bluuebunny/crossref_metadata_2025_split huggingface dataset:
Accuracy Level of Backpropagation Algorithm to Predict Livestock Population of Simalungun Regency in Indonesia
Authors: Purba Indri Sriwahyuni , Wanto Anjar , Riansah Reza Muhammad , Ahmad Yogi , Siregar Sandy Putra , Winanjaya Riki , Julham Mhd. , Silitonga Hotmalina 
Published: September 2019

Abstract
The development of livestock agribusiness includes all activities that begin with the procurement and regulation of production and marketing suggestions. With the many types of livestock found in Simalungun Regency, Indonesia should be able to increase the potential for livestock agribusiness development. In this study, the authors will analyze the best architecture that can be used to predict the number of livestock populations according to the type of livestock in Simalungun District Indonesia so that certain parties can make improvements to the development of livestock agribusiness in Simalungun District Indonesia. In this study, there are five 5 architectural models namely, 3-5-1 architecture, 3-6-1, 3-7-1, 3-8-1, and 3-9-1. Of the five architectural models, the best architectural model is 3-7-1 with 75% accuracy and 1693 epoch. While the error rate is 0.001-0.01. It is expected that this architectural model can help academics in the process of predicting the number of livestock populations in Simalungun Regency in the coming year.
ANN: Prediction of Per Capita Income Rural Community on Poverty Line Based on Province
Authors: Solikhun  , Wahyudi Mochamad , Safii M. , Efendi Syahril , Ramadhani Suci , Yunefri Yogi , Zamsuri Ahmad 
Published: September 2019

AbstractThe problem of poverty is a fundamental problem that is of concern to every country. The Indonesian state has established a poverty reduction program as the main program. Poverty occurs in urban and rural communities. This research raises the problem of poverty in rural communities. The contribution of research to the government is to predict the per capita income of rural communities according to the poverty line based on the future provinces. The data used is data from the National Statistics Agency. These data are 2015 semester 1 data up to 2018 semester 1. The algorithm for its completion uses the artificial neural network backpropagation method. Input data is 2015 data for the 1 to 2017 semester 2. The training and testing architecture model is 4, namely 6-2-1, 6-3-1, 6-2-3-1, and 6-3-2-1. Target data is 2018 semester 1 data. The best architectural model is 6-2-1 with 79 epoch, MSE 0,004801 and 100% accuracy rate. From this model, a prediction of rural income per capita in the poverty line is based on the provinces of each province in Indonesia.
A Framework for Sharing Patient Data and Service Facilities Using Ipv6 Technology to Support the Advancement of Smart Health Care Technologies
Authors: Pardede A M H , Mawengkang H , Zarlis M , Tulus T , Buaton R , Maulita Y , Fauzi A , Novriyenni N , Kadim L A N , Jamaluddin J 
Published: September 2019

Abstract
To improve patient care requires intelligent and better Health Care, where it collaboration between many people is needed and resources. The use of data together by each agency needs to be done, to avoid repetition when doing data entry. In smart hospitals patient data can be received in real-time at various offices in smart hospitals or even smart hospitals in villages and towns. Medical technicians, nurses, and doctors and patients can also have access to test data without losing time in physically transferring the same information from different hospitals to another hospital. Implementation of IPV6 as a tool for the numbering of regional region and region class of hospital services, where the type of hospital in Indonesia itself consists of 5 classes of hospitals. The results in this research are IPV6 can be applied to patients who provide location information, which is integrated with the patient’s social media or can be tracked using GPS, patients will be very helpful in utilizing better hospital service facilities, the patient data in a shared database can be assessed jointly by the authorized party, in this case the hospital or the doctor handling of the patient is referred to and can be done more optimally.
Smart Fishing Vessel Monitoring for Handling of Illegal Fishing in the EEZ Of Indonesia Using WSN TDMA
Authors: Sulindawaty  , Mawengkang Herman , Zarlis Muhammad , Effendi Syahril , Zendrato Niskarto , Fahmi Hasanul , Ikhsan Muhammad 
Published: September 2019

Abstract
Illegal fishing which until today is still a very serious attention by the government due to resource depletion can lead to fish in the EEZ of Indonesia. It was due to conduct surveillance in Indonesian waters is difficult where Indonesia is an archipelago with a lot of beaches. Wireless Sensor Network (WSN) used for monitoring, tracking and controlling short distance and long distance. Wireless Sensor Network The randomized in a particular region to get comprehensive information. However, namely the possibility of data collision will occur in the data transmission process if performed simultaneously. So the application of methods of TDMA (Time Division Multiple Access) as a channel access method for networks together, allowing users to be able to share signals with time slots that are not the same in sharing the same frequency channel. Smart fishing Vessel Monitoring function for handling the problem of illegal fishing, where the latter any fishing vessels will be monitored from the location, the number of crew, cargo and fishing licenses.
A Comparative Study of Data Mining Methods to Diagnose Cervical Cancer
Authors: Sagala Noviyanti T M 
Published: September 2019

Abstract
Cervical cancer becomes a major cause of cancer deaths in women around the world. The objective of this study is to provide a comprehensive analysis of different data mining methods to diagnose the malignant cancer samples. Different data mining algorithms (SVM, Naïve Bayes, and KNN) has been applied on four different medical tests (Biopsy, Cytology, Hinselmann, and Schiller) as four different target variables. The attributes influence the disease most is extracted since the disease has no symptoms in the early stage. The extraction involved over 32 attributes and two different algorithms such as Correlation-based Filter (CFS) and Random Forest. The results showed that the performance of Naïve Bayes classifier outperforms other classifiers after evaluation using 10-fold cross-validation method in R environment. In addition, the use of attribute selection has been proved not only can select the highly important attributes but also to increase the performance of all classifiers on cervical cancer dataset. In this study, the work reveals the classifiers can effectively achieve the best performance with the least number of highly important attributes.
Analysis Of c4.5 and ID3 Methods in Determining Student Graduation
Authors: Qowidho Titin , Zarlis M , Nababan Erna Budhiarti , Agusnady Alfian , Sembiring Berti Sari 
Published: September 2019

Abstract
From the performance measurement of the two algorithms that have been done based on the amount of data, it can be concluded that ID3 algorithm has better performance (precision, recall, and accuracy) than C4.5 algorithm. The performance measurement of the two algorithms based on the number of attributes indicates that the ID3 algorithm has better performance (precision, recall, and accuracy) than the C4.5 algorithm. Overall, From the experiments that have been carried out it can be concluded that ID3 has a better performance than C4.5 algorithm. Performance measurement of a data mining algorithm can be done based on several criteria such as accuracy of prediction, speed / efficiency, reliability, scalability and interpretation. In this study the authors suggest using the ID3 algorithm method.
The Effect of Plaintext Length on Round Trip Time With Client Server Based Advanced Encryption Standard (AES) Algorithm
Authors: Agusnady Alfian , Sitompul Opim Salim , Tulus T , Sembiring Berti Sari , Qowidho Titin 
Published: September 2019

Abstract
The length of the plaintext affects the round trip time, where the longer the plaintext, the longer round trip time. In an attempt of 35 plaintext characters obtained 1.171 ms round trip time. Whereas on an attempt of 113 plaintext characters obtained 2.355 ms round trip time. In Figure 2 can be seen the graph increase of the round trip time. The author concludes that the length of the plaintext affects the round trip time in the client server based AES algorithm. The longer the plaintext, the longer the round trip time process will run.
Implementation of Bayesian Regulation Algorithm for Estimation of Production Index Level Micro and Small Industry
Authors: Afriliansyah Teuku , Parulian Parulian , Ulva Ananda Faridhatul , Simanjuntak Marthin Yohannes , Wanto Anjar , Sihombing Danny , Sutanto Agus , Ginantra NLWSR 
Published: September 2019

Abstract
Small Industry is an industrial company whose workforce consists of 5-19 people. While the Micro Industry is an industrial company whose workforce consists of 1-4 people. The purpose of this study is to estimate the Production Index of Micro and Small Industries according to KBLI for years to come. KBLI is a reference classification used to classify Indonesian economic activities/activities into several business fields/business fields that are distinguished based on the type of economic activity that produces products/outputs in the form of goods and services. In this study, the estimation method used is the Bayesian Regulation Algorithm. This algorithm is one of the Artificial Neural Networks algorithms that can solve many estimation problems by building a trained model and showing good performance. The data to be estimated in this study are data of Micro and Small Industry Production Index according to KBLI processed from the Central Board Statistics of Indonesia. This study uses 3 architectural models, namely: 5-10-20-1, 5-15-30-1 and 5-20-40-1. The best architectural model is 5-10-20-1, resulting in 83% accuracy, MSE 0.0031434897 with a minimum error of 0.001 - 0.05.
Naive Bayes Algorithm Analysis to Determine the Percentage Level of visitors the Most Dominant Zoo Visit by Age Category
Authors: Parlina Iin , Yusuf Arnol M. , Febriati Nur Ahlina , Dewi Rafiqa , Wanto Anjar , Lubis Muhammad Ridwan , Susiani  
Published: September 2019

Abstract
Classification is a method of data analysis that is used to create models that describe data classes that are considered important. For the classification of the classification process, the data used is THPS Visitor data which consists of 4 classes including Education, Gender, Age and Visit. The classification used as a comparison of results is the Naive Bayes Classifier. By classifying the number of visitors who are most dominant visiting by age category consisting of adults, adolescents and children. This study aims to classify the highest number of values for visitors by age category. This study was reviewed using the Naive Bayes algorithm. The results of this study indicate that the visitor data that is the most dominant visiting by age category is children who have 77% accuracy is the age of children. This accuracy value is the age that most often visits THPS.
Analysis of Artificial Neural Networks Method Backpropagation to Improve the Understanding Student in Algorithm and Programming
Authors: Lubis Muhammad Ridwan , Saputra Widodo , Wanto Anjar , Andani Sundari Retno , Poningsih P. 
Published: September 2019

AbstractTo Improve the student skills in learning is constitute hope of every lecturer. For/In computer base-study programme master of programming is needed. the Algorithms and Programming are basic course that must be studied. Mean while/that for, using the backpropogation methods which is part of the Artificial Neural Networks will test and train data by using the backpropogation algorithm to improve students ability to understand the subject. The result obteined can be analyzed about the results if the output is that the closed to the target then the trainning process can be finished. Furthermore/Hereafter, The average error can be calcutate obteined from the result of the trainning that has been carried out. If the results have not reached then the backpropagation method always do iteration with make to update weignt until maximal output and can to get output of exelent with used backpropagation method.
Analysis of Sequential Order Incremental Methods in Predicting the Number of Victims Affected by Disasters
Authors: Parulian Parulian , Tinambunan Medi Hermanto , Ginting Salomo , Khalil Gibran M. , Wanto Anjar , Muharram La Ode , Nurmawati N , Bhawika Gita Widi 
Published: September 2019

Abstract
Disaster is a series of events that threaten and disrupt human life caused by natural factors, non-natural factors and human factors themselves. Therefore, disasters cause casualties, environmental damage, property losses, and psychological impacts. In this study will be discussed about the prediction of the number of victims affected by the disaster, either died, lost, injured, suffered or displaced. Data sources were obtained by the National Disaster Management Agency and the Indonesian Central Statistics Agency. The method used to predict is the Incremental Sequential Order method. This method is one part of the Artificial Neural Network method. With this method, network architecture patterns will be established to predict the number of victims affected by the disaster for years to come. The network architecture models used are 4-5-1, 4-10-1, 4-5-10-1, 4-10-20-1 and 4-15-30-1. Of the five models, the best models will be obtained, namely 4-15-30-1 with an accuracy rate of 80%. With this architectural model, predictions will be made on the number of victims affected by the disaster for years to come.
Message Security Implementation by Using a Combination of Hill Cipher Method and Pixel Value Differencing Method in Mozilla Thunderbird Email Client
Authors: Siregar B , Gunawan H , Budiman MA , Sulindawaty  
Published: September 2019

Abstract
One of the problems in this field of communication is the insecurity of messages sent across computer networks. Even though sometimes the contents of a message can be something that is sensitive and prone to abuse. One method that can be used to overcome this problem is by using a combination of cryptography and steganography. In this research, an add-on menu for Mozilla application was developed to secure messages to be sent via e-mail using Hill Cipher’s cryptographic method on messages and insert them using steganographic pixel value differencing method on image files to be extracted and returned to the form originally. The results of this study indicate that with experiments using messages with length and image file extensions that are also different, namely. bmp, .jpg, .png, and .gif can insert the initial message into the image file and be returned to its original form with a maximum length limit message 1000 characters and no manipulation of the image file from the insertion message.
Predict Foreign Exchange Revenue from CPO Commodity Exports Using Backpropagation Neural Network
Authors: Siregar B , Sitompul OS , Prayitno OZ , Sulindawaty  
Published: September 2019

Abstract
Export of CPO and its derivative products is one of the biggest revenues for Indonesian foreign exchange. Through this research, predictions of foreign exchange earnings from CPO exports are made using backpropagation artificial neural networks. The data used in the form of export data for the period September 2013 to December 2016. The final results of this research using epoch 10000, learning rate 0.2, and hidden layer 10.
Determining the Common Set of Weight in Data Envelopment Analysis with Linear Programs
Authors: Sirait Donna N. M. , Efendi Syahril , Sawaluddin  
Published: September 2019

Abstract
Data Envelopmemt Analysis (DEA) serves to assess efficiency in the use of resources (input) to achieve results (output) whose purpose is to maximize efficiency. DEA was first introduced by Charnes, Cooper dan Rhodes in 1978. DEA is a nonparametric approach which is basically the development of Linear Programming (LP). The characteristic of DEA CCR model is that it allows the DMU to measure the maximum efficiency value with the most favorable weight. The efficiency of the DMU obtained differs from the different sets of weight may not be comparable and rank on the same basis. In DEA model optional sets of input weight and output weight are usually assumed to represent the DMU that is considered the best to compare with all DMUs. This set of weights is usually different for each DMU. In this journal to determine the set of weights in the DEA is performed with a linear programs. After the linear program is determined, the value of the output weight and input weight is solved using the software POM-QM for Windows.
Monitoring System Volume of Crude Palm Oil on Vertical Tank Using Ultrasonic Sensor and Solenoid Valve
Authors: Siregar B , Hizriadi A , Faizal MR , Sulindawaty  
Published: September 2019

Abstract
During this time to find out the volume of Crude Palm Oil (CPO) in the palm oil mill, it was monitored every day on the vertical tank manually using a sounding meter. Monitoring data taken manually is less accurate and requires more time and manpower. So that this weak monitoring data can cause losses if there is oil loss in the tank. Therefore, research aims to help control vertical tanks and can detect any loss of CPO that can harm the company. This research uses data obtained by an ultrasonic sensor connected to a microcontroller and installed solenoid valve on the tank discharge faucet. Data received by the microcontroller is then sent to the server and then stored in the database to be retrieved visually on the monitoring system dashboard. The test results show that the system built can facilitate monitoring of CPO volume in vertical tanks.
Implementation of ANN for Predicting the Percentage of Illiteracy in Indonesia by Age Group
Authors: Bhawika Gita Widi , Purwantoro P , Achmad Daengs GS , Sudrajat Dadang , Rahman Arrafiqur , Makmur M , Rohmah Rina Ari , Wanto Anjar 
Published: September 2019

Abstract
Illiteracy is one of the serious problems experienced by Indonesia. The lack of care from the government and the private sector towards illiterate people makes the illiteracy rate quite high. Because of this, this problem must be one of the government’s targets going forward, because directly or indirectly illiteracy plays a role in increasing the number of poverty in Indonesia. The purpose of this study is to predict the percentage of the illiterate population in Indonesia according to the age group 15-44 years because this age group category is a productive age. The results of this prediction are expected to be a reference and benchmark for the government in determining and making policies to reduce illiteracy rates. The data that will be predicted is the illiteracy rate data for each province in Indonesia sourced from the Indonesian Central Bureau of Statistics from 2011 to 2017. The method used for prediction is Backpropagation Artificial Neural Network. Data analysis and calculation were carried out with the help of Matlab and Microsoft Excel software. This study uses 5 architectures, 4-5-1, 4-6-1, 4-9-1, 4-14-1 and 4-18-1. Of the five models, the best network architecture is 4-14-1 with an accuracy rate of 91% and the Mean Squared Error 0.00274166. Using this 4-14-1 network model, a prediction on the percentage of illiteracy in Indonesia will be calculated for 2018 until 2020.
On Hamming index generated by adjacency matrix of graphs
Authors: Ali Safri , Suwilo Saib , Mardiningsih  
Published: September 2019

Abstract
Let G be a finite simple graph and A be the adjacency matrix of G. Then each row of A is a bit string of finite length. Hamming distance between any two rows of A is defined to be the number of positions with different digit. For any two vertices vi
and vj
in graph G we define Hamming distance, generated the adjacency matrix A, between vi
and vj
as the Hamming distance between rows of A corresponding to the vertices vi
and vj
. The Hamming index of the graph G is the sum of Hamming distances over all distinct pairs of vertices vi
and vj
in G. This paper discuss Hamming index of finite simple graphs. We present a formula for Hamming index of graphs in terms of known parameters of the graph namely the number of vertices, the number of edges and the degree of each vertex. We then apply the formula to determine the Hamming index for some graph operations.
Fuzzy Controller for Solar Cell Optimization
Authors: Azmi Zulfian , Mawengkang Herman , Zarlis Muhammad , Tulus  , Efendi Syahril 
Published: September 2019

Abstract
This study describes the Fuzzy Logic Control for the movement of Solar Cells that use fuzzy logic algorithms to achieve intelligent and flexible knowledge-based systems in the design of hardware to achieve efficiency in controlling the movement of solar cells that are better and maximize the function of the solar cell motor works based on time input. Fuzzy Logic allows mapping from the input given based on time to an output. involves components of variables, membership functions, Fuzzy Logic operators and if-then rules. And with an analysis it can produce optimum output of Solar cell rotation.
Evaluation of Maturity Level of Information and Communication Technology (ICT) Governance with CobIT 5.0 Case Study: STMIK Pelita Nusantara Medan
Authors: Sihotang Hengki Tamando , Zarlis M , Efendi Syahril , Jollyta Deny , Husain  
Published: September 2019

Abstract
In entering competition the quality and predicate best the national and the quality of graduates, college trying to use information technology as an instrument for might win this competition. That IT can be used to fulfill and support the system in college, it needs assessment from information technology regularly. One method of conducting evaluation of the performance of the department of information technology is to use the framework Cobit 5 as yardstick efficiency in the use of information technology currently consisting of 5 (five) domain namely: EDM, APO, DSS, MEA A measuring instrument his as. With this method, researchers trying to make it a blueprint as the end result of utilization of information technology in college, so the management can plan exactly how of development of information technologies company to the next few years. An evaluation, known level capabilities inside the area mea and APO is entirely located at the level of 1 (performed) with the level of the target to be achieved is the level of 3 (established). Weakness governance information technology in STMIK Pelita Nusantara Medan is the lack of formalization rules and procedures management information technology. To reduce the gap between capability the current level was level and capability to be achieved, so STMIK Pelita Nusantara Medan must meet PA2.1, PA2.2, PA3.1 and PA3.2, that capability the current level was that is at the level of 1 could rise to the level of 3. Along with that, STMIK Pelita Nusantara Medan moved closer to the purpose..