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Hasil Pencarian

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Sardar, Ziauddin
London: Clive Bingley , 1979
025.46 SAR i
Buku Teks SO  Universitas Indonesia Library
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Doan Perdana
"[ABSTRAK
Intelligent Transportation System (ITS) adalah salah satu teknologi yang mengintegrasikan antar sistem informasi dan teknologi komunikasi dengan infrastruktur transportasi, kendaraan, dan pengguna jalan. Salah satu implementasi teknologi Intelligent Transportation System (ITS) adalah Vehicular Ad Hoc Network (VANET). VANET merupakan sistem komunikasi kendaraan yang mendukung untuk komunikasi Vehicle to Infrastructure (V2I) dan Vehicle to Vehicle (V2V). Sebagai bagian dari Intelligent Transportation System (ITS), komunikasi kendaraan dalam jaringan VANET dapat lebih efektif dalam menghindari kecelakaan dan kemacetan lalu lintas dari pada jika setiap kendaraan mencoba untuk memecahkan masalah ini secara individual.
Standar IEEE 1609.4 didefinisikan sebagai mode operasi Multikanal jaringan VANET pada lapisan Medium Access Control (MAC) yang terdiri dari tujuh kanal frekuensi yang berbeda, yaitu satu kanal CCH178 akan dialokasikan untuk Control Channel (CCH), yang digunakan sebagai kanal publik untuk aplikasi keamanan yang relevan di jalan. Enam kanal ya ng lainnya dialokasikan untuk Service Channel (SCH), yang digunakan sebagai kanal untuk menangani layanan multimedia dan yang tidak berhubungan dengan keamanan di jalan. Salah satu permasalahan dalam penjaminan kinerja pada IEEE 1609.4 adalah tingginya mobilitas node kendaraan dan perubahan lintasan yang berbeda. Hal ini menyebabkan delay yang tinggi dan throughput yang rendah. Peningkatan kinerja pada standar IEEE 1609.4 dapat dilakukan dengan optimasi pada proses sinkronisasi interval kanal CCH dan SCH.
Pada disertasi ini dikembangkan model baru Markov chain yang bertujuan untuk meningkatkan kinerja sistem koordinasi kanal dinamis pada standar multikanal IEEE 1609.4 terhadap pengaruh anomali kinerja, slot anomali, efek Doppler, fading Nakagami dan AWGN. Perbaikan kinerja yang dilakukan terhadap pengaruh diatas adalah dengan menggunakan nilai awal optimal Contention Window (CW). Penentuan nilai awal CW akan mempengaruhi kinerja yang dihasilkan pada model Markov chain yang digunakan. Nilai awal optimal CW didapatkan dari hasil distribusi node di setiap zone dengan menggunakan distribusi Poisson.
Dari hasil simulasi dan evaluasi kinerja yang dihasilkan, dapat dianalisa bahwa model DCF yang diajukan pada disertasi ini dapat menurunkan nilai delay transmisi CCH terhadap adanya kanal propagasi Nakagami dengan rata-rata (mean) sebesar 16.84 %. Selanjutnya, dapat disimpulkan bahwa kinerja yang dihasilkan pada model Markov chain dengan menggunakan nilai awal optimal CW didapatkan meningkatkan nilai Aggregate Throughput sebesar 42.53% dibandingkan dengan model yang diajukan oleh Wang. Sedangkan model DCF yang diajukan meningkatkan nilai probabilitas transmisi paket WAVE Service Advertisement (WSA) terhadap fenomena anomalous slot dengan persentase kenaikan rata-rata (mean) sebesar 11.35 %. Selanjutnya, dapat dianalisa bahwa model DCF yang diajukan meningkatkan nilai interval waktu dari akses contention kanal CCH terhadap efek Doppler dengan persentase kenaikan rata-rata (mean) sebesar 11.31 %;

ABSTRACT
Intelligent Transportation System (ITS) is one of the technologies that integrate information systems and communication technologies with transportation infrastructures, vehicles and road users. One implementation of the Intelligent Transportation System (ITS) is Vehicular Ad Hoc Network (VANET). VANET is a vehicle communication system which supports Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) communication. As a part of the Intelligent Transportation System (ITS), vehicles communication in VANET networks can be more effective in avoiding accidents and traffic congestion than if each vehicle try to solve this problem individually.
The IEEE 1609.4 standard is defined as the multichannel operation mode of VANET on Medium Access Control (MAC) layer. One of the problems in guaranteeing the performance of the IEEE 1609.4 is the high vehicular node mobility and different trajectory changes. These cause high delay and low throughput. Services Quality assurance to the IEEE 1609.4 standard can be done using optimizing the synchronization process of CCH and SCH channel intervals so that delay can be reduced and throughput saturation of SCH channel can be increased.
In this dissertation a new model of the Markov chain will be developed which aims to evaluate the performance of dynamic channel coordination system on the IEEE 1609.4 multichannel standard against performance anomalies influences, slot anomalies, the Doppler Effect, Nakagami fading and Additive White Gaussian Noise (AWGN). The performance improvements that is done to the effect above is to use the optimal initial value of Contention Window (CW). This is consistent with previous studies that have been done, the determination of the initial value of Contention Window (CW) will affect the resulting performance of the used Markov chain model. Optimal initial value Contention Window (CW) is obtained from the distribution of nodes in each zone by using the Poisson distribution.
From the simulation and performance evaluation results, it can be concluded that the DCF model in this dissertation can reduce the CCH transmission delay against the propagation channel Nakagami with an average of 16.84%. Moreover, it can be concluded that the performance of the resulting Markov chain model using the optimal initial value obtained CW increases value Aggregate Throughput of 42.8% against the effects of the anomaly performance. Meanwhile, the probability of packet transmission WSA influenced by anomalous slot with the percentage of mean increases approximately 11.35 %. Furthermore, it can be analyzed that the DCF model proposed result is the time interval CCH access contention influenced by anomalous slot with the percentage of mean increases approximately 11.31%;Intelligent Transportation System (ITS) is one of the technologies that integrate information systems and communication technologies with transportation infrastructures, vehicles and road users. One implementation of the Intelligent Transportation System (ITS) is Vehicular Ad Hoc Network (VANET). VANET is a vehicle communication system which supports Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) communication. As a part of the Intelligent Transportation System (ITS), vehicles communication in VANET networks can be more effective in avoiding accidents and traffic congestion than if each vehicle try to solve this problem individually.
The IEEE 1609.4 standard is defined as the multichannel operation mode of VANET on Medium Access Control (MAC) layer. One of the problems in guaranteeing the performance of the IEEE 1609.4 is the high vehicular node mobility and different trajectory changes. These cause high delay and low throughput. Services Quality assurance to the IEEE 1609.4 standard can be done using optimizing the synchronization process of CCH and SCH channel intervals so that delay can be reduced and throughput saturation of SCH channel can be increased.
In this dissertation a new model of the Markov chain will be developed which aims to evaluate the performance of dynamic channel coordination system on the IEEE 1609.4 multichannel standard against performance anomalies influences, slot anomalies, the Doppler Effect, Nakagami fading and Additive White Gaussian Noise (AWGN). The performance improvements that is done to the effect above is to use the optimal initial value of Contention Window (CW). This is consistent with previous studies that have been done, the determination of the initial value of Contention Window (CW) will affect the resulting performance of the used Markov chain model. Optimal initial value Contention Window (CW) is obtained from the distribution of nodes in each zone by using the Poisson distribution.
From the simulation and performance evaluation results, it can be concluded that the DCF model in this dissertation can reduce the CCH transmission delay against the propagation channel Nakagami with an average of 16.84%. Moreover, it can be concluded that the performance of the resulting Markov chain model using the optimal initial value obtained CW increases value Aggregate Throughput of 42.8% against the effects of the anomaly performance. Meanwhile, the probability of packet transmission WSA influenced by anomalous slot with the percentage of mean increases approximately 11.35 %. Furthermore, it can be analyzed that the DCF model proposed result is the time interval CCH access contention influenced by anomalous slot with the percentage of mean increases approximately 11.31%, Intelligent Transportation System (ITS) is one of the technologies that integrate information systems and communication technologies with transportation infrastructures, vehicles and road users. One implementation of the Intelligent Transportation System (ITS) is Vehicular Ad Hoc Network (VANET). VANET is a vehicle communication system which supports Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V) communication. As a part of the Intelligent Transportation System (ITS), vehicles communication in VANET networks can be more effective in avoiding accidents and traffic congestion than if each vehicle try to solve this problem individually.
The IEEE 1609.4 standard is defined as the multichannel operation mode of VANET on Medium Access Control (MAC) layer. One of the problems in guaranteeing the performance of the IEEE 1609.4 is the high vehicular node mobility and different trajectory changes. These cause high delay and low throughput. Services Quality assurance to the IEEE 1609.4 standard can be done using optimizing the synchronization process of CCH and SCH channel intervals so that delay can be reduced and throughput saturation of SCH channel can be increased.
In this dissertation a new model of the Markov chain will be developed which aims to evaluate the performance of dynamic channel coordination system on the IEEE 1609.4 multichannel standard against performance anomalies influences, slot anomalies, the Doppler Effect, Nakagami fading and Additive White Gaussian Noise (AWGN). The performance improvements that is done to the effect above is to use the optimal initial value of Contention Window (CW). This is consistent with previous studies that have been done, the determination of the initial value of Contention Window (CW) will affect the resulting performance of the used Markov chain model. Optimal initial value Contention Window (CW) is obtained from the distribution of nodes in each zone by using the Poisson distribution.
From the simulation and performance evaluation results, it can be concluded that the DCF model in this dissertation can reduce the CCH transmission delay against the propagation channel Nakagami with an average of 16.84%. Moreover, it can be concluded that the performance of the resulting Markov chain model using the optimal initial value obtained CW increases value Aggregate Throughput of 42.8% against the effects of the anomaly performance. Meanwhile, the probability of packet transmission WSA influenced by anomalous slot with the percentage of mean increases approximately 11.35 %. Furthermore, it can be analyzed that the DCF model proposed result is the time interval CCH access contention influenced by anomalous slot with the percentage of mean increases approximately 11.31%]"
2015
D2073
UI - Disertasi Membership  Universitas Indonesia Library
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Michelle Angel
"Penelitian ini bertujuan untuk mengkaji bagaimana pengaruh perilaku belanja konsumen apabila melakukan perbelanjaan menggunakan metode pembayaran “Buy-Now-Pay-Later” sebagai inovasi terbaru metode pembayaran online. Untuk mencapai tujuan tersebut, penelitian ini mendasarkan analisisnya pada beberapa teori utama, yaitu konsep efek numerositas (numerosity effect); perceived expensiveness, dan rasa sakit saat membayar (pain of payment concept) yang berperan sbagai mediasi antara metode pembayaran paylater dan perilaku konsumen. Dengan membagi pembayaran menjadi jumlah lebih kecil menggunakan paylater, rasa sakit yang dirasakan saat membayar menjadi berkurang, sehingga menyebabkan peningkatan perilaku belanja. Penelitian ini akan menggunakan pendekatan kuantitatif dengan penyebaran kuesioner terstruktur melalui survei online. Responden diminta untuk menjawab pertanyaan-pertanyaan yang berfokus pada situasi belanja dengan metode pembayaran paylater. Hasil penelitian ini diharapkan dapat memberikan wawasan baru mengenai implikasi metode pembayaran paylater terhadap perilaku belanja konsumen, serta bagaimana variabel mediasi berperan dalam hal ini. Penelitian ini diperoleh melalui pengolahan data menggunakan Structural Equation Modeling (SEM).

This research aims to examine how consumer shopping behavior will be affected if they use the "Buy-Now-Pay-Later" payment method as the latest innovation in online payment methods. To achieve this goal, this research bases its analysis on several main theories, namely the concept of the numerosity effect; perceived expensiveness, and pain when paying (pain of paying concept) which act as mediation between the paylater payment method and consumer behavior. By splitting payments into smaller amounts using paylater, the pain felt when paying is reduced, leading to increased shopping behavior. This research uses a quantitative approach by distributing structured questionnaires through online surveys. Respondents were asked to answer questions that focused on shopping situations with the paylater payment method. It is hoped that the results of this research will provide new insight into the implications of the paylater payment method on consumer shopping behavior, as well as how mediating variables play a role in this. This research was obtained through data processing using Structural Equation Modeling (SEM)."
Depok: Fakultas Ekonomi dan Bisnis Universitas Indonesia, 2024
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UI - Skripsi Membership  Universitas Indonesia Library
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Yofi Rosameliana
"Penelitian ini bertujuan untuk mengetahui kondisi-kondisi yang mengindikasikan terjadinya Ponzi scheme dan affinity fraud pada bisnis biro perjalanan umrah PT First Anugerah Karya First Travel dan mengetahui faktor-faktor signifikan yang mempengaruhi jemaah First Travel menjadi korban fraud. Penelitian ini merupakan metode campuran dengan menggunakan data primer dan sekunder. Data primer yang diperoleh dari wawancara dan kuesioner dan data sekunder yang diperoleh dari artikel koran online diolah dengan metode kualitatif dan kuantitatif. Berdasarkan hasil olah data kualitatif, diketahui bahwa indikasi terjadinya Ponzi scheme pada bisnis First Travel adalah menjual paket umrah yang too good to be true, skema bisnis dirahasiakan, menggunakan endorsement, memiliki agen, memberikan kuota fiktif, dan pengembalian uang setoran jemaah sulit. Kemudian, indikasi affinity fraud pada bisnis First Travel adalah kesamaan agama antara pelau dan korban, penghianatan kepercayaan, kebenaran sosial, dan timbal balik ke komunitas. Berdasarkan hasil Structural Equation Modelling, faktor signifikan yang mempengaruhi kerentanan jemaah First Travel menjadi korban affinity fraud First Travel adalah kecenderungan sikap mudah tertipu.

Abstract This study aims to determine the conditions that indicate the occurrence of Ponzi scheme and affinity fraud on the Umrah business agency PT First Anugerah Karya First Travel and the significant factors that affect the First Travel congregation being the fraud victims. This research is a mixed method whereby the primary and secondary data are utilized. The primary data obtained from interviews and questionnaires while the secondary data obtained from online newspaper articles which are processed using qualitative and quantitative methods. The qualitative data results show that of Ponzi scheme red flags in First Travel business are selling umrah package which is too good to be true, keeping secret the business scheme, using endorsement, irrational exuberance, having agents, offering fake limited offerings, and difficult on refund process. The red flags of affinity fraud are the same religion between the fraudster and the victims, exploiting trust, social truth, and contribution to community. Based on the quantitative data, the significant factors affecting the vulnerability of First Travel congregation to the victims of affinity fraud First Travel is the tendency of gullibility.
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Depok: Fakultas Ekonomi dan Bisnis Universitas Indonesia, 2018
S-Pdf
UI - Skripsi Membership  Universitas Indonesia Library
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"In general , implementation of a MIMO-OFDM (multiple-output multiple-input orthogonal frequency divission multiplexing) technique in wireless communications systems is conducted in coherent chanel condition with an estimation chanel scheme...."
Artikel Jurnal  Universitas Indonesia Library
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Zuherman Rustam
"Komputasi intelejensia yang digunakan dalam masalah klasifikasi pola dapat digolongkan menjadi dua bagian, yaitu yang berbasis pada Neural Network dan yang berbasis pada Pembelajaran Statistika (Statistical Learning). Pembelajaran yang berbasis statistika, pertama kali ditemukan oleh Vapnik pada dekade tujuh-puluhan. Untuk masalah klasifikasi pola Vapnik mengembangkan metode hyperplane optimal separation, atau dikenal juga dengan nama metode Support Vector Machines (SVM). Pada awalnya SVM dirancang hanya untuk menyelesaikan masalah klasifikasi biner, yaitu dari data-data yang ada, diklasifikasikan menjadi dua kelas. Untuk mengklasifikasikan data yang terdiri dari lebih dari dua kelas, metode SVM tidak dapat langsung digunakan. Ada beberapa metode yang dapat digunakan untuk menyelesaikan masalah klasifikasi multikelas SVM yaitu: metode One-vs-One dan metode One-vs-Rest. Kedua metode ini merupakan perluasan dari klasifikasi biner SVM. Kedua metode tersebut akan dibahas di artikel ini dan akan dilihat kinerjanya dalam mengklasifikasikan aroma. Data aroma yang digunakan dalam percobaaan ini terdiri dari 3 jenis aroma, masing-masing aroma terdiri atas 6 kelas. Pembagian kelas ini berdasarkan pada konsentrasi alkohol yang dicampurkan pada masing-masing aroma. Misalkan untuk aroma A, terdapat 6 jenis aroma A dengan kandungan alkohol : 0%, 15%, 25%, 30%, 45% dan 75%. Kinerja dari kedua metode diukur berdasarkan kemampuan untuk mengenal dan mengklasifikasikan aroma, dengan tepat dan sesuai dengan jenis atau kelas, dari data yang diberikan.

Aroma classification using one-vs-one and one-vs-rest methods. Computational Intelligence used in pattern classification problem can be divided into two different parts, one based on Neural Network and the other based on Statistical Learning. The Statistical Learning discovered by Vapnik on 70-est decade. For the pattern classification, Vapnik developed hyperplane optimal separation, which is known as Support Vector Machines Method (SVM). In the beginning, SVM was designed only to solve binary classification problem, where data existing are classified into two classes. To classify data whose consist of more than two classes, the SVM method can not directly be used. There are several methods can be used to solve SVM multiclasses classification problem, they are One-vs-One Method and One-vs-Rest Method. Both of this methods are the extension of SVM binary classification, they will be discussed in this article so that we can see their performance in aroma classification process. Data of aroma used in this experiment is consisted of three classes of aroma, each of them has six classes. The division of this class is based on alcohol concentration mixed into each of those aromas. For example, for aroma A, there are six kinds of aroma A with different alcohol concentration: 0%, 15%, 25%, 30%, 45% and 75%. The performance of these methods is measured based on their ability to recognize and classify aroma, precisely and match with the right class or variety of data existed."
Depok: Lembaga Penelitian Universitas Indonesia, 2003
AJ-Pdf
Artikel Jurnal  Universitas Indonesia Library
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"There are two categories of well-known approach (as basic principle of classification process) for leraning structure of Bayesian Neywork (BN) in data mining (DM): ...."
ITJOICT
Artikel Jurnal  Universitas Indonesia Library
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"Sistem Klasifikasi Dewey Decimal Classification ini merupakan salah satu sistem yang dikenal di kalangan pustakawan.Saking dikenalnya,hampir setiap pustakawan mengenal sistem ini minimal namanya dan bahkan mengetahui urutan kelasnya...."
SEBUPUI
Artikel Jurnal  Universitas Indonesia Library
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"Call number bagaikan nama panggilan seseorang atau nomor punggung pemain bola.Kita kita lebih mengenal Si nomor 17 untuk Christian Ronaldo ,atau si nomor 7 untuk David Beckham....."
SEBUPUI
Artikel Jurnal  Universitas Indonesia Library
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