Slide ini berisikan materi seminar proposal tugas akhir/skripsi mengenai sistem pendukung keputusan pemilihan tema tugas akhir Menggunakan metode Analytic Network Process
jangan lupa sitasi
Penelitian ini membahas mengenai tata kelola teknologi informasi (TI) yang
difokuskan pada bagian pemasaran Usaha Mikro, Kecil, dan Menengah (UMKM) di
Palembang dengan menerapkan arsitektur berorientasi layanan (SOA) sebagai kerangka
kerjanya. Penelitian ini bertujuan untuk menemukan faktor-faktor yang perlu diperhatikan
dalam menciptakan sistem pemasaran yang baik dan membuat suatu rekomendasi tata
kelola TI yang diharapkan dapat membantu UMKM dalam memperluas pangsa pasar.
Penelitian ini mengusulkan 4 faktor yang memiliki pengaruh terhadap tata kelola TI, yaitu
kelayakan produk (PF), permintaan pasar (MD), pesaing (C) dan promosi (P). Pengumpulan
data penelitian dilakukan dengan menyebarkan 100 kuesioner kepada pelaku UMKM, dan
diperoleh 100 respondent valid. Hasil pengolahan data dengan menggunakan aplikasi SPSS
versi 21.0 menunjukkan adanya pengaruh positif antara kelayakan produk (PF) terhadap
tata kelola TI dan tata kelota TI terhadap promosi (P). Rekomendasi tata kelola TI pada
penelitian ini dirancang dengan menggunakan kerangka kerja SOA web services, dimana
terdapat 2 layanan yang saling berkaitan, yaitu layanan UMKM kota Palembang dan layanan
sistem consumer.
Penelitian ini membahas mengenai tata kelola teknologi informasi (TI) yang
difokuskan pada bagian pemasaran Usaha Mikro, Kecil, dan Menengah (UMKM) di
Palembang dengan menerapkan arsitektur berorientasi layanan (SOA) sebagai kerangka
kerjanya. Penelitian ini bertujuan untuk menemukan faktor-faktor yang perlu diperhatikan
dalam menciptakan sistem pemasaran yang baik dan membuat suatu rekomendasi tata
kelola TI yang diharapkan dapat membantu UMKM dalam memperluas pangsa pasar.
Penelitian ini mengusulkan 4 faktor yang memiliki pengaruh terhadap tata kelola TI, yaitu
kelayakan produk (PF), permintaan pasar (MD), pesaing (C) dan promosi (P). Pengumpulan
data penelitian dilakukan dengan menyebarkan 100 kuesioner kepada pelaku UMKM, dan
diperoleh 100 respondent valid. Hasil pengolahan data dengan menggunakan aplikasi SPSS
versi 21.0 menunjukkan adanya pengaruh positif antara kelayakan produk (PF) terhadap
tata kelola TI dan tata kelota TI terhadap promosi (P). Rekomendasi tata kelola TI pada
penelitian ini dirancang dengan menggunakan kerangka kerja SOA web services, dimana
terdapat 2 layanan yang saling berkaitan, yaitu layanan UMKM kota Palembang dan layanan
sistem consumer.
APA ITU AUTENTIFIKASI ?
Authentification adalah proses dalam rangka validasi user pada saat memasuki sistem, nama dan password dari user di cek melalui proses yang mengecek langsung ke daftar mereka yang diberikan hak untuk memasuki sistem tersebut. Autorisasi ini di set up oleh administrator, webmaster atau pemilik situs (pemegang hak tertinggi atau mereka yang ditunjuk di sistem tersebut
White Box Testing atau Pengujian Kotak Putih, adalah salah satu cara yang dilakukan oleh software developer untuk memastikan jaminan kualitas sebuah perangkat lunak/software.
Dalam presentasi ini, akan dijelaskan tentang definisi, penggunaan, cara penggunaan, kelebihan, serta banyak hal lainnya!!
Tetap, menggunakan format .GIF, gambar-gambar dalam presentasi ini akan otomatis berjalan ketika slide dimainkan. Have fun and Enjoy!! Good luck
- Godya <> RCD
Business Process Modelling Notation (BPMN) adalah salah satu notasi paling populer yang digunakan untuk memodelkan proses bisnis.
dalam slide ini akan dipaparkan contoh dari case dunia nyata yang sederhana penggunaan dari BPMN sehingga diharapkan dapat lebih mudah dipahami.
---
Penyusun merupakan salah satu anggota tim Enterprise Architecture Kementerian Keuangan yang antusias di bidang digital transformation dan inovasi organisasi.
Mata Kuliah: Sistem Penunjang Keputusan
Pertemuan: 6
Jurusan: Sistem Informasi
Kampus: STMIK Swadharma
Sumber Gambar:
https://www.dreamstime.com/stock-images-d-man-stepping-up-to-his-successful-goal-top-business-graph-over-white-background-reflection-image32812074
https://stock.adobe.com/de/search?k=nachdenklich&filters%5Bcontent_type%3Aphoto%5D=1&filters%5Bcontent_type%3Aillustration%5D=1&filters%5Bcontent_type%3Azip_vector%5D=1&filters%5Bcontent_type%3Avideo%5D=1&filters%5Bcontent_type%3Atemplate%5D=1&filters%5Bcontent_type%3A3d%5D=1&filters%5Binclude_stock_enterprise%5D=0&filters%5Bis_editorial%5D=0&safe_search=1&ca=0&load_type=find_similar&similar_content_id=22795843&find_similar_by=all&asset_id=110287629
https://stock.adobe.com/ee/images/the-3d-guy-and-a-arrow-mark/98320291?asset_id=98670150
https://www.dreamstime.com/costs-benefits-concept-d-illustration-isolated-white-background-costs-benefits-concept-d-illustration-image138760233
https://www.dreamstime.com/stock-photography-3d-person-lifting-heavy-weight-image27592302
https://www.gograph.com/illustration/3d-person-and-credit-score-gg63491341.html
https://www.technobezz.com/best/best-gaming-laptops-buy/
https://www.peoplematters.in/article/trends/overall-salary-increase-108-2015-10738?utm_source=peoplematters&utm_medium=interstitial&utm_campaign=learnings-of-the-day
https://huskmitnavn.dk/blogs/projects/3d-drawings
APA ITU AUTENTIFIKASI ?
Authentification adalah proses dalam rangka validasi user pada saat memasuki sistem, nama dan password dari user di cek melalui proses yang mengecek langsung ke daftar mereka yang diberikan hak untuk memasuki sistem tersebut. Autorisasi ini di set up oleh administrator, webmaster atau pemilik situs (pemegang hak tertinggi atau mereka yang ditunjuk di sistem tersebut
White Box Testing atau Pengujian Kotak Putih, adalah salah satu cara yang dilakukan oleh software developer untuk memastikan jaminan kualitas sebuah perangkat lunak/software.
Dalam presentasi ini, akan dijelaskan tentang definisi, penggunaan, cara penggunaan, kelebihan, serta banyak hal lainnya!!
Tetap, menggunakan format .GIF, gambar-gambar dalam presentasi ini akan otomatis berjalan ketika slide dimainkan. Have fun and Enjoy!! Good luck
- Godya <> RCD
Business Process Modelling Notation (BPMN) adalah salah satu notasi paling populer yang digunakan untuk memodelkan proses bisnis.
dalam slide ini akan dipaparkan contoh dari case dunia nyata yang sederhana penggunaan dari BPMN sehingga diharapkan dapat lebih mudah dipahami.
---
Penyusun merupakan salah satu anggota tim Enterprise Architecture Kementerian Keuangan yang antusias di bidang digital transformation dan inovasi organisasi.
Mata Kuliah: Sistem Penunjang Keputusan
Pertemuan: 6
Jurusan: Sistem Informasi
Kampus: STMIK Swadharma
Sumber Gambar:
https://www.dreamstime.com/stock-images-d-man-stepping-up-to-his-successful-goal-top-business-graph-over-white-background-reflection-image32812074
https://stock.adobe.com/de/search?k=nachdenklich&filters%5Bcontent_type%3Aphoto%5D=1&filters%5Bcontent_type%3Aillustration%5D=1&filters%5Bcontent_type%3Azip_vector%5D=1&filters%5Bcontent_type%3Avideo%5D=1&filters%5Bcontent_type%3Atemplate%5D=1&filters%5Bcontent_type%3A3d%5D=1&filters%5Binclude_stock_enterprise%5D=0&filters%5Bis_editorial%5D=0&safe_search=1&ca=0&load_type=find_similar&similar_content_id=22795843&find_similar_by=all&asset_id=110287629
https://stock.adobe.com/ee/images/the-3d-guy-and-a-arrow-mark/98320291?asset_id=98670150
https://www.dreamstime.com/costs-benefits-concept-d-illustration-isolated-white-background-costs-benefits-concept-d-illustration-image138760233
https://www.dreamstime.com/stock-photography-3d-person-lifting-heavy-weight-image27592302
https://www.gograph.com/illustration/3d-person-and-credit-score-gg63491341.html
https://www.technobezz.com/best/best-gaming-laptops-buy/
https://www.peoplematters.in/article/trends/overall-salary-increase-108-2015-10738?utm_source=peoplematters&utm_medium=interstitial&utm_campaign=learnings-of-the-day
https://huskmitnavn.dk/blogs/projects/3d-drawings
A DESCRIPTIVE STUDY ON THE ANALYSIS OF STUDENTS ABILITY IN ANALYZING SENTENCES USING SEMANTIC ROLE
(ENGLISH DEPARTMENT FACULTY OF EDUCATION AND TEACHER TRAINING LAMBUNG MANGKURAT UNIVERSITY BANJARMASIN)
Pemanfaatan Teknologi Web di Bidang Dokumentasi & InformasiDwi Fajar Saputra
Materi ini dibawakan pada kegiatan "Stadium General" yang diselenggarakan oleh Program Studi S1 Ilmu Perpustakaan, UIN Ar-raniry. Acara berlangsung pada 5 September 2016 di Aula FAH, UIN Ar-raniry, Darusalam - Banda Aceh.
Research seminar at the University of Brighton presenting the ARISE project.
Here's the abstract:
Augmented Reality (AR) has a range of affordances that resonate with learning theory. Reflecting the early stage of the technology however, much existing research into AR focuses on technical issues and is based on prototype systems not suitable for end user deployment.
This presentation gives an insight into experiences gained in the European ARiSE (Augmented Reality in School Environments) project, which aims to develop a robust and affordable AR teaching platform suitable for deployment in schools.
In order to evaluate the tabletop AR learning platform, three consecutive prototypes of educational applications were produced, each reflecting the evolving technological capabilities of the platform and addressing different pedagogical approaches. These ranged from process visualisation in a human biology setting based on behaviourist and cognitive approaches, through guided construction of chemical elements based on constructivist ideas, to knowledge creation through communication and negotiation of meaning around cultural heritage objects with peers from another country, based on theories of social learning. The first two applications have been evaluated in summer schools involving video observations and interviews with secondary school students from Romania, Latvia and Germany.
Preliminary results indicate a high acceptance rate for the AR learning platform amongst students. The main advantages were seen in the 3D visualisation capabilities and the haptic user interface, which led to increased motivation, better concentration during learning activities, and faster and more accurate understanding of the learning content. Balancing these positive results were technical and usability issues that had a negative impact on the learning process.
The Architecture of System for Predicting Student Performance based on the Da...Thada Jantakoon
The goals of this study are to develop the architecture of a system for predicting student performance based on data science approaches (SPPS-DSA Architecture) and evaluate the SPPS-DSA Architecture. The research process is divided into two stages: (1) context analysis and (2) development and assessment. The data is analyzed by means of standardized deviations statistically. The research findings suggested that the SPPS-DSA architecture, according to the research findings, consists of three key components: (i) data source, (ii) machine learning methods and attributes, and (iii) data science process. The SPPS-DSA architecture is rated as the highest appropriate overall. Predicting student performance helps educators and students improve their teaching and learning processes. Predicting student performance using various analytical methods is reviewed here. Most researchers used CGPA and internal assessment as data sets. In terms of prediction methods, classification is widely used in educational data science. Researchers most commonly used neural networks and decision trees to predict student performance under classification techniques.
The International Journal of Engineering and Science (The IJES)theijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
CORRELATION BASED FEATURE SELECTION (CFS) TECHNIQUE TO PREDICT STUDENT PERFRO...IJCNCJournal
Education data mining is an emerging stream which helps in mining academic data for solving various
types of problems. One of the problems is the selection of a proper academic track. The admission of a
student in engineering college depends on many factors. In this paper we have tried to implement a
classification technique to assist students in predicting their success in admission in an engineering
stream.We have analyzed the data set containing information about student’s academic as well as sociodemographic variables, with attributes such as family pressure, interest, gender, XII marks and CET rank
in entrance examinations and historical data of previous batch of students. Feature selection is a process
for removing irrelevant and redundant features which will help improve the predictive accuracy of
classifiers. In this paper first we have used feature selection attribute algorithms Chi-square.InfoGain, and
GainRatio to predict the relevant features. Then we have applied fast correlation base filter on given
features. Later classification is done using NBTree, MultilayerPerceptron, NaiveBayes and Instance based
–K- nearest neighbor. Results showed reduction in computational cost and time and increase in predictive
accuracy for the student model
Correlation based feature selection (cfs) technique to predict student perfro...IJCNCJournal
Education data mining is an emerging stream which h
elps in mining academic data for solving various
types of problems. One of the problems is the selec
tion of a proper academic track. The admission of a
student in engineering college depends on many fact
ors. In this paper we have tried to implement a
classification technique to assist students in pred
icting their success in admission in an engineering
stream.We have analyzed the data set containing inf
ormation about student’s academic as well as socio-
demographic variables, with attributes such as fami
ly pressure, interest, gender, XII marks and CET ra
nk
in entrance examinations and historical data of pre
vious batch of students. Feature selection is a pro
cess
for removing irrelevant and redundant features whic
h will help improve the predictive accuracy of
classifiers. In this paper first we have used featu
re selection attribute algorithms Chi-square.InfoGa
in, and
GainRatio to predict the relevant features. Then we
have applied fast correlation base filter on given
features. Later classification is done using NBTree
, MultilayerPerceptron, NaiveBayes and Instance bas
ed
–K- nearest neighbor. Results showed reduction in c
omputational cost and time and increase in predicti
ve
accuracy for the student model
CORRELATION BASED FEATURE SELECTION (CFS) TECHNIQUE TO PREDICT STUDENT PERFRO...IJCNCJournal
Education data mining is an emerging stream which helps in mining academic data for solving various types of problems. One of the problems is the selection of a proper academic track. The admission of a student in engineering college depends on many factors. In this paper we have tried to implement a classification technique to assist students in predicting their success in admission in an engineering stream.We have analyzed the data set containing information about student’s academic as well as sociodemographic variables, with attributes such as family pressure, interest, gender, XII marks and CET rank in entrance examinations and historical data of previous batch of students. Feature selection is a process for removing irrelevant and redundant features which will help improve the predictive accuracy of classifiers. In this paper first we have used feature selection attribute algorithms Chi-square.InfoGain, and GainRatio to predict the relevant features. Then we have applied fast correlation base filter on given features. Later classification is done using NBTree, MultilayerPerceptron, NaiveBayes and Instance based –K- nearest neighbor. Results showed reduction in computational cost and time and increase in predictive accuracy for the student model
Integrated bio-search approaches with multi-objective algorithms for optimiza...TELKOMNIKA JOURNAL
Optimal selection of features is very difficult and crucial to achieve, particularly for the task of classification. It is due to the traditional method of selecting features that function independently and generated the collection of irrelevant features, which therefore affects the quality of the accuracy of the classification. The goal of this paper is to leverage the potential of bio-inspired search algorithms, together with wrapper, in optimizing multi-objective algorithms, namely ENORA and NSGA-II to generate an optimal set of features. The main steps are to idealize the combination of ENORA and NSGA-II with suitable bio-search algorithms where multiple subset generation has been implemented. The next step is to validate the optimum feature set by conducting a subset evaluation. Eight (8) comparison datasets of various sizes have been deliberately selected to be checked. Results shown that the ideal combination of multi-objective algorithms, namely ENORA and NSGA-II, with the selected bio-inspired search algorithm is promising to achieve a better optimal solution (i.e. a best features with higher classification accuracy) for the selected datasets. This discovery implies that the ability of bio-inspired wrapper/filtered system algorithms will boost the efficiency of ENORA and NSGA-II for the task of selecting and classifying features.
Unsupervised Feature Selection Based on the Distribution of Features Attribut...Waqas Tariq
Since dealing with high dimensional data is computationally complex and sometimes even intractable, recently several feature reductions methods have been developed to reduce the dimensionality of the data in order to simplify the calculation analysis in various applications such as text categorization, signal processing, image retrieval, gene expressions and etc. Among feature reduction techniques, feature selection is one the most popular methods due to the preservation of the original features. However, most of the current feature selection methods do not have a good performance when fed on imbalanced data sets which are pervasive in real world applications. In this paper, we propose a new unsupervised feature selection method attributed to imbalanced data sets, which will remove redundant features from the original feature space based on the distribution of features. To show the effectiveness of the proposed method, popular feature selection methods have been implemented and compared. Experimental results on the several imbalanced data sets, derived from UCI repository database, illustrate the effectiveness of our proposed methods in comparison with the other compared methods in terms of both accuracy and the number of selected features.
Big data cloud-based recommendation system using NLP techniques with machine ...TELKOMNIKA JOURNAL
Recommendation systems (RS) are crucial for social networking sites. Without it, finding precise products is harder. However, existing systems lack adequate efficiency, especially with big data. This paper presents a prototype cloud-based recommendation system for processing big data. The proposed work is implemented by utilizing the matrix factorization method with three approaches. In the first approach, singular value decomposition (SVD) is used, which is an old and traditional recommendation technique. The second recommendation approach is fine-tuned using the alternating least squares (ALS) algorithm with Apache Spark. Finally, the deep neural network (DNN) algorithm is utilized with TensorFlow. This study solves the challenge of handling large-scale datasets in the collaborative filtering (CF) technique after tuning the algorithms by adjusting the parameters in the second approach, which uses machine learning, as well as in the third approach, which uses deep learning. Furthermore, the results of these two approaches outperformed conventional techniques and achieved an acceptable computational time. The dataset size is about 1.5 GB and it is collected from the Goodreads website API. Moreover, the Hadoop distributed file system (HDFS) is used as cloud storage instead of the computer’s local disk for handling larger dataset sizes in the future.
Embedded System Practicum Module for Increase Student Comprehension of Microc...TELKOMNIKA JOURNAL
The result of applying the embedded system in education for students is successfully applied in
university. On the other side, many people in Indonesia use smart equipment’s (Hand phone, Remote), but
none of those equipments are used in education. University as the source of knowledge should overcome
the problem by encouraging the students to use a technology with learning about it first. Embedded
System Practicum Module Design needs a prototype method so that the practicum module that is desired
can be made. This method is often used in real life. A prototype considered of a part of a product that
expresses logic and physical of external interface that is being displayed and this method will fully depend
on user contentment. Embedded System Practicum Module Design is made to increase student
comprehension of embedded system course and to encourage students to innovate, so that many
technologies will be developed and also to help lecturers deliver course subjects. With this practicum it is
hoped that the student comprehension will increase significantly. The result of this research is a decent
practicum module, hardware or software that can help students to know better about technology and the
course subjects so that it will encourage the students to create an embedded system technology. The
result of the test has been done; there is an increase of learning value obtained by 7.8%.
WEB-BASED DATA MINING TOOLS : PERFORMING FEEDBACK ANALYSIS AND ASSOCIATION RU...IJDKP
This paper aims to explain the web-enabled tools for educational data mining. The proposed web-based
tool developed using Asp.Net framework and php can be helpful for universities or institutions providing
the students with elective courses as well improving academic activities based on feedback collected from
students. In Asp.Net tool, association rule mining using Apriori algorithm is used whereas in php based
Feedback Analytical Tool, feedback related to faculty and institutional infrastructure is collected from
students and based on that Feedback it shows performance of faculty and institution. Using that data, it
helps management to improve in-house training skills and gains knowledge about educational trends which
is to be followed by faculty to improve the effectiveness of the course and teaching skills.
This paper discusses challenges in contextual task analysis and the need of tools that support analysts to collect such information in context. Specifically we argue that the analysis of collaborative and distributed tasks can be supported by ambulatory assessment tools. We illustrate how contextual task analysis can be supported by TEMPEST, a platform originally created for experience sampling and more generally, longitudinal ambulatory assessment studies. We present a case study that illustrates the extent to which this tool meets the needs of real-world task analysis, describing the gains in efficiency it can provide but also directions for the development of tool support for task analysis.
On the benefit of logic-based machine learning to learn pairwise comparisonsjournalBEEI
In recent years, many daily processes such as internet web searching, e-mail filter-ing, social media services, e-commerce have benefited from machine learning tech-niques (ML). The implementation of ML techniques has been largely focused on blackbox methods where the general conclusions are not easily interpretable. Hence, theelaboration with other declarative software models to identify the correctness and com-pleteness of the models is not easy to perform. On the other hand, the emerge of somelogic-based machine learning techniques with their advantage of white box approachhave been proven to be well-suited for many software engineering tasks. In this paper,we propose the use of a logic-based approach to learn user preference in the form ofpairwise comparisons. APARELL as a novel approach of inductive learning is able tomodel the user’s preferences in description logic representation. This offers a rich, re-lational representation which is then can be used to produce a set of recommendations.A user study has been performed in our experiment to evaluate the implementation ofpairwise preference recommender system when compared to a standard list interface.The result of the experiment shows that the pairwise interface was significantly betterthan the other interface in many ways.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Seminar Proposal Tugas Akhir - SPK Pemilihan tema Tugas Akhir menggunakan Analytic Network Process
1. application of method analytic
network process in decision
support system for the selection
final project
Dila Nurlaila – 13102009
S1 Informatics
School Of Telematics Telkom Purwokerto
2. What will be discussed
Background of the problem
Problem of the study
Purpose of the Research
Scope of the problem
Method of the Research
Conclusion
Outline
4. confused
Semester 5 - 6
,
Semester 1 – 5
Mobile
program
ming
Animasi
3d
JaringanPemrogra
man java
And many
more
Too much learn, and not make a choice for
her passion
So that is the problem
Background of the problem
5. Background of the problem
Based on fact,
More than 80% of students informatics st3 Telkom
At the 4 semester do not have the concept of final
Prject.
6. Background of the problem
Based on fact,
29% of students do not know
at all informatics science
before studying in
informatics.
7. And many more,
From the begining, he chose the
wrong side
Stiil in the comfort zone
etc.
Background of the problem
8. Purpose of the Research
untuk mengetahui penggunaan tingkat keberhasilan
metode analytic network process yang diterapkan dalam system
pendukung keputusan untuk pemilihan tema tugas akhir
9. Problem of the study
1. Bagaimana menerapkan metode analytic network process
(ANP) dalam system pendukung keputusan untuk
pemilihan tema Tugas Akhir ?
Specially the formulation of the problem in this research
was
10. scope of the problem
1. Masalah yang dibahas pada penelitian ini adalah bagaimana menerapkan metode
analytic network process kedalam sebuah system pendukung keputusan untuk
menentukan tema Tugas Akhir
2. Study kasus dari penelitian ini adalah mahasiswa program studi S1 Informatika STT
Telematika Telkom Purwokerto yang akan mengambil mata kuliah tugas akhir
3. Dalam penelitian ini ada beberapa Set kriteria yang digunakan yaitu nilai
matakuliah dari bidang ilmu RPL dan TI, hasil tes bakat, skill mahasiswa dan
minat/passion.
11. Selecting or prioritizing alternatives from a set of available
alternatives with respect to multiple criteria, is often refer to Multi-Criteria
Decision Making (MCDM).
analytic Hierarchy Process (AHP) and Analytic Network Process
(ANP) are the common methods by which to solve Multi-Criteria Decision
Making problems.
Analytic Network Process
12. Analytic Network Process
why used the analytic network process ?
Because, The Analytic network Process method (ANP) was the development of the
Analytical Hierarchy Process method (AHP). The ANP method of could improve the AHP
weakness took the form of the capacity the connection between the criterion or the
alternative (Saaty, 2004)
13. Analytic Network Process
Tujuan
Kriteria
Subkriteria
Alternatif
Loop menunjukkan bahwa setiap elemen
hanya tergantung pada dirinya sendiri
Hierarchy
Linear (AHP)
Feedback
C
4
C
1
C
2
C
3
Network Feedback
(ANP)
Komponen
Cluster (level)
Outer
Dependence
Iner
Dependence
Elemen
The difference of AHP and ANP
14. Method of research
1. Lokasi Penelitian / case study
-
2. Kind of the research
- type of the research is Action Research (Tindakan)
3. Method of collecting data
- using a quistionnaire
15. Identification and
definition of the
problem
Classification
decision makers
Identification of
criteria and sub-
criteria decision
alternatives
Study of
Literature
Collection data
Processing data
using ANP
method
Apply the results
into modeling of
DSS
Method of research
17. Study Literaturer
1. Implementasi metode Analytic Network Process untuk membangun aplikasi executive
support system pada perusahaan consultant IT (Jurnal Ilmu Komputer – Vol 4. no.1 – April 2011)
oleh : Ngurah Agus Sanjaya ER Universitas Udayana
This research built a support system executives to determine the success of SEO projects by
applying methods of ANP,
2. Choosing a College Major : A prototype decision support system (Journal Computer in Human
Behavior, vol.10, no.3, copyright 1994 Elsevier Science Ltd) by : Barry B. Zwibelman and Robert T.
Plant University of Miami.
This article demonstrates the feasibility of a new computer technology, decision support systems
(DSSs), to assist counselors with their clients in choosing a college major:
18. Study Literaturer
3. Sistem Pendukung Keputusan Pemilihan bidang studi di Perguruan Tinggi menggunakan
metode Analytic Network Process (Jurnal Program teknologi informasi dan ilmu computer
Universitas Brawijaya) by : Robert Eka Rahendi, dkk
19. References
T. L. Saaty, “Fundamental Of the Analytic Network Process Dependence
and feedback in Decision - Making with Single Network,” Systems Science And
System Engineering, vol. 13, 2004.
J. Hidayati, “Penerapan Analytical Network Process (ANP) pada Sistem
Pengukuran Kinerja Di Kebun Sidamanik Pematang Siantar,” 2012. [Online]. Available:
http://ejournal.undip.ac.id/index.php/jgti/article/view/4088/3738.. [Diakses 20 03 2016].
Thomas. L. Saaty dan L. G. Vargas, Decision Making with the Analytic Network Process,
New York : Springer, 2006.