bluuebunny/crossref_metadata_2025 huggingface dataset:
Pelatihan Microsoft Power Point Sebagai Media Pembelajaran Interaktif Untuk Meningkatkan Kompetensi Pendidik TKQ/TPQ Tanjung Priok
Authors: Badrul Mohammad , Budihartanti Cahyani , Dewi Yumi Novita , Septiana Laila
Published: August 2023

Pendidikan merupakan salah satu bidang yang dipengaruhi oleh teknologi informasi. baik dalam proses pembelajaran formal di sekolah maupun nonformal berupa pelatihan di luar sekolah. Masih adanya 60 % guru yang penguasaan TIK-nya masih kurang. Hal ini juga dirasakan oleh pendidik dan tenaga kependidikan di lingkungan POKJA TPQ/TKQ Kecamatan Tanjung Priuk. Keterbatasan guru dalam bidang TIK akan berakibat fatal dimasa sekarang yang pendidikan banyak menggunakan teknologi. Salah satu hambatan kegiatan pebelajaran yatu terbatasnya fasilitas yang dimiliki dan akses terhadap ilmu pengetahuan yang terus berkembang, antara lain keterampilan dalam penggunaan teknologi seperti Microsoft Power Point yang terkait dengan proses belajar mengajar. Microsoft Power Point merupakan program aplikasi yang banyak sekali digunakan untuk keperluan dalam belajar seperti untuk presentasi dan sebagainya. Aplikasi ini digunakan karena memiliki fasilitas dan kelebihan yang dapat memberikan kemudahan dalam membuat suatu presentasi yang efektif, professional dan menarik dan menyenangkan sesuai dengan kaidah pendidikan anak usia dini dan mengembalikan esensi pendidikan melalui inovasi media pembelajaran berbasis teknologi. Dengan adanya pelatihan pembuatan media pembelajaran yang menarik interaktif dengan menggunakan Microsoft power point diharapkan para peserta telah mendapatkan edukasi dan pembekalan materi yang dapat diaplikasikan untuk menunjang peningkatan kualitas para tenaga pendidik serta dapat meningkatkan mutu pendidikan pada pada POKJA TKQ/TPQ Kecamatan tanjung Priok,
Sosialisasi dan pelatihan pengisian spt pajak hotel kategori rumah kos di kampung dumpoh Kota Magelang
Authors: Nugraheni Agustina Prativi , Prihastiwi Diah Agustina , Pramudyastuti Octavia Lhaksmi
Published: August 2023

The economic development in Magelang City is growing rapidly with the presence of Tidar University, especially in RW VII Kampung Dumpoh, Potrobangsan Village. This development can be seen especially in the increasing number of room rental businesses. The growing number of students living in Magelang, especially in Kampung Dumpoh, is driving the economic growth of the community. On the other hand, many owners of room rental businesses are not aware that they are obligated to collect and report taxes on room rentals. Knowledge about tax calculation and reporting is also lacking among the community. Based on this phenomenon, this Community Service Program aims to increase awareness and compliance of room rental business owners regarding the importance of reporting taxes through socialization and training. Additionally, this program will provide training on tax calculation, filling, and reporting of the tax for the room rental business
ANALYSIS OF SENTIMENT OF INDONESIAN COMMUNITY ON METAVERSE USING SUPPORT VECTOR MACHINE ALGORITHM
Authors: Sumayah Siti , Sembiring Falentino , Jatmiko Wisuda
Published: August 2023

Metaverse was widely discussed right on October 28, 2021, when Mark Zuckerberg announced the company name change from Facebook to Meta. Regarding the sophisticated Metaverse concept, it is possible to make the pros and cons between the Indonesian people. This information is widely distributed in various media crews, one of which is Twitter social media. Tweets from social media can be used to obtain data and information as material for research on sentiment analysis. This study aims to determine the response of the Indonesian people to the Metaverse. Material data was obtained from Twitter tweets with keywords or Metaverse queries. Research conducted by the Support Vector Machine Algorithm in research with TF-IDF word weighting, the tests carried out with the results of the class division of positive sentiment 70.69%, neutral 15.85%, negative 13.46% will produce values ​​of accuracy, precision, recall, and f1-score. They use various data, namely, 90% training data and 10% test data. The result is high accuracy in testing many data, 2504 data, and the accuracy value is 81%, with an average value of 79% precision, 63% recall, and 57% f1-score.
IMPLEMENTATION OF FUZZY TSUKAMOTO LOGIC TO DETERMINE THE NUMBER OF SEEDS KOI FISH IN THE SUKAMANAH CIANJUR FARMER`S GROUP
Authors: Farhan Deden , Sulianta Feri
Published: August 2023

One of the innovation programs of the Sukamanah Village Karangtengah Cianjur farmer group is in the field of fisheries. One of the programs carried out is the nursery for ornamental Koi fish. Nursery of Koi fish is done because the market demand for Koi fish is high, but there are still very few Koi fish providers. However, farmer groups are currently unable to determine the number of seeds that must be provided to meet market needs to obtain maximum profit. To overcome this, a system is required that can calculate the number of seeds needed based on fish supply and market demand. Fuzzy logic can help humans make decisions; besides, fuzzy logic is an appropriate way to map an input space into an output space. This research aims to build an application using fuzzy logic to determine the number of seeds needed based on the amount of supply and market demand for Koi fish. The data used is sourced from the Sukamanah Farmer’s group, Cianjur. The results showed that using fuzzy logic succeeded in predicting the number of koi fish seeds that must be provided with an accuracy rate of 94,78% using the MAPE method.
IMPLEMENTATION OF CERTAINTY FACTOR METHOD IN PEST AND DISEASE DIAGNOSIS IN HYDROPONIC PLANTS
Authors: Syahreza Riski Afdhalis , Hutahaean Jeperson , Afrisawati Afrisawati
Published: August 2023

Pest and disease attacks often occur in hydroponic plants so that many plants are damaged and result in losses for farmers or crop failure. The problem of pests and plant diseases is the main obstacle in increasing agricultural productivity, these conditions affect farmers' income and the provision of hydroponic plant food. The farmers do not know what types of pests and symptoms of diseases attack plants, making it difficult to handle diseases on hydroponic plants. Likewise for hydroponic plants located at the Agricultural Service of Asahan Regency which are attacked by pests, hydroponic experts say that the appearance of small leaf spots appears on the upper side of the leaves that damage hydroponic plants and because the cause of pests that cause disease in hydroponic plants is unknown, so farmers are hesitant to take countermeasures. An expert system is a computer program designed to make decisions such as decisions taken by an expert or expert. Therefore, an expert system with the Certainty Factor method is made in the diagnosis of pests and diseases in hydroponic plants. The purpose of this study was to apply the certanity factor method to diagnose pests and diseases in hydroponic plants. The results of the pest data test found spider mites with a confidence level of 79% and wet rot disease with a confidence level of 62%. The conclusion obtained is that the certainty factor method can detect early types of pests and diseases on hydroponic plants quickly and accurately.
CLASSIFICATION OF BATIK MOTIF USING TRANSFER LEARNING ON CONVOLUTIONAL NEURAL NETWORK (CNN)
Authors: Alya Riqqah Fadiyah , Wibowo Merlinda , Paradise Paradise
Published: August 2023

The number of batik motifs in Indonesia is not comparable to the knowledge possessed by the Indonesian people about batik motifs. The diversity of batik motifs can be a problem because classifying them can only be done by those who are familiar with batik in depth, both the pattern and the philosophy behind the motif, most of which are elderly people. To classify batik accurately and quickly is to use image classification technology. In this study, data were obtained from the previous researchers' GitHub repository, google images, and camera shots with a total dataset of 3,534 images. The data only focused on five batik motifs, namely Ceplok, Kawung, Parang, Megamendung, and Sidomukti. Before the batik motif is processed, preprocessing is carried out to obtain various quality data. Then the dataset was trained using the CNN model then the results were retrained using the VGG-16 and Xception Transfer Learning models. The researcher made several model scenarios, namely the CNN model without Transfer Learning and the model with Transfer Learning which took into account the effect of the learning rate values ​​of 0.0004 and 0.0001. Therefore, the results of the CNN model without Transfer Learning (M0) obtained training accuracy results of 89.64%. While the results of the model with the best Transfer Learning is the M2 model (CNN + VGG-16, learning rate = 0.0001) with an accuracy of 91.23%, a loss of 24.48%, and the test results obtained an accuracy of 89%. Based on the results of the classification method, it can be concluded that the CNN model with Transfer Learning performs classification better in terms of accuracy and computation time than the CNN model.
COMPARATION OF DISTRIBUTED DATABASE MODEL BY CLUSTERING METHOD IN E-GOVERNMENT SYSTEM. STUDY AT KEMENKEU RI
Authors: Wicaksono Adinda Krida , Nurrakhman Fauzie , Samidi Samidi
Published: August 2023

MySQL is one of the most popular open source database in the world based on its performance, its reliability, and its easiness that has been proved. MySQL is categorized into community version and commercial version. The commercial version has standalone architecture models and clusters.Database Clustering is one of distributed database model. The case study used is Kemenkeu Learning Center (KLC) Application which is an e-government application in Ministry of Finance. KLC application used for interactive learning media for all ASN especially ASN in Ministry of Finance. This makes the KLC application being categorized into a very high critical application, so it takes a good response time and has high availability. One of the most important factors to fulfill this need is by deciding the appropriate MySQL database architecture for KLC application. This research was conducted by creating 3 (three) database architecture models according to best practice from MySQL, namely the Standalone architecture model, InnoDB Cluster and NDB Cluster. Then tested with several different scenarios to get results in the form of response time and percentage of errors that indicate high availability capabilities. The tools used in testing are Apache JMeter. From the test results, it is found that the MySQL NDB Cluster is the right database architecture model in an effort to realize the need for database services with the best response time and high availability capabilities.
OPEN JOURNAL SYSTEM SECURITY CAPABILITY LEVEL ASSESSMENT USING COBIT 5 FRAMEWORK AT ABDURRAB UNIVERSITY
Authors: Alfaraby M. , Megawati Megawati , Maita Idria , Muttakin Fitriani
Published: August 2023

Data security is very important in the digital era, this makes it an important issue for companies, organizations and educational institutions. Such as the Open Journal System (OJS) security which is useful for managing online journals. Abdurrab University has utilized the Open Journal System (OJS) to manage published journals. However, the management of the Open Journal System (OJS) security has not been managed properly, such as Abdurrab's Open Journal System (OJS) which has been hacked, there is still a lack of documentation and system security procedures and has never been assessed the level of capability of the information system so that it is not known exactly the level of security management of the Open Journal System (OJS) at Abdurrab University. This study aims to assess the capability level of Abdurrab University's Open Journal System (OJS) using the COBIT 5 domain DSS05 framework and Process Assessment Model (PAM) to assess system capabilities and guide IT management and provide effective and efficient recommendations. The results of the study obtained a questionnaire calculation value of 2.40 with Process Attribute Level domain DSS05 PA 2.1 Performance Management and PA 2.2 Work Product Management until an achievement score of 63.33% was obtained which was included in the Largely Achieved category with achievements at level 2 (Managed Process). The conclusion of this study is that the level of security capabilities of the Open Journal System (OJS) of Abdurrab University needs to be increased to level 3 (Established Process) because it has not been fully met, so that this research can be used as a reference for improvement by Abdurrab University.
OPTIMIZING SENTIMENT ANALYSIS OF PRODUCT REVIEWS ON MARKETPLACE USING A COMBINATION OF PREPROCESSING TECHNIQUES, WORD2VEC, AND CONVOLUTIONAL NEURAL NETWORK
Authors: Maodah Fahry , Utami Ema , Sudarmawan Sudarmawan
Published: August 2023

This research attempts to identify the most accurate and effective model in performing sentiment analysis on product reviews in marketplaces using preprocessing techniques, word2vec, and CNN. We collected 20,986 reviews from 720 products in a marketplace using scrap method, then cleaned and labeled the data to include 515 positive reviews, 490 negative reviews. We then performed preprocessing on the data using four different scenarios and identified word vector representation using word2vec. Subsequently, we applied the results of word2vec to the CNN architecture to classify sentiment in product reviews. After trying various variations of each technique, we found that a combination of the third preprocessing technique (case folding, punctuation removal, word normalization, and stemming), the second word2vec parameter combination (size 50, window 2, hs 0, and negative 10), and the fourth CNN parameter combination (kernel size 2, dropout 0.2, and learning rate 0.01) had the best accuracy of 99.00%, precision of 98.96%, and recall of 98.96%. We also found that the word normalization technique greatly helped to increase model accuracy by correcting improperly written or incorrect words in the reviews. Based on the evaluation of word2vec, the hs 0 method produced a higher average accuracy compared to the hs 1 method because the hs 0 method used negative sampling which helped the model understand the context of the trained words. In the CNN parameter, higher learning rates can cause the model to learn faster, but can also cause the model to be unstable, while lower learning rates can make the model more stable but can also cause the model's learning process to be slower.
APPLICATION OF THE ITERATIVE MODEL IN DESIGNING AN ACADEMIC E-COUNSELING SYSTEM AT BINA DARMA UNIVERSITY
Authors: Ipan Megawaty , Oktarina Tri
Published: August 2023

Bina Darma University does not yet have a system for guidance on final assignments, theses, theses so that the mentoring process becomes hampered. Problems are caused by several factors, namely conditions, distance, different schedules between lecturers and students. coupled with the current pandemic conditions, the implementation of online lectures so that the guidance process is not optimal, the mentoring history is not well documented, and the most common thing encountered in the field is that students cannot submit complaints related to academic activities. The purpose of this research is to build a student academic e-counseling system at Bina Darma University. The benefits obtained from research are that the guidance/counseling process can run smoothly even though the supervisor does not meet directly with the students, the guidance history data is well documented and coordinated. Become a forum for students in delivering and consulting with their lecturers. The research method uses a descriptive method while the system development method in this study is the iterative model method. the stages of this method are planning, analysis, design, implementation, Maintenance. The results of this study are in the form of student e-counseling systems such as final assignments, theses, and theses. Where this system can manage title submission data, guidance, virtual guidance, student data, supervisor data. Can be accessed online by lecturers and students anytime and anywhere.
IMPLEMENTATION OF STEGANOGRAPHY ON DIGITAL IMAGE WITH MODIFIED VIGENERE CIPHER ALGORITHM AND LEAST SIGNIFICANT BIT (LSB) METHOD
Authors: Miftakhul Fahmi Gilang , Isnaini Khairunnisak Nur , Suhartono Didit
Published: August 2023

Digital image can be utilized as a media to hide messages. There should be a special treatment in securing the messages so that the information accessibility can be controlled. Hiding messages to an image can be conducted using steganography. It can be combined with cryptography algorithms in order to make it harder to be accessed by unauthorized parties. The modification of cryptography algorithms can improve the confidentiality of the message content. This research is aimed to know the implementation of steganography in desktop applications using Least Significant Bit (LSB) that is combined with the modification of Vigenere Cipher algorithms. The developed software namely waterfall supports the creation of applications. The result of the research shows that the encrypted picture will change into gray or display in grayscale so that the hidden message will be more difficult to be accessed by the attacker. The encrypted picture will also have a bigger size file than the original version and the extended file. The LSB method will work precisely according to the formula of the modified cryptography algorithm. The further research is suggested to focus on the variation of media for content message and the picture format in their encryption.
DECISION SUPPORT SYSTEM SELECTING CRYPTOCURRENCY EXCHANGE USING AHP METHOD
Authors: Monica Dewi , Atmojo Wahyu Tisno
Published: August 2023

Cryptocurrency is a digital currency that functions as a standard currency and can be traded virtually without service fee and have a reliable institution. Investors and traders are interested in buying or acquiring cryptocurrencies and expect to make a profit when selling them. Apart from mining, cryptocurrencies can obtain by buying through cryptocurrency exchanges. The cryptocurrency exchange is helpful as an intermediary for buying and selling crypto assets. There are many types of cryptocurrency exchanges circulating, and it makes users have to select carefully the exchanger they will use. Based on this problem, a decision support system is needed to facilitate the decision-making. The method used in this research is the Analytical Hierarchy Process (AHP). This method is selected because it helps multi-criteria decision-making, solves complex problems into small forms, and receives input from human understanding by defining problems, making hierarchies, conducting comparative assessments, determining priorities, and calculating consistency values. The final result of this research using the AHP method can be seen that Binance is the most recommended cryptocurrency exchange to be used for investing or trading because it earns a percentage of 35.34%, followed by FTX at 28.35%, Huobi Global at 18.05%, Gate.io at 6.96%, KuCoin at 5.76%, and Indodax 5.55%. The results of this calculation are obtained by calculating the priority criteria and alternatives.
APPLICATION OF MULTI FACTOR EVALUATION PROCESS (MFEP) METHOD FOR THE SELECTION OF BUILDING MATERIAL SUPPLIERS ON MAHAKARYA SUKRI PERKASA (MSP) CIREBON
Authors: Rubiyanto Erwin Sudrajat , Akbar Faisal , Fahlevvi Mohammad
Published: August 2023

The property sector is growing along with the increasing need for housing by people in Indonesia. Mahakarya Sukri Perkasa (MSP), is one of the companies engaged in property and housing development. Supplier selection is one of the essential aspects that ensure the smooth operation of the company. From January to May 2021, MSP received 10 consumer complaints from 60 housing development units. Consumers complained that the housing that had been built and occupied suffered damage to certain parts after several months of use. One of the causes of damage is that the quality of the building materials used is not good. This happens because when choosing a supplier for the purchase of building materials, the MSP decides on the cheapest price list of goods. If consumer complaints increase continuously, it will of course result in a decrease in the level of consumer confidence which will reduce MSP income. MSPs need a decision support system that can produce detailed supplier recommendations. The calculation method used in this study is MFEP (Multi-Factor Evaluation Process). There are 5 assessment criteria used, namely price, quality, the diversity offered, supplier response, and delivery time. The results of highest Weight Evaluation test results are 0.86 obtained by Cirebon Mega Bangunan (CMB) with an initial weight of 0.6 price factors, quality 1, the diversity offered 1, supplier response 1, and delivery time 0.6.
IMPLEMENTATION OF ARTIFICIAL NEURAL NETWORK WITH BACKPROPAGATION ALGORITHM FOR RATING CLASSIFICATION ON SALES OF BLACKMORES IN TOKOPEDIA
Authors: Aini Dalfa Habibah Nurul , Kurniasari Dian , Nuryaman Aang , Usman Mustofa
Published: August 2023

The rating assessment classification contains feedback from consumers, which is given in the form of stars which aims to assess a product. However, the amount of data in the classification process often have differences in each class or is called an imbalanced dataset. These problems can affect the classification results. An imbalanced dataset can be overcome by applying random oversampling. To classify the rating assessment, this study proposes the Neural network method, which has a good accuracy level with the backpropagation algorithm and applies random oversampling to overcome the unbalanced amount of data. The results indicate that the neural network method with the backpropagation algorithm can classify the available data with an accuracy level of 85%. The application of resampling data using random oversampling and determining the amount of distribution of training data, testing data, number of epochs and the correct number of batch sizes affect the results obtained.
TONE DETECTION ON TERANIKA MUSICAL INSTRUMENT USING DISCRETE WAVELET TRANSFORM AND DECISION TREE CLASSIFICATION
Authors: Qothrunnada Fadia , Saidah Sofia , Hidayat Bambang , Busrizal Putri Tasya , Darwindra
Published: August 2023

Musical instruments are one of the cultures that must be preserved. Teranika is one of the traditional musical instruments from the Majalengka area, which is made of clay. Currently, the manufacture of conventional musical instruments is still done manually, so there are still differences in the tone produced. Meanwhile, the quality of a musical instrument is determined by the accuracy of the technique. Therefore, we need a system that can accurately detect the method's accuracy. The author designed a tone detection system for Teranika musical instruments to help artisans carry out quality control. This system will detect whether or not the musical instrument is successfully matched with the right tone and agent. The technique contained in this musical instrument is Do Re Mi Fa So La Si Do high. To overcome these problems, the author makes this tone detection system using the Discrete Wavelet Transform method and the Decision Tree classification. The working principle of this system is that the recorded sound of musical instruments will be transmitted to this system. Then the sound will be processed as input and matched with the essential voice in the database. The output of this system produces samples according to the sampling frequency used. The test results show the best results at decomposition level 6, a thresholding value of 0.05, and a Fine Tree classification type with an accuracy of 87.5%
IMPLEMENTATION OF DATA MINING WITH CLASSIFICATION AND FORECASTING METHOD USE MODEL GAUSSIAN NAÏVE BAYES FOR BUILDING STORE (STUDI CASE: TB SINAR JAYA)
Authors: Valentinus Fernando , Sujono Fabian , Ariansyah Ilham , Capah Dwi Ade Handayani
Published: August 2023

In the construction industry, the building materials business is a necessity, one of the businesses that is currently growing rapidly is the property business. The public’s need for a place to live becomes a business opportunity sought by the public. The Industry 4.0 transformation brought building materials stores to the online market, one of which is Tokopedia. TB. Sinar Jaya has a dataset of inventory and sales with a total of approximately 15,000 data rows which are updated each month. With large amounts of data, data mining and machine learning methods are needed in data management. 5 years rapid development of TB. Sinar Jaya has not been without problems, such as competition with online stores that offer lower prices than offline stores and a lack of strong marketing strategy. In this case, TB. Sinar Jaya wants help in making marketing strategy decisions by utilizing information system technology and minimizing existing problems. Based on these problems, it is necessary to implement data mining and machine learning gaussian algorithms naïve bayes to find out the average prices available on Tokopedia to increase sales and carry out classification, forecasting and TSA (Time Series Analysis) at TB Sinar Jaya. Based on the results of testing/research, the gaussian naive Bayes algorithm has good accuracy results with an accuracy level of 0.71 and gains insight, that is, for potential buyers they can do Wishlist efficiency, and for segments that generate profits below 50% of the total profit the researcher recommends carrying out a campaign program according to customer profile in order to improve the resulting profitability.
INFORMATION FOR THE IDENTIFICATION AND VERIFICATION OF PROSPECTIVE POVERTY SOCIAL ASSISTANCE RECIPIENTS
Authors: Supriyanto Aji , Mulyani Sri , Ariyanto Tri , Razaq Jeffri Alfa
Published: August 2023

One important aspect of the poverty alleviation strategy is the availability of accurate poverty data, so that the government in providing social assistance (Bansos) can be right on target. The problem is that if there is an inaccuracy in the identification process when recording citizen data, it will affect the process of verifying and validating data on prospective Social Assistance recipients. Inaccuracies in prospective Social Assistance recipients can occur due to the process of collecting data on citizen identities and applying the wrong criteria for poverty requirements and the data is not up to date. The purpose of this research is to develop an information system to identify, verify, and validate data on prospective Social Assistance recipients. The identification stage for potential recipients of social assistance is carried out at the RT/RW and Kelurahan levels. The verification stage is carried out by fulfilling the requirements of the poverty criteria. Meanwhile, the validation stage is used to determine the ranking of potential social assistance recipients. The verification process is carried out at the Kelurahan and Kecamatan levels, while the validation process is at the Regency/City level. The waterfall method is used in the development of information system prototypes for prospective Social Assistance recipients with system analysis and design using use case, activity, and sequence diagrams. The prototype was tested with CRUD and trial & error, the result is a prototype system application that is able to collect citizen data by applying a priority scale for prospective recipients of social assistance based on a web by fulfilling the requirements of 14 poverty criteria according to the Central Statistics Agency (BPS).
LECTURERS ADMISSIONS SELECTIONS MODEL USING FUZZY K-NEAREST NEIGHBOR METHOD
Authors: Meilina Lely , Sastra Nyoman Putra , Wiharta Dewa Made
Published: August 2023

Higher Education, or tertiary education, is the final stage which is optional in formal education. It is usually organized in the form of a university, academy, seminary, high school, or institute. Every tertiary institution needs qualified and professional educators because they have an important role in the process of implementing the Tri Dharma of Higher Education. Recruitment for teaching staff usually has several stages and standardization of assessment in selection proces. In order for the process of selecting educators to be carried out objectively, a support system is need to carry out the assessment process. This study applies the Fuzzy K-Nearest Neighbor (FK-NN) method for the classification process in determining prospective educators who pass or not. Data classification is a new data or object grouping into classes or labels based on certain attributes. The application of the FK-NN method has several stages, namely weighting the criteria, then calculating the closeness of the test data and training data, finding the value of k-nearest neighbors between the training data and testing data and determining the membership of each data. Tests were carried out using the Confusion matrix method on several variations of the k value where the highest percentage was obtained from the value of k = 5. The test results for all k values obtained an average accuracy rate of 89.22%, 89.22% precision and 82.45% recall with 114 training data and 50 test data. Based on the average value of the test results, it can be concluded that the FK-NN method is feasible and good to use for the selection of educators with the classification of pass or not.
ANALYSIS OF E-OFFICE SYSTEM USER SATISFACTION AT LAND OFFICE PEKANBARU CITY USING END USER COMPUTING SATISFACTION METHOD
Authors: Fachrurozi  , Febi Nur Salisah  , Tengku Khairil Ahsyar
Published: August 2023

An E-Office system is available at the National Land Agency, which is part of the Ministry of Agrarian Affairs and Spatial Planning and the National Land Agency. It is designed to make office administration easier. However, the use of E-Office is still not optimally used, such as the minutes feature that is underused, errors in sending letters that are sent not as desired, the dashboard display is less attractive and the guide menu cannot be accessed because of a link error. The purpose of this study is to evaluate user satisfaction with the E-Office system and identify its results. The End User Computing Satisfaction (EUCS) method with six variables (content, accuracy, format, ease of use, timeliness, user satisfaction) was used by researchers to assess user satisfaction with the E-Office system. 37 individuals from the E-Office system user population comprised the sample. The results of the proposed hypothesis test show that the hypothesis is accepted and has a significant effect of 78.9% on user satisfaction.
IMPROVING PERFORMANCE OF STUDENTS’ GRADE CLASSIFICATION MODEL USES NAÏVE BAYES GAUSSIAN TUNING MODEL AND FEATURE SELECTION
Authors: M Hafidz Ariansyah  , Esmi Nur Fitri  , Sri Winarno
Published: August 2023

Student grades are a relevant variable for predicting student academic performance. In achieving good and quality student performance, it is necessary to analyze or evaluate the factors that influence student performance. When a educator can predict students' academic performance from the start, the educator can adjust the way of learning so that learning can run effectively. The purpose of this research is to study how it is applied to determine the interrelationships between variables and find out which variables have an effect, then use it as a feature selection technique. Then, researchers review the most popular classifier, Gaussian Naïve Bayes (GNB). Next, we survey the feature selection models and discuss the feature selection approach. In this study, researchers will classify student grades based on existing features to evaluate student performance, so it can guide educators in selecting learning methods and assist students in planning the learning process. The result is that applying Gaussian Naïve Bayes (GNB) without feature selection has a lower accuracy of 10.12% while using feature selection the accuracy increases to 10.12%.
FINE-GRAINED SENTIMENT ANALYSIS IN SOCIAL MEDIA USING GATED RECURRENT UNIT WITH SUPPORT VECTOR MACHINE
Authors: Sofiya Wida , Setiawan Erwin Budi
Published: August 2023

Social media platforms are widely used to share opinions, leading to a large growth of text data on the internet. This data can be a key source of up-to-date and inclusive information by conducting sentiment analysis. Typically, sentiment analysis research classifies binary based on the polar values generated. However, this has its limitations, such as classifying sentences containing positive and negative expressions, leading to incorrect predictions. Fine-grained sentiment analysis provides more precise results by associating values with more than two classification targets. The objective of this study is to carry out sentiment analysis at a fine-grained level related to public policy in Indonesia using the GRU-SVM model with feature extraction and expansion techniques. However, sentiment analysis research still faces challenges in NLP. Deep learning have successfully overcome the challenges of traditional machine learning models in terms of efficiency and performance. This study proposes GRU-SVM model. GRU is used because it can adaptively control dependencies, making it more efficient in memory usage, while SVM is used as it is state-of-the-art in sentiment analysis. Result of the study show that the selection of word representation techniques, the addition of feature extraction techniques, datasets, data ratios, and feature expansion are crucial in the model testing process. The GRU-SVM model achieved the best performance with an accuracy of 96.02%. Overall, the results of this study demonstrate that the GRU-SVM method is effective in analyzing sentiments in Indonesian tweets.
DECEPTION BASED TECHNIQUES AGAINST RANSOMWARES: A SYSTEMATIC REVIEW
Authors: Georgina Canny Siska , Sakinah Farroh , Fadholi M. Ryan , Yazid Setiadi , Syafitri Wenni
Published: August 2023

Ransomware is the most prevalent emerging business risk nowadays. It seriously affects business continuity and operations. According to Deloitte Cyber Security Landscape 2022, up to 4000 ransomware attacks occur daily, while the average number of days an organization takes to identify a breach is 191. Sophisticated cyber-attacks such as ransomware typically must go through multiple consecutive phases (initial foothold, network propagation, and action on objectives) before accomplishing its final objective. This study analyzed decoy-based solutions as an approach (detection, prevention, or mitigation) to overcome ransomware. A systematic literature review was conducted, in which the result has shown that deception-based techniques have given effective and significant performance against ransomware with minimal resources. It is also identified that contrary to general belief, deception techniques mainly involved in passive approaches (i.e., prevention, detection) possess other active capabilities such as ransomware traceback and obstruction (thwarting), file decryption, and decryption key recovery. Based on the literature review, several evaluation methods are also analyzed to measure the effectiveness of these deception-based techniques during the implementation process.
dimensão escolar do ENEM
Authors: Pohl David , Fiorelli Silva Ileizi Luciana
Published: August 2023

A presente pesquisa foi realizada a partir de um estudo de caso comparado. O que se compara é o processo de internalização do Enem em duas escolas estaduais e urbanas do munícipio de Londrina/PR. Chamamos de “dimensão escolar” tal processo de internalização e problematizamos o mesmo como possível motivador de práticas sociais diversas em contextos diferenciados pelo nível de prestígio das escolas. O trabalho se inscreve no campo da Sociologia da Educação Brasileira. A metodologia é delineada pelo estudo de caso comparado, no qual foram aplicadas entrevistas semiestruturadas com foco em diretores e ex-diretores nas escolas. Os gestores foram selecionados por serem considerados os responsáveis, ou não, pelo processo análogo à implementação do Enem enquanto política pública. O referencial teórico utilizado foi o da sociologia neoinstitucional, sendo pensadas agência e estrutura de modo interrelacionado e simultâneo. Verificamos que na escola com menor nível de prestígio, da qual se esperava menos práticas sociais motivadas pelo Enem, ficou evidente uma intencionalidade e atividade maior de seus agentes motivados pelo exame. De modo diverso, na escola de maior prestígio e com fama consolidada nos rankings informais do Enem, verificamos uma motivação de práticas sociais bem menor, porém uma utilização do mesmo para sustentar o prestígio e consequente demanda por vagas na instituição.
Para quem são estruturadas as cidades?
Authors: Rhein Juliany Siqueira
Published: August 2023

O presente artigo objetiva discutir conceitualmente o impacto do urbanismo neoliberal na materialização do direito à cidade, tomando como base para essa reflexão a obra de recuperação ambiental e urbanização do bairro Seminário, no município do Crato/CE, cujo financiamento ocorreu por meio de um acordo de empréstimo celebrado entre o Governo do Estado do Ceará, por intermédio da Secretaria das Cidades, e o Banco Internacional para Reconstrução e Desenvolvimento (BIRD). Traça como caminho metodológico a pesquisa bibliográfica e a pesquisa documental e dialoga com autores que se fundamentam na teoria social e crítica para analisar diretamente as categorias urbanismo neoliberal, direito à cidade e financiamento internacional de políticas públicas, bem como transversalmente a categoria reassentamento involuntário. Entende que as discussões são embrionárias e que novos diálogos plurais deverão ser viabilizados para o alcance da essência do objeto, mas vislumbra que as cidades contemporâneas estão sendo estruturadas para o escoamento de mercadorias e acomodação do capital, impedindo, muitas vezes, que o citadino usufrua dos espaços construídos socialmente e com recursos públicos de forma igualitária, havendo, portanto, um desigual acesso ao direito à cidade.
A Teoria Sociológica Clássica e a análise de Políticas Públicas
Authors: Boni Bittencourt Matheus
Published: August 2023

Neste artigo, apresentamos uma discussão sobre a contribuição dos principais teóricos sociais clássicos para a reflexão sobre as políticas públicas e sociais. Entre convergências problemáticas e divergências teóricas e políticas, as contribuições de Marx, Engels, Durkheim e Weber são mais complementares que excludentes entre si. Na medida do possível, tentamos trazer dos conceitos dos clássicos a atualidade, como a questão da mercantilização do trabalho remetendo a Marx, das atribuições de regulação social e garantia de direitos a Durkheim, e da conexão conflituosa entre política e burocracia a Weber. Menos que uma exposição sistemática, esse trabalho procura estimular o debate teórico sobre as políticas públicas no nosso contexto.
Apresentação
Authors: Tavares-dos-Santos José-Vicente , Viscardi Nilia
Published: August 2023

A relação íntima entre literatura e sociedade, forma e história, texto e contexto social demonstra que os fatos históricos, as condições sociais e os elementos políticos relacionam-se intrinsecamente com a construção da obra literária, constituindo-se como fatores indiscutíveis à compreensão da literatura. O objetivo da sociologia do romance é a reconstrução das homologias entre a sociedade e a forma romanesca, mediante múltiplas dimensões: a) homologia de estruturas com a liberdade individual; b) estudo sociológico, estrutural e genético; c) a categoria da mediação é fundamental nesta empreitada; d) O romance novecentista produziu diversas personificações do herói problemático, desvelando a ruptura entre o herói e a sociedade; e) o romance veio a conformar uma nova sensibilidade em relação ao tempo, mesclando forma e conteúdo. Por conseguinte, torna-se possível uma sociologia do romance: as narrativas alimentam a imaginação sociológica, derivada do prazer do texto. No texto romanesco, percebe-se uma perspectiva crítica. Em uma perspectiva internacionalista, mediante interpretações sociológicas e literárias, em uma história espacializada, os textos a seguir vão explorar a relação entre literatura, sociedade e violência nas obras romanescas de uma série de autores - de vários países: Portugal, Tchecoslováquia, Brasil, Colômbia, Chile, Uruguay, México e Índia. Trata-se de estudar a correspondência entre a unidade expressa pela criação cultural, pelo escritor, e a evolução da estrutura de uma determinada sociedade, percebendo a transculturação presente na obra literária.
romance testemunhal como romance de formação
Authors: Passiani Enio , Anjos Gabriele dos
Published: August 2023

Por que narrar o sofrimento sob a forma de memórias, (auto)biografias ou a partir de outros registros, como o romance? Para além do trabalho de elaboração do sofrimento e da violência, pode-se notar que o testemunho pode fazer parte da construção de sentido a eventos passados, o que não significa a reconstituição virtualmente fidedigna dos eventos, dos participantes (vítimas, perpetradores e testemunhas), dos cenários etc., mas as diferentes formas a partir das quais a violência e o sofrimento são tratados, figurados e significados.A partir desses pressupostos, analisamos o livro Memórias de um sobrevivente, de Luiz Alberto Mendes, no qual é apresentada a “carreira penal” do autor como criminoso. Pretendemos demonstrar que o romance testemunhal, em casos específicos como este, apresenta-se também como espécie de romance de formação: não a formação do indivíduo burguês típico, modelar, consagrado em Os anos de aprendizado de Wilhelm Meister, de Goethe, mas a formação do indivíduo subalternizado, produto de uma sociedade capitalista periférica marcada por profundas desigualdades, exclusões e toda sorte de violências.
Kafka, a justiça ausente, a inconclusividade do relato e o romance policial e da violência
Authors: Tavares-dos-Santos José-Vicente
Published: August 2023

Retomar sociologicamente as formulações literárias de de Franz Kafka, do início do Século XX, vai nos fornecer alguns elementos morfológicos e expressivos para a análise do romance da violência contemporâneo na América Latina. Encontramos em sua obra a expressão da crise do indivíduo, dos limites da racionalização e das metamorfoses da injustiça e do poder disciplinar e burocrático na sociedade contemporânea. Sua obra retrata as ansiedades e a alienação do homem do século XX, imerso na grande cidade, fragmentada e inacabada. Kafka produziu um modelo do mundo social da luta simbólica em várias dimensões, desde a relação originária – a relação com o pai – até a relação com a sociedade dominante, em termos de um tipo ideal: uma máquina que produz uma incerteza e, ao mesmo tempo, opacidade e violência. Uma máquina que maquina, e se dá o poder de denominação, exercendo uma violência simbólica. Há uma contribuição de Kafka para a explicação do romance da violência no século XXI: suas grandes obras são semelhantes a romances de detetive atuais, nos quais fracassa a descoberta do criminoso: faltava-lhe o cálculo e a resolução do enigma. O herói do romance dissolve-se em metamorfoses ou impossibilidades, em longas viagens sem destino, ou esperas inquietantes e infinitas. Franz Kafka, portador de uma cultura universal, da literatura norte-americana à arte e literatura europeias, dos contos africanos aos clássicos chinês, deixou uma obra singular sobre a modernidade, reafirmando sempre a importância dos romances. Reaparecem, em suma, os efeitos da literatura de Kafka em estabelecer outras condições de possibilidade para o romance policial, seja para o roman noir ou para o romance da violência.
A novel approach for skin lesion symmetry classification with a deep learning model
Authors: Talavera-Martinez Lidia , Bibiloni Pedro , Gonzalez-Hidalgo Manuel
Published: August 2023

Symmetry is a distinguishing feature when diagnosing the malignancy of skin lesions, those with an irregular shape –asymmetry– are more likely to have a worse prognosis. This work presents a novel approach for skin lesion symmetry classification of dermoscopic images based on deep learning techniques. Also, we introduce a new dataset of labels for 615 skin lesions. During experimentation, we also evaluate whether it is beneficial to rely on transfer learning from pre-trained CNNs or traditional learning-based methods. As a result, we present a new simple, robust, and fast classification pipeline that outperforms methods based on traditional approaches or pre-trained networks, with a weighted-average F1-score of 64.5%.
Anomaly Detection in Surveillance Videos Using Spatio-Temporal Context Information
Authors: Benitez-Restrepo Hernan , Figueroa Roger
Published: August 2023

Several computer vision algorithms have been proposed to detect anomalous activities (robberies, murders, vandalism, among others) in videos. According to the learning approach, they can be classified into probabilistic distribution modeling, sparse coding, and deep learning based methods. The main drawbacks of these approaches are (i) extraction of low-level features that do not capture complex behaviors of instances on the scene, (ii) generation of features from irrelevant regions, (iii) overlooking of relationships among objects, and (iv) omission of long-term dependencies. To solve these issues, we propose a deep learning architecture that leverages the relationships among objects. It achieves this by using an attention mechanism and learning long-term dependencies using a multilayer recurrent neural network (multilayer LSTM). An AUC score of 0.749 on the UCF-Crime dataset confirms that the proposed algorithm competes effectively against several state-of-the-art approaches for anomaly detection in surveillance videos. It also explains the relationship between regions in the video frames and the anomaly detections.
Control of a Virtual Reality Environment for Upper Limb Movement using a Motor Imagery-based Brain Computer Interface
Authors: Mancha Oscar , Antelis Javier , Mendoza-Montoya Omar
Published: August 2023

This work presents the design, implementation and evaluation of a virtual reality (VR) environment controlled using a Motor Imagery (MI) based Brain Computer Interface (BCI). BCIs enhance the effective communication and interaction between humans and computers. Such systems are increasingly prevalent in diverse applications, including education, entertainment, and health. The aim of this system is to create a rehabilitation environment for upper limb motor recovery, in the form of a VR game. In the system, the user performs left and right arm MI, detected using machine learning algorithms to perform an ability within the virtual environment. The system was evaluated with five healthy participants in one experimental session each. Each experimental session consisted of a training and an evaluation routine, in which the participants were asked to imagine each MI task randomly to gather training data and then, with the trained classification algorithm, the users were evaluated by playing the game, needing to perform the correct ability to attack each enemy. The 3-class classification algorithms showed a ranged accuracy of 39.6% to 68.6%, with an average of 54.3%; the evaluation accuracy ranged from 46.2% to 76.9%, with an average of 59.2%.
Contrast Enhancement in Infrared and Color Images by Homomorphic Filtering and Cluster-Chaotic Optimization (CCO)
Authors: Chavarin Angel , Avalos Omar , Galvez Jorge , Wario Fernando , Perez Nayeli
Published: August 2023

Image contrast enhancement is a technique used in image processing to extract more information from an image, which can be used in complex image analysis systems. This study proposes a new approach to enhance image contrast using homomorphic filtering (HF) and the cluster chaotic optimization metaheuristic algorithm, an alternative to conventional methods. Chaotic algorithms are based on chaos theory, which defines chaos as the behavior of nonlinear systems that are unstable and nonperiodic. HF is a technique that enhances images with non uniform lighting and removes multiplicative noise. Unlike histogram equalization, commonly used in conventional methods, HF uses generalized superposition. To evaluate the effectiveness of this approach, we conducted several tests.