Reviewerly/exHarmony huggingface dataset:
SGD Implicitly Regularizes Generalization Error

We derive a simple and model-independent formula for the change in the generalization gap due to a gradient descent update. We then compare the change in the test error for stochastic gradient descent to the change in test error from an equivalent number of gradient descent updates and show explicitly that stochastic gradient descent acts to regularize generalization error by decorrelating nearby updates. These calculations depends on the details of the model only through the mean and covariance of the gradient distribution, which may be readily measured for particular models of interest. We discuss further improvements to these calculations and comment on possible implications for stochastic optimization.
Shifting Left for Machine Learning: An Empirical Study of Security Weaknesses in Supervised Learning-based Projects

Context: Supervised learning-based projects (SLPs), i.e., software projects that use supervised learning algorithms, such as decision trees are useful for performing classification-related tasks. Yet, security weaknesses, such as the use of hard-coded passwords in SLPs, can make SLPs susceptible to security attacks. A characterization of security weaknesses in SLPs can help practitioners understand the security weaknesses that are frequent in SLPs and adopt adequate mitigation strategies. Objective: The goal of this paper is to help practitioners se-curely develop supervised learning-based projects by conducting an empirical study of security weaknesses in supervised learning-based projects. Methodology: We conduct an empirical study by quantifying the frequency of security weaknesses in 278 open source SLPs. Results: We identify 22 types of security weaknesses that occur in SLPs. We observe ‘use of potentially dangerous function’ to be the most frequently occurring security weakness in SLPs. Of the identified 3,964 security weaknesses, 23.79 % and 40.49 % respectively, appear for source code files used to train and test models. We also observe evidence of co-location, e.g., instances of command injection co-locates with instances of potentially dangerous function. Conclusion: Based on our findings, we advocate for a shift left approach for SLP development with security-focused code reviews, and application of security static analysis.
Minimum standards for evaluating machine-learned models of high-dimensional data

The maturation of machine learning and technologies that generate high dimensional data have led to the growth in the number of predictive models, such as the "epigenetic clock". While powerful, machine learning algorithms run a high risk of overfitting, particularly when training data is limited, as is often the case with high-dimensional data ("large p, small n"). Making independent validation a requirement of "algorithmic biomarker" development would bring greater clarity to the field by more efficiently identifying prediction or classification models to prioritize for further validation and characterization. Reproducibility has been a mainstay in science, but only recently received attention in defining its various aspects and how to apply these principles to machine learning models. The goal of this paper is merely to serve as a call-to-arms for greater rigor and attention paid to newly developed models for prediction or classification.
Flight Simulation and Control of a Quadrotor based on MATLAB/Simulink

Nowadays anyone can fly Unmanned Aerial Vehicle (UAV) and land it according to the specified instructions drafted by the manufacturer. However, the controlling phase is growing day by day as one of the crucial roles of UAV. Obtaining control for autonomous landing is the crucial and critical step. So based on various literature surveys and centering into Industry 4.0, this proposed work deals with image flight simulation and control of Quadrotor, which is an important field of Industry 4.0 in future production and business power. This research is eyed on Quadrotor, a type of flying vehicle with four rotor blades wherein the opposite pairs rotate in alternate direction, which is very useful for vertical take-off and landing. The Quadrotor is created by using CATIA software which is best suited for modelling and developing real time application. The model is extracted in MATLAB/SIMULINK in which a variety of blocks are available under the set of control and aerospace blocks. Then, a suitable simulation environment and controller are made. The advantage of making this proposed work in MATLAB is that it has the features of testing, controlling, and maintaining various operations without equipping any mechanical components, and there is no risk for property or lives.
Analisis Predictive Maintenance Peralatan Lab Berbasis Machine Learning

The rapid development of AI is also supported by our entry into the digital era and the Internet of Things (IoT). In using laboratory equipment, students are required to comply with the rules so that the equipment can be maintained properly. However, the tool used will cause thirst for the tool. This becomes a problem when the tool is needed for learning, while the tool does not function properly or is completely damaged. The research method used in Predicting Labor Equipment of the Department of Electronics FT-UNP is the Cross-Industry Standard Process for Data Mining (CRISP-DM) development method. CRISP-DM is a very reliable model. By utilizing Predictive Maintenance technology on each existing equipment, we can analyze data to identify damage with failure mode, so as to obtain data regarding the frequency of occurrence of damage and the severity of damage to labor equipment and setting a warning for labor technicians, at this time there will be an alarm for technicians to perform checking of equipment.
PKM Pendampingan dan Pelatihan Microsoft Office untuk Meningkatkan Keterampilan Santri Pesantren Nurul Hidayah

The development of technology has helped a lot of human work. One of the things that we can enjoy from these technological developments include Microsoft Word, Microsoft Excel and power points. Microsoft Word, functions as a word processing software includes creating, editing, and formatting documents. The students have not been able to operate Microsoft word, Excel and Power Point because they are not taught at school, the high cost of computer courses among students. One of them is to train the ability to use a word processing application, namely Microsoft Word. Community service activities are emphasized in the form of training on how to apply Microsoft Office for students of the Nurul Hidayah Islamic Boarding School. It is hoped that with this training, students can know more about the basic techniques of using Microsoft Office by utilizing Microsoft Word, Microsoft Excel, Microsoft Power Point. The results of the service activities carried out provide experience and skills for students in using Microsoft Office. Thus, the implementation of community service activities at the Nurul Hidayah Islamic Boarding School Foundation Using Microsoft Office provides significant benefits for improving the skills of students in utilizing information technology and computers. The students were very enthusiastic about participating in further training activities. The students already understand and can run Microsoft Office applications.
Klasterisasi Pasien Rawat Inap Peserta BPJS Berdasarkan Jenis Penyakit Menggunakan Algoritma K-Means

Medical records of patients from the Health Insurance Administering Body (BPJS) consist of complete patient data along with a complex history of patient services stored in every health facility. Inpatient medical record data contains important data as well as contains useful information as new knowledge using data mining techniques. This study aims to assist and provide new information related to the clustering of BPJS inpatients at the Arifin Achmad Hospital, Riau Province, so as to obtain information related to the spread of the patient's disease. The data used are medical records of inpatients in 2021. The data obtained are then processed using the K-Means clustering algorithm with a total of 3 clusters. The study resulted in cluster K1 dominated by Malignant neoplasm, breast, unspecified (C50.9) and Non-Hodgkin's lymphoma, unspecified type (C85.9) disease. Cluster K2 is dominated by fracture of neck of femur, closed (S71.00) and Dengue haemorrhagic fever (A91).
PKM Pelatihan dan Pendampingan Literasi (Baca Tulis) untuk Meningkatkan Mutu Pendidikan bagi Siswa MI Tarbiyatul Islam

Education 4.0 does not only focus on the use of technology, but students' reading interest also needs to be improved to meet Education 4.0. The rapid flow of information and technology in the 4.0 education era has an impact on the limited time that students have to read. In fact, students' literacy skills in reading and writing can certainly be indispensable for students to keep abreast of all developments, especially those related to their education. Reading is one of the important things in all kinds of learning processes. Through reading various sciences, which can lead to success, we can get. This article aims to describe the implementation of the reading literacy movement for elementary school students at MI Tarbiyatul Islam Kandang Jati Kulon. From the initial observations, it was shown that the teachers at the school were still passive in carrying out the reading and writing literacy movement. The teachers at Madrasah Ibtidaiyah (MI) have not actively paid attention to efforts to increase students' reading literacy. Through various fun activities for students, and trying to foster a love of reading and writing in students through the application of reading and writing literacy movements. Proven enthusiasm in participating in the training from beginning to end, the results of this training and mentoring show that through fun activities as an effort to implement the reading literacy movement, students become more enthusiastic and enthusiastic to increase interest in reading.
PEMBERIAN E-SERTIFIKAT UNTUK MENINGKATKAN SEMANGAT BELAJAR SISWA DI SDN SIMOKERTO I/134 MASA PANDEMI COVID-19

The purpose of this study was to determine the increase in students' enthusiasm for learning in terms of collecting assignments through the provision of e-certificates in Simokerto I/134 Elementary School in Surabaya during Covid-19 pandemic. The provision of this e-certificate is to increase student responsibility in working on collecting assignments on time. Considering that during online learning there are many obstacles experienced by students including device and internet network problems. In addition, students are more interested in online games than doing assignments given by the teacher. The results of this study explained that the enthusiasm of the second grade students of SDN Simokerto I/134 Surabaya in doing assignments and collecting them increased through the provision of e-certificates. Students compete to give their best and on time to get the e-certificate. This provision can be considered as a reward so that students will increase their enthusiasm for learning, along with that student learning outcomes also increase. For this reason, in learning, the teacher should provide a new innovation so that students are more interested and enthusiastic in participating in learning in class.
PENINGKATAN MOTIVASI BELAJAR SISWA MELALUI LKPD INTERAKTIF BERBASIS LIVEWORKSHEETS DALAM PEMBELAJARAN ONLINE

This study aims to increase students' motivation for learning during online learning during the pandemic. In addition, by increasing the motivation for learning, it is also expected to increase student learning outcomes through the use of interactive worksheets based on live worksheets. The subjects of this study were fourth grade students at SDN Kapasan V/147 Surabaya. This study uses quantitative and qualitative descriptive methods. The research instruments used include questionnaires, tests, and observations. In the first cycle, the result of teacher activity was 84%, while student activity was 72%, and for students' motivation for learning, it was 81%. In Cycle II, the results of the study increased, namely teacher activity increased to 90%, student activity increased to 88%, and student motivation for learning increased to 92%. From these results, it can be concluded that the use of interactive worksheets based on live worksheets can increase students' motivation for learning in online learning.
ANALISIS KEBUTUHAN PENGEMBANGAN E-MODUL BIOLOGI BERBASIS SOLUSI PEMBELAJARAN MEDIA INTERAKTIF DI ERA PANDEMI

This study aims to obtain initial data on the need to develop interactive media-based e-modules at the junior high school level, because of the need for a medium during the COVID-19 pandemic which has had a major impact on almost all sectors, including education which requires educators to be creative in developing learning resources, especially online learning resources. The method used in this research is descriptive qualitative by using several samples from all students of SMP/MTs in Malang, while the sample used includes 30 students of class IX in MTs. Al Itihad Poncokusumo, 30 Class IX students at SMPN 2 Tumpang, 15 students at SMP PGRI Tumpang Class IX and 15 Class IX students at SMPN 1 Jabung. Data collection techniques were carried out using observation, distributing questionnaires and interviews. Data were analyzed using descriptive analysis. The results of the needs analysis test showed that 93.57% of students stated that they felt they needed interesting learning media and could make it easier to understand the material with a score and 93.67% of students agreed that there was an e-module to facilitate learning. Meanwhile, all teachers agreed on the need to develop e-books, e-modules and other types of electronic teaching materials, so that online-based teaching materials are needed to support the learning process in the era of the COVID-19 pandemic. There is a need for the development of interactive media-based e-modules as a learning solution in the pandemic era. The results of this needs analysis test can be used as basic data for the development of interactive media-based e-modules.
PEMANFAATAN MEDIA SWAY DALAM PEMBELAJARAN DARING UNTUK MENINGKATKAN SEMANGAT BELAJAR SISWA

The purpose of this research was to increase students' enthusiasm for learning during online learning. Students feel bored with the type of task given by the teacher which were monotonous. In addition, students are often late in collecting assignments given by the teacher. It takes media or the help of interesting props so that students are excited. Sway media included creative media that can increase students' enthusiasm for learning. This research included classroom action research with the subject of class II students at SDN Simokerto V/138 Surabaya. The results showed that students' enthusiasm for learning had increased. In the first cycle, 72% of students were enthusiastic about participating in learning, increasing to 95% in the second cycle. In addition, the activities of teachers and students also increased. It can be concluded that the use of media sway can increase the learning spirit of class II students at SDN Simokerto V/138 Surabaya.
PEMEROLEHAN BAHASA INDONESIA SEBAGAI B2 (BAHASA KEDUA) PADA ANAK DOWN SYNDROME DI LKS DARUL AZHAR

This study aims to determine the acquisition of Indonesian as a second language in children with Down syndrome. This research is important to be improved in order to improve the ability to speak Indonesian because it is the language of unity in Indonesian society. The research used qualitative method with samples obtained from 20 children with special needs at the LKS Darul Azhar orphanage through interviews and dialogue with children with special needs at the LKS Darul Azhar orphanage. These children are Down syndrome children who are introduced to Indonesian as B2 or a second language to learn, although not as fast as ordinary children. Environmental support and teaching methods for acquiring a second language greatly affect the tempo of acquiring B2. The acquisition of a second language (Indonesian) in Down Syndrome children needs to be developed because it has a positive impact on the development of communication which is also supported by the process of acquiring learning through training in vowel errors, preliminary tests through pronunciation of words and expressions, finding and characterizing lexical and grammatical.
EFEKTIVITAS PENGGUNAAN MICROSOFT TEAMS DALAM PEMBELAJARAN DARING

This study aims to determine the effectiveness of using the Microsoft Teams application during online learning for third grade students at SDN Simokerto VI/139 Surabaya. Microsof t Teams was an application that has been used as an online learning medium during the COVID-19 pandemic. The research method that has been used wass descriptive qualitative. Researchers collected data and then described respondents' answers about using the Microsoft Teams application. The research instrument used was a questionnaire and observation. The results showed that 29 students or 93% stated that it was easier to use Microsoft Teams in online learning. Microsoft Teams is also easily accessible to students during lessons. Through Microsoft Teams, it becomes easy for students to learn with easy access, and helps students learn during online learning. In addition, students more easily understand the material presented by the teacher so that it has an impact on good student learning outcomes. Students are more enthusiastic about learning because they can communicate with teachers and friends even though they are not face to face
PENINGKATAN KETERAMPILAN MEMBACA PERMULAAN MENGGUNAKAN POWER POINT DALAM PEMBELAJARAN DARING

The purpose of this study was to improve students' reading skills in the early reading aspect with the help of power points for first grade students at SDN Simokerto VI/139 Surabaya. Power point is made with a unique display accompanied by this animation which is expected to improve students' initial reading skills. The subjects in this study were 28 first grade students with data collection through tests and observations. The research used is PTK with two cycles. The results showed that there were differences in students' reading skills before and after using power point, where the students' skills in the first cycle during the initial introduction using power point obtained 71.4% results, then increased to 87.5% in the second cycle with increasing skills and the activeness of students in pre-reading activities using the help of power point teaching media, which showed an increase of 16.1%.
PENGGUNAAN APLIKASI FORM OFFICE 365 UNTUK MENINGKATKAN SEMANGAT BELAJAR SISWA DALAM PEMBELAJARAN DARING

The purpose of this study was to determine the increase in students' enthusiasm for learning in class I distance learning at SDN Wiyung I/453 Surabaya. In online learning, an application that supports and is easy to operate for students is needed, namely the Office 365 Form. This application is used to determine student learning outcomes and student responses after learning. The research method used is CAR with the instruments used are tests and observations. The results showed an increase in students' enthusiasm for learning during online learning cycle I and cycle II. Students show high motivation in learning. High enthusiasm for learning resulted in student learning outcomes also experiencing changes for the better. It can be concluded that the use of the Form Office 365 application in online learning can increase student enthusiasm and learning outcomes where in the first cycle 72% of students who do and submit assignments on time increase to 94% in the second cycle.
Data Mining Menggunakan Algoritma K-Means Clustering dalam Analisis Tingkat Potongan Harga Terhadap Harga Jual Sepeda Motor Honda

Knowledge Discovery in Database (KDD) has a structured analysis process to obtain the latest information. Data mining plays a role in extracting hidden information with one method, namely clustering. The purpose of this study was to determine the appropriate level of discount for each type of Honda motorcycle. The data processed in this study were sourced from the Marketing Main Dealer for Honda Motorcycles, West Sumatra. Furthermore, this data is processed by the Data Mining technique using the K-Means Clustering Algorithm. The processing stage is to determine the number of clusters and centroids, then calculate the distance between the centroid point and each object in the data. Predefined objects are grouped to determine cluster members based on distance. The calculation is continued until the resulting centroid value remains and the cluster members do not move to another cluster. The results of testing this algorithm are 3 clusters with 42 test data, in cluster 1 there are 34 types of vehicles that get discounted prices, then cluster 2 of 7 types of vehicles can get discounts and cluster 3 of 1 type of vehicles can not get discounts. The analysis of the test results has been able to determine the level of discount on the selling price of Honda motorcycles. By grouping customer interest data, it can be recommended to provide discounted sales prices in order to help marketing management increase sales of Honda motorcycles.
SmartKex: Machine Learning Assisted SSH Keys Extraction From The Heap Dump

Digital forensics is the process of extracting, preserving, and documenting evidence in digital devices. A commonly used method in digital forensics is to extract data from the main memory of a digital device. However, the main challenge is identifying the important data to be extracted. Several pieces of crucial information reside in the main memory, like usernames, passwords, and cryptographic keys such as SSH session keys. In this paper, we propose SmartKex, a machine-learning assisted method to extract session keys from heap memory snapshots of an OpenSSH process. In addition, we release an openly available dataset and the corresponding toolchain for creating additional data. Finally, we compare SmartKex with naive brute-force methods and empirically show that SmartKex can extract the session keys with high accuracy and high throughput. With the provided resources, we intend to strengthen the research on the intersection between digital forensics, cybersecurity, and machine learning.