Jurnal Pilar Nusa Mandiri https://ejournal.nusamandiri.ac.id/index.php/pilar <p>The PILAR Nusa Mandiri Journal is a formation of the Information Systems study program, which was originally a medium for accommodating scientific writings of STMIK Nusa Mandiri Jakarta Information Systems lecturers. Along with the times, this journal has become a National journal that has P-ISSN: 1978-1946 and E-ISSN: 2527-6514. PILAR Nusa Mandiri has become a Rank 3 Accredited Journal&nbsp;and is trying to become a higher accredited journal. PILAR Journal Nusa Mandiri is published 2 times in 1 year, namely in March and September. This journal is&nbsp;<span class="tlid-translation translation"><span title="">Rank 3 Accreditation Certificate (S3), Accreditation is valid for 5 years. Starting from Vol. 12, No. 1 the Year 2016 to Vol. 16, No. 2 the Year 2020.&nbsp;Journal of PILAR Nusa Mandiri, re-accreditation remains at Rank 3 (SINTA 3), starting Vol. 15 No. 2 of 2019 based on the Decree of the Minister of Research and Technology / National Research and Innovation Agency Number 85 / M / KPT / 2020, April 1, 2020</span></span></p> PPPM Nusa Mandiri en-US Jurnal Pilar Nusa Mandiri 1978-1946 <div class="page"> <p>The Authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to the PILAR Nusa Mandiri journal as the publisher of the journal, and the author also holds the copyright without restriction.</p> <p>Copyright encompasses exclusive rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms, and any other similar reproductions, as well as translations. The reproduction of any part of this journal, its storage in databases, and its transmission by any form or media, such as electronic, electrostatic and mechanical copies, photocopies, recordings, magnetic media, etc. , are allowed with written permission from the PILAR Nusa Mandiri journal.</p> <p>PILAR Nusa Mandiri journal, the Editors and the Advisory International Editorial Board make every effort to ensure that no wrong or misleading data, opinions, or statements be published in the journal. In any way, the contents of the articles and advertisements published in the PILAR Nusa Mandiri journal are the sole and exclusive responsibility of their respective authors and advertisers.</p> </div> COMPARISON OF LINEAR REGRESSIONS AND NEURAL NETWORKS FOR FORECASTING ELECTRICITY CONSUMPTION https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/1459 <p>Electricity has a major role in humans that is very necessary for daily life. Forecasting of electricity consumption can guide the government's strategy for the use and development of energy in the future. But the complex and non-linear electricity consumption dataset is a challenge. Traditional time series models in such as linear regression are unable to solve nonlinear and complex data-related problems. While neural networks can overcome the problems of nonlinear and complex data relationships. This was proven in the experiments in this study. Experiments carried out with linear regressions and neural networks on the electricity consumption dataset A and the electricity consumption dataset B. Then the RMSE results are compared on the linear regressions and neural networks of the two datasets. On the electricity consumption dataset, A obtained by RMSE of 0.032 used the linear regression, and RMSE of 0.015 used the neural network. On the electricity consumption, dataset B obtained by RMSE of 0.488 used the linear regression, and RMSE of 0.466 used the neural network. The use of neural networks shows a smaller RMSE value compared to the use of linear regressions. This shows that neural networks can overcome nonlinear problems in the electricity consumption dataset A and the electricity consumption dataset B. So that the neural networks are afforded to improve performance better than linear regressions. <strong>&nbsp;</strong>This study to prove that there is a nonlinear relationship in the electricity consumption dataset used in this study, and compare which performance is better between using linear regression and neural networks<strong>.</strong></p> Tyas Setiyorini Frieyadie Frieyadie ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc/4.0 2020-09-08 2020-09-08 16 2 135 140 10.33480/pilar.v16i2.1459 APPLICATION OF BACKPROPAGATION NEURAL NETWORK ALGORITHM FOR CIHERANG RICE IMAGE IDENTIFICATION https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/1500 <p>Rice is a food source for carbohydrates that are most consumed in Indonesia, because of this the production is higher compared to other food crops. There are several superior rice varieties planted by the farmers, one of them is Ciherang. This type is widely planted by farmers because has high selling as economic value and can be used as premium rice. The existence of several types of rice that had a high sales value makes some person was deceitfulness by mix the rice with premium quality with bad quality. Many people do not know the problem of distinguishing types of rice from one to another that has the same shape. Classification techniques using the backpropagation neural network algorithm and image processing are used to identify one of the most preferred types of rice, Ciherang. The network architecture model on the backpropagation algorithm is very influential on the value of accuracy. In determining the best network’s architectures, 4 times attempted where network architecture with 5 nodes in the input layer, 8 nodes in the hidden layer, and 1 node in output layer produce the highest accuracy of 82,66%.</p> Dita Aprilia Jajam Haerul Jaman Riza Ibnu Adam ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc/4.0 2020-09-08 2020-09-08 16 2 141 148 10.33480/pilar.v16i2.1500 STUDENT PERFORMANCE ANALYSIS USING C4.5 ALGORITHM TO OPTIMIZE SELECTION https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/1348 <p>Education is one of the fields that generate heaps of data. Pile of data that can utilized by higher education institutions to improve tertiary performance. One way to process data piles in the education is to use data mining or called education data mining. The quality assessment of educational institutions conducted by the community and the government is strongly influenced by student performance. Students who have poor performance will have a negative impact on educational institutions. Student data is processed to obtain valuable knowledge regarding the classification of student performance. One method of data mining is the C4.5 algorithm which is known to be able to produce good classifications. In this research and optimization method will be used namely optimize selection on the c4.5 algorithm. Based on the research, it is known that the optimization selection optimization method can improve the performance of algorithm c4.5 from 85% to 87%.</p> Hilda amalia Yunita Yunita Ari Puspita Ade Fitria Lestari ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc/4.0 2020-09-08 2020-09-08 16 2 149 154 10.33480/pilar.v16i2.1348 EDUCATIONAL DATA MINING FOR STUDENT ACADEMIC PREDICTION USING K-MEANS CLUSTERING AND NAÏVE BAYES CLASSIFIER https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/1432 <p>This study proposes the merging of the K-Means clustering data mining method and the Naïve Bayes classifier (K-Means Bayes) for better results in data processing for Student Academic Performance data. Data was taken from the Student Academic Performance dataset which is used as a test case. The amount of data used in this study were 131 data and 21 attributes. The accuracy of the results obtained from the combination of the proposed method is 97.44%. The results obtained when compared with calculations using the K-Means method and calculations using the Naïve Bayes method, the proposed method (K-Means Bayes) gives better results. Although the initial centroid determination on the K-Means method is done randomly, the impact can be reduced by adding the Naive Bayes classifier method which results in a better accuracy value, thereby increasing the accuracy of the method used. Compared to the K-Means and Naïve Bayes methods, the proposed method increases the accuracy of about 27% of the Naïve Bayes algorithm and about 23% of the K-Means algorithm. With the results obtained, it can be concluded that the proposed method can improve predictions of student academic performance data. The initial centroid determination for grouping in the K-Means method can affect the quality of the accuracy of the data produced</p> Dewi Ayu Nur Wulandari Riski Annisa Lestari Yusuf Titin Prihatin ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc/4.0 2020-09-08 2020-09-08 16 2 155 160 10.33480/pilar.v16i2.1432 ANALYSIS OF INTER-RELIGIOUS TOLERANCE SENTIMENTS IN INDONESIA ON CONVERSATIONS ON SOCIAL MEDIA TWITTER https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/1520 <p>Conversations on social media Twitter related to tolerance among religious communities in Indonesia are fascinating. However, it is a sensitive issue. In reality, there is often a war of comments about the implementation of tolerance between religious people in carrying out their own beliefs. The community is not careful in issuing opinions that can result in social insecurity, insecurity, and national instability. This condition will significantly affect the state of the country's economy. In some cases, political problems can be a trigger for intolerance between religious communities. The purpose of this study is to compare the performance of classification accuracy on positive or negative sentiments from conversations that intersect with the problem of tolerance among religious communities during the past year. In this study, we compared the performance of the accuracy of the modeling of sentiment analysis classification on public conversations on social media Twitter related to tolerance between religious communities in Indonesia. Because the text that will be carried out modeling comes from the Indonesian language, to facilitate labeling, translation is carried out into English, then a performance comparison of the sentiment analysis classification modeling with SVM algorithm, Naïve Bayes, Decision Tree, and k-NN. Based on the experiments, it was concluded that the SVM algorithm has the highest performance for the classification of sentiment analysis categories up to 65.03% compared to the Naïve Bayes algorithm, which reached 59.92%, Decision Tree, which reached 63.52% and k-NN which reached 57 66%.</p> Yogie Pribadi Noor Hafidz Yamin Nuryamin Windu Gata ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc/4.0 2020-09-08 2020-09-08 16 2 161 168 10.33480/pilar.v16i2.1520 TWITTER SENTIMENT ANALYSIS OF POST NATURAL DISASTERS USING COMPARATIVE CLASSIFICATION ALGORITHM SUPPORT VECTOR MACHINE AND NAÏVE BAYES https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/1423 <p>Natural disasters trigger people, especially Twitter users to provide information or opinions in the form of tweets. The Tweet can be an expression of sadness, concern, or complaint. Processing of data from these tweets will create trends that can be used for information needs such as education, economics, and others. Natural disasters are events that threaten human life caused by nature, including in the form of earthquakes. The method used is the Support Vector Machine and Naive Bayes from the tweet. The data collected is filtered from tweets by deleting duplicate data. In calculating the Natural Disaster sentiment analysis using a comparison of the Support Vector Machine and the Naive Bayes algorithm, the difference in accuracy is 3.07% where the results of the Support Vector Machine are greater than Naive Bayes. The purpose of this research is to analyze sentiment for the distribution of disaster aid that does not flow information due to information &amp; coordination in the field. so as to provide information on the location of natural disasters, natural disaster management, and its presentation to victims that can be shared evenly in an efficient time due to information and natural management so that the distribution of aid is hampered</p> Ainun Zumarniansyah Rangga Pebrianto Normah Normah Windu Gata ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc/4.0 2020-09-15 2020-09-15 16 2 169 174 10.33480/pilar.v16i2.1423 SURVEY PAPER: SOFTWARE AUTOMATED TESTING TOOL USING SYSTEMATIC LITERATURE REVIEW METHOD https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/1456 <p><em>Software testing is one of the most important roles in successful software development. The increasing complexity of software development requires the development team to use automated testing tools to test the quality and functionality of the application. In software testing, choosing a testing tool must be appropriate and in accordance with the software to be tested. Using the Systematic Literature Review method, this research collects and analyzes previous survey papers from 2 keywords, "Comparative of Automated Software Testing Tools" and "A Critical Analysis of Automated Software Testing Tools" on Google Scholar with a span of 2010 - 2020. Results from papers collected through 5 stages of the SLR, resulting in 11 papers that were reviewed. From these 11 journals, obtained 5 automated testing tools that are often discussed, Selenium, QTP, TestCompelete, Watir, and Ranorex. The results of this study indicate that there is no software automatic testing tool that is truly perfect because every automated software testing tool has its own strengths and weaknesses and it is expected that the results of this study can help software testers in choosing automatic testing tools according to their needs.</em></p> Dheanda Absharina Fahirah Fahirah Fenni Agustina ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc/4.0 2020-09-16 2020-09-16 16 2 175 182 10.33480/pilar.v16i2.1456 INFORMATION SYSTEM VALENT FOR PT ENSEVAL PUTERA MEGATRADING ON MOBILE USING EXPO https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/1499 <p>Every year, routinely PT. Enseval Putera Megatrading held several events which were held face-to-face and online and involved many parties, from the employees' board of directors and external parties as sources. The events held include: National Work Meeting (RAKERNAS), Mid Year Work Meeting, Product Launching, EMDP Graduation, Enseval Anniversary, Innovation Forum, and others. There are at least 3 stages that the Event Owner must go through in organizing and achieving the goals of an event, pre-event starting from the formation of the committee to determining the concept of the event that will take place, running events starting from registering participants who are present in the event to maintaining the event's run down, post events ranging from gathering feedback on events to publishing materials. An event management system is absolutely necessary to support the success of the event. Valent, which is a React Native based mobile application, is the right step to answer this need. React native is an application that is used using the JavaScript programming language to create applications in developing applications on smartphones based on Android and iOS. (Zammetti, 2018) This allows Valent to run on 2 OSes at once (Android &amp; IOS) so that all event participants can enjoy the benefits of the Valent application directly from their respective smartphones.</p> Sean Michael Magdalena A. Ineke Pakereng ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc/4.0 2020-09-15 2020-09-15 16 2 183 190 10.33480/pilar.v16i2.1499 CONSTRUCTING MOODLE-BASED ONLINE LEARNING FOR VOCATIONAL SCHOOL https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/1481 <p>During the Covid-19 pandemic, every level of educational institutions is demanded to employ online learning based on their condition and capability. Many efforts have been done to sustain the teaching and learning process without a face-to-face system. The characteristic of the learning model in vocational school is identical to education specified in the technical field which encompasses several fields of expertise and is passed down to expertise program and expertise competency which require an integrated system. One of the ways to meet the demand is constructing online learning with a learning management system based on Moodle (Modulator Object-Oriented Dynamic Learning Environment). The aim of this model is to create an effective and integrated learning environment in order to create ease in observation and evaluation. This research used Zachman Framework which was started by determining scope system encompassing data, process and computer network configuration; designing business model by using Use Case Diagram; designing the model of the information system by using Class Diagram, Activity Diagram and &nbsp;Sequences Diagram; designing technology model by creating users’ interface program; and proceed to the implementation by customizing the Moodle software to create Moodle-based online learning which can be used in vocational schools.</p> Dwinita Arwidiyarti Henni Comala Hikmi ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc/4.0 2020-09-15 2020-09-15 16 2 191 198 10.33480/pilar.v16i2.1481 IMPLEMENTATION OF K-MEANS ALGORITHM AS A CLUSTERING METHOD FOR SELECTING ACHIEVEMENT STUDENTS BASED ON ACADEMIC GRADE https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/1575 <p>Increased student success and low student failure rates are a reflection of good quality in the field of education. Awareness of the importance of education determines the quality in utilizing existing resources, including human resources, facilities and infrastructure as well as technological resources. The large number of students in school as well as the variety of different abilities and academic qualifications for each student, makes it difficult for the school to facilitate the search for outstanding student selection based on academic scores. Therefore it is necessary to do the data to be processed into information and knowledge as a grouping of outstanding students from assignment scores, test scores, and student practice scores as variables that will be supporting values in the selection of outstanding students. Data mining can be proposed as an approach that can be used to predict the selection of outstanding students. In this study, the application of the kmeans clustering algorithm is proposed to predict the selection of outstanding students based on academic scores.</p> Indah Dwijayanthi Nirmala Prima Dina Atika ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc/4.0 2020-09-15 2020-09-15 16 2 199 204 10.33480/pilar.v16i2.1575 APPLICATION OF EXPERT SYSTEM FOR ANDROID-BASED FOOD LAND SUITABILITY AND HOLTICULTURE https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/1461 <p>Plant land suitability is a way of evaluating the characteristics of planted land-based on certain criteria to determine which types of plants are most suitable for planting in that land, land suitability has not been utilized properly by farmers due to limited knowledge about the varieties of plant types that can be planted in their land, selection The types of plants are still based on traditions and elements of the surrounding agricultural environment which are only limited to a few types of plants without taking into account the suitability of the plants planted to their land characteristics. For this reason, an expert system application was created to help farmers determine the suitability of land for food crops and horticulture on an Android basis because on an Android basis it can make it easier for users, especially farmers to determine the suitability of their land without the need to find a plant land expert and can easily accessible to anyone, anywhere. To produce a good expert system, the research method will be used, namely the certainty factor method. The results of testing expert system applications with certainty factor methods are proven to be able to provide accurate land suitability information</p> Lis Saumi Ramdhani Desi Susilawati Rizal Amegia Saputra ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc/4.0 2020-09-15 2020-09-15 16 2 205 212 10.33480/pilar.v16i2.1461 COMPARISON OF DATA MINING CLASSIFICATION METHODS TO DETECT HEART DISEASE https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/1388 <p><em>Heart disease is a disease that is deadly and must be treated as soon as possible because if it is too late, it has a big risk to one's life. Factors causing the disease of the heart is the use of tobacco, the physical who are less active, and an unhealthy diet. With existing data, the study is to compare the three algorithms, namely: Naive Bayes, Logistic Regression, and Support Vector Machine (SVM) which aims to determine the level of accuracy of the best of the dataset that is used to predict disease heart. This research produces the best accuracy of 87%, which is generated by the Naive Bayes method</em></p> Ira Ekanda Putri Dwi Rahmawati Yufis Azhar ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc/4.0 2020-09-28 2020-09-28 16 2 213 218 10.33480/pilar.v16i2.1388 ENGINEERING SUPPLY INFORMATION SYSTEMS BY APPLICATION OF THE METHODS OF ECONOMIC ORDER QUANTITY (EOQ) AT THE SUPERMARKET (CASE STUDY: SAHABAT KITA SWALAYAN) https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/1599 <p>Sahabat Kita Swalayan is a supermarket located in the city of Bangkinang. The supermarkets have some of the drawbacks of sales, purchases, and supply systems. The frequent losses at this market are due to overstocked and stocked stores. The market also has no record of sales and purchase, so there is no accounting for obvious items. Furthermore, the supermarket owner who makes reservations to the supermarket by mere estimates fails to notice the supply. That way, the stock in the cellar will be overstocked and out of line with the proper sales target. To know the optimum number of purchases and the exact time of repurchase of goods, a system of supply was developed using a method of the economic order quantity (EOQ). The method of the economic order quantity (EOQ) was used to identify the number of ordering optimum stock items. By using reorder points (ROP), it can define the limit of what is in store. Furthermore, the system uses the single exponential smoothie method to predict sales figures. The study led to an undeveloped supply information system that can be implemented in the process of our friend's supermarkets that can be used by the supermarket owner and employee. It is hoped that because of this system, it is possible to help supermarkets maintain pen control.</p> Aini Istiqomah Istianah Muslim ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc/4.0 2020-10-01 2020-10-01 16 2 219 224 10.33480/pilar.v16i2.1599 MEASUREMENT OF READINESS AND INFORMATION TECHNOLOGY ADOPTION BASED ON ORGANIZATIONAL CONTEXT AMONG SMEs https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/1642 <p>The importance of using information technology forces organizations to switch to using this technology in the daily activities of the organization in running a business and this cannot be separated from the SMEs organization. This research was conducted to measure the readiness level of a Small, and Medium Enterprise (SMEs) organization in the use and adoption of information technology based on the organizational context. This research uses quantitative methods by conducting surveys and interviews with policymakers organized by SMEs to avoid inaccurate information. Surveys and interviews were conducted in the Jabodetabek area. Data will be processed using PLS-SEM software for statistical analysis and inferential analysis, while for descriptive analysis using SPSS and spreadsheets. The results obtained indicate a significant relationship between the readiness level variable and the IT adoption variable.</p> Asrul Sani Nur Nawangtyas Agus Budiyantara Ninuk Wiliani ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc/4.0 2020-09-15 2020-09-15 16 2 225 232 10.33480/pilar.v16i2.1642 DESIGNING GEOGRAPHIC INFORMATION SYSTEM CULINARY TOUR LOCATION IN THE WEST LOMBOK REGION MOBILE-BASED APPLICATION https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/1663 <p>Lombok Island is an island in West Nusa Tenggara which is separated by the Lombok and Bali straits to the west and Alas Strait to the east of Sumbawa. The tourism potential in the West Lombok region is currently in great demand by local and foreign tourists because the tourist objects offered in the West Lombok region are very diverse, such as natural, religious, cultural, and culinary tours. Many restaurants offer culinary but often when indicating the location of a culinary, the information obtained is sometimes limited to street names and location characteristics. Meanwhile, the clarity of where the culinary location is not mapped in detail. So far, culinary connoisseurs use manual methods to find culinary locations such as Instagram, Facebook, and Blogspot. For tourists, this manual method is less effective because it consumes a lot of time and address information for getting to culinary locations is inadequate. One solution that can be used to obtain information is a geographic information system (GIS). The goal is to make it easier for culinary lovers to find culinary tourism locations. The research method used in this research is the Research and Development research method with preliminary stages, data and information collection, interviews and observations, system design with modeling, design validation, design revision, development, limited trial, limited trial revision, trial field, revision of field trials, dissemination<strong>,</strong> and implementation.</p> Surni Erniwati Ahmad Subki ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc/4.0 2020-09-15 2020-09-15 16 2 233 240 10.33480/pilar.v16i2.1663 DESIGNING CLASS SCHEDULE INFORMATION SYSTEM BY USING TABOO-SEARCH METHOD https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/1661 <p>Drafting of class schedule at the Faculty of Information and Communication Technology, Mataram University of Technology (FTIK UTM) is still done manually. So that, there are some problems such as lecturer teaching schedule at the same time at one time as well as student learning time at the same time at one time and studying more than 3 times a day. Therefore, manual scheduling requires a lot of time and it must be done very carefully. The method used to solve this problem is the Taboo- Search Method which is used to solve the problem of scheduling. The Taboo-Search Method is a method that seeks the best solution from existing solutions by creating a list of solutions or taboo lists, solutions that have been used previously will no longer be displayed for the next problem. The research method used in this research is the method of research and research and development which starts from the preliminary stage to find problems that occur up to the implementation stage so that it is generated an information system of course schedule at the Faculty of Information and Communication Technology, Mataram University of Technology. The purpose of this research is to produce a class schedule information system so that it can help arrange class schedules more quickly and precisely.</p> Zaeniah Zaeniah Salman Salman ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc/4.0 2020-09-15 2020-09-15 16 2 241 248 10.33480/pilar.v16i2.1661 DECISION SUPPORT SYSTEM SELECTION OF THE BEST ANDROID SMARTPHONE USING THE METHOD OF MOORA https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/1667 <p>In the current conditions of each person must have a smartphone due to a lot of activities are done online. These activities can be in the form of learning, purchasing, transportation, and so forth. Smartphones offered currently have various specifications, sometimes prospective buyers feel confused to choose a smartphone as what they need. To overcome the problems in the decision of the selection of the best android smartphone that is with the decision support system using the method of Multi-Objective Optimization based on Ratio Analysis (MOORA). In this study, the data collected based on the 100 questionnaires that were distributed. The criteria used, namely random access memory (RAM), camera, price, storage capacity, battery life, and screen size. The results of the calculation obtained in this study determine each brand and type of smartphone the best android. Expected in this study can help prospective buyers who are confused in choosing the best android smartphone</p> Siti Ernawati Imam Taftazani Al Hakim Tuslaela Tuslaela ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc/4.0 2020-09-15 2020-09-15 16 2 249 254 10.33480/pilar.v16i2.1667 PREDICTION OF SURVIVAL OF HEART FAILURE PATIENTS USING RANDOM FOREST https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/1665 <p>Human survival, one of the roles that is controlled by the heart, makes the heart need to be guarded and be aware of its damage. Heart failure is the final stage of all heart disease. The medical record tool can measure symptoms, body features, and clinical laboratory test values, which can be used to perform biostatistical analyzes but to highlight patterns and correlations not detected by medical doctors. So technology assistance is needed to do this in order to predict the survival of heart failure patients. With data mining techniques used in the available history data, namely the Heart Failure Clinical Records dataset of 299 instances on 13 features used the Random Forest algorithm, Decision Tree, KNN, Support Vector Machine, Artificial Neural Network and Naïve Bayes with resample and SMOTE sampling techniques. The highest accuracy with the resample sampling technique in the random forest is 94.31% and the SMOTE technique used in the random forest produces an accuracy of 85.82% higher than other algorithms.</p> <p>&nbsp;</p> Sri Rahayu Jajang Jaya Purnama Achmad Baroqah Pohan Fitra Septia Nugraha Siti Nurdiani Sri Hadianti ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc/4.0 2020-09-15 2020-09-15 16 2 255 260 10.33480/pilar.v16i2.1665 IMPLEMENTATION OF LARAVEL FRAMEWORK IN THE DEVELOPMENT OF LIBRARY INFORMATION SYSTEM (STUDY CASE: SMK PGRI 2 SALATIGA) https://ejournal.nusamandiri.ac.id/index.php/pilar/article/view/1666 <p>library is a means of support for students to develop their potential by increasing their knowledge through books. good library management is needed to facilitate students to support their learning. SMK PGRI 2 Salatiga has a library. the system applied to manage this library uses conventional methods where all library data is recorded into books. This system has a weakness that is prone to errors in recording and searching data. To deal with this problem, we need a system that can help manage library data. library information system can assist library management because all data can be recorded into the system and accessed through the system. This research was conducted to build a library information system that implements the laravel framework as an application framework. Laravel has various functions that can be used to help web application development. Based on the application testing carried out, the library information system of SMK PGRI 2 Salatiga has been running according to design and can handle library data recording by implementing the functions of the laravel</p> Embang Aulia Wicaksono Magdalena Ariance Ineke Pakereng ##submission.copyrightStatement## http://creativecommons.org/licenses/by-nc/4.0 2020-09-15 2020-09-15 16 2 261 270 10.33480/pilar.v16i2.1666