bluuebunny/crossref_metadata_2025 huggingface dataset:
Impetus and influences of Online Learning Interaction based on Non-English Lecturers’ Perspectives in global class program
Authors: Luke J Y , Sela S T
Published: July 2020

The purpose of this paper aimed to investigate the impetus and influences of executing Online Learning Interaction in the Global Class Program. There were sixteen university lecturers involved in this study. Data were collected through an online survey using Google form. The analysis of data used descriptive analysis using percentages. The results indicate that Online Learning Interaction carried out in English classrooms resulted in positive effects for university lecturers. The most influential effect of executing Online Learning Interaction to facilitate lessons in English was aiding to enhance technological skills in learning. Then, the second biggest effect was facilitating to transformation global vision or mindset of the lecturers. The third and fourth places were improving the effectiveness of communication in learning and enhance delivering skills. Moreover, the study indicates that ICT satisfaction in learning was the dominant motive to execute Online Learning Interaction in English Classroom contexts.
Automated Midline Setting for Brain Image Analysis to Detect Intracerebral Hemorrhage
Authors: Fahmi F , Nasution I K , Sawaluddin
Published: July 2020

One crucial step in detecting intra-cerebral hemorrhage automatically is to develop a midline setting that will divide the brain structure into 2 parts: the right hemisphere and the left hemisphere. This is useful for the process of detecting bleeding in the brain. By comparing the right hemisphere and the left hemisphere, bleeding detection can be done quickly and automatically on the application system. In this study, we proposed a method that was developed based on the pixel scan algorithm and the determination of the center of weight of the segmented part of the brain. The midline was set as the longest line possible drawn from edges of the brain skull. The result was then compared to manual reading by conducting user agreement surveys to radiology experts. The result shows that more than 75% of the cases experts strongly agree and agree with the midline setting automatically set by the algorithm, but 65% of them were dissatisfied and suggested improvement of the algorithm.
Comparative Analysis of Eigenface and Learning Vector Quantization (LVQ) to Face Recognition
Authors: Chandra R , An-Nissa S , Zamzami E M
Published: July 2020

Face recognition is a topic most often discussed in this era because it can be applied and developed for several needs that can be useful in daily life. Face recognition always use learning method like eigenface and learning vector quantization (LVQ). The learning process is using the face of a digital image taken from a camera in five angles for one person that will apply for dataset learning (training and learning data set), and the live image is taken from the camera for testing (testing data image). The first step image will be detected with a haar cascade and captured by a camera. It will use to processing images to get the best image and prepare to be input into the network. From the experiments with 10 testings with various parameter values, the experiment results obtained the LVQ is more accurate than eigenface to identifying faces with average accuracy 66.29% and eigenface is 56.67% with comparison 9.62%, but eigenface is faster in running time with average time 4.39 seconds and 7.38 seconds for LVQ with comparison 2.98 seconds.
Numerical simulation of a rectangular microstrip patch antenna for 3.35 GHz applications
Authors: Hanafiah Rambe Ali , Lutfi Muhammad , Suherman  , Zulfin Muhammad , Pinem Maksum
Published: July 2020

This paper described the design and numerical simulation of a rectangular microstrip patch antenna for applications at 3.35 GHz. The numerical simulation carried out with the aid of AWR software. The initial design was done by mathematical calculation. Then the initial design is modeled and numerically simulated to get the optimal design. Optimized parameters are length of the patch and width of the feed line. Based on the optimal results obtained a minimum return loss of -15.98 dB and bandwidth below the return loss of -10 dB is 93 MHz (3.311 - 3.404 GHz).
Traffic Light Controlling for Emergency Vehicle Line Based on GPS Tracking and Position Using GPRS Network
Authors: Seniman  , Zendrato Niskarto , Arisandi Dedy , Lubis Fahrurrozi
Published: July 2020

In big and metropolitan city, traffic jam is common problem and often to be occured. And that is the most critical problem for emergency vehicles. Where time and urgency are the most priority to be handled. In this research, emergency vehicle was utilized with any GPS device. The vehicle tracking service is provided for real time tracking. We use open source vehicle tracking framework/server Traccar. The same as with common GPS device, the emergency vehicle continusously sends its latitude, longitude and speed to GPS server. The research focused on Traffic Light Device which built of ESP32 microcontroller, GPRS module Air202 and battery power supply with charging function. While emergency vehicle reports its position to GPS server, the traffic light device continuously checks the emergency vehicle’s position data from the GPS server. The idea is to take the advantage of GPS server API, where traffic light device using HTTP GET communication with implementation of embedded cookies, session and keep alive to access the GPS server API. Traffic light device then calculates straight distance to emergency vehicle based on its predefined fixed latitude and longitude. If emergency vehicle located within the user defined threshold radius of traffic light device, then the traffic light turn green to allow emergency vehicle for passed its line. As the result of this research, traffic light device has been successfully read emergency vehicle device’s location data and measured their distance within 1 to 2 seconds.
Implementation of Linear Congruential Generator (LCG) Algorithm, Most Significant Bit (MSB) and Fibonacci Code in Compression and Security Messages Using Images
Authors: Elveny M , Syah R , Jaya I , Affandi I
Published: July 2020

The use of technology makes information spread more quickly compared to conventional methods that humans used before they knew technology. However, there is information that is only intended for certain people or institutions because the information is very confidential. The obstacle in exchanging information is the problem of information / data security. Because of that, an electronic message security algorithm which is quite well-developed is cryptographic (cryptography) and steganographic (steganography) algorithms. The development of increasingly advanced technology and the addition of more and more computer users also cause data to accumulate and transfer data from one device to another. The data is generally compressed first so that the exchange process does no take too long. Therefore, we need a system that can secure messages while reducing image data to be more efficient in the process of transmission and delivery. To implement this problem the system is designed using the Linear Congruential Generator (LCG) algorithm and the Most Significant Bit (MSB) as a security medium and using the Fibonacci Code algorithm as compression of the image. In implementation the system has a weakness in compressing images that not dominate colors because the size of the data becomes larger. In addition, the compression ratio on the variation of text length has decreased and has increased in the image variation experiments where if the compression ratio decreases, indicating better compression.
Preliminary Study for identifying Rice Plant Disease Based on Thermal Images
Authors: Silvi Lydia Maya , Aulia Indra , Jaya Ivan , Sofiah Hanafiah Diana , Hakim Lubis Rizky
Published: July 2020

Accurate and timely identification of plant disease can help stakeholders and farmers to mitigate losses due to pests and diseases. One of the identification techniques is indirect detection using thermal imaging technology. This technology has been considered a fast way without damaging the profile of a plant. In this paper, we describe the preliminary study of the thermal images gathering, so that the rice plant disease on the leaf canopy can be identified by using a thermal imaging camera.
Augmented Reality Virtual House Model Using ARCore Technology Based on Android
Authors: Syahputra M F , Hardywantara F , Andayani U
Published: July 2020

Scale model is a necessary building design in architecture as a way for architects to represent the results of the design as a physical model. The making of scale model requires components that costs some money. With the development of Augmented Reality (AR) technology, designer could bring the model design without having to make a scale model through marker tracking on a brochure. However, with the development of the technology itself, the researcher applies an AR method that can put an object in real environment by detecting flat surfaces. The method is Markerless AR. With this method, the use of marker tracking which requires a marker to remain on the frame of the camera is no longer needed. The technique in the new method will use plane detection that can detect flat surfaces by specifying points on the textures of the frame which is captured by the camera. The necessary stage is to define point cloud that will be used to mark the textures and the plane as a place to put the model in the form of virtual object. Object placed above the plane will remain stable despite having the camera moves around it, the plane will not move around because it is a result of virtual projections. The result of using plane detection will provide a space for the user to observe the model more clearly, such as on a floor or on a table because the model can be rescaled and rotated. Users also can move freely without being hindered by the marker tracking.
Developing Framework for Web Based e-Commerce: Secure-SDLC
Authors: Sugiantoro Bambang , Anshari Muhammad , Sudrajat Danang
Published: July 2020

Software development usually follows the stages known as the Software Development Life Cycle (SDLC). Development begins with the requirements phase and then continues with the design, development of test plans, implementation (coding), testing, and deployment. However, the security aspect has not been explicitly reflected in SDLC. In fact security must be present at every stage of the SDLC. Application of security in the process of developing software, especially e-Commerce, one of which uses the Security Development Lifecycle-Agile (SDL-Agile) method. The advantage of the SDL-Agile method is the application development process which incorporates a safety factor in each application development process, which is concise, and emphasizes user satisfaction. This objective of this paper examine the deployment of SDL Agile Method for eCommerce website to measure its confidentiality, integrity, and availability of the systems.
Visual aid presentation as a learning method: a case study in learning English of management students in Binus University
Authors: Willyarto M N , Werhoru D , Januarta S , Rivaldo
Published: July 2020

Schools, colleges and universities are now embracing the use of visual aid presentation (e.g., PowerPoint) in the classroom. Studies have consistently indicated that students generally believed that the use of technology for oral presentation would facilitate their learning. Students in such condition believed that the class was more organized, clear and interesting. Students also liked the teacher/lecturer more and indicated that they would like to take another class from the teacher/lecturer when the he or she used technology means of presentation. This research was focusing on the perspective of students in Binus University regarding the advantages or disadvantages of this model of learning process in regard of interesting or boring and long or short endurance of understanding. The visual aid presentation here meant that the students were the ones who were performing the presentation, instead of the teacher/lecturer. The research method used was descriptive qualitative based on the survey and interview of some sample students who were chosen randomly, who were taking English course in first/second semester.Based on some researches, the visual aid presentation in learning process was showing positive impact for teachers and students. Therefore, the hypothesis on this research was that the visual aid presentation on learning process would bring an interesting environment, long endurance of understanding and improving students’ behavior. It was expected that the result of this research could be used to improve the learning method of English learning in Binus University in order to support Binus Vision to be a global university and to enrich graduates with the skill of oral presentation.The respondents were selected from management students in Binus, Alam Sutera Campus, and randomly chosen. All of the respondents replied that learning by doing presentations was giving more understanding on topics, boosting up self-confident, teaching public speaking, handling nervous and creating a dynamic class environment to avoid boredom. From the students’ point of view, this learning method was giving advantage for students and long endurance of understanding.
Motor Vehicle Security using Microcontroller, GPS and Android as Innovation to Prevent Motor Thieves
Authors: Sihombing P , Daulay I S , Efendy S , Syarif I
Published: July 2020

Nowadays, transportation plays a big part in our daily lives. Everyday, people in Indonesia are increasingly using vehicles especially motorcycles. Unfortunately, along with the increasing number of motorcycle users, motorcycle theft has also increased. In this paper, we propose the prevention of theft and recovery of motorcycles by using sensors and microcontrollers connected to smartphones. In case of theft, the sensor will be activated automatically and the user will be notified by this system via an alarm warning. Users not only can see the location of the motorcycle at this time but also can turn off the engine through a smartphone even though the distance is long as there is an internet network. The results showed that the system can turn on/off motorcycle engines automatically using an Android Smartphone. The vibration sensor could activate the alarm and send a notification to the owner of a motorcycle. The motorcycle can be monitored by GPS devices that have been embedded on a motorcycle.
Additively weighted Hamming index of graphs
Authors: Mardiningsih  , Suwilo Saib
Published: July 2020

Hamming distance between two vertices of a finite simple graph is defined to be the Hamming distance of rows of (0,1)-matrix of the graph correspond to the two vertices. Hamming index of a graph is the sum of Hamming distances between all pairs of vertices in the graph. In this paper, we introduce the notion of additively weighted Hamming index of graph where the Hamming distance between two vertices is weighted by the sum of the degrees of the two vertices. We discuss the additively weighted Hamming index of a graph with respect to adjacency and incidence matrix of the graph. We relate the additively weighted Hamming index of a graph to the order of the graph, the size of the graph and the degree of each vertex in the graph. We then use this relationship to determine the additively weighted Hamming index of graph whose vertices have almost uniform degree.
Mathematic
Authors: Nasution Mahyuddin K M , Salim Sitompul Opim , Nasution Sawaluddin , Aulia Indra , Elveny Marischa
Published: July 2020

This paper provides a classical interpretation of mathematics from terms to categories such as arithmetic, geometry, algebra, and trigonometry. The background of interpretation is based on mathematics itself as reasoning, which contains systematic and structure. However, the mathematical term is recognized by them, but it comes with a variety of symbols and ways of interpretation. That interpretation is accumulated into universe of discourse which is a means of mathematics itself, and it states the mathematic.
Interaction Mixed Reality Rare Animal Indonesia with Voice Input Using Microsoft Hololens
Authors: Syahputra M F , Kurniawan D S , Siregar B
Published: July 2020

Indonesia is one country that is known for its natural wealth. Various types of flora and fauna living in this country. Examples of rich fauna that exist in Indonesia and can still be found at this point that one-horned rhino (Java rhinoceros), Sumatran elephant, Sumatran tiger, deer Bawean even dragons. However, over the times that make more and more people are not responsible for expanding residential land for private purposes and poaching that occurred in Indonesia, the animals are increasingly difficult to find because of habitats and their populations are dwindling. In this research, researchers applied a mixed reality technology with voice input to bring the Indonesian endangered species that has begun difficult to be found with the actual scale without having to disturb the habitat or environment. How it works is a mixed reality which brings together the virtual world with the real world. So that thanks to the development of today’s technological world, users can feel the direct presence of these animals without having to hunt or look for them.
Data Science
Authors: Nasution Mahyuddin K M , Salim Sitompul Opim , Budhiarti Nababan Erna
Published: July 2020

The presence of new science does not necessarily occur just like that. Every science starts from interests, discussion, and looks for a basic foundation, but in general the main foundation of science is mathematics. Data science includes structured and systematic knowledge about data. However, many other sciences that has a relationship with the data in question, ranging from statistics to computer science. This paper aims to reveal the obstacle and limitations of other science into a data science completely, on that basis the definition of data sciences needs to be elaborated, then confirm data science as new science and not depend directly on several other sciences.
Feature Selection Approach for Solving Imbalanced Data Problem in Single Nucleotide Polymorphism Discovery
Authors: Nurhasanah R , Hasibuan L S , Kusuma W A
Published: July 2020

Single Nucleotide Polymorphism (SNP) is a type of molecular marker which constitutes the phenotypic variations between individuals in certain species. In recent years, the advantages of SNP were widely considered in many fields, for instance in designing precision medicine in humans and assembling superior cultivars in plant breeding. The main challenge in SNP discovery is imbalanced data distribution between classes, where the number of true SNPs in question is much fewer than false SNPs. While the study in observing the benefit of feature selection in classification problem was widely reported, the use of this technique in solving imbalanced class problem still become interesting topic for research. In this study, we selected the features that most contribute in identifying SNP using Feature Assessment by Sliding Thresholds (FAST) method. FAST evaluates the contribution of each feature in identifying SNPs based on the Area under ROC Curve (AUC) value. SNP identification using 4 best features resulted in improved classifier performance in terms of G-Means compared to using 24 features. In addition, using feature selection techniques can reduce computational time and save resource needed.
Waspmote-Based Landslide Early Disaster Detection System with GSM Communication
Authors: Fachrizal F , Zarlis M , Efendi S
Published: July 2020

Landslide early detection system consists of a sensing system and an alarm system that is not in the same location (remote area). The sensing system is located in a vulnerable area, while the alarm system is placed in a residential area. The sensing system uses sensors found in Plug and Sense from Libelium to read rainfall, soil moisture and soil movement and use a 3G module. The alarm system uses Arduino Uno R3 as a controller and has a Relay and SIM800l module. The installation area of the system depends on the area that has an internet network. From the overall test results, the system successfully measured rainfall, soil moisture, and soil movement. The system also managed to activate an alarm if there is a potential for landslides and successfully sends measurement data to the website. The activation of the alarm system has a delay of about ± 30 seconds. Keywords: Landslide Early Warning, Plug and Sense Smart, 3G, Arduino, Waspmote.
Spatial Modelling to Optimize the Positioning of Air Defense Surveillance Radars with Minimal Shadow Zone
Authors: Wijaya S D R , Bura R O , Prihanto Y
Published: July 2020

Indonesia’s strategic position between two continents and two oceans has resulted in an obligation for Indonesia to be involved in various international cooperation and international conflicts. The declaration of the development of the maritime sector to be the cornerstone of Indonesia’s main strength requires support from the air defense sector. The current condition of Indonesia’s air defense sector, especially the Air Surveillance Radar has not worked optimally resulting in an air defense operation that has not been maximized. The properties of high-frequency electromagnetic waves used in Doppler radar have a straight line of sight. Mountains, hills, and artificial objects/buildings can become obstacles, create blank areas (areas that cannot be covered by radar) behind them, and reduce the performance of the radar coverage. The use of sensing technology, in particular, the geographic information system to determine the position of air surveillance radar placing is an effective solution to optimize the coverage radars exist. The rectangular rule approach method combined with the land surveying technique is a combination of methods that can be used to measure the volume of air defense radar coverage. The level optimization of radar position planning point can be determined by processing the obstacle volume, land slope, earthquake and landslide vulnerability, and land cover conditions into the calculation of the fuzzy inference system technique. This study examines the concept of using Geographic Information Systems to measure the level of radar optimization when placed in a planned position. This research aims to produce a method review on optimizing the performance of air surveillance radar coverage by utilizing remote sensing technology to determine the radar placement position.
SSAM: A Haskell Parallel Programming STM Based Simple Actor Model
Authors: Kim Y , Cheon J , Hur T , Byun S , Woo G
Published: July 2020

As computers with manycore architecture are being widely spread, parallel programming becomes a pending issue. While parallel programming has been a challenging issue, Haskell is known to be of the best available one. The immutability and declarative nature of Haskell suit well the need for parallelism. In our previous work, we implemented the SAM, a parallel programming model based on Haskell. In this paper, we propose the SSAM, an updated version of SAM, by solving the performance overhead of SAM socket. We discuss the architecture of SSAM and its major functions and show the 14% scalability upgrade in a performance test.
Nikkei Stock Market Price Index Prediction Using Machine Learning
Authors: Harahap Lukman A , Lipikorn Rajalida , Kitamoto Asanobu
Published: July 2020

Stock market prediction has always been a difficult process, most of the prediction rely solely on the data of the corresponding stock market. Relationship of gold and oil price with stock market performance has been proven significant in some major world stock index. Prediction of stock market price index using machine learning methods is expected to perform well, with the ability of machine learning method to predict using nonlinear inputs. The methods were commonly able to predict relatively well in predicting the values of Japanese Nikkei 225 and Japanese Nikkei 400 indexes.
Ant Colony Optimization (ACO) Algorithm for Determining The Nearest Route Search in Distribution of Light Food Production
Authors: Fahmi H , Zarlis M , Nababan E B , Sihombing P
Published: July 2020

At this time the development of technology that forces everything must move fast, the efficiency of time becomes a measure of the success of a distribution or production. the continuity of production and the success of production itself is related to distribution. When the distribution fails, production will fail. Indonesian people especially in North Sumatra often consume snacks when free time and snacks are the most consumed food by the Indonesian population until now the production of snacks in Indonesia rose to 50% in 2019, causing the food production to have a concept in timely distribution without experiencing delays in distributing goods that have been produced. One of the expeditions in Indonesia experienced problems in terms of late distribution of goods up to 15-20%, this would have a bad impact on the industry in the future, so to overcome the problems above the application of the ant colony optimization algorithm can help the above problems by placing 4 ants and the ants will spread from point A to point H. In the results of this study, there are 4 ants that move together where the best results are obtained by ant 2, closest to the point H, where the value obtained reaches 0,00015
Prediction of Vocational Students Behaviour using The k-Nearest Neighbor Algorithm
Authors: Nasution Fadliansyah , Muiza Zamzami Elviawaty
Published: July 2020

This article discusses the implementation of the k-NN algorithm in predicting student behavior. The school is a management unit that has data that correlate with students. All student data is stored in an academic information system that can be processed to predict student behavior. One of the data assessing student behavior is in the database of counseling guidance. Some data that will be processed include attendance, lateness notes of problems, teacher responses, tuition payments, broken home. The sample being tested was the data of 100 vocational students from various classes and various majors and divided into two categories. From this experiment, it can be seen that the most accurate K value is the value of K = 1, 3 and 4. The accuracy of the testing data generated is 94.9%.
Analysis of Decision Support Systems on Recommended Sales of the Best Ornamental Plants by Type
Authors: Rusdiyanto R. , Karman Joni , Toyib Hidayat Asep , Muli Peranginangin Adat , Tambunan Frinto , Hutahaean Jeperson
Published: July 2020

The research objective is to recommend the sale of the best ornamental plant species to lovers of ornamental plants by using decision support system techniques. Ornamental plants are a type of ornamental plants that can survive in various conditions. In this case ornamental plants are also very vulnerable to disease such as root rot, shoot rot and others. Many types of ornamental plant sellers do not know how to handle ornamental plants that have diseases or symptoms when they occur. The study was conducted in Simalungun District with a sample of thirteen traders selling ornamental plants using observation and questionnaire distribution techniques. Selection of ornamental plants based on the types in this study include: Orchid Plants (A1), Tulips (A2), Bougenvil (A3) and Jasmine (A4). The assessment criteria used include: Plant height (C1), Plant quality (C2), Plant type (C3) and Plant age (C4). The method used in this research is Simple Additive Weighting. The results showed that Orchid Plant (A1) was the best alternative for selling ornamental plant species (V1: 0.91) and Jasmine (A4) as a second alternative (V2: 0.8).
Feature engineering strategies based on a One-point Crossover for fraud detection on Big Data Analytics
Authors: Soleh M , Djuwitaningrum E R , Ramli M , Indriasari M
Published: July 2020

A wide range of new opportunities for fraudulent online activities has arisen with the growing popularity of online shopping and big data issue. E-payment fraud schemes are collecting billions of dollars from customers, distributors and service providers every year. A lot of machine learning methods for fraud detection problems have been proposed which can be categorized into supervised, unsupervised and semi-supervised methods. In this paper, we proposed biologically inspired technic in the feature engineering phase for handling imbalanced data to increase the total data of a small number of classes by oversampling. One-point crossover used to generate the new data of minority classes. The best algorithm performance obtained to predict the fraud transaction from various machine learning models is Classification and Regression Tree with the corresponding accuracy, precision, recall, and F-1 Score are 96%.
Application of Scrum Maturity Model: A Case Study in a Telecommunication Company
Authors: Setiyawan J , Gunawan F , Raharjo T , Hardian B
Published: July 2020

Digitalization and internet penetration force telecommunication companies to perform a transformation to survive, to face competitions, and to gain opportunities. PT XYZ is a telecommunication company that has introduced a new leaner and agile working method for digital transformation. The organization is undergoing a transformation to implements an agile approach using a scrum framework. There are two divisions that use scrum that currently plagued with time estimation difficulties and inability to create an agile backlog due to the old change request mechanism. Scrum Maturity Assessment (SMM) is used to measure current scrum practice maturity. The data is retrieved using a questionnaire that was given to two Scrum Master from two divisions which have been implementing Scrum. There are 83 questions derived from SMM assessment questions. SMM assessment indicated the scrum practice is Level 1 (Initial). There are 31.76% of scrum practices in IT division and 36.25% of scrum practices in CS division need to be improved to achieve Level 5 Optimizing. In order to achieve Level 5, we proposed 38 steps and six recommendations which will guide the scrum practice improvement process.
An Indonesian Adaptation of the E-Learning Usability Scale
Authors: Hasibuan D P , Santoso H B , Yunita A , Rahmah A
Published: July 2020

This paper investigates how the instruments of E-Learning Usability Scale adapted in the Indonesian context. The need for adapting the original version arises while assessing the usability of e-learning in a higher degree in Indonesia, namely Student-Centered e-Learning Environment or (SCELE). In the process of usability evaluation, a questionnaire is needed. E-learning Usability Scale (EUS), which is created by Sandoval (2016) will be used as the usability scale. However, the EUS was originally built in the English version and it has not been developed in the Indonesian version. Overall, there are five steps to adapt the usability scale to Indonesian culture which are forward translation, synthesis of the translation from the first step, back translation, consulting to the experts, and reliability testing. The results show that Croncbach’s Alpha of the adaptation Indonesian of EUS was 0.922. It can be concluded that the proposed version is reliable to be used by usability researchers. In the future, the adapted version that is proposed in this study is beneficial to help usability researchers, academicians and practitioners in Indonesia while conducting usability testing for e-Learning applications.
Deep Learning approach for predicting the therapeutic usage of Jamu
Authors: Wijaya S H , Saumnuari M , Nasution A K , Ramadhan D A , Hasibuan L S
Published: July 2020

As a country with the largest number of medicinal plants in the world, Indonesian uses medicinal plants as a composition of herbal medicine. The ingredient of herbal medicine is generally made based on experiences and hereditary. This research aims to build a scientific background of Jamu through analysis of the relationship between medicinal plants used as the composition of Jamu and its therapeutic usage. Deep Learning was chosen as a classifier because it shows good effectiveness in generating predictive models in many studies. As a comparison, we also applied the Random Forest and Support Vector Machine as classifiers and examined the classifier performances while predicting the therapeutic usage of Jamu. To handle the imbalanced data between efficacy classes, the Synthetic Minority Oversampling Technique was applied before model generation. The result shows that the highest accuracy for Deep Learning is 88.74%, relatively higher than Random Forest and Support Vector Machine, which obtain accuracy values of 78.84% and 77.60%, respectively. Variable importance of the best prediction model using Deep Learning identified 105 medicinal plants, and 39 of them were selected as potential plants for 14 therapeutic usages.
A comparison of SARIMA and LSTM in forecasting dengue hemorrhagic fever incidence in Jambi, Indonesia
Authors: Khaira U , Utomo P E P , Aryani R , Weni I
Published: July 2020

Dengue Hemorrhagic Fever (DHF) is one of the common and fatal diseases in Indonesia. Jambi city is one of the dengue-endemic areas in Jambi province. To reduce the incidence rate of dengue, an early warning based on forecasting is necessary. Time-series forecasting of DHF can provide useful information to support and help public health officers for planning on DHF prevention. This paper compares two methods for Time-series forecasting of DHF incidence, namely seasonal autoregressive integrated moving average (SARIMA) and Long Short-Term Memory (LSTM). The forecasting performance is assessed using the monthly number of DHF incidence data from January 2012 to April 2019 were acquired from the district health offices. To show the effectiveness of the model, the performances are evaluated based on two metrics: mean absolute error (MAE) and root mean square error (RMSE). In the first analysis, we found that the SARIMA ((1,0,0) (1,0,0)12) is the most suitable model to predict the number of monthly DHF incidence with RMSE value of 30.07 and MAE 18.97, and the second one used the LSTM with one hidden layer (1-64-1) architecture with RMSE of 30.41 and MAE 18.27. Based on the experiment between SARIMA and LSTM perform relatively well to predict the future.
The Development of Self-Service Application at Martabak Air Mancur Restaurant
Authors: Sagala N T M , Andreas  , Putro E
Published: July 2020

The amount of time spent in requesting and waiting for the meal in Martabak Air Mancur restaurant may permanently multiply the number of customers in the line waiting especially during peak hours and on weekend. It will affect the quality service of the restaurant and the loyalty of the customer. From the observation, most of the customers spent a great deal of time making an order when faced with many proportionate choices. The study proposed a system by using self-service technology and the waterfall model. In the beginning, the time needed from making an order to finishing the payment is 15 minutes. The system built can reduce the transaction time to 10 minutes.
Analysis of Euclidean Distance and Manhattan Distance in the K-Means Algorithm for Variations Number of Centroid K
Authors: Suwanda R , Syahputra Z , Zamzami E M
Published: July 2020

K-Means is a clustering algorithm based on a partition where the data only entered into one K cluster, the algorithm determines the number group in the beginning and defines the K centroid. The initial determination of the cluster center is very influential on the results of the clustering process in determining the quality of grouping. Better clustering results are often obtained after several attempts. The manhattan distance matrix method has better performance than the euclidean distance method. The author making the result of conducted testing with variations in the number of centroids (K) with a value of 2,3,4,5,6,7,8,9 and the authors having conclusions where the number of centroids 3 and 4 have a better iteration of values than the number of centroids that increasingly high and low based on the iris dataset.
Analysis of Attribute Reduction Effectiveness on The Naive Bayes Classifier Method
Authors: Syafira D , Suwilo S , Sihombing P
Published: July 2020

Naïve Bayes is a prediction method that contains a simple probabilistic based on the application of the Bayes theorem (Bayes rule) with the assumption that the dependence is substantial. Classification is a technique in data mining to form a model from a predetermined data set. Data mining techniques are the choices that can overcome in solving this problem. Therefore, researchers make a comparison of Naïve Bayes by modifying using PCA. Improving the comparative performance of the Naive Bayes method by weighting using Principal Component Analysis (PCA) and Naive Bayes was carried out in this study. Research conducted on the classification model of Naïve Bayes (PCA + Naïve Bayes) using the Iris dataset that simplified into two attributes, four classes and 147 instances with an accuracy rate of 97.78% with a classification error rate of 2.22%. Meanwhile, the Conventional Naïve Bayes classification model uses four attributes with four classes from the Iris dataset, which has an accuracy rate of 95.45% with a classification error rate of 4.55%. Based on the test results of the classification model, it can be concluded that the success of the PCA can be used as a reference to improve the accuracy performance of the Naïve Bayes classification model.
Analysis of Accuracy Improvement in K-Nearest Neighbor using Principal Component Analysis (PCA)
Authors: Lubis A H , Sihombing P , Nababan E B
Published: July 2020

This research conducted to simplify and eliminate attributes or features that are less relevant without reducing the intent and purpose of the original data using Principal Component Analysis (PCA) to improve the performance (accuracy) of the K-NN (K-Nearest Neighbour) classification method. Modifying the method yields an average accuracy of 88%, where the K value is at K = 3 to K = 9. While the lowest accuracy value generated from K-Nearest Neighbors Conventional with PCA + K-NN classification models for the Pekanbaru Air Quality dataset has an average accuracy of 87% where when the K value is at K = 2, K = 4, K = 6 and K = 8. The highest average error is 0.11% where when the value of K is at K = 2, K = 4, K = 6 and K = 9. While the lowest average error value generated from K-Nearest Neighbors Conventional with PCA + K-NN classification model of the Pekanbaru Air Quality dataset is 0.08% where when the K value was at K = 5.
Utilization of Augmented Reality to Showcase Historical Buildings in Medan City
Authors: Syahputra M F , Umaya A , Rahmat R F
Published: July 2020

Medan is the capital of the province of North Sumatera, Indonesia. Medan city is known as a city that has a lot of old buildings heritage legacy of the former Dutch. It is unfortunate as a result of the lack of maintenance and attention from the government and community making the historic buildings gradually demolished and replaced with new buildings. By using Image-Based-Modelling in the process of making 3D buildings. This application of Augmented Reality Tour is expected to be a recognition media, and can increase the interest in studying history.
Text Classification on Islamic Jurisprudence using Machine Learning Techniques
Authors: Jamal K , Kurniawan R , Batubara A S , Nazri M Z A , Lestari F , Papilo P
Published: July 2020

Indonesia, which is the world’s most populous Muslim-majority nation, Islamic education is not an alternative to secular education but compulsory to any Muslims learn the way of life. The two primary sources of the religion of Islam is the Quran and Hadith. These two are where the majority of the teachings come from. However, when looking for guidance, a Muslim often refers to Islamic scholars to interpret the verses and hadith for them and educate themselves on a topic. However, due to many circumstances, people could not meet and ask a scholar personally regarding Islamic jurisprudence. Chatbot is one of the solutions. Chatbot offers users new opportunities to improve the learning and engagement process, reducing the typical cost of face-to-face consultation. However, to train a chatbot on Islamic Jurisprudence, a text classifier is needed to build a strong knowledge base for the chatbot. This study adopted a standard methodology for building a text classification model. This study used 600 Islamic jurisprudence text data obtained from the books and the web written by an influential Islamic scholar named Ustadz Abdul Somad (UAS). Machine learning algorithms such as Bayesian Network and Naïve Bayes, were employed to classify the text data. Based on the experimental testing results, the Naïve Bayes algorithm is more accurate in all evaluation models, 84.25% using training set, and 76.54% using 10-Fold cross-validation. Meanwhile, the Bayesian Network algorithm is faster in terms of time taken on all evaluation models. Thus, it can be concluded that the text classification model using Naïve Bayes and String to Word Vector filter have the potential to be used effectively but still has plenty of room for improvement.
Optimizationof Municipal Solid Waste Transporter in Batam City using Genetic Algorithm
Authors: Purnajaya A R , Hanggara F D
Published: July 2020

Municipal Solid Waste is an endless problem because as long as life is still running, waste will always be produced. Batamcity shows that there is poor scheduling of transportation of garbage from community settlements to temporary collection points (TPS) to the final disposal site (TPA) of Batam City. The study aims to optimize the number of waste transporters by applying a genetic algorithm. In this study, genetic algorithm can optimize the number of Batam City TPS transporters based on the number of TPS per district, the volume of TPS, and the distance between TPS to TPA. The number of waste transporters available in Batam City in dump trucks, arm rolls, pickups, and motorized pedicabs are 54, 44, 100, and 40 respectively. The result determines the optimization numberof waste transporters with a genetic algorithm succeeded in making the volume gap as small as possible, particularly 15.96% with the target volume of waste transportation and reducing 26.38% of the average gap in the actual volume of waste transportation. In addition, the non-transportable wastevolume optimally by using dump trucks, arm rolls, pickups, and motorized pedicabs is 58.92, 120.21, 346.31, and 380.74 ton respectively.
Developing PC-Based Driving Simulator System for Driver Behavior Analysis Research
Authors: Iqbal Mohammad , Sari Karmila , Ade Sekarwati Kemal , Kemala Putri Dian
Published: July 2020

Driving simulator is one of important system for driving behavior studies. It offers a replicable virtual driving environment and it has possibility to create a various scenarios to carry out in real environment. The problem in development of this simulator is how to reduce a prices in certain point areas have made it possible to create low-cost driving simulators, but with the features that are usually found only in expensive driving simulators. This article is presented a low cost PC-based driving simulator. The aim is to use the simulator as a platform for studies of the driver’s behavior. The complete simulator is using three 27” LED screen, handle by a standard PC, typically used for computer games. As Input we using steering, pedal and shifter G29, with force feedback. For software we using city car home edition as tools to measure validity user and developing simulator to driver’s behavior study.
Implementation of Modified Cheapest Insertion Heuristic on Generating Medan City Tourism Route
Authors: Rachmawati Dian , Wilyanto
Published: July 2020

Arranging the sequence of places to visit is the common problem that tourists or foreigners encountered when visiting a new site, especially for foreigners that visit Medan City. This kind of case similar to Traveling Salesman Problem cases. Therefore we could use one of the modified TSP algorithm to solve it, which is Modified Cheapest Insertion Heuristics. The Modified Cheapest Insertion is a method to insert the cheapest weight starting from 2 points of place until all of the sites are being connected from the starting point until the endpoint. The strength of Modified Cheapest Insertion Heuristics is the calculation will remain stable even for a large number of inputs. In this research, all of the desired-to-visit places are being connected as a route.
Chatbot Implementation with Semantic Technology for Drugs Information Searching System
Authors: Amalia A , Sipahutar P Y C , Elviwani E , Purnamasari F
Published: July 2020

This research aims to design medicine information based on the ontology scheme and to display the relationship between information through chatbot as search media. The diversity of information does not guarantee to gather a relevant search result with user’s needs. A conventional search engine would be substantially beneficial in information searching yet could not able to comprehend meaning of found information and its relationship with other information. However a machine could understand the relationship and the meaning of information through the implementation of semantic technology, which is ontology. Ontology is implemented to represent semantic metadata information. The information designed with the ontology model would be very assistive in searching for data which is relevant to users’ need. The result of implementing ontology as a knowledge base in this research able to display the information of a disease and its relationship with medicine used as the medication for such a particular disease. The evaluation of our system shows that 90% of queries from users generate a valid response from the chatbot. Therefore, this research could be used as a reference in search of medical information and describe its relationship with a particular disease or related to medicine.
Network Fault Effectiveness and Implementation at Service Industry in Indonesia
Authors: Lubis Fahrurrozi , Lubis Muharman
Published: July 2020

The efficiency of network administrators have been decreased concurrently due to complexity and heterogeneous of network built in certain environment of company. Actually, large heterogeneous network has created a crisis and conflict for many organizations. Available network tools and solutions are not only expensive but also difficult to install, configure, manage and maintain. This paper discusses the implementation of network fault in the service industry to match with the expectations of stakeholders to be able to achieve the higher efficiency and to carry out proactive processes although the practical truth is often the opposite way.
Internet Provider Service Value Delivery Index Problem: Case Study of the NetHost
Authors: Lubis Fahrurrozi , Lubis Muharman
Published: July 2020

Common problems in service delivery is might related to the issue of timing, marketing cost, user experience, generating lead, identifying prospect, forecasting demand, value proposition, security, privacy, identity management and many more. Unfortunately, company often decided on the wrong context and concept lead to misrepresentation and misinterpretation on the requirement for the service improvement. Thus, the direct intervention through certain criteria in the characteristics and attribute of service delivery should be conducted with judgment assessment. It is done in order to identify the target and examine the policy used to support the outcomes. Thus, this study explore the model used for particular company, which in this case NetHost to provide insights on how the assessment can be fruitful in the long term investment for intangible aspects of service delivery.