Reviewerly/exHarmony huggingface dataset:
Investigation of the Applicability of ASTER Satellite Images for Exploration of Barite Mineralization in the Bitlis Region

The purpose of this study is to examine the exploration for barite mineralization by using remote sensing data and field verification work. The mineralization is situated at the sites of Kulluce, Pertuk, Hacinan, Kamurangazi, and Isikli in the Bitlis province. Barite is found in vein, lens, and stratiform forms in the Devonian epimetamorphic rocks and carbonate rocks, and the Permian limestone. Due to presence of the ferrous and clay minerals along the contacts of the barite outcrops, alteration mineral indices were seen as an indicator on the satellite image. The ASTER satellite image is used for discrimination of lithologic contacts, identification of lineaments and mapping of alteration minerals. Alteration minerals (iron oxide and alunite, kaolinite, and illite-smectite-sericite) were used the methods of reflectance spectroscopy and spectral mapping using ASTER imagery by mineral indices of minerals in host rocks. Also, the mapping of calcite, muscovite and dolomite in the host rocks was performed by band ratio indexes. Lineaments and probable faults were revealed using a relief map obtained from the ASTER image and digital elevation model. They show an extension in dominant NE-SW direction with less N-S trending. Based on the interpretation of all data, overlapped by the ArcGIS software, it was determined that probable potential barite areas were compatible with tectonic lines of the field. It has been observed that three different barite outcrops were identified during the fieldwork. This work demonstrates the ability of ASTER image to provide information on barite and host rocks, which is a valuable for mineral exploration.
Determination of Bot Groups in Social Network Accounts by Multiple Sequence Alignment Method

Social networks have become very important power in our age. The ability of people to meet their needs through social networks has been an important factor in the formation of this power. Many events such as shopping, communication, hobby and research can be done through social networks. Twitter is one of the leading platforms of these social networks. Twitter is a social networking platform that offers a simple but powerful service. Most of the functionality is found in messages with a maximum of 280 characters, in other words in tweets. These tweets mean big data for researchers. An average of 5700 tweets are generated on Twitter per second. There is a lot of important information in this large volume of data. This information can be analyzed and used for many purposes. This information can be used to spread false information such as selection and manipulation of the stock market. In this study we will examine the structure of the accounts that emit this harmful information.
DotCHA: An Interactive 3D Text-based CAPTCHA

We introduce a new type of 3D text-based CAPTCHA, called DotCHA, which relies on human interaction and overcomes the limitations of existing 2D and 3D CAPTCHAs. DotCHA asks users to rotate a 3D text model to identify the correct letters. The 3D text model is a twisted form of sequential 3D letters around a center pivot axis, and it shows different letters depending on the rotation angle. Because each model consists of many small spheres instead of a solid letter model, DotCHA is classified as a scatter-type CAPTCHA and resists character segmentation attacks. Moreover, DotCHA is resistant to machine learning attacks because each letter is only identified in a particular direction. We demonstrate that DotCHA is resistant to existing types of attacks while maintaining usability.
Effectiveness of Indigenized Learning Module for Grade II Ayta Pupils

The classroom action research focused on the Effectiveness of Indigenized Learning Module for Grade II Ayta pupils in Bueno Elementary School, Capas West District. The diverse group of learners in Bueno, Capas, Tarlac were mixed ethno linguistic group of Ayta Mag Antsi, Sambal Botolan, Ayta Abellen and Capampangan. The Indigenized Module in Improving Aytas’ Number Sense used the indigenous language of Ayta Mag Antsi and Sambal Botolan because of dominant used of the language in Grade II. The implementation of Indigenized Module on Mathematics conducted during the third quarter of the school year 2018-2019. The researcher used Purposive sampling method for non-probability sampling technique that was selected with the 36 Grade II IP learners. The one Group Pretest/ Posttest Design with Table of Specification were used in the study. The instrument used in the test is Kudder- Richardson Formula 20. Furthermore, the researcher used interview questions on learning experiences and observation notes. The scores subjected to test of difference or t-test in order to identify the significant difference of their scores supplemented by Shapiro-wilk test for normality. The Indigenized Module in Improving Ayta’s Number Sense was effective. Findings revealed that the used of Indigenized Module improved the academic performance of the IP learners. In addition, they obtained higher mean in their posttest and delayed posttest compared to their pretest which lead to higher mean percentage score. Accepting the fact that innovative teaching approaches had a great influence in encouraging IP learners to perform better with the help of the culture bearer, the researcher was able to confirm that Indigenized Module was effective. Lastly, IP learners were active on the class especially when the culture bearer explains the lesson using the indigenous language while the IP learners who can’t speak Ayta language were silent however the non-IP teacher explains the lesson using the language of Capampangan and Tagalog for them to understand.
Evaluation and Mitigation of Android Application in PT. Aku Pintar Indonesia

Aku Pintar Indonesia enterprise is one of the educational start-up industries currently developing an Android-based system. System errors could appear in various both the features and administrative processes. The system repair priority could be given to the easiest system error first without taking into account the risk that would arise. The company needed to change its risk management by providing the priority of system repair and considering the effects and frequency of the occurrences. This research aims to help Aku Pintar Indonesia enterprise in choosing the priority of system error repair in order to improve their services to their users. This research used FMEA which allows the risk level of each error modes being assessed. System errors and its frequency were identified by web-based Google Play Console. The disadvantage level appeared from each errors determined by utilizing expert judgment in a Focus Group Discussion (FGD). The risk level of each system errors determined by the frequency of each and the level of the disadvantages, then measure the value of the Risk Priority Number by multiplying the results of severity and occurrence so that the risk value is obtained. The next process of risk mapping based on the risk level uses a modification of the risk mapping table to obtain the error rate for making priority improvements. This research produced a complete document that contains the information needed to plan and prevent repetitive errors, and can reduce the initial system error rate by 4% to 2.4% according to reports from the Google Play Console system
Real-Time Domain Transform Recursive Filtering Dehazing Method Based on Polarization Image

Compared with the visible image restoration details, the polarization image is more abundant with the polarization characteristics to restore the target details. In order to overcome the problem that the current polarization-based dehazing algorithms, which the model parameters is susceptible to high-brightness objects and the noise of the restored image is more, we propose a universal polarization-based dehazing algorithm based on domain transform recursive filtering. On this basis, the quadtree spatial indexing method, the dark channel prior and the domain transform recursive filtering are researched to effectively estimate the model parameters. Then, the limitations of the parameters depending on the sky are broken through. Finally, according to the physical polarization-based dehazing model, the haze-free image can be well restored. Our experimental results show that the proposed approach not only enriches more texture details and reduce the noise as well, but also improves the time complexity of the algorithm.
Implementation Three Pass Protocol on Multiplicative Cipher

A three-pass protocol one of the frameworks in cryptography that provides privacy and multiplicative cipher is one of the traditional cryptographic algorithms that based on symmetric key encryption algorithms.In this research, we used the three-pass protocol method with the multiplicative cipher by combine them, this combination allows the sender and the receiver to exchange and distribute encryption key securely, hence, they don't need to send the key because each of them using its personal key for the message encryption and decryption process, so, the security of the multiplicative cipher improved.
Combining Method For Identifying Tilapia Is Worthy Of Export

Tilapia is much producing from Indonesia. That Fish has many advantages because it is acceptable to all religions and does not require any specific method of slaughter. From the aspect of nutrition, fish is also superior because it is the highest natural source of omega-3 fatty acids. However, the fish is easily damaged so it needs careful handling, good, and correct and fast so that the quality of the fish can be maintained for as long as possible so as not to decay/damaged in the process of exporting fish exports, and can provide optimal benefits. For that, we need to make a system that can determine which fish are qualified for the selection process of fish quality can be done quickly and also can be exported with time-efficient. The methods used for determining fish quality are AHP and TOPSIS. AHP aims to search the value of weight against each criterion while Topsis for determination of its decision. The combination of both methods will provide accurate and reliable fish determination results.
Media Interaktif Pengenalan Angka Dengan Jari Tangan Menggunakan Metode PCA (Principal Component Analysis)

In computer science image processing, the scope of its development is very rapid, not only used on images, but also with the introduction of a video. Finger number recognition has now been developed for many applications and to help solve problems. The use of the hand as an identifier has many benefits, especially its practicality. The main problem is a camera that represents an image consisting of a relatively large size vector. There are many techniques to reduce the dimensions of the video or camera that will be processed, one of which will be discussed here is to implement interactive learning of numerical recognition with a finger, in the number recognition application with this finger will be detected the shape of the hand that can be captured by the camera which will identify a name (number). In designing this application, the author uses Visual Studio 2010 with the C sharp programming language (C#). Keywords : Hand recognition, interactive media, Principal Analysis Component
Keywords Searching XML Data for Fatwa in Indonesia

Fatwa is a legal opinion or interpretation produced by religious scholars (Ulama) on a matter related to Islamic law. Fatwa means “answer”, “advice” or even “opinion” in Arabic. The Council of Indonesian Ulama (MUI), a council that harbors Muslims in Indonesia issued Fatwa as a legal decision according to Islamic law about issues of consideration such as social, economic, cultural, and political aspects that occurred in Indonesia. Written in a structured document, Fatwa contains information theorems based on the decision related to the fatwa in question. This study is intended to produce a keyword-based on Fatwa document issued by MUI. Each keyword is extracted according to the document structure. The result then generated as search queries over hyperlinked XML documents. The output of this study will support the search engine for the official MUI Website, and the result returns more documents with high relevancy to the keywords.
SISTEM INFORMASI GURU DI SEKOLAH DASAR

The development of information technology nowadays is developing and advancing rapidly. Schools must look for other alternatives in dealing with problems faced by schools. One of the things that can be done by school is to use an information system in its managerial. Information system at SD Negeri 22 Alai using the Studentsâ€™ Data application. Studentsâ€™ Data is a data collection system and management of micro educational data online and real time. There are several main types of data managed in the Studentsâ€™ Data system, including school data, educator data, employee data, and school staff data. Information systems that are operated are very helpful for principals or leaders in taking policies and evaluating policies and other managerial tasks.
Effectiveness of Discovery learning Models Assisted by Puzzle Mind maps on the Activities and Learning Outcomes of the Structure and Function of Animal Tissue Materials

The research aims to determine the effectiveness of discovery learning models assisted by puzzle mind maps on the activities and learning outcomes of the Structure and Function of Animal Tissue Materials. This research was conducted at SMAN 13 Semarang in the Odd Semester Academic Year 2018/2019. This research is a Quasi Experiment study with Nonequivalent Control Group Design. The population in this research were all students of Class XI MIPA of SMAN 13 Semarang. The sample used was Class XI MIPA 1 and XI MIPA 2 which was taken by purposive sampling technique. The results showed that the learning outcomes showed that there were no significant differences between the learning outcomes of the control class and the experimental class (sig. ˃ 0.05). Data on student activity obtained by observation and filling in questionnaire sheets showed that 100% of the experimental class students entered very active and active category, while in the control class showed that 89.3% of students entered were very active and active category. This shows that the experimental class is able to surpass the indicator ≥ 90% in the student activity. The conclusion is the application of discovery learning models assisted by puzzle mind map of the Structure and Function of Animal Tissue Materials effectively applied to increase student activity but not to improve learning outcomes.
Tripal EUtils: a Tripal module to increase exchange and reuse of genome assembly metadata

Abstract Data and metadata interoperability between data storage systems is a critical component of the FAIR data principles. Programmatic and consistent means of reconciling metadata models between databases promote data exchange and thus increases its access to the scientific community. This process requires (i) metadata mapping between the models and (ii) software to perform the mapping. Here, we describe our efforts to map metadata associated with genome assemblies between the National Center for Biotechnology Information (NCBI) data resources and the Chado biological database schema. We present mappings for multiple NCBI data structures and introduce a Tripal software module, Tripal EUtils, to pull metadata from NCBI into a Tripal/Chado database. We discuss potential mapping challenges and solutions and provide suggestions for future development to further increase interoperability between these platforms. Database URL: https://github.com/NAL-i5K/tripal_eutils
Implementation of the K- Nearest Neighbor and Neural Network for Predicting School Readiness to Enter Elementary School

Entering elementary school is a new experience for children, both those who have attended school at a previous level or who have never been. Some children have problems at school due to maturity and readiness. To do a psychological test too, it costs money and only a small proportion of parents can do it. The alternative was used as a web-based prediction system without psychology tests. This study aimed to predict the readiness of children entering elementary school. There were three decision classifications: ready; doubt, and not ready. The algorithms used were K-Nearest Neighbor and Neural Network to classify dataset and probe data. The variable was sourced from the profile of the child and his parents. Testing data were tested to obtain the highest accuracy. The results showed that neural networks had significantly better accuracy than K-Nearest Neighbor. It could be used as a recommendation in the prediction system. At least, the system was expected to be able to provide the right decisions, both for children, parents and the environment.
Comprehensive Practice Course Construction of Internet of Things Technology

The Internet of Things (IoT) specialty belongs to the discipline of engineering application, requiring students to have strong practical and innovative abilities. Therefore, experimental teaching plays a very important role in the cultivation of innovative talents and quality education. However, the traditional experimental teaching system can not keep up with the development of the IoT discipline, and has shown many drawbacks. Therefore, it is urgent to conduct research on the IoT experimental teaching system and establish the IoT technology practical course to improve students' comprehensive practical ability.
The hypergraph matching based on CCRP

Hypergraph matching plays an important role in the development of computer vision and has gained more and more attention. Although many algorithms have been generated, it is always difficult to solve the mathematical model of the hypergraph matching. Most algorithms use approximately local optimal solution to replace the global optimal solution of objective function. This will cause the hypergraph matching is unable to obtain the optimal solution in limited time. In order to solve this problem, we propose a new hypergraph matching algorithm based on CCRP to overcome the relaxation problem. We compare the proposed method with several excellent matching algorithms in three common benchmarks including Synthetic, CMU House and Willow. Our experimental results demonstrate the superiority of our new algorithm in matching accuracy and robustness against noise and deformation.
IMPLEMENTASI JARINGAN KOMPUTER PADA PERPUSTAKAAN BANK INDONESIA (BI) KEDIRI

Bank Indonesia (BI) Library Kediri in implementing computer networks is quite adequate. Based on research in the field, the Bank Indonesia Kediri Library has not maximized computer network facilities for users or users. This is due to the constraints of the procurement process and the development of library space which results in constraints on various library facilities. This study aims to analyze the application or implementation of computer networks at the Bank Indonesia (BI) Kediri Library. The study was conducted through a qualitative descriptive research method with a type of case study on the application of computer networks in the Kediri BI library. Network devices that are implemented at KPw Bank Indonesia Kediri are MAN (Metropolitan Area Network). The network that is implemented in the Bank Indonesia Kediri library is a LAN (Local Area Network), which is connected to the network center in the BI office itself. The application of library automation is adequate with processing activities, availability of OPAC, circulation services and library reports. Various constraints on the network in the BI Kediri library inhibit the service process in the library, so there is a need for manual services so that services in the library such as the loan and return process continue to run.
How to handle risky experiments producing uncertain phenomenon like cold fusion?

Some experiments are risky in that they cannot repeatedly produce certain phenomenon at will for study because the scientific knowledge of the process generating the uncertain phenomenon is poorly understood or may directly contradict with existing scientific knowledge. These experiments may have great impact not just to the scientific community but to mankind in general. Banning them from study may incur societies a great opportunity cost but accepting them runs the risk that scientists are doing junk science. How to make an informed decision to accept/reject such study scientifically for the mainstream scientific community is of great importance to mankind. Here, we propose a statistical methodology to handle the situation. Specifically, we consider the likelihood of not observing the phenomenon after n trails so that it is statistically significant to have nil result. Consequently, we reject the hypothesis that there is some probability that we observe the phenomenon.
NOVEL SIRKUS POHON KARYA ANDREA HIRATA SEBAGAI MATERI AJAR SASTRA: ANALISIS PSIKOLOGI SASTRA DAN NILAI PENDIDIKAN KARAKTER

The purposes of this research are to describe: (1) structure of novel Sirkus Pohon by Andre Hirata; (2) id, ego, and superego of the main character novel Sirkus Pohon; (3) the value of character education in the novel Sirkus Pohon; and (4) the relevance of novel Sirkus Pohon as material of learning literature in senior high school. This research was conducted by descriptive qualitative method and psychology of literature. The result show that: (1) every elements of novel have in relation to the elements of other to make a story that a solid; (2) each of the characters has the character of different so that make them have balance id, ego, and superego different also; (3) the value of education character contained in the novel covering honest, discipline, hard work, the responsibility, appreciate the achievements, creative, care social, caring environment, and friends; and (4) novel Sirkus Pohon relevant made learning materials if viewed from aspects of the contens, presenting, language, and graph.
Explaining Multi-label Black-Box Classifiers for Health Applications.

Today the state-of-the-art performance in classification is achieved by the so-called “black boxes”, i.e. decision-making systems whose internal logic is obscure. Such models could revolutionize the health-care system, however their deployment in real-world diagnosis decision support systems is subject to several risks and limitations due to the lack of transparency. The typical classification problem in health-care requires a multi-label approach since the possible labels are not mutually exclusive, e.g. diagnoses. We propose MARLENA, a model-agnostic method which explains multi-label black box decisions. MARLENA explains an individual decision in three steps. First, it generates a synthetic neighborhood around the instance to be explained using a strategy suitable for multi-label decisions. It then learns a decision tree on such neighborhood and finally derives from it a decision rule that explains the black box decision. Our experiments show that MARLENA performs well in terms of mimicking the black box behavior while gaining at the same time a notable amount of interpretability through compact decision rules, i.e. rules with limited length.