bluuebunny/crossref_metadata_2025 huggingface dataset:
Strengthening the values of Islamic education for students with a more modern character at the Tebuireng Jombang Islamic Boarding School
Authors: Saefrudin Saefrudin
Published: January 2024

Reality Facts at the Tebuireng Jombang Islamic Boarding School. In an effort to educate the character of students who are more modern, the Tebuireng Jombang Islamic boarding school has prepared a model which becomes a reference or approach in implementing existing character education. Implementing education with a place to live for students. Through this system, it is very easy for students to be coached and educated by Islamic boarding school caregivers, ustadz and supervisors by carrying out all institutional activities, both formal and non-formal. Guidance is by enforcing discipline through the existence of rules that students must follow, such as discipline in worship, discipline in dressing. , discipline, getting students used to participating in activities in the boarding school through various activities starting from the implementation of worship (congregational prayer, sunnah prayer, Monday and Thursday fasting, joint prayer, recitation of the sorogan yellow book, bandongan tadarrus Al-Qur'an , seminars, halaqoh, jamiyah Diba promises and organizational activities) as well as carrying out other routine boarding activities, such as sports, eating together, studying together, and sleeping together. Apart from carrying out positive activities, this activity also aims to increase the value of ukhuwah Islamiyah/brotherhood among fellow students in Islamic boarding schools.

Key Word: Islamic boarding school values, Islamic boarding school characters and Modern
Implementation of Writing, Talaqqi, Tarjim, and Takrir Methods In The Process of Memorizing The Qur'an At Pesantren Ayatur Rahman Cerme Gresik
Authors: Maziyah Alif , Amirudin Noor
Published: January 2024

The Qur'an is the word of Allah that was revealed to the Prophet Muhammad through the Angel Gabriel (peace be upon him). The Qur'an is the most sublime dhikr from the all-wise Rabb, the Qur'an is a real light, a cure for the disease that is in the chest, and guidance and mercy for believers [Majdi Ubaid, 2014]. While memorizing the Qur'an is one of the efforts to protect the verses of Allah SWT, memorizing it makes humans always guided in living the life of the world even in the hereafter will get salvation or intercession. Memorizing the Qur'an is an effort to string letter by letter, verse by verse letter by letter in the Qur'an. The memorizers of the Qur'an have various ways of doing the process of memorizing the Qur'an. The difference in the method of memorizing the Qur'an is none other than because of the different ways of learning for each human being, some tend to listen first or auditory, and some are visual, namely by reading many times. Therefore, as one of the final assignments of the lecture, we conducted research at the Ayatur Rahman Qur'anic Boarding School in Cerme-Gresik. This type of research is qualitative with interview, observation, and documentation methods. The results of the author's research show that the method used at the Ayatur Rahman Qur'anic Boarding School in Gresik consists of four methods, namely Talaqqi, writing method, tarjim method, and Takrir method
Queen Card Learning Strategy in Increasing Student Activeness in Jurisprudence Subjects at MA Tarbiyatut Tholabah Kranji Paciran Lamongan
Authors: Alanshari M Zainuddin , Aristinah Dewi
Published: January 2024

This research is entitled Queen Card Learning Strategy in Increasing Student Activeness in Fiqh Subjects at MA Tarbiyatut Tholabah Kranji Paciran Lamongan. Queen Card is a learning strategy using cards that have different functions on each side. This strategy is a development of the Jigsaw strategy, only this strategy uses cards as a medium for group formation. The aim of this research is to find out how the Queen Card strategy is used in fiqh subjects at MA Tabiyatut Tholabah Kranji Paciran Lamongan and to find out how active students are in using the Queen Card strategy in fiqh subjects at MA Tarbiyatut Tholabah Kranji Paciran Lamongan. The type of research used is descriptive qualitative, research location at MA Tarbiyatut Tholabah Kranji Paciran Lamongan. The data collection techniques used were observation, interviews and documentation. Meanwhile, data analysis techniques are carried out by means of data reduction, data presentation, and drawing conclusions. Data sources in this research include the principal of MA Tarbiyatut Tholabah, fiqh subject teachers and students. The results of this research, the first to implement the Queen Card strategy, are that students can be more active, interact well, and develop thinking and speaking skills. Second, the Queen Card strategy succeeded in increasing student activity, building good interactions between group friends and between students and teachers, and had a positive impact on increasing students' final grades
DATA WAREHOUSE MODELLING INFORMATION SECURITY LOG MANAGEMENT IN BUILDING A SECURITY OPERATION CENTER IN CENTRAL GOVERNMENT AGENCIES WITH KIMBALL METHOD
Authors: Asmita Maya , Henny Henny , Samidi Samidi
Published: January 2024

Central Government, is a government agency that manages important and confidential state data and information. The data that is managed needs to be maintained for reliability and security in order to avoid the risk of loss, leakage and misuse of information. To maintain this data, an optimal information security device is needed. Information security tools used today have a variety of functions resulting in many important logs that must be managed, analyzed and evaluated. The log data from each of these information security devices is still separate and must be processed manually to obtain simpler and more efficient data so that it can be monitored and presented to management. The purpose of this research is to make the right data warehouse modeling in order to assist in the process of presenting information quickly and accurately related to the processing of data logs of information security devices as a report that will be given to management in support of the Zero Tollerance data security policy. The method used in designing this data warehouse is using the Kimball 9 step method. The results obtained are in the form of a starflake schema and a data warehouse log of information security devices consisting of a malware fact table, intrusion facts and attack facts that can be used as centralized data monitoring that will be implemented at the Security Operation Center. Testing is done using Pentaho software tools. This data warehouse is expected to provide a quick, accurate, and continuous summary of information so that it can assist management in the decision-making process and policy making for the future.
CLASSIFICATION OF VOCATIONAL HIGH SCHOOL GRADUATES' ABILITY IN INDUSTRY USING EXTREME GRADIENT BOOSTING (XGBOOST), RANDOM FOREST, AND LOGISTIC REGRESSION
Authors: Agustiningsih Afikah , Findawati Yulian , Alnarus Kautsar Irwan
Published: January 2024

The education world is one of the main sources in producing Human Resources. Vocational High School (SMK) is one level of school that presents various majors that are ready to compete in the industrial world. Therefore, a school institution needs to have a system to determine the quality of education provided to students so that they can compete in the industrial world. This study designs a system that is capable of classifying SMK student graduates as an evaluation for the school institution. The goal is to enable the school to devise strategies for producing better student quality in the following year. There are four classes in this study, namely those who work, those who are not working yet, those who are in college, and those who are entrepreneurs. There are several stages in building the classification system, including pre-processing, processing, and evaluation. This research uses three machine learning algorithms, namely XGBoost, Random Forest, and Logistic Regression. The results of the three methods obtained a training score of 91.70%, a test score of 66.88%, and an accuracy score of 67% generated by the XGBoost algorithm. The Random Forest algorithm produced a training score of 97.36%, a test score of 68.71%, and an accuracy score of 67%. Meanwhile, Logistic Regression produced a training score of 51.14%, a test score of 50.43%, and an accuracy score of 50%.
MULTI-CRITERIA DECISION ANALYSIS USING COMPLEX PROPORTIONAL ASSESSMENTS AND RANK ORDER CENTROID METHODS IN THE SELECTION SYSTEM FOR TUTORING INSTITUTIONS
Authors: Fatmayati Fryda , Nuraini Rini , Nugraheni Murien , Soares Teotino Gomes
Published: January 2024

Tutoring can help increase students' self-confidence, reduce anxiety about tests or assignments, and overcome learning barriers. The large number of tutoring institutions that offer various programs makes parents or students have to be observant when choosing them. To choose a tutoring institution, parents or students must know all the profiles and programs of the institution to be selected. This creates a difficult and long time to come up with a choice. The purpose of this study is to use the Multi Criteria Decision Analysis (MCDA) approach through the Complex Proportional Assessment (COPRAS) method and the Rank Order Centroid (ROC) method to create a Decision Support System (DSS) that will make it easier to choose a tutoring institution. The ROC approach serves to determine the weight based on the order of importance of the criteria. The COPRAS method is used because this method takes utility into account by assessing the usefulness of each alternative. This research produced a web-based tutoring institution selection DSS that can provide alternative recommendations based on criteria determined by decision-makers. The results of system calculations and manual calculations do not show a different value, which shows that the system produces a valid COPRAS approach value. Based on the results of usability testing, the built DSS scored 89.17%; in other words, the system is feasible to use.
APPLICATION OF THE AHP METHOD IN DETERMINING OUTSTANDING STUDENT BASED ON INDICATORS OF EDUCATION AND STUDENT ACTIVITIES AT FTI UKSW
Authors: Munda' Mourin , J. P Sri Yulianto
Published: January 2024

The decision making system is a computer-based system that aims to assist in the decision-making process by using existing data to solve semi-structured problems. This research aims to develop an efficient and objective approach for selecting outstanding students in the higher education environment of FTI UKSW. Until now, FTI UKSW has been using manual methods to determine outstanding student. The Analytical Hierarchy Process methods is employed as the primary framework in this research to measure and analyze relevant criteria and sub-criteria for the selection of outstanding student. In assessing outstanding students, several criteria are required, including Cumulative Grade Point Average, Academic Research, Skills/Achievements, English Proficiency, and Extracurricular Activities. The determination of outstanding student using the Analytical Hierarchy Process methods is designed in the form of a web application to simplify the decision-making process for the faculty. The results of the Analytical Hierarchy Process analysis produce relative priorities for each student based on educational indicators and extracurricular activities. Thus, this research provides a systematic framework for decision making in selecting outstanding students that is more objective.
COMPARING THE PERFORMANCE OF OSPF AND OSPF-MPLS ROUTING PROTOCOL IN FORWARDING TCP AND UDP PACKET
Authors: Miswar Nur , Herman Herman , Riadi Imam
Published: January 2024

Routing is an important process in computer networks, which involves selecting a path for packet data. The routing mechanism is governed by protocols at layer three of the OSI model or layer two of the TCP/IP model. Routing can be static or dynamic, with dynamic routing algorithms automatically determining the best path in the network. One commonly used dynamic routing protocol is Open Shortest Path First (OSPF), which automatically selects the optimal route for data packets based on received network topology information. The need for more advanced and scalable routing solutions led to the development of Multi-Protocol Label Switching (MPLS), introducing the concept of label switching for faster and more efficient data forwarding. This research aims to analyze the performance of OSPF and OSPF MPLS routing scenarios regarding TCP and UDP services. Through evaluation of Quality of Service (QoS) parameters, including throughput, packet loss, delay, and jitter. This study simulates the network using GNS3 software, with TCP and UDP services transmitted for durations of 15, 30, and 60 seconds. The results showed performance for both scenarios with an average index value of 3.75, indicating "good" network performance according to TIPHON standards across all measurement sessions. Although MPLS OSPF showed slightly lower throughput compared to non-MPLS OSPF, both scenarios showed very low packet loss, low delay, and stable jitter. The evaluation also highlights that the use of OSPF MPLS for UDP services reduces the time delay. Both non-MPLS OSPF and MPLS OSPF effectively support TCP and UDP services, with MPLS OSPF showing advantages in certain QoS parameters, especially for UDP services.
TEXT CLUSTERING IN KARO LANGUAGE USING TF-IDF WEIGHTING AND K-MEANS CLUSTERING
Authors: Br Sembiring Trisna Amanda , Hasibuan Muhammad Siddik
Published: January 2024

The aim of this research is to see how many presentations there are between dialects and look for clusters. There is also a method used for weighting, namely tf-idf, there are several steps used in this method, namely starting from the tokenizing process, transform cases, stopwords filter and token filter. to search for clusters using the k-means clustering method on rapidminer. The results of this research obtained a tf-idf weighting value, namely ginger dialect 37.5% for the number of word occurrences and 62.5% for the total of all words documented. Furthermore, for the Julu dialect, it was 37.5% for the number of word occurrences and 62.5% for the total of all words documented. The Singaporean Lau dialect accounts for 38% of the number of word occurrences and 62% of the total number of words documented. The singteruh deleng lau dialect accounts for 38% of the number of word occurrences and 62% of the total number of words documented. The Liang Melas dialect accounts for 38% of the number of word occurrences and 62% of the total number of words documented. Based on k-means clustering, it produces cluster 0: 68 items, cluster 1: 3 items, cluster 2: 15 items, cluster 3: 10 items, cluster 4: 4 items with a total sample of 100 items. The conclusion obtained is that the Ginger dialect and the Julu dialect are identical, while the Singaporean Lau dialect, the Teruh Deleng and Liang Melas dialects are also identical.
CLASSIFICATION OF TOMATO QUALITY BASED ON COLOR FEATURES AND SKIN CHARACTERISTICS USING IMAGE PROCESSING BASED ARTIFICIAL NEURAL NETWORK
Authors: Agung Andi Sadri , SR Amin Farid Dirgantara , Hersyam Muh Syachrul , Kaswar Andi Baso , Andayani Dyah Darma
Published: January 2024

Tomato (Solanum Lycopersicum) is a plantation commodity in Indonesia with a production rate that tends to increase every year. With a high economic value, maintenance is important so that the quality is getting better. The problems that arise at this time are related to the determination of the quality of tomatoes which is still done manually and depends on humans so classification using technology is considered important to be developed. Previously there has been researching related to the classification of tomatoes. However, accuracy and computation time still need to be improved. Therefore, in this research, a method of classification of tomatoes was carried out using Artificial Neural Network (ANN) Backpropagation algorithm by utilizing color features and skin characteristics based on image processing. This research followed several stages, from acquiring 300 tomato images with 3 class levels to the classification process using ANN Backpropagation. Several training scenarios and tests were conducted to select the feature combined with the highest accuracy and fastest computation time. The combination of 3 best features used is RGB color feature with shape and texture features as skin characteristic parameters. Based on training results with 210 training images, an accuracy of 100% was obtained with a computation time of 2.58 seconds per image. While test results with 90 test images, accuracy reaches 95.5% with a computing time of 1.39 seconds per image. So it can be concluded that the method used has gone well in classifying tomato image quality based on color features and skin characteristics.
RECOGNITION OF REAL-TIME HANDWRITTEN CHARACTERS USING CONVOLUTIONAL NEURAL NETWORK ARCHITECTURE
Authors: Gumilang Muhammad Satrio , Avianto Donny
Published: January 2024

Pattern recognition, including handwriting recognition, has become increasingly common in everyday life, as is recognizing important files, agreements or contracts that use handwriting. In handwriting recognition, there are two types of methods commonly used, namely online and offline recognition. In online recognition, handwriting patterns are associated with pattern recognition to generate and select distinctive patterns. In handwritten letter patterns, machine learning (deep learning) is used to classify patterns in a data set. One of the popular and accurate deep learning models in image classification is the convolutional neural network (CNN). In this study, CNN will be implemented together with the OpenCV library to detect and recognize handwritten letters in real-time. Data on handwritten alphabet letters were obtained from the handwriting of 20 students with a total of 1,040 images, consisting of 520 uppercase (A-Z) images and 520 lowercase (a-z) images. The data is divided into 90% for training and 10% for testing. Through experimentation, it was found that the best CNN architecture has 5 layers with features (32, 32, 64, 64, 128), uses the Adam optimizer, and conducts training with a batch size of 20 and 100 epochs. The evaluation results show that the training accuracy is between 85, 90% to 89.83% and testing accuracy between 84.00% to 87.00%, with training and testing losses ranging from 0.322 to 0.499. This research produces the best CNN architecture with training and testing accuracy obtained from testing. The developed CNN model can be used as a reference or basis for the development of more complex handwriting pattern recognition models or for pattern recognition in other domains, such as object recognition in computer vision, facial recognition, and other object detection.
FACEMASK DETECTION USING YOLO V5
Authors: Suroiyah Lailatul , Rahmawati Yunianita , Dijaya Rohman
Published: January 2024

The use of facemasks is one of the obligations when carrying out activities outside the home during the COVID-19 pandemic, but despite the COVID-19 pandemic, the use facemasks is still needed. One of the supporting factors driving this is air pollution. The use of facemasks can reduce the risk of respiratory diseases, because it is important to use facemasks when carrying out activities in place with a high risk of air pollution such as industrial areas, this is done to maintain the safety of its users both in term of healh and comfort. So consistency is needed for users to use masks, through current technological developments detecting the use of masks is one of the right solutions to this problem. One of the mask detection methods used in this study is YOLO (You Only Look Once). YOLO is a method that detects objects using a single neural network consisting of several layers of convolution networks for image feature extraction, then prediction of bounding box coordinates is performed simultaneously. The YOLO v5 training model in this study was carried out with a combination of minimum values ​​on img, batch, and epoch resulting in a maximum F1 value and mAP@50 of 86%.
AUTOMATIC GIT REPOSITORY DEPLOYER IN UBUNTU USING PYTHON, JENKINS AND CLOUD FIRESTORE AT PT XYZ
Authors: Dewangga Felix Vicky Lugas , Nugraha Saian Pratyaksa Ocsa
Published: January 2024

PT XYZ is a retail company using Cloud Computing to support its business operations. The company requires the back-end application deployment process to be done automatically on each server computer. The problem occurs insecure in the process of the back-end application deployed manually causing human error vulnerabilities and inefficient when the version of application change occurs to operate on each server computer takes time as long as the number of server computers that need to be configured. The research aims to design a deployer system that help company to deploy back-end applications on each Ubuntu server computer automatically efficiently and securely. The research method uses Research and Development to create system. The research produces a design and build of an automated deployer system using Jenkins to create data configuration that aim the version of back-end application as target deploy and stored in the Cloud Firestore database. The stored data causing deployer system change version back-end application as stored data using GIT command and provide application to operate as service on each server computer. Operation result of application recorded as data deployment that stored in the Cloud Firestore then Jenkins detect it to store data as deployment log. Based on the results, the deployer system considered is able to operate back-end application automatically according the target version on each server computer as eficient and secure deployment process. This conclusion is supported by the results of the questionnaire, which obtained a 85% percentage and was classified as "Strongly Agree" with the created system.
COMPARISON OF LEAST SQUARE AND QUADRATIC METHODS ON PREDICTION THE NUMBER OF NEW STUDENT APPLICANTS
Authors: Atin Hasanah  , Kusrini Kusrini , Kusnawi Kusnawi
Published: January 2024

New student registration is held every year with several mechanisms. However, in recent years the number of applicants has decreased even though it had experienced a surge in the previous year. So that, it is necessary to have a prediction to predict the number of applicants in the coming year. In addition, the results of these predictions can be used as material for consideration in determining the quota/ceiling for the number of new student admissions in the following academic year. This research used the Least Square and Quadratic methods to predict the number of new student applicants based on data on the number of applicants from the 2014/2015 to 2022/2023 academic years. Performance testing of the two methods was tested with three (3) testing methods : MAE, MAPE, and MSE. The performance test found that the Quadratic method is more suitable with the MAPE value in the "Good" forecasting accuracy category, which is 11%. For the MAE value, it gets 452,17 and an MSE of 302069,04. While Least Square produces a MAPE value in the "Enough" forecasting accuracy category of 30%, for the MAE value, it gets 996,97 and an MSE of 1494205,36.
ENHANCING SENTIMENT ANALYSIS WITH CHATBOTS: A COMPARATIVE STUDY OF TEXT PRE-PROCESSING
Authors: Indri Tri Julianto  , Kurniadi Dede , B. Balilo Jr Benedicto
Published: January 2024

Text pre-processing plays a crucial role in the Sentiment Analysis process. Machine Learning models like Chat GPT-3.5 by OpenAI and Google Bard serve as alternative methods for text pre-processing. This study aims to evaluate the capabilities of both Chatbots in the text pre-processing stage while assessing their performance using a dataset obtained by crawling from source X. The study involves a comparison of Chat GPT-3.5 and Google Bard using Decision Tree and Naïve Bayes algorithms. The validation process employs K-Fold Cross Validation with a K value of 10. Additionally, three sampling methods, namely Linear, Shuffled, and Stratified Sampling, are utilized. The findings reveal that Chat GPT-3.5 performs best when using the Decision Tree algorithm with a K-Fold Cross value of 10, and employing Stratified Sampling, achieving an Accuracy of 90.68%, Precision of 90.63%, and Recall of 100%. On the other hand, Google Bard's optimal performance is achieved with the Decision Tree algorithm, a K-Fold Cross value of 10, and Shuffled Sampling, resulting in an Accuracy of 74.00%, Precision of 72.73%, and Recall of 98.77%. The study concludes that Chat GPT-3.5 and Google Bard are viable alternatives for text pre-processing in Sentiment Analysis. Performance measurements indicate that Chat GPT-3.5 outperforms Google Bard, achieving an Accuracy of 90.68%, Precision of 90.63%, and Recall of 100%. These results were validated by comparing them to human annotations, which achieved an accuracy score of 85.20%, Precision of 85.71%, and Recall of 99.03% when using the Decision Tree algorithm with a K-Fold Cross value of 10 and employing Stratified Sampling. This suggests that Chat GPT-3.5's text pre-processing performance is on par with human annotations.
DESIGNING A 3D ROGUELIKE GAME WITH PROCEDURAL CONTENT GENERATION USING THE GRAPH GRAMMARS METHOD
Authors: Vatresia Arie , Putra Utama Ferzha , Yulianto Adi
Published: January 2024

Roguelike is a genre of role-playing video game in which the player explores dungeons through procedurally generated levels. If they lose, the player loses progress, and the character starts over again. Procedural Content Generation (PCG) is a computer program that can create game content automatically, randomly, and uniquely, either by itself or with human assistance. In this study, the 3D roguelike game was designed with players playing a character to explore dungeons. Players will enter at one point, explore the surrounding environment, defeat the enemies encountered, avoid traps, collect treasure, and finally exit at another point. Each time the player starts a new game session, the game will generate a dungeon with a mission structure that changes randomly to create a variety of gameplay. This mission generation is implemented using the Graph Grammar method. The game is built using the Unity game engine and is intended to run on Android devices. Based on the black box test results, all the game's features are running well according to their functions. The built games will be evaluated using the GUESS-18 to determine the level of player satisfaction. Based on the evaluation results, the game is included in the "GOOD" category, with an overall score of 49.07 out of 63 maximum scores. The game that has been built is superior in the aspect of personal gratification, while it is weak in the aspect of social connectivity.
Seleksi Anggota Paduan Suara Menggunakan Fuzzy Inference System Tsukamoto
Authors: Suryoprayogo Hertanto , Ilmi Nurul
Published: January 2024

Paduan suara merupakan grup dalam merepresentasikan sebuah lagu dan terdiri atas berbagai macam warna suara yang dipadukan sehingga menghasilkan harmonisasi dalam membawakan sebuah lagu yang berkualitas. Pengambilan keputusan dalam penentuan calon anggota paduan suara agar dapat melakukan seleksi calon anggota yang memenuhi kualitas persyaratan yang dibutuhkan. Penelitian ini mengimplementasikan metode Fuzzy Inference System Tsukamoto dalam menentukan kelayakan calon anggota paduan suara, menggunakan 5 input variabel kriteria penilaian kelayakan calon anggota. Hasil penelitian kemudian dibandingkan dengan keputusan pakar dan dilakukan uji korelasi menggunakan sistem perankingan Spearman, dan menghasilkan akurasi yang tinggi dengan nilai 0.769.
Tinjauan Pustaka Sistematis: Perkembangan Metode Peramalan Harga Emas
Authors: Yulianing Tyas Sasmi Hidayatul
Published: January 2024

Prediksi harga emas merupakan hal yang menantang untuk diteliti karena harga emas bersifat fluktuatif. Selain itu, emas juga menjadi alat investasi utama urutan ketiga berdasarkan laporan survei pasar ritel emas tahun 2019. Oleh karena itu kebutuhan emas selalu meningkat 15% setiap tahunnya. Hal ini menjadi pemicu bagi berkembangnya berbagai metode peramalan emas. Pada penelitian ini akan dilakukan tinjauan pustaka sistematis untuk mengidentifikasi perkembangan metode peramalan harga emas. Metode yang digunakan adalah Systematic Literature Review dan dihasilkan sebanyak 28 artikel ilmiah untuk direview. Berdasarkan analisis diketahui bahwa sebagian besar metode yang digunakan adalah berbasis deep learning. Metrik performa metode yang digunakan pada mayoritas literatur adalah RMSE dan MAE. Sedangkan data set yang digunakan adalah data keuangan seperti harga emas, nilai tukar mata uang, indeks saham, harga minyak dan nilai inflasi.
Rancang Bangun Dan Implementasi Metode Waterfall Pada Sistem Monitoring Service Motor Berbasis Web (Studi Kasus : Deni Motor Tangerang)
Authors: Marco Marco Triber
Published: January 2024

Deni motor merupakan salah satu usaha yang bergerak dibidang pelayanan jasa service dan penjualan sparepart motor. Deni motor setiap harinya mempunyai pelanggan yang datang untuk melakukan service atau pembelian sparepart. Saat ini proses service yang ada di Deni motor masih berjalan secara manual, yaitu pelanggan menuju ke area pendaftaran service untuk mendaftarkan sepeda motornya untuk di service. Selanjutnya mekanik akan mengecek data terakhir kali kapan motor tersebut diservice, dan setelah itu motor diservice oleh mekanik, sementara pelanggan menunggu diruang tunggu yang telah disediakan. Setelah mekanik selesai memperbaiki sepeda motor, maka mekanik akan menyerahkan data keluhan sepeda motor dan bukti selesai service ke bagian kasir, dan dari kasir akan memanggil pelanggan yang telah selesai di service sepeda motor untuk melakukan pembayaran. Proses service yang cukup panjang dan lama biasanya terjadi pada pengerjaan service di bagian mekanik yang mengerjakan service. Hal ini diperoleh dari keluhan pada kerusakan sepeda motor dari setiap pelanggan berbeda, sehingga menimbulkan perbedaan waktu selesai dalam pengerjaannya. Untuk meningkatkan kinerja sumber daya manusia yang efektif dan efisien dengan permasalahan yang ada pada bengkel, maka dibuatlah sebah sistem monitoring aplikasi service motor berbasis web yang bertujuan membantu dan memudahkan mekanik dalam mengolah data service yang ada di Deni Motor. Metode pengembangan perangkat lunak menggunakan metode waterfall yang meliputi: analisa kebutuhan sistem, desain, pengkodean, pengujian dan implementasi.
PERANCANGAN SISTEM MONITORING PEMBAYARAN AIR PAM BERBASIS ANDROID MENGGUNAKAN METODE WATERFALL (Studi kasus : RT.002,RW.01 CIPADU LARANGAN, KOTA TANGERANG BANTEN)
Authors: Lia Lia Asmaradani
Published: January 2024

Air PAM merupakan kebutuhan pokok masyarakat khususnya di rt.002 Cipadu Kota. Tangerang yang sangat kekurangan air bersih namun pelayanan pegawai PDAM yang sangat terbatas, karena masih dilakukan dengan cara tidak praktis. Begitu pula dalam proses pencatatan pembayaran masih menggunakan pencatatan, dan untuk memudahkan kendala tersebut dibuatlah sebuah sistem aplikasi pencatatan pembayaran menggunakan android ini yang digunakan oleh pegawai PDAM maupun pelanggan. Dengan menggunakan metode pengumpulan data serta wawancara, observasi dan studi pustaka serta analisis data, sehingga proses pencatatan pembayaran dapat dilakukan dengan mudah dan cepat. Dan hasil dari penelitian ini adalah telah dibuatnya sistem monitoring pembayaran air PAM di rt.002 berbasis android dan memudahkan pelanggan dapat mengetahui jumlah tagihan air setiap bulannya
DNS Server Berbasis Ubuntu-22.04.1-Eve-NG-5.0.3.105
Authors: Fachrurrozi Nurwan Reza
Published: January 2024

Setelah lulus dari Fakultas Teknik IT Telkom Jakarta, mahasiswa akan menguasai teknologi jaringan. Untuk menaikkan tingkat kualifikasi, diperlukan banyak pengalaman praktis di lapangan. Perangkat komputasi harus terhubung ke jaringan lokal yang sangat diperlukan untuk manajemen terpusat dalam melakukan tugas, memfasilitasi pengumpulan data, dan berbagi sumber daya dalam organisasi. IP yang berbeda dapat di alamatkan pada setiap komputer untuk terhubung ke jaringan melalui nirkabel. Di dalam memfasilitasi akses, perangkat server dapat mengimplementasikan domain name server. Hal ini menjadi mudah dalam mengingat nama domain daripada alamat IP. Metode dalam penulisan ini dimulai dengan Analisis merupakan analisa kebutuhan hardware & software, Perancangan yaitu membuat topologi jaringan, Implementasi & Konfigurasi dalam aplikasi ubuntu-eve-ng, dan Pengujian ialah menguji hasil aplikasi. Uji coba yang dijalankan dalam menguji koneksi pengguna ke server menggunakan alamat IP dan domain yang menghasilkan koneksi, serta kueri dan alamat domain yang dikonversi menggunakan perintah nslookup dari PC pengguna ke server. ke alamat IP dalam Studi kasus penerapan praktikum di Fakultas Teknik IT Telkom Jakarta.
Pemasangan Jaringan listrik Hybrid di Ruang Satpam Telkom Universitasity Jakarta berbasis Arduino
Authors: Royhan Muhamad Muhamad
Published: January 2024

Energi listrik  diperlukan untuk mengaktifkan perangkat listrik. Perangkat listrik terdiri atas perangkat listrik arus bolak-balik (AC) dan arus searah (DC). Beban listrik searah adalah Jaringan CCTV digunakan untuk monitor di linkungan gedung yang layarnya di gedung satpam, Di Telkom University (Tel U) Jakarta  monitor CCTV berpusat di ruang satpam.  CCTV harus beroperasi terus-menerus tidak boleh padam. Jika terjadi pemadaman listrik PLN maka CCTV tidak dapat beroperasi. Untuk mengantisipasi jika terjadi pemadaman dari PLN, dapat dilakukan dengan memasang Pembangkit Listrik Tenaga Surya (PLTS). Untuk pengaturan perpindahan energi PLN dengan PLTS dipasang auto switch. Jika terjadi pemadaman listrik PLN maka auto switch memindahkan atau menyambungkan ke PLTS, dan sebaliknya jika listrik PLN sudah aktif, maka beban terhubung ke PLN. Dengan sistem auto switch tidak memerlukan operator untuk memindahkan catu daya baik dari PLN maupun dari baterai. Perangkat PLTS yang digunakan adalah A , solar panel   100 WP, baterai 40 Ah jenis litium, inverter   1500 Watt.
Side Channel Attack pada Perangkat Lunak Media Penyimpanan DiskCryptor
Authors: Fathiyana Rana Zaini , - Yudiansyah , Fajriyah Siti Zahrotul , Azahra Rahma Wafii
Published: January 2024

Meningkatnya popularitas penggunaan perangkat portabel memberikan dampak positif bagi peningkatan produktivitas dan efisiensi, namun menimbulkan dampak lainnya yaitu terjadinya resiko kehilangan data yang signifikan. Perangkat ini dapat dengan mudah hilang atau dicuri. Walaupun harga perangkat portabel tersebut tidak seberapa dibandingkan dengan nilai data yang tersimpan di dalamnya. Teknologi enkripsi merupakan jawaban kebutuhan keamanan data perusahaan, melindungi data di komputer portabel atau media penyimpanan removable. Full disk encryption (FDE) merupakan solusi untuk menjaga kerahasiaan data yang tersimpan pada perangkat portabel atau laptop. Dengan FDE memungkinkan seluruh kapasitas dan data pada hard drive komputer akan diubah menjadi bentuk yang hanya bisa dimengerti oleh orang yang memiliki kunci untuk mendeskripsi data yang telah dienkripsi. DiskCryptor merupakan salah satu contoh perangkat lunak enkripsi yang berjalan pada sistem operasi Windows yang memiliki Lisensi Publik Umum GNU. Pada penelitian ini membahas mengenai ancaman keamanan (side channel attack) yang mungkin terjadi di perangkat lunak DiskCryptor diantaranya Cache Attack, Power Analysis, Timming Attack, Kebocoran Sistem Operasi, Password Cracking, Cold-Boot Attack, dan Pre-Boot Authentication.
A Study on Mathematical Literacy Required by Adults
Authors:   The Korean Society for Lifelong Education, Cho Eun Young
Published: January 2024

In this study, we analyzed the current perception of mathematical literacy among Korean adults and determined their mathematical literacy needs, based on a theoretical review of how the concept of mathematical literacy required for adults has changed. Mathematical literacy, which refers to the mathematical ability currently required, is a concept that integrates mathematical skills, knowledge, and attitudes. Following the theoretical review, it was found that the mathematical literacy provided by lifelong education in Korea falls short of the current requirements for adults. The study revealed that the current mathematical literacy expected of adults involves the application of mathematical skills such as reasoning, modeling, information processing, and communication as well as routine basic arithmetic. Furthermore, adults' perceptions of mathematical literacy closely aligned with the definitions presented by PISA, ALL, and PIAAC. The results of the study suggest the following actions: re-conceptualizing the mathematical skills needed by Korean adults, shifting the perception of mathematics education from a lifelong learning perspective, offering positive mathematical experiences to adults, and identifying areas for further research.
The Elephant in the Room: Fluid Dynamics in the age of Machine Learning
Authors: Juniper Matthew
Published: January 2024

"With four parameters I can fit an elephant, and with five I can make him wiggle his trunk," said John von Neumann in a powerful exhortation that physical models should contain only a handful of parameters. A century later, we seem happy to use physics-agnostic neural networks containing millions of parameters. What would von Neumann say? How should physical modellers respond? In this talk, I will frame a response within a Bayesian framework, in which physical principles such as conservation of mass and momentum are expressed as high quality prior information with quantified uncertainties. I will show how Bayesian inference becomes computationally tractable when combined with adjoin methods, and demonstrate this through assimilation of 3D Flow-MRI data directly into CFD, and selection of models in an acoustic problem.
Macroeconomic Impact On Indonesia's Economic Growth
Authors: Fadilah Nur Zatil , Fauziah Fenty , Kusumawati Yulia Tri
Published: January 2024

This study aims to determine the effect of inflation and the rupiah exchange rate on Indonesia's economic growth. This study used a type of quantitative research. The collection of data and information obtained in this study uses secondary data published through the Central Bureau of Statistics, Bank Indonesia, Journal articles and other related research. The data period used is Indonesian data for 2018-2022 in the form of quarters (time series). The data analysis technique used in this study is to use multiple regression models with times series data using Econometric Views Software (Eviews). The results show that inflation partially has a significant effect on economic growth and the exchange rate has no significant effect on economic growth. Simultaneously, inflation and exchange rates have no significant effect on economic growth.
Musik Tingkilan: Antara Tradisi dan Kuasa
Authors: Dewi Aji Qamara
Published: January 2024

Tingkilan merupakan sebuah tradisi yang menjadi bagian dari kebudayaan Kutai Kartanegara. Kutai Kartanegara sendiri memiliki 3 jenis Tingkilan yang mengikuti 3 jenis kebudayaan di Kutai Kertanegara. Social claim, pemberian nama atas "tradisional" dan "modern" tersebut dilakukan setelah adanya keberadaan kelompok "modern". Cara pandang para pelaku musik Tingkilan berpijak pada kekinian terlebih dahulu, baru kemudian membandingkan dengan masa lalu, dengan berkaca pada modern memunculkan tradisional. Kekuatan bertahannya para pelaku musik Tingkilan adalah legitimasi adat yang menjadi legitimasi kekuasaan untuk menunjukkan kekuasaan simbolik. Buku ini mencoba memaparkan perjuangan pemusik Tingkilan tradisional di tengah maraknya modernisasi musik yang kian memanas. Keduanya bersisian namun sebenarnya terjadi pertarungan secara simbolik, yang pada pelaksanaannya dikenal sebagai kekerasan simbolik.
Kell-e foglalkozni az irigységgel? A diszpozicionális irigység pszichológiai jelentősége
Authors: Arató Judit , Rózsa Sándor
Published: January 2024

Háttér: Az irigység témájával évezredek óta foglalkozik az emberiség, a pszichológia tudománya is szinte a kezdetektől fogva érdeklődik iránta. Nincs azonban egységes álláspont a diszpozicionális irigység konceptualizálásában, magyar mintán pedig alig van a témát érintő kutatás, holott a diszpozicionális irigység a nemzetközi kutatási eredmények alapján pszichológiai szempontból jelentősnek tekinthető. Célkitűzés: Az elemzések elsődleges célja a diszpozicionális irigység hazai kutatásának ösztönzése, azáltal, hogy feltárjuk és a nemzetiközi szakirodalom alapján megerősítjük legfontosabb korrelátumait, modellt építünk. Módszer: A mintát a Károli Gáspár Református Egyetem „Életünk a koronavírus-járvány idején” című kvázi reprezentatív mintájú kutatásában a 18. életévüket betöltő személyek adták (n = 2205). Az egyes változók közötti kapcsolatok feltárására korrelációs elemzések szolgálták, a változók közötti kapcsolatrendszer feltérképezésére modell elemzés (SEM) készült. Eredmények: A modell alapján elmondható, hogy a diszpozicionális irigység jól meghatározza a depressziót és a jóllétet. A modell a diszpozicionális irigység varianciájának 27%-át, a depresszió varianciájának 38%-át, az általános jóllét varianciájának 42%-át magyarázza. A nők és a férfiak diszpozicionális irigység szintje között szignifikáns, de elhanyagolható hatásmértékű különbség van. Következtetés: A diszpozicionális irigység és a jóllét kapcsolata mintánkon megerősítést nyert, a vizsgálatok a diszpozicionális irigység pszichológiai jelentőségét és további vizsgálatának szükségességét támasztják alá. A részletesebb elemzés a gyakorlat számára is hasznos lehet.
A konspiratív gondolkodás és a bizalom szerepe az oltási bizonytalanságban
Authors: Rózsa Sándor , Arató Judit , Mészáros Veronika , Kiss Enikő Csilla , Kövesdi Andrea , Nyitrai Erika , Ferenczi Andrea , Fazekas Ágnes , Ferencz Valéria , Mirnics Zsuzsanna
Published: January 2024

A COVID-19 világjárvány hatására számos összeesküvés-elmélet látott napvilágot, amelyeknek középpontjában a járvány kitörésének körülményei, vagy a vakcina eltitkolt manipulációs felhasználása állt (pl. biometrikus adatok gyűjtése, befolyásolás). Az ilyen konspiratív meggyőződések jelentős negatív hatást gyakorolnak az oltási attitűdre és kedvezőtlenül befolyásolják az oltási szándékot. Tanulmányunkban az oltási bizonytalanságot meghatározó tényezők azonosítására és komplex hatásmechanizmusainak feltárására vállalkozunk, melynek empirikus hátterét az „Életünk a koronavírus-járvány idején” című online, megközelítően reprezentatív mintavételű keresztmetszeti kutatás adta (N=1779, 922 nő és 857 férfi). Az alkalmazott tesztbattéria az oltási bizonytalanságot meghatározó tényezők széles körét öleli fel: pl. védőoltással szembeni attitűd, a koronavírussal összefüggő konspiratív gondolatok, bizalom a tudományban és a kormányban, félelem a COVID-tól, egészségtudatosság, stressz. Eredményeink megerősítik, hogy a koronavírussal kapcsolatos konspiratív meggyőződéseknek jelentős szerepe van az oltásellenes attitűd kialakulásában, ami pedig oltási bizonytalanságot vagy az oltás elutasítását eredményezi. Átfogó kauzális modellünk rávilágít arra is, hogy a konspiratív gondolatok a tudományba és a kormányba vetett bizalom csökkenésén keresztül közvetve is képesek negatívan befolyásolni az oltással szembeni attitűdöt, és így magát az oltási szándékot. Az oltási bizonytalanság olyan oltásspecifikus prediktorainak hatásmechanizmusát is sikerült igazolnunk, mint például a koronavírustól való félelem, vagy az influenza elleni védőoltások korábbi felvétele. Átfogó modellünk alapján az alapvető szociodemográfiai jellemzők (nem, életkor és iskolai végzettség) szerepe is hangsúlyos, bár ezek a tényezők többnyire csak közvetve hatnak az oltási bizonytalanságra. A kapott eredmények betekintést nyújtanak az oltási bizonytalanság komplex kapcsolatrendszerébe és segítenek megérteni a kialakulás folyamatát, mindezek mellett pedig hasznos gyakorlati támpontokat nyújthatnak az oltási bizonytalanság és az elutasítás csökkentését célzó beavatkozások tervezésébe.
Összeesküvés-elméletekben való hit, korai maladaptív sémák és személyiségjellemzők
Authors: Mirnics Zsuzsanna , Nagy Virág , Szilágyi Tünde , Rózsa Sándor
Published: January 2024

Vizsgálatunk célja a konspirációs hiedelmek és a korai maladaptív sémák közti kapcsolat feltárása volt a COVID-19 világjárvány időszakában. A vizsgálati mintát 1290 nő és 915 férfi online tesztkitöltése alkotta, amit a Károli Gáspár Református Egyetem „Életünk a koronavírus-járvány idején” című kutatásának adatbázisából merítettük. A konspiratív hiedelmek mérőeszközét Brotherton és munkatársai (2013) alapján, ehhez kapcsolódó elővizsgálatok nyomán állítottuk össze. A korai maladaptív sémák rövid mérőeszköze mellett a Big Five személyiségdimenziók mérésére a BFI-10 személyiségkérdőívet, a lelki közérzet vizsgálatára pedig a PHS-WB Jóllét Skálát és a DASS-21 kérdőívet vettük fel. Eredményeink szerint gyenge, de szignifikáns kapcsolat volt a korai maladaptív sémák és az összeesküvés hiedelmek között. A Big Five személyiségjegyek szintén enyhe, de szignifikáns bejósló változóként jelentek meg statisztikai számításainkban, a Nyitottság dimenzió esetében a várttal ellentétes irányban. Az összeesküvésekben való hit fontos prediktorának mutatkozott az iskolai végzettség. Adataink arra engednek következtetni, hogy pszichés betegség által nem érintett személyek mintáján a korai maladaptív sémák kis mértékben függenek össze az összeesküvés hiedelmekkel. A korai maladaptív sémákra jellemző kognitív torzítások ilyformán nem teljesen felelnek meg az összeesküvés hiedelmek által implikált kognitív torzításoknak. Eredményeink felvetik egyúttal, hogy azok a személyiségjegyek, amelyek az összeesküvés hiedelmeknek nagyobb teret adnak (pl. szkizotípia) csak enyhébb mértékben vannak jelen egy normál mintánál. A Nyitottság személyiségdimenzió az általunk használt mérőeszközben a pszichés rugalmasság mutatója lehet, kevésbé utalhat a nem konvencionális hiedelmekre.