130 research outputs found
Exploring Research Trends and Impact: A Bibliometric Analysis of RESTI Journal from 2018 to 2022
No full textThis study provides a comprehensive analysis of the RESTI Journal, a prominent publication in the field of systems engineering and information technology. The analysis aims to evaluate the journal's publication output, citation impact, and overall contribution to the field. The study utilizes data from the Dimensions database, focusing on articles published between 2018 and 2022, resulting in a dataset of 594 articles. To analyze the collected data, the study employs bibliometric and network visualization tools such as Bibliometrix and VOSviewer. The analysis reveals a notable increase in the number of publications over time, indicating a growing interest and research activity in the field. Furthermore, the distribution of author productivity deviates from Lotka's law, highlighting variations in author patterns and productivity levels. An examination of institutional affiliations reveals Telkom University as the dominant institution, making a substantial contribution to the journal. Visualizations based on author-provided titles, abstracts, and keywords highlight research trends in image recognition and classification, with a particular emphasis on utilizing Convolutional Neural Networks (CNN) and Support Vector Machines (SVM). Overall, this study provides valuable insights into the performance and trends of the RESTI Journal. The findings contribute to a deeper understanding of the journal's impact and its role in advancing knowledge in systems engineering and information technology. These insights can inform researchers, practitioners, and stakeholders in the field, guiding future research directions and enhancing the scholarly impact of the RESTI Journal
PENGARUH PERAN PEMIMPIN TERHADAP KEPUASAN KERJA KARYAWAN PT. DHANAR MAS CONCERN BANDUNG
No full textResti Fitria Martiany
1001746
Skripsi ini dibimbing oleh:
Hady Siti Hadijah, S.Pd. M.Si.
Masalah yang menjadi kajian dalam penelitian ini adalah mengenai kepuasan kerja karyawan staf PT. Dhanar Mas Concern Bandung. Tujuan dari penelitian ini adalah untuk mengetahui gambaran efektivitas pengaruh peran kepemimpinan terhadap kepuasan kerja karyawan di PT. Dhanar Mas Concern.
Teori yang digunakan untuk memecahkan masalah dalam penelitian ini adalah Teori Perilaku Organisasi dalam perspektif psikologis. Penelitian ini terdiri dari dua variabel yaitu peran pemimpin pada Variabel X dengan indikator: peran sebagai tokoh utama/peran yang dituakan (Figurehead Role), peran kepemimpinan (Leader Role), peran penghubung (Liaision Role), peran sebagai pemantau (Monitor Role), Peran sebagai penyebar informasi (Disseminator Role), peran sebagai juru bicara (Spokesman), peran sebagai wirausaha (Entrepreneur Role), peran sebagai penghalau gangguan (Disturbance Handler Role), peran sebagai pembagi sumber daya (Resource Allocator Role), dan peran sebagai negosiator (Negotiator Role) dan kepuasan kerja pada Variabel Y dengan indikator: moral kerja, kedisiplinan dan prestasi kerja.
Penelitian ini menggunakan metode survey, dengan teknik pengumpulan data melalui penyebaran angket dan menggunakan skala pengukuran Likert, ukuran sampel 51 orang karyawan staf PT. Dhanar Mas Concern. Teknik analisis data yang digunakan adalah analisis regresi sederhana.
Berdasarkan hasil penelitian maka diperoleh informasi bahwa variabel peran kepemimpinan berada pada kategori cukup efektif. Indikator tertinggi pada peran sebagai pembagi sumber daya (Resource Allocator Role) sedangkan indikator terendah pada peran sebagai tokoh utama/peran yang dituakan (Figurehead Role). Variabel kepuasan kerja karyawan berada pada kategori sedang/cukup puas. Indikator tertinggi adalah prestasi kerja, sedangkan indikator terendah pada kedisiplinan. Uji hipotesis menunjukkan bahwa peran kepemimpinan berpengaruh positif dan signifikan terhadap kinerja karyawan staf di PT. Dhanar Mas Concern. Nilai koefisien korelasi yang diperoleh menunjukkan bahwa peran kepemimpinan dan kepuasan kerja karyawan memiliki korelasi yang kuat.
Issues that were analyzed in this study is the job satisfaction employee staff at PT. Dhanar Mas Concern Bandung. The purpose of this study is to describe the effectiveness of leadership roles influence on job satisfaction of employee staff at PT. Dhanar Mas Concern.
The theory is used to solve the problem in this research is the Theory of Organizational Behavior in the psychological perspective. The study consisted of two variables: the role of leadership in the indicator Variable X: the role of the main character/role of the elder, the role of the leader, the role of liaison, the role as monitors,the role as a disseminator of information, a role as a spokes person, the role of entrepreneurs, the role as a blocker disorder, the role of the shared resource, and the role of negotiator and job satisfaction on the indicator Variable Y: morale, discipline and work performance.
This study used survey method, the technique of collecting data through question naires and measurements using a Likertscale, a sample size of 51 staff employees of PT. Dhanar Mas Concern. The data analysis technique used is a simple regression analysis.
Based on the research results obtained information that the variable is in the category of leadership role quite effectively. The highest indicator on the role as a divider resource (Resource Allocator Role) while the lowest indicator on the role as the main character / role of the elder (figurehead Role). Employee job satisfaction variables in middle category / quite satisfied. Performance indicator is the highest, while the lowest indicator in the discipline. Hypothesis testing showed that leadership role and a significant positive effect on employee staff performance at PT. Dhanar Mas Concern. Correlation coefficient values obtained indicate that the role of leadership and employee job satisfaction have a strong correlation
Heart Attack Notification and Monitoring System Using Internet of Things
No full textPeople are frequently shocked when someone passes away suddenly without any prior symptoms. One of the contributing factors is a heart attack. This condition might occur anywhere and at any time. A sudden heart attack can be highly perilous for a person who is alone, without family members or friends because the family cannot be informed of the victim's condition or their location. Therefore, it is vital to raise awareness of heart attacks. With the support of the Internet of Things, this study aims to develop a wearable device that people may use to monitor their heart health and connect with hospitals to get alerts in case of a heart attack. This system also provides family members with access to a web-based patient monitoring tool. The heart beat is considered as the parameter in developing this system. There are three types of evaluation which are conducted in this study, namely: 1) Sub-system evaluation; 2) Black-box testing; and 3) Integrating system testing. The three evaluation results show that all assembled hardware components are work properly and the system effectively satisfies the objectives of monitoring, buzzer activation, hospital and patient family notification, and so forth, with 1.96% average sensor error, which is still considerably acceptable.
People are frequently shocked when someone passes away suddenly without any prior symptoms. One of the contributing factors is a heart attack. This condition might occur anywhere and at any time. A sudden heart attack can be highly perilous for a person who is alone, without family members or friends because the family cannot be informed of the victim's condition or their location. Therefore, it is vital to raise awareness of heart attacks. With the support of the Internet of Things, this study aims to develop a wearable device that people may use to monitor their heart health and connect with hospitals to get alerts in case of a heart attack. This system also provides family members with access to a web-based patient monitoring tool. The heart beat is considered as the parameter in developing this system. There are three types of evaluation which are conducted in this study, namely: 1) Sub-system evaluation; 2) Black-box testing; and 3) Integrating system testing. The three evaluation results show that all assembled hardware components are work properly and the system effectively satisfies the objectives of monitoring, buzzer activation, hospital and patient family notification, and so forth, with 1.96% average sensor error, which is still considerably acceptable
Sybil Attack Prediction on Vehicle Network Using Deep Learning
No full textVehicular Ad Hoc Network (VANET) or vehicle network is a technology developed for autonomous vehicles in Intelligent Transportation Systems (ITS). The communication system of VANET is using a wireless network that is potentially being attacked. The Sybil attack is one of the attacks that occur by broadcasting spurious information to the nodes in the network and could cause a crippled network. The Sybil strikes the network by camouflaging themselves as a node and providing false information to nearby nodes. This study is conducted to predict the Sybil attack by analyzing the attack pattern using a deep learning algorithm. The variables exerted in this research are time, location, and traffic density. By implementing a deep learning algorithm enacting the Sybil attack pattern and combining several variables, such as time, position, and traffic density, it reaches 94% of detected Sybil attacks.
Vehicular Ad Hoc Network (VANET) or vehicle network is a technology developed for autonomous vehicles in Intelligent Transportation Systems (ITS). The communication system of VANET is using a wireless network that is potentially being attacked. The Sybil attack is one of the attacks that occur by broadcasting spurious information to the nodes in the network and could cause a crippled network. The Sybil strikes the network by camouflaging themselves as a node and providing false information to nearby nodes. This study is conducted to predict the Sybil attack by analyzing the attack pattern using a deep learning algorithm. The variables exerted in this research are time, location, and traffic density. By implementing a deep learning algorithm enacting the Sybil attack pattern and combining several variables, such as time, position, and traffic density, it reaches 94% of detected Sybil attacks
Pneumonia Image Classification Using CNN with Max Pooling and Average Pooling
No full textPneumonia is still a frequent cause of death in hundreds of thousands of children in most developing countries and is generally detected clinically through chest radiographs. This method is still difficult to detect the disease and requires a long time to produce a diagnosis. To simplify and shorten the detection process, we need a faster method and more precise diagnosis of pneumonia. This study aims to classify chest x-ray images using the CNN method to diagnose pneumonia. The proposed CNN model will be tested using max & average pooling. The proposed model is developed in previous studies by adding batch normalization, dropout layer, and the number of epochs used. The dataset used will be optimized with oversampling & data augmentation techniques to maximize model performance. The dataset used in this study is "Chest X-Ray Images (Pneumonia)," with 5,856 data divided into two classes, namely Normal and Pneumonia. The proposed model gets 98% results using average pooling, where the results increase by 9-13% better than the previous study. This is because the overall pixel value of the image is highly considered to classify normal lungs and pneumonia.
 
Covid-19 Fake News Detection on Twitter Based on Author Credibility Using Information Gain and KNN Methods
No full textTwitter is one of the social media that is used as a tool to share various kinds of information about various kinds of things that are of concern to social media users. One of the information shared is information about COVID-19, which is known that the COVID-19 pandemic is currently spreading throughout the world at a very alarming rate. COVID-19 is an infectious disease caused by SARS-COV-2. The World Health Organization (WHO) claims that the spread of COVID-19 is supported by the spread of false/fake news. So to find out the truth of the news, a COVID-19 fake news detector is needed so that users don't fall for the hoaxes circulating. This study aims to classify COVID-19 news on Twitter based on author credibility. Credibility in question is a person's perception of the validity of information and is a multidimensional concept that is used as a means of receiving information to assess the source of communication. The method used in this research is Information Gain and KNN. KNN (K-Nearest Neighbor) is a supervised learning algorithm that works by classifying a set of data based on classified training data. Information Gain is used to ranking the most influential attributes, and KNN is used to classify data based on learning data taken from the nearest neighbors. The research consists of 6 main stages, namely data collection (crawling data), data preprocessing, feature extraction, feature selection, data split into training data and testing data, KNN stage, and data evaluation stage. The research carried out succeeded in obtaining an accuracy value of 91%, a correlation value between credibility and hoax of 0.115, and a p-value <0.005.
Twitter is one of the social media that is used as a tool to share various kinds of information about various kinds of things that are of concern to social media users. One of the information shared is information about COVID-19, which is known that the COVID-19 pandemic is currently spreading throughout the world at a very alarming rate. COVID-19 is an infectious disease caused by SARS-COV-2. The World Health Organization (WHO) claims that the spread of COVID-19 is supported by the spread of false/fake news. So to find out the truth of the news, a COVID-19 fake news detector is needed so that users don't fall for the hoaxes circulating. This study aims to classify COVID-19 news on Twitter based on author credibility. Credibility in question is a person's perception of the validity of information and is a multidimensional concept that is used as a means of receiving information to assess the source of communication. The method used in this research is Information Gain and KNN. KNN (K-Nearest Neighbor) is a supervised learning algorithm that works by classifying a set of data based on classified training data. Information Gain is used to ranking the most influential attributes, and KNN is used to classify data based on learning data taken from the nearest neighbors. The research consists of 6 main stages, namely data collection (crawling data), data preprocessing, feature extraction, feature selection, data split into training data and testing data, KNN stage, and data evaluation stage. The research carried out succeeded in obtaining an accuracy value of 91%, a correlation value between credibility and hoax of 0.115, and a p-value <0.005
Identifikasi Manajemen Resiko yang diusulkan pada Operasional SME dalam Penerapan Sistem ERP Jangka Panjang.
No full textRisk management in business strategic based on the survey that has been done by UKM Ebjed Kaos Factory, Bantul (Yogyakarta) by doing interview directly toward one of the supervisor of the factory which states that the risk in business can affect the part of benefit from the result of their production, it is because in the last few years the results of the expected profits was in fact not stable by applying the strategy, it needs strategy with a frameworks in their ERP system, so that every process of production that has done can have information data which is programmed, analyzed and compared to the risk level of the previous production. All the information data based on their sample of logistic experience in the last few years with an interview approaches model towards 2 from 16 employees, 1 chief inventory staff and the main leader of their UKM factory. The results of this approach Provides almost 80% information that the author needs. Then the author designs and implements a strategy that can generate relevant Information data for the framework of risk management of every logistic area of their UKM. In conclusion, when they’re consider with an efficient strategy, it will surely make a profit for t if every risk faced can be designed and implemented well.Management resiko dalam strategy bisnis berdasarkan survey yang telah dilakukan pada UKM Pabrikan Ebjed Kaos Bantul (Yogyakarta) dengan melakukan wawancara secara langsung terhadap salah satu pengawas produksi yang menyatakan bahwa Resiko dalam bisnis mempengaruhi sebagian keuntungan dari hasil proses produksi mereka. Alasnya karena dalam beberapa tahun terakhir hasil dari setiap produksi pada kenyataanya tidak begitu stabil dengan strategy yang di terapkan, ini membutuhkan stategy dengan sebuah kerangka kerja pada sistem ERP mereka, sehingga setiap proses produksi yang di lakukan mempunyai data informasi yang telah di rancang, di analisa dan dibandingkan tingkat resikonya dengan proses produksi sebelumnya. Semua data informasi berdasarkan sampel pengalaman logistik mereka dalam beberapa tahun terkahir dengan model pendekatan wawancara terhadap 2 dari 16 karyawan, 1 kepala staf persediaan dan pemimpin utama UKM Pabrik mereka. hasil dari pendekatan ini memberikan hampir 80% informasi yang kami butuhkan, kemudian kami merancang dan mengimplementasikan sebuah strategy yang dapat menghasilkan data informasi yang relevan untuk kerangka kerja management resiko dari setiap area logistik UKM mereka. Dengan mengutamakan strategy yang efisien Akan menghasilkan keuntungan jika setiap resiko yang di hadapi dapat dirancangkan di implementasikan dengan baik
CORRELATION BETWEEN STUDENTS’ PRONUNCATION ABILITY AND THEIR READING FLUENCY AT SMK TELKOM PEKANBARU
No full textABSTRACT
Resti sarimah (2022): The Correlation Between Students’ Pronunciation and Students’ Reading Fluence at TELKOM Vocational High School Pekanbaru
This research explored about students‟ pronunciation which could help students increase their reading fluency. In the learning process of English course, teachers delivered the learning based on the reference book and predominantly the learning focused on the English skills (listening, speaking, reading, and writing). Especially in their reading skill, the teacher focused on all aspects to develope the students‟ reading skill. As teacher‟s explanation, in teaching reading he/she asked the students to understand the text in front of the class and other students listen to their friends well and corrected the wrong pronunciation when reading the text. Beside that, the teacher also read so that they could read the text fluently.
This research was conducted on grade XI students of TELKOM Vocational High School Pekanbaru consisting of 5 classes with total population 153 students. The author used total sampling as the technique of sample selection. The author used product moment correlation formula from pearson because it took two variables namely independent and dependent variables combined and the scale of data measurement was interval scale.
The research results show that there is correlation between students‟ pronunciation and their reading fluence at TELKOM Vocational High School Pekanbaru. This is supported by the value achieved by the students after the researcher gave a test. The result of Pearson Product Moment Correlation was 0.743. The result of dependency level = 0, in the table of 5% with significance level 0.05. In other words, pronunciation has correlation to the students‟ reading fluence at TELKOM Vocational High School Pekanbaru
Classification of Acute Lymphoblastic Leukemia based on White Blood Cell Images using InceptionV3 Model
No full textAcute lymphoblastic leukemia (ALL) is the most common form of leukemia that occurs in children. Detection of ALL through white blood cell image analysis can help with the prognosis and appropriate treatment. In this study, the author proposes an approach to classifying ALL based on white blood cell images using a convolutional neural network (CNN) model called InceptionV3. The dataset used in this research consists of white blood cell images collected from patients with ALL and healthy individuals. These images were obtained from The Cancer Imaging Archive (TCIA), which is a service that stores large-scale cancer medical images available to the public. During the evaluation phase, the author used training data evaluation metrics such as accuracy and loss to measure the model's performance. The research results show that the InceptionV3 model is capable of classifying white blood cell images with a high level of accuracy. This model achieves an average ALL recognition accuracy of 0.9896 with a loss of 0.031. The use of CNN models such as InceptionV3 in medical image analysis has the potential to improve the efficiency and precision of image-based disease diagnosis
Meta Analisis Pengaruh Model Pembelajaran Problem Based Learning terhadap Kemampuan Berpikir Kritis Siswa SD pada Muatan
No full textTujuan penelitian ini untuk mengetahui penerapan model pembelajaran Problem Based Learning dalam meningkatkan kemampuan berpikir kritis siswa Sekolah Dasar. Dimana model pembelajaran Problem Based Learning ini adalah model yang berbasis dengan permasalahan yang mampu meningkatkan kemampuan berpikir kritis siswa. Pada penelitian ini menggunakan Meta Analisis dengan langkah pertama yang dilakukan yaitu dengan merumuskan masalah, kemudian mengumpulkan data, menyajikan data, kemudian kesimpulan. Dari beberapa jurnal yang sudah dianalisis dapat disimpulkan bahwa penggunaan model problem based learning dapat meningkatkan kemampuan berfikir kritis siswa sekolah dasar
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