bluuebunny/crossref_metadata_2025_split huggingface dataset:
A hybrid tool-path with no pause generation algorithm for 3D printing
Authors: Zhang YU , Li Haochen , Wang Tongcai , Liu Bingshan , Wang Gong 
Published: February 2021

Abstract
With the development of the manufacturing industry, 3D printing has gradually become a focus of attention due to its unique advantages such as fast speed and low threshold. As an important part of the printing process, scanning path planning directly affects the quality of the molded part. Based on the existing path research, this paper proposes a new filling algorithm, which uses the idea of Fermat spiral to achieve continuous filling, and the contour offset, partition and some unfilled areas are optimized respectively. Finally, the new algorithm is tested on common graphics to prove its superiority.
Resource Allocation Algorithm for Physical Layer of Broadband Power Line Carrier Communication Applied to Electric Internet of Things
Authors: Yin Xiyang , Yan Long , Lv Guoyuan 
Published: February 2021

Abstract
Broadband power line carrier communication adopts adaptive orthogonal frequency division multiplexing OFDM technology to effectively increase the communication rate, and provides ample communication resource guarantee for the realization of power multiservice applications. Aiming at the problem of broadband power line carrier communication resource allocation, this paper proposes a low-complexity physical layer resource allocation algorithm. First, based on the equal power allocation method, the set of subcarriers required by each user to meet their minimum rate requirements is determined, and the multi-user resource allocation problem is reduced to a single-user optimal power allocation problem, and then the Lagrange multiplier method is used to optimize the power of the sub-carrier set used by each user to further improve the system throughput. Experiments show that the algorithm in this paper has higher throughput and can meet the minimum rate requirements of more users.
Estimation Method of Line Loss Rate in Low Voltage Area Based on Mean Shift Clustering and BP Neural Network
Authors: Tan Huang , Li Yuan , Yu Liang , Liu Jing , Ni Linna , Diao Xinping 
Published: February 2021

Abstract
The main problems faced in the line loss management of the distribution network are the incomplete meter configuration, the difficulty of collecting operating data, and the excessive number of components and nodes. These problems lead to a very complicated calculation of line loss rate. This paper proposes an improved BP neural network estimation method for passive low voltage area line loss rate driven by low voltage area characteristic data, and realizes it through programming. First, the characteristic data required for calculating the line loss rate of the low-voltage passive station area is selected and classified according to the station area capacity after standardization. The BP neural network model improved by Mean Shift clustering method is used to calculate the line loss rate for the station area data of the same capacity, which provides scientific basis and data support for the calculation of the station area line loss rate and the management of high-loss stations in the future. A passive low-voltage station with a capacity of 315KVA in Zhejiang Province was used as the modeling object to perform simulation calculations to verify the accuracy of the proposed method.
Sufficient Context for Real-Time Semantic Segmentation
Authors: Fan Borui , Wu Wei 
Published: February 2021

Abstract
In recent years, the research on semantic segmentation has progressed rapidly, and many segmentation models with good effects have emerged, but these models often require a large amount of parameters. In actual application scenarios, the computing resources and memory of the device are limited, so the research on lightweight real-time semantic segmentation has very important practical significance. In this paper, we propose SDSNet, which is mainly composed of SDS module that includes some SDS-units. SDS unit is based on split-shuffle and dilated convolution, which can get sufficient context by increasing the interaction capability between channels and expanding the receptive field without increasing the amount of calculation.Our network combines the high feature generated by the SDS module with low-level spatial information, yielding a perfect segmentation results. Experiments on CityScapes prove that the proposed SDSNet achieved a comparable result to the state-of-the-art models.
PMSM parameter identification based on improved PSO
Authors: Li Zongwei , Chen Dongdong , Chen Ying , Lei Hongdan , Zhu Hongguan 
Published: February 2021

Abstract
The results of the standard PSO algorithm are easy to fluctuate and the time-varying error is too large. By introducing the strategy of Gaussian decline and Gaussian disturbance, an improved PSO motor parameter identification method is proposed. When the motor parameters change, the improved PSO method can be used to identify the motor parameters faster, more accurate and more stable. The simulation results show that the improved PSO overcomes the recognition results of the standard PSO and improves its recognition accuracy.
Effect of Different Solvents On The Phytochemical Compounds of Sargassum sp. From Yogyakarta and East Nusa Tenggara
Authors: Herawati Dheasy , Pudjiastuti Pratiwi 
Published: February 2021

Abstract

Sargassum sp. is one of the brown algae species. Two species of Sargassum were collected from Deere coast, Alor East Nusa Tenggara (NTT), and Krokoh beach, Gunung Kidul Yogyakarta. This paper compares the phytochemical screening of two species of Sargassum sp. by using three different polarity solvents. The two species of Sargassum sp. were dried, cut, and ground into powder. Their species were extracted successive using ethanol, ethyl acetate, and n-hexane. Phytochemical screening all of the extracts of Sargassum sp were performed with the spot tests as the standard methods. The ethanol extracts of Sargassum sp. from Yogyakarta and NTT showed the presence of saponins, tannins, terpenoids/steroids, and flavonoids. The ethyl acetate and n-hexane extract from the two species of Sargassum sp. have contents of tannins, terpenoids/steroids, and flavonoids. Tannins and terpenoids/steroids were major compounds in ethyl acetate extract both Sargassum sp. from Yogyakarta and NTT. Results showed that different solvents possibly different phytochemical compounds. Phytochemical of seaweed is influenced by species, habitat, isolation method, and harvest season.
Forecasting Unemployment in North Sumatra Using Double Exponential Smoothing Method
Authors: Syafwan Havid , Syafwan Mahdhivan , Syafwan Elvathna , Hadi Aulia Fitrul , Putri Pristiyanilicia 
Published: February 2021

Abstract
The reseach aims to predict the unemployment in the province of North Sumatra in 2020 using the Double Exponential Smoothing (DES) method. The data used is derived from the Central Agency Statistik (BPS) of North Sumatra province where the actual data is taken within 20 years from 2000 to 2019. The accuracy method in this research uses MAD to count the number of errors, MSE to evaluate forecasting methods, and MAPE to calculate the percentage of errors. Results of this research in the form of forecasting the number of unemployment in North Sumatra in 2020 that is 381459 people in the value of alpha 0.6 with a MAD value of 77402.12, MSE value of 12524690448.31, and MAPE value of 16.35%.
Employee Performance Analysis using Analytical Hierarchy Process and Weighted Product Combinations Algorithm
Authors: Agus Raja Tama Andri , Sembiring Muhammad Ardiansyah , Sibuea Mustika Fitri Larasati , Mardalius  , Nata Andri 
Published: February 2021

AbstractOne of the efforts to improve employee performance is through giving gifts to employees who have good loyalty and performance. Decision making to determine the best employees can be done by the company by assessing the performance that has been done by its employees within a certain period. Employee performance evaluation at Azaria Café & Resto is influenced by several criteria, namely cleanliness, hospitality, accary, equipment maintenance, product quality, speed. The purpose of this study is to combine AHP and weighted product methods to determine the priority of the award recipient employees. The method used in this research is AHP (Analytical Hierarchy Process). Through AHP, priority criteria will be assessed that will be used in alternative dating. The calculation of the AHP method gives the result that is the order of importance of the best criteria and recommendations of employees with an accuracy rate of 96.2%, where the order of the most important criteria starts from product quality, cleanliness, accreditation, equipment maintenance, speed, and hospitality. And employees who were recommended as the best employees using weighted Product method (WP) for Azaria Café & Resto is an employee with high value, Arif (27.4%).
Application of data mining techniques using the K-Means Method on Unmet Need of Health Services by Province in Indonesia
Authors: Wahidin W , Mugihartadi M , Aviani Tri Hasanah Bimastari , Pratiwi Heny , Wijaya Yusup Indra , Andie A , Windarto Agus Perdana , Waluyo Ari 
Published: February 2021

Abstract
The research objective is to cluster the Unmet Need of health services in Indonesia by region by utilizing data mining techniques. The data source was obtained from the Central Statistics Agency (abbreviated BPS) in the health category using Unmet Need data on health services by province (2015-2018) consisting of 34 data records. The variable used is the Unmet Need of health services by province (percent). The data mining technique used is k-means which is part of clustering. Data processing is performed using RapidMiner 5.3 software. The cluster labels used in the study are high cluster (C1) and low cluster (C2). The results state that the application of k-means can be carried out where 9 provinces are in cluster C1 consisting of Riau, West Nusa Tenggara, East Nusa Tenggara, Central Kalimantan, South Borneo, Central Sulawesi, Southeast Sulawesi, Gorontalo and West Sulawesi with final centroids (C ) = 6.96 and 25 provinces are in cluster C2 with final centroid (C) = 4.36. The results of mapping in the form of regional clusters can provide information for the government and should Unmet Need health services in Indonesia must be worth 0% for each region.
Application of the Simple Multi Attribute Rating Technique (SMART) Method in the selection of thrush medicine products based on consumers
Authors: Darmowiyono Mulyanto , Yuliyanto Wakhid , Purnomo Kardianto Indra , Marlini Wenny , Pratiwi Heny , Windarto Agus Perdana , Wijaya Harma Oktafia Lingga 
Published: February 2021

Abstract
The purpose of the research is to analyze marketing strategies in the selection of Mouth sores products based on consumers. The data source was obtained by observing, interviewing and giving questionnaires to 375 respondents randomly by using Google Form. The output of the research is the ranking of Mouth sores products. The technique used is utilizing one of the decision support system methods, namely Simple Multi Attribute Rating Technique (SMART) in providing recommendations for results. The alternative thrush medicine products that are used are: Adem Sari (A1), Jesscool (A2), Alangsari (A3), Larutan Penyegar cap Kaki Tiga (A4) and Larutan Penyegar cap Badak (A5). The rating criteria given are Composition (C1), Packaging (C2), Taste (C3), Price (C4) and How to use (C5). The results of the SMART method calculation give the first recommendation is Alangsari (A3) with a final value = 0.84 and Jesscool (A2) as the second recommendation with a final value = 0.45.
Clustering of Public Opinion on Natural Disasters in Indonesia Using DBSCAN and K-Medoids Algorithms
Authors: Mustakim  , Fauzi Muhammad Zakiy , Mustafa  , Abdullah Assyari , Rohayati  
Published: February 2021

Abstract
Natural disasters are disasters caused by events or series of events caused by nature such as earthquakes, tsunamis, volcanic eruptions, floods, tornadoes, and landslides. Some of these natural disasters have taken a lot of public attention, from empathy, sadness and criticism that form an opinion on social media. One of the most popular social media used by the public is Twitter. Opinions written by Twitter users are called tweets. A collection of tweets can be processed to obtain information by using data mining techniques namely Text Mining. In this study, the Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm and K-Medoids were used. The result of this study shows that DBSCAN is the best algorithm because it has the Silhouette Index (SI) validity of 0.9140 and the average execution time in RapidMiner Studio is 83.40 seconds. Meanwhile, the K-Medoids algorithm has a Silhouette Index (SI) validity of 0.2259 and an average execution time in RapidMiner Studio 849.93 seconds. The frequency of the word “earthquake” dominates for the positive category, the word “disaster” dominates the negative category, and the word “flood and earthquake” dominates the negative category.
Analysis of Decision Support System with Analytical Hierarchy Process Method
Authors: Adnan Ahmad Zaelani , Holili Moh. Hidayatul , Indrawan Bisma , Wahyuningsih Sri , Prasastono Sri Heneng , Windarto Agus Perdana , Waluyo Ari 
Published: February 2021

Abstract
Many factors can increase work motivation besides income and profits. The leadership style in a company also greatly influences work motivation in the work environment. This study aims to analyze the leadership style that most influences work motivation by utilizing decision support systems (DSS) techniques. Sources of data were obtained by observing, interviewing and giving random questionnaires at the Tirtauli regional water company (PDAM) in Pematangsiantar. The DSS technique uses the Analytical Hierarchy Process (AHP) method. The criterion variables used in the study were Directing Style (K1), Participation Style (K2), Supporting Style (K3), Achievement Style (K4) and Delegation Style (K5). The results of the AHP method analysis show that the most influential leadership style in motivating work is the delegation style of a leader (K5) with a final value of 0.6326 and a directing style (K1) with a final value of 0.4861. The results of the research can be used as input to the leader in applying a leadership style so as to increase motivation in the work environment to achieve company goals.
The Implementation of Probabilistic Neural Network Algorithm for Classification of Family Hope Program in Pekanbaru City
Authors: Novita Rice , Anzir Qumfa , Mustakim  , Alhidayatillah Nur , suriani Julis 
Published: February 2021

Abstract
The poverty rate in Indonesia continues to increase, especially in Pekanbaru city. It was recorded in 2017 the poverty in Pekanbaru City reached 176.908 inhabitants. The poverty can be seen from the Education Factor, Economic Factor, Health Factor and Infrastructure Factor. This aim of this study is to classify beneficiary of poverty from education and health factors using the PNN Algorithm. The criteria used for the classification of education classes and health classes include elementary, junior high, high school, toddlers and pregnant women. The data used in this study were from the Harapan family program in Pekanbaru City. In clustering training data and test data, K-Means Algorithm was used. The results of the clustering are 3,543 test data and 1,520 testing data with DBI value of 0.194 and the result of calculation of Probabilistic Neural Network algorithm with accuracy value is 99.07%. In testing the algorithm using the confucion matrix method, the recall value is 99.30% and the precision value is 97.81%. The high level of health and education is an important factor in the development and progress of an area.
Application of Analytical Hierarchy Process Method for SQM on Customer Satisfaction
Authors: Yusuf Ramayani , Damayanti Fenny , Purnomo P , Suryana Aep Tata , Kartikaningsih Dewi , Windarto Agus Perdana , Waluyo Ari 
Published: February 2021

Abstract
The research objective was to analyze service quality management on customer satisfaction by utilizing decision support system (DSS) techniques in the completion process. The research data source is the Regional Drinking Water Company (abbreviated as PDAM) “Tirtauli” in Pematangsiantar city. The object of the research is the customers / users of PDAM services which are carried out by means of random observations and questionnaires. The DSS technique used is the analytic hierarchy process (AHP) method. The result of the method is a recommendation in the form of a ranking of service quality management on customer satisfaction. The criteria used to measure customer satisfaction in research are physical evidence (K1), reliability (K2), responsiveness (K3), assurance (K4), care (K5). The calculation results of the AHP method state that two very influential criteria in improving service quality management on customer satisfaction are assurance (K4) with a final value of 0.1929 and reliability (K2) with a final value of 0.1912. The results of the research are expected to provide information and input to the management of PDAM Tirtauli in improving service quality management in order to achieve customer satisfaction.
University Level Management Toward Industrial Revolution 4.0 using COBIT 5 Framework
Authors: Hartati Seri , Syamsuadi Amir , Arisandi Diki 
Published: February 2021

Abstract
The Industrial Revolution 4.0 (IR 4.0) has escalating the demands for accountability and transparency for every organization, yet changing the organizational design paradigm. Adaptive power and fast responsive are the critical points In RI 4.0 to achieve the vision and mission of the organization. This is a challenge for organization such as universities to adapt in the era of disruption. The transformation of educational organizations is become the preference toward an excellent public services oriented and preparing the competent human resources in their expertise. This research propose a formulation for universities to investigate the readiness of the university to prepare the era of RI 4.0 using Cobit 5 Framework. The descriptive method with a qualitative approach are conducted in this work. By using purposive and snowball sampling from Universities in Riau, we found the Universities was on the level of managed process. The results can be delivered to the university as an outlook of readiness toward disruption era in the IR 4.0.
Development of Radio Frequency Identification (RFID) in the Campus Parking System based on Microcontroller
Authors: Hidayat Rahmad , Rushendra  , Afiyah Salamatul , Sufyani Rosyidin , Adani Farhan 
Published: February 2021

Abstract
In a conventional parking system that is currently still widely used, vehicle owners must show the parking card or the receipt for the parking hours, so that the fee will be paid. In this experimental study, a parking system was developed by utilizing Radio Frequency Identification (RFID) technology based on a microcontroller control system. The use of this technology makes it possible to make a subscription parking system that is served automatically and flexibly by a parking lot. RFID has data information that can be used as a user’s identity to enter the parking area. In this research, parking system design and implementation were made by simulating a miniature portal door system to enter and exit vehicles on campus using RFID cards/tags as subscription IDs. AT89C51 microcontroller is used as a system controller. By using this RFID technology, the parking subscription system becomes more flexible and faster.
Utilization of the field of data mining in mapping the area of the Human Development Index (HDI) in Indonesia
Authors: Rahmat Adi , Hardi H , Syam Febrizal Alfarasy , Zamzami Z , Febriadi Bayu , Windarto Agus Perdana 
Published: February 2021

Abstract
The Human Development Index (abbreviated as HDI) is an indicator used by a country to measure success in efforts to develop human quality. The purpose of this research is to make HDI mapping in areas in Indonesia by utilizing data mining techniques. Source of data used comes from official data from the Indonesian Central Statistics Agency (https://www.bps.go.id/) consisting of 34 data records (2018-2019). Indicators used in mapping are Life Expectancy at Birth (X1), Expectations of Old School (X2) and Average Length of School (X3). The data mining technique used is part of clustering, namely K-Medoids. The analysis process uses the help of RapidMiner software 5.3. Determination of the number of clusters (k) in the mapping using the Davies Bouldin (DBI) parameter with a maximum value (k = 4) = 0.856. By using four mapping labels (C1 = “very high” group; C2 = “high” group; C3 = “medium” group; C4 = “low” group), the results of C1 = 5 province; C2 = 16 provinces; C3 = 10 provinces and C4 = 3 provinces. Based on the results of the mapping of regions in Indonesia, Indonesia’s HDI is still far behind when compared to countries in ASEAN. In the future, this will be submitted to the government to make HDI a priority because it involves the welfare and quality of Indonesian people.
A Technology Acceptance Framework Inside the Indonesian Online Learning Platform
Authors: Harja Yuda Dian , Ambarwati Rita , Handiwibowo Gogor Arif 
Published: February 2021

Abstract
The user’s acceptance of the technology is one of the big moves towards progress in online network technology. It is, therefore, essential to recognize the factors which influence the success of technology acceptance. This research attempts to establish the value of online learning technologies. Within this analysis, the acceptance factors of OLP technologies are evaluated using an updated UTAUT2 model. This work is a quantitative analysis with an interview method in which respondents would have used the technologies of the OLP. The anticipated outcome of this research is the most critical factor in embracing the OLP technology, which will then be used by the technical providers of the OLP to make strategic decisions for further growth.
Automobile Insurance Processing using Deep Convolutional Networks
Authors: Rajkumar R. , Neema Ronhit , Chaitanyanathreddy N. , Varun G. , Govinda K. 
Published: February 2021

Abstract
We focus on automating the task of automobile insurance processing using Deep Convolution Networks, due to the limited data we find that using transfer learning and using variational Auto encoders to find features works well, we have created four models, classification of car or not, classification of whether car is damaged or not, classification of where the damage has occurred and the severity of the damage respectively. We show different methods that can be used in performing car damage analysis and this paper is not an exhaustive search over the entire domain car damage insurance and claims processing. This paper records the different techniques we have employed in order to analyze the car damage.