Reviewerly/exHarmony huggingface dataset:
SISTEM INFORMASI MANAJEMEN DOKUMEN MENGGUNAKAN METODE PROTOTYPING PADA PT. BANGUN INDAH SAPUTRA

PT. Bangun Indah Saputra is a service company that serves the process of making documents. The purpose of this study is to provide convenience in the management of document maker data. In addition, data security and accuracy are more guaranteed and human resources become more efficient. The research methodology used is Grounded Research method with data collection techniques, namely observation and literature studies that are relevant to the rental system. To build this system is used system design tools that are data flow chart (DAD) context, Zero and detail and by using Java programming language with Netbeans and MySQL database using XAMPP. This system can facilitate the work of the admin in the record so as to increase the effectiveness and consistency of the company PT. Bangun Indah Saputra
PENGUJIAN USER ACCEPTANCE TEST PADA APLIKASI BANGBELI

The development of the Bangbeli application is one of the efforts to increase the number of users. However, to ensure that these changes and additions meet the users' needs, user validation is required to verify that the developed application meets the defined business requirements and functionalities, thereby providing benefits to both the company and end users. User acceptance testing aims to determine the respondents' feedback on a system that has been created. The results of this testing yield the user acceptance test results, which consist of three aspects: design interface, user-friendliness, and efficiency. The agreement percentages for each aspect are 69.64%, 71.12%, and 68.76% respectively.
PENERAPAN ALGORITMA NAÏVE BAYES CLASSIFIER MENGGUNAKAN R-PROGRAMMING UNTUK PENGELOMPOKAN JENIS KELUHAN APLIKASI PLN MOBILE SECARA OTOMATIS GUNA MENINGKATKAN KEPUASAN PELANGGAN

The PLN Mobile application was first released on the Google Play Store and App Store in 2016 by the PLN Board of Directors and was relaunched with additional features in 2020. This application was created to realize customer satisfaction from the services provided by PLN. However, in practice there are still complaints from customers and many are written in the comments column on the Google Play Store and App Store platforms. From the many comments, management wants to absorb all aspirations for improvement in increasing customer satisfaction. Management wants to know the statistics on the types of complaints categories reported. Due to the large number of comments, a method is needed to find out the category of disturbance automatically without having to read it one by one. This study offers the Naïve Bayes Classifier algorithm using R programming to provide the required complaint category statistics. Based on the algorithm system that was built, the categorization results obtained are in accordance with the contents of the customer comment messages. With these results, categories of customer comments can be generated automatically, making it easier for management to obtain statistical data related to complaints.
Characteristics and Management of Drainage Infrastructure in Medan Sunggal District, Medan City

Climate change, characterized by high-intensity rainfall, coupled with inadequate drainage systems, small and shallow river dimensions, and a lack of community awareness, has caused flooding and inundation in Medan Sunggal District. This study aims to understand the characteristics and management of drainage infrastructure in Medan Sunggal Subdistrict, Medan City, to identify its characteristics and implement suitable management efforts. The research adopts a positivism paradigm with a positivistic approach, relying on empirical facts (sensual empiricism). The research methodology used is purely qualitative descriptive, focusing on an in-depth understanding related to the characteristics, context, and research subjects. Data collection methods include Guest Tour and comparative techniques. The results of this study show that the characteristics of drainage infrastructure in the study area form a network pattern. The types of channels in the study area are primary channels, secondary channels, and tertiary channels. They consist of artificial channels with open concrete construction, located above the ground with a combined drainage system. While most of the physical conditions are good, some exhibit minor damage. A significant portion of the drainage water is stagnant. Flood-prone areas constitute 41%, areas with infrequent flooding are at 43%, and areas that have never experienced flooding are at 16%. Management recommendations for the study area include providing green open spaces, creating biopore infiltration holes, constructing detention and retention ponds, using paving blocks/grass blocks, conducting maintenance (normalization and rehabilitation) of drainage, and involving the community in each management aspect.
Development of Interactive Virtual Tour Based on 360-Degree Panorama Technology at the Bandung City Museum

Virtual tours have been widely used to introduce sites or buildings, but not much in education and tourism fields. The Covid-19 Pandemic has encouraged the growth of digitalization in all fields, including the development of museum virtual tours as an effort to provide visitor access among various restrictions. Along with these developments, the Bandung City Museum seeks to present an interesting museum virtual tour that can provide the best experience to its user. The purpose of this research is to find out the development and evaluation of an Interactive Virtual Tour Based On 360-Degree Panorama Technology At The Bandung City Museum. The research method used is Research and Development, with an analysis of potential and problems to improve the final product. The Virtual Tour allows users to navigate around the Museum building and listen to the narration, as well as read brief information about each object. For improvement, the virtual tour was also evaluated for usability by the users. Overall responses show that the virtual tour received positive feedback and was able to create satisfaction for the users, with several things to improve such as sound, images, and navigation quality.
Siamese network with contrastive learning and adaptive template updating for object tracking

Visual object tracking is a crucial task across numerous computer vision applications. However, object tracking algorithms face significant challenges stemming from deformation and fast motion, which frequently incur dramatic changes to the target’s appearance. To address this problem, we propose a Siamese-network-based object tracking method that combines contrastive learning and adaptive template updating. First, we designed a contrastive branch based on a Siamese network, which constructs a contrastive network with a template branch. The objective of this network is to capture the invariance associated with different images of the same target. Subsequently, we implemented an adaptive template updating strategy for the timely capture of appearance changes in targets and adjusted the size and position of the bounding box. Finally, the α-complete intersection over union function was introduced to continuously optimize the generation of bounding boxes during training, guiding the model to produce more accurate tracking boxes and further improving the algorithm performance. The experimental results demonstrate that our algorithm achieves advanced performance on five datasets, namely GOT-10k, LaSOT, UAV123, OTB2015, and NFS.
Lexicon of Wild Plants in Gempol Village, Limbangan District, Kendal Regency: An Ecolinguistic Study

Gempol Village, Limbangan District, Kendal Regency is located at the foot of Mount Ungaran. The people of Gempol Village are people who are familiar with the lexicon of wild plants. This lexicon is still maintained from generation to generation. This research aims to determine the level of intergenerational community knowledge of the wild plant lexicon. The lexicon of wild plants in this research was further narrowed down to a lexicon of wild plants that are used for consumption. This study uses a qualitative approach and is assisted with quantitative data to calculate the percentage of understanding of the wild plant lexicon. The lexicon list was obtained using interview techniques with key informants to find out the lexicon of wild plants in Gempol Village. Then data was collected through a questionnaire filled out by the people of Gempol Village. Based on the results obtained, age group I (6-25 years) in the K (Know) category obtained a percentage of 78%. Age group II (26-45) got a percentage of 94%, while age group III (46-90) knew 100% of the wild plant lexicon. This shows that the people of Gempol Village still maintain a lexicon of wild plants in communicating in everyday life.
Generation of Independence for Classification in the Bio-inspired Networks

Machine learning, deep learning and neural networks are extensively developed in many fields, in which neural network architectures have shown a variety of applications. However, there is a need for explainable fundamentals in complex neural networks. In this paper, it is shown that bio-inspired networks are useful for the explanation of network functions. First, the asymmetric network is created based on the bio-inspired retinal network. They have orthogonal bases which correspond to the Fourier bases. Second, the classification performance of the asymmetric network is compared to the conventional symmetric network, which is developed as a biological model for the sensory processing. Further, the higher dimensional orthogonal bases are generated and their replacement operations are shown to be useful for the classification. It is shown that the generation of higher dimensional independence is realized in the layered networks using Shur complement.
Probabilistic seismic-hazard analysis for the western Kingdom of Saudi Arabia

First posted December 29, 2023 For additional information, contact: Volcano Science Center - Menlo ParkU.S. Geological Survey345 Middlefield Road, MS 910Menlo Park, CA 94025Contact Pubs Warehouse We present a probabilistic seismic-hazard analysis (PSHA) for the west-central part of the Arabian Peninsula. Our study area includes the northern Harrat Rahat volcanic field and the nearby city of Al Madīnah, Kingdom of Saudi Arabia. This young, active volcanic field experienced one historical eruption in 1256 C.E. (654 in the year of the Hijra) that vented 20 to 22 kilometers (km) southeast of the center of Al Madīnah, which has a present population of about 1.4 million. The field also erupted numerous times in the late Pleistocene and possibly in the early Holocene. We used recently developed regional ground-motion prediction equations for Saudi Arabia to calculate the severity of ground shaking as a function of distance from the earthquake source. This information was combined with two key volcanic parameters for this area: (1) the return period of volcanic eruptions and (2) the spatial probability of the next vent opening. The calculated ground-motion levels of peak ground acceleration and peak ground velocity with a 2-percent probability of exceedance in 50 years are expected to be about 0.14 the acceleration due to gravity (g) and 10 centimeters per second (cm/s), respectively, at the most probable vent opening location, about 25 km southeast of Al Madīnah’s center, and about 0.07 g and 3 cm/s, respectively, in the city interior. These ground motions are higher than previous estimates that did not consider the nearby earthquakes associated with volcanic activity.
PENGEMBANGAN MEDIA PEMBELAJARAN BERBASIS TI MENGGUNAKAN CANVA BAGI GURU DI SMA PGRI BLAHBATUH PLUS PARIWISATA (PARISMA)

Canva is a design application that uses drag and drop techniques and can access several existing features such as fonts, images and shapes during the process of making learning media with the rapid development of technology, there is a need for training at SMA PGRI Blahbatuh Plus Pariwista (Parisma) because there are still many educators who have not maximized in mastering the use of Canva as a means of making learning media.&#x0D;
Using Gray Literature to Influence Software Engineering Curricula

Software engineering (SE) evolves rapidly, with changing technology and industry expectations. The curriculum review bodies (e.g., ACM and IEEE-CS working groups) respond well but can have refresh cycles measured in years. For Computer Science and SE educators to be agile, predictive, and adapt to changing technology trends, judicious use of gray literature (GL) can be helpful. Other fields have found GL useful in bridging academic research and industry needs. GL can be extended to SE to aid faculty preparing students for industry. We address two questions: first, given the velocity of technical change, do current curricular guidelines accurately reflect industry practice and need for our graduates? Second, how can we track current and emerging trends to capture relevant competencies? We argue a study of the scholarly literature will have a limited impact on our understanding of current and emerging trends and curriculum designers would do well to utilize GL. We close with recommendations for SE educators.
Fast Inference of Mixture-of-Experts Language Models with Offloading

With the widespread adoption of Large Language Models (LLMs), many deep learning practitioners are looking for strategies of running these models more efficiently. One such strategy is to use sparse Mixture-of-Experts (MoE) - a type of model architectures where only a fraction of model layers are active for any given input. This property allows MoE-based language models to generate tokens faster than their dense counterparts, but it also increases model size due to having multiple experts. Unfortunately, this makes state-of-the-art MoE language models difficult to run without high-end GPUs. In this work, we study the problem of running large MoE language models on consumer hardware with limited accelerator memory. We build upon parameter offloading algorithms and propose a novel strategy that accelerates offloading by taking advantage of innate properties of MoE LLMs. Using this strategy, we build can run Mixtral-8x7B with mixed quantization on desktop hardware and free-tier Google Colab instances.
Grouping of Image Patterns Using Inceptionv3 For Face Shape Classification

The human face is an extraordinary part where nearly everybody is not quite the same as each other. One perspective that should be visible plainly is the shape. Face shape grouping can be used for amusement, security, or excellence. One technique that can be utilized in picture grouping is the InceptionV3 model. InceptionV3 is the structure of the Convolutional Neural Network (CNN) created by Google, which can tackle picture examination and item discovery issues. This engineering is utilized to order face shapes into five classes: Round, Heart, Square, Oblong, and Oval. At that point, the Google Pictures dataset goes through the pre-handling stage, and the Shrewd Edge Identifier is applied to each picture. Hair turns into a commotion. Consider recognizing the side of the face because it does not make any difference what the hairdo resembles. What is important is the side of the face. When there is a dataset of elongated class and heart class with a comparable hairdo, InceptionV3 will identify the component and expect the two pieces of information to come from a similar class. The exchange learning strategy is done in preparation for the last Layer of ImageNet's InceptionV3 model. This strategy puts the high precision level with an exactness of 93% preparation and testing between 88% - 98%. InceptionV3 could arrange upwards of 692 from 747 datasets or around 92.65%. The most reduced information class is the heart class, where out of 150 information, InceptionV3 can characterize upwards of 130 information.
Analysis of Classification Algorithm Performance on User Review Sentiment of the Muamalat DIN Application

Banking applications have become an integral part of modern society. One such application is Muamalat DIN, launched by Bank Muamalat Indonesia with the aim of facilitating customers in conducting various transactions and activities. User reviews of this application vary widely, ranging from positive to negative comments. The purpose of this study is to evaluate user attitude on reviews of Bank Muamalat Indonesia's digital banking product, the Muamalat DIN application. This research offers insights into the efficacy of the SMOTE balancing technique compared to undersampling by utilizing a methodology that includes data collection via scrapping techniques, data preprocessing, and the application of Multi Layer Perceptron (MLP), XGBoost, and LightGBM classification algorithms. The results show that SMOTE-paired XGBoost works better for sentiment categorization. The study's conclusion emphasizes the significance of choosing the right data balancing method to increase sentiment analysis's accuracy in Islamic banking applications, which can be used as a foundation for strategies aimed at enhancing customer service and making decisions.
Lightweight Boosting Models for User Response Prediction Using Adversarial Validation

The ACM RecSys Challenge 2023, organized by ShareChat, aims to predict the probability of the app being installed. This paper describes the lightweight solution to this challenge. We formulate the task as a user response prediction task. For rapid prototyping for the task, we propose a lightweight solution including the following steps: 1) using adversarial validation, we effectively eliminate uninformative features from a dataset; 2) to address noisy continuous features and categorical features with a large number of unique values, we employ feature engineering techniques.; 3) we leverage Gradient Boosted Decision Trees (GBDT) for their exceptional performance and scalability. The experiments show that a single LightGBM model, without additional ensembling, performs quite well. Our team achieved ninth place in the challenge with the final leaderboard score of 6.059065. Code for our approach can be found here: https://github.com/choco9966/recsys-challenge-2023.
Performance And Functional Testing With The Black Box Testing Method

Software testing is an essential stage in software development because it plays a role in maintaining the quality of the software produced. The objective of software testing is for verification and validation, namely ensuring that the software being developed works according to the expected functions when the software is designed. In addition to improving quality, the software being developed must also have minimal errors and test whether the software is feasible to use or not. This research employed the black box testing method. Black box technical testing was a test of the input or output functionality of the software. The research also described the testing model using automated testing, which was carried out by Apache JMeter tools on performance tests and Katalon Studio to functional tests on the Perbanas portal. The final results of this research depicted the test model from studying business processes, creating test scenarios for automated testing to analyzing the test results. The performance test results aimed to find out how much throughput (transactions per second) and Response Time are. Meanwhile, functional test results aimed to find out whether the expected functions and outputs were appropriate or not. The results of the performance test on the login feature that had been carried out, the best was taken, i.e., sample data that entered approximately 5000 samples for 250 users for a load test per 5 minutes; only 0.06% failed with an average of 15 transactions per second (TPS) by a maximum response time of 68 seconds and a minimum response time of 0.2 seconds. KEYWORDS: Apache JMeter, automation test, black box test, functional test, Katalon Studio, performance test
Design Of Public Facilities For Persons With Disabilities At Al-Azizi Mosque, Batam City Using The Axiomatic Design (AD) Method

Humans are special creatures both physically and intellectually. Humans have the ability to adapt, but not everyone will be able to make good adjustments, especially people with disabilities. It is known that out of a total of 7 billion world population in 2021, 15% of them are persons with disabilities. Based on data on persons with disabilities released by the Ministry of Social Affairs of the Republic of Indonesia, it is known that in the Riau Archipelago as many as 2733 residents are persons with disabilities. Physical illness or movement disorder is the most common disease among other diseases experienced by persons with disabilities in Indonesia. At present the accessibility needs of persons with disabilities in public buildings such as mosques should have met the needs of persons with disabilities but the reality on the ground shows that there are still minimal accessibility facilities in places of worship, especially mosques. Al-Azizi Mosque which is located in RT. 01 RW. 021 Tanjung Sengkuang Kec. Batu Ampar - Batam is currently still not paying attention to the accessibility of persons with disabilities. The purpose of this study is to design public facilities for Persons with Disabilities at the Al-Azizi Mosque in Batam City using the Axiomatic design (AD) method. The Axiomatic Design (AD) method is carried out by defining the basis for product development/design by providing a mapping technique between the function requirements and design parameters. This method can help so that the design and development of a product is more structured, logical, and focuses on a design that fits the function. It is hoped that with this research a public facility design can be formed that is able to accommodate the needs of disabled mosque users.
Developing Local Wisdom-Based Instructional Materials in Minangkabau Context for English for Tourism Course

This study aims to develop a model of local wisdom-based instructional materials in Minangkabau context for the English for Tourism course. To realize the aim, an R&amp;D design was applied by adapting Borg &amp; Gall’s first four stages, namely product analysis, initial product development, expert validation, and product revision. Product analysis includes analyzing the characteristics and needs of students towards the teaching materials; b) interviews with competent resource persons to obtain input for initial product development; c) a review of the relevant theory of initial product development. Initial Product Development includes formulating core topics, designing syllabus, gathering resources for designing draft, and designing, editing and printing prototypes. Validation was conducted to figure out whether the prototype model had integrated Minangkabau local wisdom in teaching materials for the course and was suitable for learning into speaking. The product analysis stage resulted in initial product development in the form of a prototype consisting of 14 units, where each unit consists of 4 parts, namely: introduction, common expressions, sample conversations, and role play. The validation results confirm that, in general, in terms of the relevance of teaching materials to course objectives, the prototype was valid (3.15 out of 4) and very valid (4.03 out of 5). In addition, in terms of the principles of learning speaking skills, the prototype was very valid (3.66 out of 4). Furthermore, from the aspect of integrating Minangkabau local wisdom into teaching materials, this prototype has provided a model for practical conversations for tour guiding activities in Minangkabau context.