analysis 2020-10-03T20:03:48+07:00 Rusdiansyah Rusdiansyah rusdirds@gmail.com Harun Al Rasyid harun.har@bsi.ac.id Suryanto Sosrowidigdo suryanto.sys@bsi.ac.id <p>This study aims to determine the internal and external conditions faced by the Samo Samo Recycle House, as a basis for determining the appropriate alternative strategies for recycling waste business. Strategy formulation is carried out after the identification and determination of internal and external strategic factors. Internal strategic factors are then included in the IFAS (Internal Factors Analysis Summary) matrix, while external strategic factors are included in the EFAS (External Factors Analysis Summary) matrix, and the combination of the two matrices produces a Cartesisus Diagram to determine which company is in the diagram position. From the results of the calculation above, it is known that the coordinate point is located at (y = -0,12; x = 0,39). The coordinate results are presented in the SWOT matrix diagram. After knowing the meeting point of the diagonals (X), the position of the business unit is known in Quadrant II. This position shows the Samo Samo Recycling House, then in business strategies, including: Creating new designs to attract prospective buyers, Strengthening the competitiveness of commodities through improving the quality of results and business efficiency. Quality and creative human resource development</p> 2020-10-03T00:00:00+07:00 Copyright (c) 2020 Rusdiansyah Rusdiansyah, Harun Al Rasyid, Suryanto Sosrowidigdo https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10593 Expert System for Diagnosing Pregnancy Complaints by Forward Chaining 2020-10-03T20:45:06+07:00 Embun Fajar Wati embun.efw@bsi.ac.id Anggi Puspitasari anggi.apr@bsi.ac.id <p>Limited time in consulting becomes an obstacle for midwives in diagnosing complaints in pregnant women, especially those who are already in the III trimester and approaching the labor process. Misdiagnosis results in inaccuracies in the provision of solutions and actions. Initial treatment that corresponds to the complaints of pregnant women especially the third trimester is expected to reduce mortality rates in the mother and fetus. Expert System can be a timely solution with not too long so as to improve the quality of examination on midwives. The methods used are identification, primary and secondary data collection, forward chaining data analysis combined with bayesian, and evaluation with the calculation of the percentage of system success. Samples taken by 20 patients and 4 patients were declared unsyed because they had only one complaint. Meanwhile, 16 patients had some complaints that complied with the Rules. A total of 11 out of 16 patients or about 70% had valid results between the diagnosis of experts/midwives with the system. It can be concluded that the system works well to diagnose complaints in patients with a third trimester gestational age so that midwives can provide appropriate initial solutions and treatment in reducing maternal and infant mortality.</p> 2020-10-03T00:00:00+07:00 Copyright (c) 2020 Embun Fajar Wati, Anggi Puspitasari https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10587 Implementation of Apriori Algorithm Data Mining for Increase Sales 2020-10-04T19:57:54+07:00 Reza Alfianzah rezaalfianzah88@gmail.com Rani Irma Handayani rani.rih@nusamandiri.ac.id Murniyati Murniyati murni.mni@bsi.ac.id <p>Any company or organization that wants to survive needs to determine the right business strategy. The product sales data carried out by Lakoe Dessert Pondok Kacang will eventually result in a pile of data, so it is unfortunate if it is not re-analyzed. The products offered vary with a wide variety of products as many as 45 products, to find out the products with the most sales and the relationship between one product and another, one of the algorithms is needed in the data mining algorithm, namely the a priori algorithm to find out, and with the help of the Rapidminer 5 application, with a support value 2,4% and a confidence value 50%, products that customers often buy or are interested in can be found. This study used sales data for March 2020, which amounted to 209 transaction data. From the research, it was found that the item with the name Pudding Strawberry and Pudding Vanilla was the product most purchased by consumers. With knowledge of the most sold products and the patterns of purchasing goods by consumers, Lakoe Dessert Pondok Kacang can develop marketing strategies to market other products by analyzing the profits from selling the most sold products and anticipating running out or empty of stock or materials at a later date.</p> 2020-10-03T00:00:00+07:00 Copyright (c) 2020 Reza Alfianzah, Rani Irma Handayani https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10529 Drug Stock Prediction at Balige HKBP Hospital Using Adaptive Neuro-Fuzzy Inference System 2020-10-04T20:30:06+07:00 Arie Satia Dharma ariesatia@gmail.com Lily Andayani Tampubolon lilyatb@gmail.com Daniel Somanta Purba daniel96@gmail.com <p>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.</p> 2020-09-13T00:00:00+07:00 Copyright (c) 2020 Arie Satia Dharma https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10594 The Implementation of Artificial Intelligence in Charity Box at Mosque and Musholla as RFID Based Security System 2020-10-05T23:13:15+07:00 Defnizal Defnizal defnizal@upiyptk.ac.id Risa Nadia Ernes risanadiaernes@upiyptk.ac.id <p>The high crime rate in Indonesia has had a bad impact and loss on society, so that various efforts have been made to increase awareness and security in society. Charity box theft is a target of crime for criminals. For this reason, it is necessary to take strict steps in terms of vigilance and security so that the crime of theft of charity boxes can be avoided. One of the steps to increase awareness and safety is to apply the concept of security to the charity box. By utilizing several supporting sensors and supporting components in the charity box, the security system will work automatically, so that if there is a charity box theft, the system will provide an SMS notification to the mosque management. This research is focused on the problem of security facilities and supervision of charity boxes in mosques or mushalla. Using this system will reduce the risk of theft of charity boxes in mosques and mushalla, because apart from being equipped with an alarm and SMS gateway, this system is also equipped with RFID so that access to open charity boxes can be safer. This form of system works if the charity box is lifted or dismantled by force, the system will provide notification in the form of an alarm and SMS, so that the crime of theft of the charity box can be more aware of.</p> 2020-10-05T00:00:00+07:00 Copyright (c) 2020 Defnizal Defnizal, Risa Nadia Ernes https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10612 Facial Recognition Implementation using K–NN and PCA Feature Extraction in Attendance System 2020-10-06T12:12:26+07:00 Juliansyah Putra Tanjung juliansyahputratanjung@unprimdn.ac.id Bayu Angga Wijaya bayuanggawijaya@unprimdn.ac.id <p>Attendance is the fact that someone is present at an event or goes regularly to an institution, or attendance at an event is the number of people present at that time. The Saifiatul Amaliyah school itself is one of the many schools in Indonesia where the attendance of students or attendance is still done manually. This can cause problems, namely allowing fraud when filling in attendance and errors in data recapitulation. Therefore, in this study a computerized face attendance was created, which was formed using the K-Nearest Neighbor (K-NN) method and combined with the extraction of the Principal Component Analysis (PCA) feature where the attendance process can be done with a person's face. The face attendance system using the K-NN and PCA methods has an accuracy of 82%.</p> 2020-10-01T00:00:00+07:00 Copyright (c) 2020 Juliansyah Putra Tanjung, Bayu Angga Wijaya https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10589 Data Mining Model For Designing Diagnostic Applications Inflammatory Liver Disease 2020-10-16T15:42:46+07:00 Omar Pahlevi omar.opi@nusamandiri.ac.id Amrin Amrin amrin.ain@bsi.ac.id <p>Hepatitis is an infectious disease that is a public health problem that affects morbidity, mortality, public health status, life expectancy, and other socio-economic impacts. Early diagnosis of hepatitis is very important so that it can be treated and treated quickly. In this study, the authors will apply and compare several data mining classification methods, including the C4.5 algorithm, Naïve Bayes, and k-Nearest Neighbor to diagnose hepatitis, then compare which of the three methods is the most accurate. Based on the results of measuring the performance of the three models using the Cross Validation, Confusion Matrix and ROC Curve methods, it is known that the C4.5 method is the best method with an accuracy of 70.99% and an under the curva (AUC) value of 0.950, then the k-Nearest Neighbor method with accuracy of 67.19% and the value under the curve (AUC) 0.873, then the naïve Bayes method with an accuracy rate of 66.14% and a value under the curve (AUC) of 0.742.</p> <p>&nbsp;</p> <p>&nbsp;</p> 2020-10-06T00:00:00+07:00 Copyright (c) 2020 Omar Pahlevi, Amrin Amrin https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10565 Prediction of Netizen Tweets Using Random Forest, Decision Tree, Naïve Bayes, and Ensemble Algorithm 2020-10-06T23:29:30+07:00 Yan Rianto y-rianto@yahoo.com Antonius Yadi Kuntoro antonius.aio@nusamandiri.ac.id <p>The current Governor of DKI Jakarta, even though he has been elected since 2017 is always interesting to talk about or even comment on. Comments that appear come from the media directly or through social media. Twitter has become one of the social media that is often used as a media to comment on elected governors and can even become a trending topic on Twitter social media. Netizens who comment are also varied, some are always Tweeting criticism, some are commenting Positively, and some are only re-Tweeting. In this research, a prediction of whether active Netizens will tend to always lead to Positive or Negative comments will be carried out in this study. Model algorithms used are Decision Tree, Naïve Bayes, Random Forest, and also Ensemble. Twitter data that is processed must go through preprocessing first before proceeding using Rapidminer. In trials using Rapidminer conducted in four trials by dividing into two parts, namely testing data and training data. Comparisons made are 10% testing data: 90% Training data, then 20% testing data: 80% training data, then 30% testing data: 70% training data, and the last is 35% testing data: 65% training data. The average Accuracy for the Decision Tree algorithm is 93.15%, while for the Naïve Bayes algorithm the Accuracy is 91.55%, then for the Random Forest algorithm is 93.41, and the last is the Ensemble algorithm with an Accuracy of 93, 42%. here.</p> 2020-09-13T00:00:00+07:00 Copyright (c) 2020 Antonius Yadi Kuntoro https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10653 Expert System for Monitoring Elderly Health Using the Certainty Factor Method 2020-10-09T11:06:14+07:00 Linda Marlinda linda_marlinda2000@yahoo.com Widiyawati Widiyawati widiyawati.zul@gmail.com Reni Widiastuti reni.rws@bsi.ac.id Wahyu Indrarti wahyu.wii@bsi.ac.id <p>A person who is in the elderly phase will experience various decreases, ranging from decreased memory or senility, hormone production, skin elasticity, muscle mass, bone density, strength and function of body organs, and the immune system. As a result, it is difficult for the elderly or the elderly to fight against various kinds of disease-causing bacteria or viruses, comorbidities, and adaptation to the social environment. Due to the complexity of this health problem, improvements can not only be made in the aspect of health services but also improvements in the environment and engineering of population factors or hereditary factors, but it is necessary to pay attention to behavioral factors that have a considerable contribution to the emergence of health problems. This research uses the certainty factor (CF) method which can provide a measure of belief in a symptom as a measure of how much the value is in the later diagnosis. The purpose of making this expert system is so that patients, patient families, and medical teams can monitor the health of the elderly daily. The results of this study indicate that using the CF method has an accuracy rate of 91 percent for the prediction of patients who have cholesterol</p> 2020-10-07T00:00:00+07:00 Copyright (c) 2020 Linda Marlinda https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10579 An Expert System Diagnosis Human Eye Diseases Using Certainty Factor Method Web-Based 2020-10-07T15:01:45+07:00 Bayu Angga Wijaya bayuanggawijaya@unprimdn.ac.id Juliansyah Putra Tanjung juliansyahputratanjung@unprimdn.ac.id <p>Eye is the important senses. If the eye is disrupted then ignore it, it will disturb. In fact, many people delay to checked eye diseases that them suffered, due to the lack of knowledge society, the cost is quite expensive and the imbalance between patients and doctors so that should be queued if will check the eye health. It is necessary for the expert system that can diagnose eye diseases, so a people can checking their eye diseases suffered without have to go to the doctors. This expert system is based on web with the programming language PHP and MySQL database. In the process of withdrawal conclusion, system using the certainty factors method that use a value to assume degree of confidence from an expert to a data. Expert system provides results in the form of the possibility of illness suffered, the value of the percentage of beliefs from the illness and the treatment solution based on the value of confidence that given and system is able to know the type of eye disease experienced by the user based on the symptoms chosen by the user. So, it can help the people to know the eye disease their suffered and the action can be done faster.</p> 2020-10-01T00:00:00+07:00 Copyright (c) 2020 Bayu Angga Wijaya, Juliansyah Putra Tanjung https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10599 Assosiation Rules for Product Sales Data Analysis Using The Apriori Algorithm 2020-10-07T17:29:48+07:00 Jarseno Pamungkas ukazseven@gmail.com Yopi Handrianto yopi.handrianto@gmail.com <p>To increase sales transactions, the company must be able to compete with other competitors so that it requires an appropriate strategy in carrying out the sales process carried out. In addition to the marketing strategy, the company must be able to analyze the products sold based on the number of sales that have occurred so that the company can see which products are more dominant in consumer demand so that the company can determine a more effective sales strategy. PT. Surya Indah City is a company engaged in the sale of various clothing and accessories. In an effort to increase sales of its products, an analysis is needed to be able to increase company revenue by utilizing sales transaction data it has. To analyze the relationship between clothing products and accessories which are more predominantly sold and other available clothing and accessories products, a data mining algorithm is used, namely the a priori algorithm. With the help of the tanagra application to carry out the calculation process, the dominant product that consumers are interested in can be determined. By using two variables that meet support and minimum confidence, it can be concluded that the most sold products are from the type of clothing, namely clothes and pants. It was concluded that the results of the known final association rules, if you buy a shirt, you will buy pants with 50% support and 75% confidence. If you buy pants, you will buy clothes with 50% support and 85% confidence.</p> 2020-10-07T00:00:00+07:00 Copyright (c) 2020 Yopi Handrianto https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10611 Designing an Arduino-based Automatic Cocoa Fermentation Tool 2020-10-08T23:46:00+07:00 Balkhaya Balkhaya balkhaya@poltas.ac.id Dirja Nur Ilham dirja.poltas@gmail.com Rudi Arif Candra rudi_candra@poltas.ac.id Hasbaini Hasbaini hasbainibean@gmail.com Fera Anugreni anugreni@poltas.ac.id <p>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. The 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 moldiness 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. From the results of the tests carried out, the tool is able to read both hot and cold temperature conditions, and the LM35 sensor can work well in detecting temperature changes from 350C to 400C or vice versa.</p> 2020-10-01T00:00:00+07:00 Copyright (c) 2020 Dirja Nur Ilham https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10635 Design of an Automatic Water Pump on a Traditional Boat 2020-10-10T12:43:52+07:00 Ihsan Ihsan Ihsan@poltas.ac.id Dirja Nur Ilham dirja@poltas.ac.id Rudi Arif Candra rudi_candra@poltas.ac.id Amsar Yunan amsar@poltas.ac.id Hardisal Hardisal hardisal@poltas.ac.id <p>Draining traditional boat water efficiently is sometimes considered to be of little importance to most fishermen. Because it is considered a normal thing without realizing it can be detrimental, both in terms of time and work. One of the things that often makes the use of draining water less efficient is that the draining of boat water is still done manually with human intervention. So that fishermen are preoccupied with removing puddles of boats and hindering their work. Based on the above problems, this study aims to make a traditional boat water drain control system automatically. This tool functions to control the volume of water in the boat as well as turn on and turn off the water pump engine automatically. This tool is able to remove puddles that enter the fishing boat automatically. The working principle of this tool, if the water hits the sensor ≥ 5 cm, the pump and buzzer will start and if the water doesn't hit the sensor, the pump and buzzer will automatically shut down.</p> 2020-10-08T00:00:00+07:00 Copyright (c) 2020 Dirja Nur Ilham, Ihsan Ihsan, Rudi Arif Candra, Amsar Yunan, Hardisal Hardisal https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10564 Sentiment Analysis Of Full Day School Policy Comment Using Naïve Bayes Classifier Algorithm 2020-10-14T08:45:27+07:00 Miftahul Kahfi Al Fath kahfialfath@gmail.com Arini Arini arini@uinjkt.ac.id Nashrul Hakiem hakiem@uinjkt.ac.id <p>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.</p> 2020-10-01T00:00:00+07:00 Copyright (c) 2020 Miftahul Kahfi Al Fath, Arini Arini, Nasrul Hakiem https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10649 The K-Medoids Clustering Method for Learning Applications during the COVID-19 Pandemic 2020-10-08T21:53:02+07:00 Samudi Samudi samudi.net@gmail.com Slamet Widodo slamet.smd@bsi.ac.id Herlambang Brawijaya Herlambang.braw@bsi.ac.id <p>A disease that is currently widespread today is caused by the spread of the coronavirus disease or what is commonly called COVID 19. This virus is very dangerous to health because it attacks organs in the human body from various sources, either from the air or direct touch. With the existence of COVID 19, it has an impact on all countries, especially the State of Indonesia, which consists of various islands, which are also affected by the COVID 19 virus. So that the central government takes a policy to carry out social distancing to every one to break the chain of spreading this virus, with this social distancing it has an impact on all activities that occur every day. As an impact on the learning process that usually takes place in class, it turns into online learning that uses several supporting applications in the learning process during the COVID 19 pandemic. With online learning from various applications, it attracts researchers to research with the K-Medoid Clustering Algorithm in using applications during the pandemic COVID 19.</p> 2020-10-08T00:00:00+07:00 Copyright (c) 2020 Samudi Samudi, Slamet Widodo, Herlambang Brawijaya https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10603 Credit Loan Selection During the Pandemic Recommendation MCDM-Promethee Method 2020-10-21T15:44:10+07:00 Akmaludin Akmaludin akmaludin.akm@nusamandiri.ac.id Erene Gernaria Sihombing erene.egs@nusamandiri.ac.id Linda Sari Dewi lindw.lrw@nusamandiri.ac.id Rinawati Rinawati rinawati.riw@nusamandiri.ac.id Ester Arisawati esterarisawati@yahoo.com <p>In the current state of COVID-19, many middle and lower-income businesses such as Micro, Small and Medium Enterprises (UMKM) have experienced a decrease in their income turnover, so that they require additional capital costs to carry on their business life. To provide additional capital loans, there are several requirements that must be met by every UMKM. Like an independent business that is carried out, whether it is permanent or only limited to domicile, then how long have they started the business they have built up to now, do they have collateral as loan guarantee, do they have a good level of business productivity during the running, seen from the report made, do you already have a lot of customers from the business you run. This is a benchmark for providing loans to UMKM. The method that can be recommended is Promethee, which is part of the Multi-Criteria Decision Making (MCDM) concept as a rating method in determining loan issues recommended by the Promethee method. The results obtained from the ranking with the Promethee method, namely that of the six selected and evaluated UMKM, the first rank was from the UMKM-3 with the highest weight value of 0.208, followed by UMKM-1 with a weight of 0.042 and followed by UMKM-5 which were still considered feasible even though they were not valuable. negative, while the other two UMKMs cannot be said to be eligible for a loan, namely UMKM-2 and UMKM-4 because they are negative.&nbsp;&nbsp;&nbsp;&nbsp;</p> 2020-10-08T00:00:00+07:00 Copyright (c) 2020 Akmaludin Akmaludin https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10610 The Infusion of Notification Design With an Application of Social Media Based on a Internet of Things (IOT) 2020-10-10T15:31:37+07:00 Rudi Arif Candra rudi_candra@poltas.ac.id Devi Satria Saputra devisatriasaputra@gmail.com Dirja Nur Ilham dirja.poltas@gmail.com Herry Setiawan herry.setiawan@poltas.ac.id Hardisal Hardisal hardisal@poltas.ac.id <p>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.</p> 2020-10-08T00:00:00+07:00 Copyright (c) 2020 Dirja Nur Ilham, Rudi Arif Candra, Devi Satria Saputra, Herry Setiawan, Hardisal Hardisal https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10643 Decision Support System For Determining Exemplary Students Using SAW Method 2020-10-10T11:41:48+07:00 Adjat Sudradjat adjat.ajt@bsi.ac.id Henny Destiana henny.hnd@bsi.ac.id Aprilah Amira Sefenizka aprilaha2704@nusamandiri.ac.id <p>In order to motivate students to continue to excel, MTs Al Falah undertakes activities to develop students' potential through determining exemplary students. However, the decision to determine exemplary students is not based on academic and non-academic abilities, but on the subjectivity of the principal and teachers. So that many complain about the decision of the selection of exemplary students who are not well targeted or deserve to be exemplary students. There is no information system that supports the determination of exemplary students on MTs Al Falah, It is less precise in determining the exemplary students on MTs Al Falah, decision support systems in Determination of the Exemplary Students using the Simple Additive Weighting (SAW) method is based on 5 criteria, namely the value of knowledge, the value of skills, class rank, extracurricular activity, extracurricular values. The results obtained will be in the form of exemplary student rankings. Then the student who gets the highest score in five categories with a percentage of 0.97 is Afifah Angelia Azhariyanti. The Simple Additive Weight method can help the school especially in determining a number of issues regarding education, one of which is to determine exemplary students. Because this method is a weighted method of rating the performance of each alternative.</p> 2020-10-10T00:00:00+07:00 Copyright (c) 2020 Adjat Sudradjat, Henny Destiana, Aprilah Amira Sefenizka https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10620 A Geographic Information System for Managing and Mapping Irrigation Infrastructure 2020-10-12T09:17:22+07:00 Rachmat Wahid Saleh Insani rachmat.wahid@unmuhpnk.ac.id Syarifah Putri Agustini agustini.putri@unmuhpnk.ac.id <p>Indonesia is one of the world's major agricultural nation which offers wide diversity of tropical products and agricultural commodities produced in substantial number of agricultural areas. Some of these areas are equipped with irrigation infrastructures which delivers water management throughout the land. Irrigation helps grow agricultural crops, maintain landscapes, and revegetation disturbed soils in dry areas. Water resources are finite while cyclic droughts on agricultural areas affecting the amount of water remains, thus creating unbalanced water demand and supply. Therefore, building an effective plan and management for irrigation infrastructure must be conducted using reliable information. The objective of this study is to develop a geographic information system to help managing and mapping process of irrigation infrastructure, such as flood gate and water ways. This system also helps to manage all the irrigation area and infrastructure data by providing geological information, search, and managing database function. We developed a web application for system interactivities. We also work together with Dinas Pekerjaan Umum dan Penataan Ruang of Kabupaten Kubu Raya, as they are managing nearest irrigation land which available to be inspected for research. The system has been tested in a real-life case study. As a result, the system enhances the efficient management of irrigation area and infrastructure data. Users stated that this geographic information system has many benefits to irrigation area management., i.e, ensuring data authorization with user information when data is recorded, real time image capture for each irrigation infrastructure, and digital maps to gain a wide overview of irrigation area information on Kabupaten Kubu Raya</p> 2020-10-12T00:00:00+07:00 Copyright (c) 2020 Rachmat Wahid Saleh Insani, Syarifah Putri Agustini https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10570 Web-Based Desktop Support Trouble Ticket System Design In PT. Mnc Mediacom Cable 2020-10-14T15:18:08+07:00 Besus Maulana Shulton besus.bem@nusamandiri.ac.id Eva Zuraidah evazuraidah6635@yahoo.com <p><em>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.</em></p> 2020-10-01T00:00:00+07:00 Copyright (c) 2020 Besus Maulana Shulton, Eva Zuraidah https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10621 Period Study Accuracy Prediction using Sequential Minimal Optimization Algorithm 2020-10-15T22:34:18+07:00 Hendri Noviyanto hendrinoviyantoo@gmail.com Bayu Mukti bayu.unsa@gmail.com <p>The study period is quite influential in the assessment of a university. The imbalance in the ratio of students to lecturers causes the quality of teaching and learning to decline, this is because one lecturer has to manage many students. Acquisition of accreditation scores and society's assumptions about higher education are also strongly influenced by the number of student graduations on time. Therefore, the prediction of the accuracy of the study period is needed as consideration for related parties to solve the problem of student learning delay. Sources of data in this study were taken from a database stored at the University of Surakarta, namely the Temporary Achievement Index with data of 209 instances and 5 attributes. The proposed method in this study is the Sequential Minimal Optimization algorithm. The validation method uses k-fold Cross-Validation with a value of K = 10. This method is compared with other methods such as naive Bayes, KNN, and Decision Tree. The results of this study, the proposed method can predict the accuracy of the study period quite well with the acquisition of accuracy of 88.52%. However, several other methods such as NaiveBayes obtained better accuracy of 90.91%, KNN of 91.86%, and Decision Tree of 96.65%. From the results of the comparison of these methods, the Decision Tree obtained the highest accuracy value. In future studies, researchers aim to enrich features in the prediction process. These features are related to student activities, such as student backgrounds, social activities, additional activities on campus and off-campus, and other aspects.</p> 2020-10-15T00:00:00+07:00 Copyright (c) 2020 Hendri Noviyanto, Bayu Mukti https://jurnal.polgan.ac.id/index.php/sinkron/article/view/10588 Twitter Comment Predictions on Dues Changes BPJS Health In 2020 2020-10-20T01:08:08+07:00 Riza Fahlapi riza.fahlapi@gmail.com Yan Rianto y_rianto@yahoo.co.jp <p>The Social Security Administering Body (BPJS) is a facility established by The government in providing services to citizens in The field of health welfare. The Spirit of cooperation in the utilization of health services which is very much currently a constraint in the budget is still insufficient in covering health services as a whole. For this reason, government policy is following with PERPRES No. 75 in 2019, the Government officially raised the BPJS Health contributions for 2020. The increase in BPJS Health contributions certainly caused a lot of comments. Namely Twitter, one of the social media that is used by the public to express disapproval or support for this government policy. This study, testing was carried out related to the prediction of comments from social media on community responses to the increase in BPJS Health contributions taken by the government. In the test carried out 3 (three) input algorithms. For every single algorithm including getting results through the K-NN method with an accuracy of 71.83% and AUC value of 0812, for the Naïve Bayes method produces an accuracy of 81.63% and AUC value of 0586. As for the C 4.5 method, the accuracy is 65.37% and the AUC value is 0628. While testing conducted through the Ensembles Vote method which combines the 3 algorithms above gives the best results with an accuracy of 80.10% and AUC value is 0871 for Twitter comment predictions.</p> 2020-10-20T00:00:00+07:00 Copyright (c) 2020 Riza Fahlapi, Yan Rianto