bluuebunny/crossref_metadata_2025_split huggingface dataset:
Increasing mathematical literacy ability and learning independence through problem-based learning model with realistic mathematic education approach
Authors: Maslihah S , Waluya S B , Rochmad  , Kartono  , Karomah N , Iqbal K 
Published: June 2021

Abstract
The purpose of this study was to see the effect of implementing the PBL model with the RME approach on mathematical literacy skills and learning independence. This research is a combination research using a sequential explanatory design. The quantitative research method was carried out in the first stage by following a quasi-experimental model which was designed in the form of a non-equivalent (pre-test and post-test) control group design then continued by further analyzing the results of the quantitative method using qualitative methods. This study shows that there is an effect of the Problem Based Learning model with the Realistic Mathematic Education approach on mathematical literacy skills and learning independence and describes the relationship between independent learning and mathematical literacy skills.
Learning effectiveness with seven jump method assisted with e-module on statistics problem solving
Authors: Sukestiyarno Y L , Hartutik  
Published: June 2021

AbstractIn this era of disruption, it is time to invite students to learn independently. This study applies a module-assisted Seven Jump learning model for class X students with statistics material. The research scenario begins with clarifying assignments, determining problems, and providing problems. The student’s task is to analyze, evaluate needs to test hypotheses independently. This independent activity process is presented and delivered through an e-module. This study aimed to get effective learning, namely increasing student learning independence, the positive influence of independent learning to the achievement of problemsolving abilities, and the problem-solving abilities achieve learning completeness. This experimental quantitative research with the scope of class X statistics material with the variables of students’ learning independence and problem-solving abilities. Data obtained by observation and tests and processed by increasing N-Gain analysis, regression test and t-test completeness. The results showed that students with independent learning through the Seven Jump stages that have been packaged in e-modules condition the students to solve problems by discussing, looking for additional literature to test hypotheses. It is proven that the students’ learning independence has increased, the N-Gain value is 1.4, and it influences problem-solving ability by 72%. From the test of learning outcomes, the students’ problem-solving abilities reached an average of 77, exceeding the completeness score of 70. Thus the effectiveness of learning was achieved.
Developing electronic bahasa Indonesia (E-BIPA) 2.0 version media to improve critical literacy of foreigner students
Authors: Ahmadi F , Hapsari I P , Irvan M F 
Published: June 2021

Abstract
In this era of industrial revolution 4.0, technology is growing rapidly with the emergence of high-tech electronic goods equipped with internet facilities to further speed up the communication process. The objective of this research was to develop Electronic Bahasa Indonesia (E-BIPA) 2.0 Version to improve critical literacy of foreigners’ student. This study is Research and Development (R&D) using ADDIE model. The data of this study were obtained through observation, interviews, questionnaires, and scale. The feasibility of E-BIPA 2.0 Version media was obtained from assessments by media and material experts. The results of the validators indicate that the E-BIPA 2.0 Version is very feasible to be seen from the media aspects with score is 85 and from material aspects with score is 87. Based on the results, the E-BIPA Version 2.0 media is very feasible for Indonesian lecturer to be used in teaching foreigner students. The E-BIPA 2.0 Version media was expected to support critical literacy of foreigner students in learning Indonesian language.
The measurement of self-efficacy students in mathematics lesson tenth students of senior high school
Authors: Medyasari L T , Zaenuri  , Dewi N R 
Published: June 2021

Abstract
Self-efficacy can be defined as a person’s assessment of abilities that the individual has in achieving something that has been targeted. The study aims to describe self-efficacy on students at mathematics lessons. The population in this study is the fifth annual public high school class in 2019/2020. The sample in this study is the 10th X Science class at the state high school of 5 Semarang using the simple random sampling technique. The instrument used in this study is a non-test instrument of self-efficacy of 20 statements and observations. The data analysis technique used in this study is a descriptive data analysis. The research shows that the average of the score on the overall scale of self-efficacy belongs to a positive category. The probability of self-efficacy in the study of mathematics consists of students with high selfefficacy by 16.67%, students with medium self-efficacy are 63.44%, and students with low selfefficacy are at 20%.
Academic achievement analysis of Universitas Negeri Semarang students using the naïve bayes classifier algorithm
Authors: Purwinarko A , Hardyanto W , Aryani N P 
Published: June 2021

Abstract
This study aims to evaluate the academic data of students in third year and classified in the category of students who can graduate on time or not. This system uses students master data and student academic data as input data. Data of students who have graduated will be used as training and testing data while the data of students who have passed will be used as target data. Input data will be processed using the Naïve Bayes Classifier (NBC) data mining algorithm to form a probability table as the basis for the student graduation classification process. The output of this system is in the form of a classification of student academic performance that is predicted to pass and provides recommendations for the graduation process on time or graduates in the most appropriate time with optimal grades.
Designing a performance dashboard as a monitoring tool at PT Sun Star Motor MT Haryono Semarang: data approach
Authors: Aginsha A G , Noranita B 
Published: June 2021

Abstract
Information Management of the performance measurement of PT Sun Star Motor MT Haryono Semarang currently still provides less valuable information. This study aims to design a performance dashboard as a tool for monitoring company performance at PT Sun Star Motor MT Haryono Semarang so that information about company performance can be more valuable, especially for leaders. This research was conducted by taking into account the needs of users based on the company’s KPI. This research method refers to Hariyati’s “Dashboard Development Methodology.” This research phase is identifying needs and reviewing dashboard information. The design produced three performance dashboards: Main Dashboard, Service Division Dashboard, and the Unit Division Dashboard. The first dashboard presents performance information of PT Sun Star Motor MT Haryono Semarang as a whole, those who use the dashboard are the branch and acc manager. The second dashboard presents performance information from PT Sun Star Motor MT Haryono Semarang and the party that has access is the service manager. The third dashboard contains company performance information for unit divisions; the user is the supervisor. The dashboard information that has been designed is then reviewed by the user based on the company’s KPI and user needs.
A sentiment analysis study for twitter using the various model of convolutional neural network
Authors: Sartini  , Subiyanto  , Alim M M F 
Published: June 2021

Abstract
Sentiment analysis about natural language processing had been developed by various methods such as machine learning. In Indonesia, fewer studies on sentiment analysis have been studied using machine learning with specific datasets. The use of machine learning results in low accuracy that is applied in a wider scope. Therefore, the deep learning method developing to improve the accuracy of sentiment analysis. This paper presents different configuration parameters based on deep learning using the Convolutional Neural Network (CNN) algorithm to improve accuracy performance. The CNN models are presented by various parameters such as the number of convolutional layers, number of filters, and filter size to analyze the model’s performance. Indonesian-Sentiment-Analysis-Dataset which consists of 10.806 tweets has been used with the Word2Vec model for Indonesian as a word vector representation. The CNN models are trained on 80% of the dataset and tested on the remaining 20% of the dataset. The proposed CNN models’ results are compared with machine learning algorithms such as SVM, KNN, and SGD. The CNN models performed better than machine learning and got the best accuracy of 81.4% for general sentiment analysis in Indonesian.
Efficient feature selection analysis for accuracy malware classification
Authors: Romli R N , Zolkipli M F , Osman M Z 
Published: June 2021

Abstract
Android is designed for mobile devices and its open-source software. The growth and popularity of android platform are high compared to another platform. Due to its glory, the number of malware has been increasing exponentially. Android system used a permission mechanism to allow users and developers to manage their access to private information, system resources, and data storage required by Android applications (apps). It became an advantage to an attacker to violent the data. This paper proposes a novel framework for Android malware detection. Our framework used three major methods for effective feature representation on malware detection and used this method to classify malware and benign. The result demonstrates that the Random forest is with 23 features is more accurate detection than the other machine learning algorithm.
Improved accuracy of recognizing of low-quality face images using two directional matrix in 2D-PCA algorithms and euclidean distance
Authors: Kuncoro R D K , Sugiharti E 
Published: June 2021

Abstract
Face recognition is a technique that can be used to distinguish the characteristic facial patterns of a person. A very influencing factor in the facial recognition process is image quality, so it can affect the level of accuracy. Improving the accuracy of low-quality facial recognition can be done by processing the image for its feature extraction using Two Directional Matrix on 2D-PCA. From the extraction process, the Eigenfaces value is then generated to be classified. Image classification is done by using Euclidean Distance. Furthermore, the accuracy results between image recognition with or without Two Directional Matrix will be compared. The data used were the AT&T face of database and database of Essex. Of the 18 tests carried out on the Two Directional Matrix method, it was proven to improve facial recognition accuracy by as many as 12 trials. In 5 other experiments the accuracy decreased and 1 experiment was unable to increase or decrease facial recognition accuracy. The highest accuracy result in the experiment using AT&T was 98.25%, while in Essex it was 97.27%. Suggestions for further research by conducting experiments with more diverse dataset ratios in order to get better low-quality image accuracy results.
User experience measurement of adaptive online module system using user experience questionnaire
Authors: Hidayat A , Utomo V G 
Published: June 2021

Abstract
Traditionally, research in Human-Computer Interaction (HCI) kept focusing on system usability. Nowadays, user experience is also taken into consideration, complementing system usability, as important aspects of the system. Adaptive Online Module System is an adaptive e-learning system that automatically adjusts its behavior according to the student’s learning style. User Experience Questionnaire (UEQ) Indonesian version is selected in this study to assess the user experience of Adaptive Online Module System. Most results of the Adaptive Online Module System user experience measurement are positive. In the grouped result, adaptive online module system has positive scores in Attractiveness, Pragmatic Quality and Hedonic Quality. On all six scales of UEQ result (Attractiveness, Perspicuity, Efficiency, Dependability, Stimulation and Novelty). Adaptive Online Module System has a positive benchmark. The benchmark results are ranging from above average to excellent. Adaptive Online Module System also has a positive result and sufficient consistency in all of six scales except novelty scale.
Students’ attitude towards mathematics in discovery learning using concrete and virtual manipulative
Authors: Hidayah I , Prayoga R A 
Published: June 2021

Abstract
Students’ attitude towards mathematics is a factor that affects students’ learning activities and mathematics achievement. The purpose of this study is to observe the relationship between the indicators that construct students’ attitude towards mathematics in discovery learning using concrete and virtual manipulative. This study uses a quantitative method with a pre-experimental design model. The sample in this study was students of class VIIB as virtual class and VIIC as concrete class at SMP Negeri 31 Semarang. The research sample is given a post-survey after the implementation of discovery learning. SPSS and LISREL are used to analyze the measurement model (CFA). Based on the analysis of goodness of fit statistics, 13 of the 18 parameters state that the causative model of the model in this study is appropriate and compatible to be applied to concrete and virtual classes. In the concrete class, the measurement model shows acceptable reliability and validity. While in the virtual class, the measurement shows that reliability is not fulfilled and there is an invalid indicator, namely anxiety towards mathematics. The average of R
2 value of the indicators in constructing students’ attitude towards mathematics in concrete class is 47.8% while the virtual class is only 41.4%.
Group chat analysis of hoax detection during the covid-19 pandemic using the k nearest neighbors algorithm and massive text processing
Authors: Umam K 
Published: June 2021

Abstract
Group chat is the most widely used choice of various short information. Besides being easy to send messages, sharing short messages in group chat is considered effective compared to sending massively to several users. The ease of sending short messages in group chat is often used as the spread of fake news and untrue news or hoaxes, especially during the Covid-19 pandemic, the information shared can be easily shared by anyone without seeing a valid source. The dissemination of information related to Covid-19 without a clear source is a dangerous act, because it can lead users into false information and endanger themselves. Fake message detectors have not been widely implemented in instant message applications, for this reason, there is a need for a detector and a machine to analyze activities in group chat and see whether the message is included in content containing fake news or not. If a group chat has a lot of fake news, you can be sure that the group chat is not good to follow. The use of the K-Nearest Neighbors algorithm is considered quite effective in classifying an object, the results can be determined whether it is included in fake news, miss-information news, or true news. The process of processing messages is carried out by the massive text processing method because the characteristics of the text are different for each user so that text processing can be maximized for later classification. As a result, group chat can be analyzed based on active time, user messages, user activity, and messages sent between users.
Implementation of ERP system functionalities for data acquisition based on API at the study program of Universities
Authors: Budiman K , Putra AT , Alamsyah  , Sugiharti E , Muslim M A , Arifudin R 
Published: June 2021

Abstract
ERP was built to simplify existing business processes so that business processes became more effective and efficient. The term “business” also refers to individuals or organizations organized efforts and activities to produce added value, unexceptionally in education. Higher education institutions have an education system that must be accredited as an assessment of the institution’s performance. Based on the accreditation assessment criteria carried out by BAN-PT, there are at least nine assessment criteria in which almost all universities have their data in their system. This paper discusses collecting the right data to acquire data from various systems within the university into an integrated accreditation system. The data transactions between various university information systems and accreditation systems implementing the Application Programming Interface (API) to make the data acquisition process more effective. The results showed an increase in accreditation data collection speed, and assessors could see quickly and clearly through the data collected in the accreditation system.
Technology utilization in parereja villagers’ empowerment during covid 19 pandemic
Authors: Hidayah I , Tatirah  , Latiana L , Widowati  
Published: June 2021

Abstract
Parereja village is located in Brebes Regency, Central Java. Brebes Regency is one of the regencies with a low human development index indicator. Regency condition describes the village unit condition in regency area. The main strategic issues in Brebes Regency Long-Term Regional Program Plan are education and health fields, the two of which cannot be separated. The target communities for technology utilization in villager’s empowerment were elementary school-aged children, POSPAUD mothers, and women. During Covid 19 pandemic, many things caused face-to-face activities impossible. Community empowerment programs were done by implementing healthy living pocketbooks for children, using social media as a reference for making educational props and early childhood development activities, and education and life skills training. Technology applications for making pocketbooks were using pinterest.com references and batik tutorial videos. Positive children’s responses showed the successful use of pocket books. POSPAUD mothers’ success was shown by children’s creativity products, and the success of women’s programs was shown by batik products. This activity was beneficial for the program’s success and met technology literacy targets (technology literacy).
Combining support vector machine with radial basis function kernel and information gain for sentiment analysis of movie reviews
Authors: Abidin Z , Destian W , Umer R 
Published: June 2021

Abstract
A movie review can be considered as an essential data source for both movie producers and potential consumers. The reviews are usually used as a benchmark for knowing the movie’s quality and are utilized as references to whether the film is worth watching. The study of sentiment analysis has received more attention from researchers. This current study aims to classify the sentiment analysis of movie reviews obtained from the IMDb site. The support vector machine (SVM) method was employed to classify the movie review’s sentiments. Meanwhile, the radial basis function (RBF) kernel and information gain (IG) were used to enhance classification. Feature selection was conducted by removing irrelevant features and selecting features with a strong correlation to classification. The IG algorithm was used for feature selection. The current study revealed that the classification accuracy of movie review sentiment analysis using the SVM algorithm, SVM + RBF kernel, and SVM+RBF Kernel+IG are 81.50%, 82.25%, and 87.25%, respectively.
Oryctes rhinoceros attraction to pheromone traps placed near the light source at night
Authors: Indriyanti D R , Wijayanti D , Setiati N 
Published: June 2021

Abstract
The objective of this study was to analyze O. rhinoceros attraction to the pheromone that was placed near and far from the light source. Samples were obtained using pheromone traps placed at a distance of ± 5 m (near) and ± 500 m (far) from the light source. Each village was installed with 10 pheromone traps, 5 traps were placed near the light source, and another 5 traps were far from the light source. Observation on O. rhinoceros imago captured was conducted for 12 weeks. The results showed that O. rhinoceros is more attracted to the pheromone traps placed near the light source. The sex ratio of male and female imago from traps placed both near and far from the light were 1:1.2 and 1:1.3, respectively. This study can provide information regarding O. rhinoceros monitoring using pheromone traps combined with the light to attract more O. rhinoceros imago.
Carcass and fatness traits of Central Javanese local ducks based on Lipoprotein Lipase (LPL) and Perilipin (PLIN) genes
Authors: Susanti R 
Published: June 2021

Abstract
This research is an exploratory study that determines the genotypes of carcass and fatness traits in Central Javanese local ducks based on the lipoprotein lipase (LPL) and perilipin (PLIN) genes. A 35 ducks were sampled from seven local ducks in Central Java. The duck’s DNA was isolated from its feathers. PLP and PLIN genes were amplified by PCR method using specific primers. In the RFLP analysis, PCR products were digested with the restriction enzymes MvaI (BstNI) (5’CC/WGG) and Bsp1286. (SduI) (GDGCH/C), for LPL and PLIN gene, respectively. The results of PCR-RFLP analysis on local ducks in this study showed a monomorphic in exon 2 of the PLIN gene and polymorphic in exon 5 of the LPL gene. Based on the LPL gene, as many as 29 ducks (82.85%) had GG genotypes, 3 ducks (8.57%) had AG types and 3 ducks (8.47%) had AA types. Both PLIN and LPL genotypes were clustered the Central Javanese local ducks into 3 haplotypes (A-C). The duck samples were dominated by haplotype A (82.85%) followed by haplotype B (8.57%) and haplotype C (8.57%). Results showed that 82.85% of Central Javanese local ducks genetically had a good of fatness traits but a low of carcass traits.
Antibacterial activity of ethanol extract, n-hexan, ethyl acetate and butanol fraction of Momordica charantia L. seed against Staphylococcus epidermidis
Authors: Rahmi M , Sari T M , Despanita  
Published: June 2021

Abstract
Acne is a skin disease caused by excessive production of oil, causing clogged pilosebaceous follicular ducts and inflammation. One of the bacteria triggered acne is Staphylococcus epidermidis. Acne treatment usually uses antibiotics that inhibit inflammation and bacterial growth. To reduce the effects of using chemical drugs, research is needed to find natural treatment solutions such as using the bitter melon plant. The part that is often used from bitter melon is flesh of the fruit, while the seeds are only used as waste, so researchers are interested in examining the antibacterial activity of bitter melon seeds. Tests were carried out on ethanol extract, fraction of n-hexane, ethyl acetate and butanol in bitter melon (Momordica charantia L.) seeds against Staphylococcus epidermidis by determining the minimum bakterisid concentration (MBC) using the liquid dilution method of a concentration of 80%; 40%; 20%; 10%; 5%; 2.5%; 1.25% and 0.625%. The value of minimum bakterisid concentration (MBC) is indicated by the absence of colony growth on agar media. The minimum bakterisid concentration (MBC) in this study was only obtained in the ethyl acetate fraction, at a concentration of 40%, while in extracts and other fractions the MBC value was not obtained.