Reviewerly/exHarmony huggingface dataset:
Analisis Tingkat Keamanan Aplikasi SIMAK Menggunakan Standard ISO/IEC 27002:2013 (Studi Kasus: UPTTIK Universitas Siliwangi)

The issue of data security seems to be one of the most intriguing topics to observe in the development of information technology in recent time/. The information technology related to the management processes, one of which is the SIMAK application at the University of Siliwangi needs a higher security concern. This study aims to determine the level of security of the SIMAK application in which the researchers can provide recommendations to SIMAK managers. This could be the basis for the future improvements. Researchers used 4 domains from ISO / IEC 27002: 2013, namely domain 5, it contains information security policies. Domain 6, it contains organizational information security. Domain 9, it contains access control. Lastly, Domain 11, it contains physical and environmental security. When they are specified from the four domains, 38 controls are obtained. Security, from the results of the questionnaire and weighting, the result of the 5 domains maturity value is= 1.49, the result of the domain 6 maturity value is= 1.52, while domain 9 maturity value is= 1.32 and domain 11 maturity value constitute to 1.97. If it is averaged, the Siliwangi University SIMAK application is at level 2 or repeatable.
THE EFFECTIVENESS OF JAKARTA SMART CITY APPLICATION IN ENHANCING COMMUNITY RESILIENCE IN FACING FLOOD RISK

Jakarta is the most populated city in Indonesia with a long history of natural disasters, particularly floods. The city's geographical condition has been said as the leading cause of the recurrent floods that happen over the years. This situation has predominantly affected the people living in the flood-prone locations in several settlements along the Ciliwung riverbanks. The government has conducted various efforts to enhance the city resilience towards flood incidence, including utilizing smart city approach, such as flood monitoring applications to give a real-time information related to certain circumstances that possibly caused flooding. This effort aims to increase the community awareness toward disaster events.The aim of this paper is to analyse the effectiveness of people using the flood mitigation application as an early warning system in Jakarta. To construct this objective, questions for instance as to what extent people are familiar with the application, how much they understand its function, and whether they face any difficulties in using the application during the flood events are proposed. The quantitative approach is being used in this research to gather people's opinions towards the application, specifically JAKI. Preliminary results suggest that there are still some gaps in the implementation of technology applied with how society comprehends it, resulting in the interference with the application’s intention as an early warning system. Some important features that need to be reformed in favor of public use are the application basis, target group, data selection, and application in disaster management schemes. While the research is still on-going, an understanding that technology should be aligned with the community's ability to use it should be redefined in the implementation of smart city principles in Jakarta.
The configuration space of a robotic arm in a tunnel of width 2

We study the motion of a robotic arm inside a rectangular tunnel of width 2. We prove that the configuration space S of all possible positions of the robot is a CAT(0) cubical complex. Before this work, very few families of robots were known to have CAT(0) configuration spaces. This property allows us to move the arm optimally from one position to another.
UPAYA MENINGKATKAN HASIL BELAJAR BAHASA INDONESIA PADA KOMPETENSI MENENTUKAN KOSA KATA TENTANG PERISTIWA SIANG DAN MALAM DENGAN MENGGUNAKAN MODEL PEMBELAJARAN EXAMPLE NON-EXAMPLE PADA SISWA KELAS I SDN BERANGAS 1 KECAMATAN ALALAK

In the process of teaching and learning, there is often one direction of learning, thelearning media are not appropriate and then no variety of learningmethods, causing a lack ofstudent interest in learning and low completeness of learning outcomes.This research hasbeen conducted using the example non example learning method in two cycles, each cycle isdivided into two meetings with the percentage of teacher and student activity scores.Theresults showed that in the first cycle of the first meeting, the score of teacher and studentactivity respectively obtained 66.7% with a fairly good category and 63.6% of students beingactive. At the second meeting, the results obtained were 70.8% in the good category and68.2% of the students were active. In the second cycle, there was an increase in the scorecompared to the first cycle, the second cycle of the first meeting had an increase of 77.1% inthe very good category and 75% of the students were active. At the second meeting it reached85.4% in the very good category and 81.8% of students were active.The results showed thatthe method used was very effective in increasing student activity and improving Indonesianlearning outcomes on the competence of determining vocabulary about day and night events.
Digital Signature Algorithm for M-Payment Applications Using Arithmetic Encoding and Factorization Algorithm

Mobile communication systems employ an encoding-encryption model to ensure secure data transmission over the network. This model encodes the data and encrypts it before transmitting it to the receiver's end. A non-trivial operation is performed to generate a strong secret key through which the data is encrypted. To support the security level of this model, arithmetic encoding is performed upon the data before encryption. The encrypted data is hashed using a lightweight hashing algorithm to generate a small and fixed length hash digest to overcome the overheads before it is communicated to the other end. To authorize the message being sent by the sender to the receiver, signature plays an important role. To avoid forging using proxy signature, blind signature, etc., a hybrid scheme is proposed in this article. The mobile communication system is enhanced by introducing the hybrid encode-encrypt-hashing mechanism which stands secure against the plain text attacks, mathematical attacks, and increases confidentiality of the data, security of the key, and thereby enhances the security of the system. In this paper, the design is applied over the mobile payment system which is considered as one of the appreciable mobile services. It proves that the designed security model can ensure swift transactions in a secure way.
ACCURACY OF IDIOM TRANSLATION IN SIDNEY SHELDON’S THE SKY IS FALLING INTO INDONESIAN LANGIT RUNTUH

&lt;p&gt;The purpose of this research is to know the accuracy of idiom translation and strategies that are used by the translator in translating the idiom into Bahasa Indonesia. This research uses qualitative descriptive analysis. After analyzing the results of accuracy of idiom translation from the three evaluators in the novel entitled The Sky is Falling, the researcher gets the conclusion that accuracy in “0” scale takes the highest position. There are three strategies used by the translator in translating idioms. They are paraphrase which marks 87%, borrowing the source language idioms with 6%, omission of entire idioms with 2%, using an idiom of similar meaning but dissimilar form with 5%.&lt;/p&gt;&lt;p&gt;Keywords: Accuracy, Idiom Translation, Novel entitled &lt;em&gt;The Sky is Falling&lt;/em&gt;.&lt;/p&gt;
A Large Scalar Multiplication Algorithm using Modified Pell Numbers for Key Generation

Cryptographic algorithms consist of two parts, a key and an algorithm, to encrypt and decrypt data. The key is an essential part that works with the algorithm. The security of encryption schemes depends on the key size (key length) and the longer the key, the better the security it provides. Applying an elliptic curve has for key agreement provides a high-performance architecture and high security. The main process for calculating key points in Elliptic Curve Cryptography (ECC) is called scalar multiplication, which relates to point addition and point doubling. An efficient algorithm, proposed as the Large Scalar Multiplication Algorithm using Modified Pell Numbers (LSMA-MPN), was introduced to speed up the calculation of points on elliptic curves during large scalar multiplications. This system also reduced computation time by applying Modified Pell numbers in a 22 matrix representation. The experimental results showed that computation time was reduced by approximately 67% in comparison with the computation time required by a general algorithm.
THE INFLUENCE OF MALL ON ENHANCING STUDENTS’ LITERACY SKILLS

This study investigates the influence of MALL (Mobile Assisted Language Learning) on enhancing students' literacy skills in the international program of accounting. The mobile-phone platforms worked as media of interaction with the students in the learning-teaching and outside the classroom. The mobile phone is used as a medium for practising both reading and writing. This research was a quantitative study using an experimental design. The population of the study was the students of the International Program of Accounting department. The result showed that Sig. (2-tailed) .197 &gt; 0.05 which means there was no significant effect in the use of MALL to enhance the students' literacy skills in general. Instead, the use of MALL has a significant effect in improving the spelling which was Sig. (2-tailed) 0.043 &lt; 0.05, and grammar for the plural and singular parts for Sig. (2-tailed) 0.025&lt;0.05.
Text Summarization of Czech News Articles Using Named Entities.

The foundation for the research of summarization in the Czech language was laid by the work of Straka et al. (2018). They published the SumeCzech, a large Czech news-based summarization dataset, and proposed several baseline approaches. However, it is clear from the achieved results that there is a large space for improvement. In our work, we focus on the impact of named entities on the summarization of Czech news articles. First, we annotate SumeCzech with named entities. We propose a new metric ROUGE_NE that measures the overlap of named entities between the true and generated summaries, and we show that it is still challenging for summarization systems to reach a high score in it. We propose an extractive summarization approach Named Entity Density that selects a sentence with the highest ratio between a number of entities and the length of the sentence as the summary of the article. The experiments show that the proposed approach reached results close to the solid baseline in the domain of news articles selecting the first sentence. Moreover, we demonstrate that the selected sentence reflects the style of reports concisely identifying to whom, when, where, and what happened. We propose that such a summary is beneficial in combination with the first sentence of an article in voice applications presenting news articles. We propose two abstractive summarization approaches based on Seq2Seq architecture. The first approach uses the tokens of the article. The second approach has access to the named entity annotations. The experiments show that both approaches exceed state-of-the-art results previously reported by Straka et al. (2018), with the latter achieving slightly better results on SumeCzech's out-of-domain testing set.
Typability and Type Inference in Atomic Polymorphism

It is well-known that typability, type inhabitation and type inference are undecidable in the Girard-Reynolds polymorphic system F. It has recently been proven that type inhabitation remains undecidable even in the predicative fragment of system F in which all universal instantiations have an atomic witness (system Fat). In this paper we analyze typability and type inference in Curry style variants of system Fat and show that typability is decidable and that there is an algorithm for type inference which is capable of dealing with non-redundancy constraints.
Real Time Object Detection Android Application using Machine Learning Concepts for Visually Impaired People.

The primary role in detecting the objects in this complex evolution necessitates a computer vision system that can deal with both indoor and outdoor classes. This zeal has necessitated increased attention in recent decades. Object identification with a single labelling approach has been used in previous implementation techniques. In their daily lives, visually impaired and blind people face a variety of obstacles. The proposed project's aim is to create an Android-based application for people who are blind or visually impaired.The system's goal is to detect real-time objects and Indian currencies that are scanned through a mobile camera and notify blind people about them through audio or vocal information. The proposed framework makes use of Machine Learning and Google's TensorFlow Lite object detection API.It's a useful app that makes it much easier for blind and visually disabled people to complete daily tasks with less effort.It's a small contribution to India's Make-In-India movement.
Optimized COCOMO parameters using hybrid particle swarm optimization

Software effort and cost estimation are crucial parts of software project development. It determines the budget, time, and resources needed to develop a software project. The success of a software project development depends mainly on the accuracy of software effort and cost estimation. A poor estimation will impact the result, which worsens the project management. Various software effort estimation model has been introduced to resolve this problem. COnstructive COst MOdel (COCOMO) is a well-established software project estimation model; however, it lacks accuracy in effort and cost estimation, especially for current projects. Inaccuracy and complexity in the estimated effort have made it difficult to efficiently and effectively develop software, affecting the schedule, cost, and uncertain estimation directly. In this paper, Particle Swarm Optimization (PSO) is proposed as a metaheuristics optimization method to hybrid with three traditional state-of-art techniques such as Support Vector Machine (SVM), Linear Regression (LR), and Random Forest (RF) for optimizing the parameters of COCOMO models. The proposed approach is applied to the NASA software project dataset downloaded from the promise repository. Comparing the proposed approach has been made with the three traditional algorithms; however, the obtained results confirm low accuracy before hybrid with PSO. Overall, the results showed that PSOSVM on the NASA software project dataset could improve effort estimation accuracy and outperform other models.
Design and Build an Android-Based Digital Academic Guidebook Application at Universitas Teknologi Sumbawa

In order to increase the effectiveness of the existence of an academic guidebook at the Universitas Teknologi Sumbawa (UTS), the authors conducted a study that aims to design and build the Digital Academic Guideline Application University of Sumbawa Technology (UTS). The data collection methods used in this research are interviews and literature study as well as the prototype method as a software development method. Applications generated from this study are hybrid and android-based with version 4.4 (Kitkat). The process of making this application uses HTML5, CSS3, PHP5.6, and MYSQL as a database, and beta test as a testing method. In this academic guide application, it contains information on UTS academic guides which includes data on universities, faculties, study programs, lecturers, and courses as well as other information
Curve reconstruction from a set of measured points

In this article, a method of cubic spline curve fitting to a set of points passing at a prescribed distance from input points obtained by measurement on a coordinate measuring machine is described.When reconstructing the shape of measured object from the points obtained by real measurements, it is always necessary to consider measurement uncertainty (tenths to tens of micrometres).This uncertainty is not zero, therefore interpolation methods, where the resulting curve passes through the given points, do not lead to acceptable results in practice.Also, conventional B-spline approximation methods cannot be used because, for real distances between measured points (tenths to units of millimetres), the distance of the input data from the resulting approximation curve is much greater than the measurement uncertainty considered.The proposed reconstruction method allows to control the maximum distance of the resulting curve from the input data and thus to respect the uncertainty with which the input data was obtained.
Developing Android Based Emergency Call Application

This research is motivated by the high number of accidents in Indonesia caused by several factors, including difficulty in contacting emergency services, ignorance of the public to contact emergency services, and not knowing the location of emergency services. For this reason, this research has carried out the design and development of mobile applications for the public to contact Android-based emergency services. The application development method used is Rapid Application Development (RAD), which is suitable for short development times and according to needs. In this RAD method consists of four stages, namely the stages of planning needs, designing, construction and also implementation. This study produces a mobile application for community service based on android which aims to enable the public to contact community services quickly and accurately.
UPAYA PENINGKATAN KOMPETENSI GURU DALAM MENYUSUN SILABUS DAN RPP MELALUI WORKSHOP DI SD NEGERI 15 JALAN API KERETA PARIAMAN

The research subjects were teachers of SD Negeri 15 Jalan Kereta Api. Research procedure with two cycles. Each cycle consists of two workshops, each of which includes planning, action, observation, and reflection. Data collection techniques with observation, documentation. The data analysis carried out in this study were reduction, data presentation and conclusion drawing. The results revealed that there was an increase in teachers in making learning devices in each cycle. The results of this study indicate that the implementation of the workshops can improve the ability of teachers to compile syllabus and lesson plans as well as increase the number of teachers in preparing these tools. What is expected is achieved.
Otrouha: A Corpus of Arabic ETDs and a Framework for Automatic Subject Classification

Although the Arabic language is spoken by more than 300 million people and is one of the six official languages of the United Nations (UN), there has been less research done on Arabic text data (compared to English) in the realm of machine learning, especially in text classification. In the past decade, Arabic data such as news, tweets, etc. have begun to receive some attention. Although automatic text classification plays an important role in improving the browsability and accessibility of data, Electronic Theses and Dissertations (ETDs) have not received their fair share of attention, in spite of the huge number of benefits they provide to students, universities, and future generations of scholars. There are two main roadblocks to performing automatic subject classification on Arabic ETDs. The first is the unavailability of a public corpus of Arabic ETDs. The second is the linguistic complexity of the Arabic language; that complexity is particularly evident in academic documents such as ETDs. To address these roadblocks, this paper presents Otrouha, a framework for automatic subject classification of Arabic ETDs, which has two main goals. The first is building a Corpus of Arabic ETDs and their key metadata such as abstracts, keywords, and title to pave the way for more exploratory research on this valuable genre of data. The second is to provide a framework for automatic subject classification of Arabic ETDs through different classification models that use classical machine learning as well as deep learning techniques. The first goal is aided by searching the AskZad Digital Library, which is part of the Saudi Digital Library (SDL). AskZad provides other key metadata of Arabic ETDs, such as abstract, title, and keywords. The current search results consist of abstracts of Arabic ETDs. This raw data then undergoes a pre-processing phase that includes stop word removal using the Natural Language Tool Kit (NLTK), and word lemmatization using the Farasa API. To date, abstracts of 518 ETDs across 12 subjects have been collected. For the second goal, the preliminary results show that among the machine learning models, binary classification (one-vs.-all) performed better than multiclass classification. The maximum per subject accuracy is 95%, with an average accuracy of 68% across all subjects. It is noteworthy that the binary classification model performed better for some categories than others. For example, Applied Science and Technology shows 95% accuracy, while the category of Administration shows 36%. Deep learning models resulted in higher accuracy but lower F-measure; their overall performance is lower than machine learning models. This may be due to the small size of the dataset as well as the imbalance in the number of documents per category. Work to collect additional ETDs will be aided by collaborative contributions of data from additional sources.
Number of reply comments (User Comments/Interactions)

The variable ‘number of reply comments’ is an indicator of interactivity in online discussions. The number of reply comments is a simple measure of how much response a user comment has received. It is applicable if platforms that host comment sections offer the technical possibility to users to respond directly to existing user comments. The reply comments (also called ‘sub-level comments’ or ‘child comments’) then usually appear indented below the existing user comment they refer to (also called ‘top-level comment’ or ‘parent comment’). The measure does not provide information about the quality of the interaction between the commenters. It neither covers interactivity that occurs “outside” of comment threads below top-level comments, i.e. commenters responding in new top-level comments instead of sub-level comments. Field of application/theoretical foundation: Normative approaches to discourse ethics (e.g. Habermas, 1992) evaluate interactivity as a prerequisite for high-quality discourses. Example studies: Medium Measure Unit of analysis Studies Online; online discussions below news posts Number of reply comments (sub-level comments) to a top-level comment Individual user comments Naab &amp; Küchler (work in progress) Info about variables Variable name/definition: Anzahl der Antwortkommentare auf einen Nutzerkommentar Operationalization/coding instructions: Manuell: Zählen Sie die Kind-Kommentare (Antwortkommentare, Second-Level-Kommentare), die zu einem Eltern-Kommentar (Top-Level-Kommentar) verfasst wurden und tragen die Anzahl ein. Automatisiert: Sofern ein Datensatz alle Nutzerkommentare eines Kommentarthreads, Informationen über das Eltern- bzw. Kind-Level jedes Kommentars sowie eine Zuordnung aller Kind-Kommentare zu einem Eltern-Kommentar enthält, ist es möglich, die Anzahl der Kind-Kommentare für jeden Eltern-Kommentar per Auswertungssoftware zu aggregieren. Level of analysis: Kommentarthread (Eltern-Kommentar + alle zugehörigen Kind-Kommentare/Antwortkommentare) References Naab, T.K. &amp; Küchler, C. (work in progress). Unveröffentlichtes Codebuch aus dem DFG-Projekt „Gegenseitige Sanktionierung unter NutzerInnen von Kommentarbereichen auf Nachrichtenwebseiten und auf Facebook“. Augsburg. Habermas, J. (1992). Faktizität und Geltung: Beiträge zur Diskurstheorie des Rechts und des demokratischen Rechtsstaates. Suhrkamp.