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"Penelitian ini bertujuan untuk menguji pengaruh risiko kebangkrutan terhadap imbal hasil saham, dan mengacu pada penelitian yang dilakukan oleh penelitian Chen dan Hill (2013). Beberapa metode perhitungan risiko kebangkrutan digunakan, yaitu Z-Score Altman (1968), discrete time hazard Campbell et. al. (2008), dan Chava dan Jarrow (2004). Sampel pada penelitian ini berjumlah sebanyak 86 perusahaan untuk Z-Score Altman, 162 perusahaan untuk discrete time hazard Campbell et. al., dan 156 perusahaan untuk discrete time hazard Chava & Jarrow. Hasil yang didapatkan adalah ditemukannya pengaruh yang positif dan tidak linear antara risiko kebangkrutan dengan imbal hasil saham.

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This research aims to test the effect of bankruptcy risk, proxied by probability of bankruptcy, towards stock returns, and is inspired by the research done by Chen and Hill (2013). Several methods of bankruptcy risk calculation are used; Altman Z-Score (1968), Campbell et. al. Discrete Time Hazard (2008), and Chava and Jarrow Discrete Time Hazard (2004) and are tested on non-financial, public companies Indonesia - of which this kind of research has not widely tested yet. The number of samples used for Altman Z-Score are 86 companies, 156 companies are used in Campbell et. al. Discrete Time Hazard, and 162 in Chava & Jarrow Discrete Time Hazard. The research shows that there are positive, significant, and non-linear effects from probability of bankruptcy, as a proxy of bankruptcy risk, towards stock returns."

"ABSTRAKPada penelitian ini dilakukan perancangan random number generator RNG berbasis discrete time DT chaos dengan menggunakan modifikasi chaos satu dimensi sebagai fungsi deterministik pada proses destilasi. Sistem chaos satu dimensi 1D merupakan sistem dinamik sederhana yang banyak diterapkan dalam pembangkitan bilangan acak. Pada penelitian awal, kami telah mengkombinasikan ring oscillator RO sebagai sumber entropi dari RNG dengan logistic map sebagai fungsi deterministik. Telah dilakukan beberapa penelitian terkait dengan menggunakan sistem chaos 1D, yang mampu menghasilkan rangkaian bit acak secara statistik. Pada penelitian ini kami melakukan modifikasi logistic map yang akan diaplikasikan sebagai RNG berbasis DT chaos. Logistic map merupakan sistem chaos yang sering diterapkan pada sistem kripto. Selain karena mudah diimplementasikan pada perangkat keras, logistic map juga memiliki tingkat keamanan yang lebih baik dibandingkan sistem chaos fungsi nonlinier lainnya. Modifikasi menghasilkan dua persamaan deterministik baru yaitu MLP I dan MLP II, yang mampu mengolah data real, -1, 1 untuk menghasilkan luaran berupa bilangan potisif dan negatif, -1, 1 . Dengan menggunakan pembuktian secara empiris dan teoritis, didapatkan fungsi ekstraktor dengan nilai tertentu untuk mengubah bilangan real yang dihasilkan oleh fungsi deterministik menjadi rangkaian bit dengan nilai entropi tinggi. Hasil uji keacakan dengan menggunakan NIST 800-22 menunjukkan bahwa rangkaian bit yang diperoleh dinyatakan acak dengan nilai proporsi yang dihasilkan untuk seluruh uji berada pada interval 0.9804-0.9994 dengan P-value>. Jika dibandingkan dengan zigzag map sebagai fungsi deterministik pada RNG berbasis DT chaos, MLP II mampu menghasilkan rangkaian bit yang lebih acak dibandingkan zigzag map tanpa post-processing. Pengujian keacakan menggunakan uji DieHard menunjukkan bahwa 80 Mbit output MLP II dinyatakan acak dengan P-value = 0, 1 . Implementasi metode RNG berbasis DT chaos dengan fungsi MLP II menggunakan ZedBoard Zynq 7000 memperlihatkan jumlah source yang digunakan lebih efisien dibandingkan RNG berbasis DT chaos dengan fungsi zigzag map yaitu look up tables LUT sebanyak 2 , flip flop FF sebanyak 1 dan digital signal processing DSP sejumlah 4.5 .

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ABSTRACTThis research designs a discrete time DT chaos based random number generator RNG , which uses one-dimension chaos modification as deterministic function in the destillation process. One-dimensional chaos 1D is a simple dynamic system, which is widely applied to generate random numbers. In the preliminary research, we have combined ring oscillator RO as the RNG entropy source with logistic map as a deterministic function. We have done some related research using a 1D chaos system, which is capable to generate random bits statistically. Our work modifies logistic map that will be applied as DT chaos-based RNG. The logistic map is a chaotic system that is usually applied in the cryptosystem. In addition to easy hardware implementation, the logistic map also has a better level of security than other nonlinear chaos function. The modification performed yields two new deterministic equations, namely MLP I and MLP II, which are capable to process data of real numbers, -1, 1 , and generate positive and negative numbers, -1, 1 . Through empirical and theoretical verification the extractor function is obtained with a certain value to convert the real number that is generated by a deterministic function into a sequence of bits which has high entropy value. Through NIST 800-22 randomness test it is revealed that the obtained bit sequence is random with the proportion values at intervals 0.9804-0.9994 and P-value > ? . Comparing with the zigzag map as a deterministic function in the DT chaos-based RNG, MLP II map generates more random bit sequence than the zigzag map. Furthermore as much as 80Mbit MLP II output passed the Diehard test with P-value = 0, 1 . Implementation of the DT chaos-based RNG method with the MLP II function using ZedBoard Zynq 7000 shows the number of sources used more efficient than the DT chaos-based RNG with the zigzag map function of 2 look up tables LUT , flip flop FF as much as 1 and digital signal processing DSP of 4.5 ."

"ABSTRAKThis research focus on consideration of stochastic demand in deterministic Vehicle Routing Problem with Compartment (VRPC) model. VRPC in this research consider split delivery, multi product, and time windows characteristic. Stochastic demand in this research is handled using scenario-based approach. The demand is modeled by constructing discrete scenarios then implementing it in the deterministic VRPC model. The change of customer demand over time is considered as normal probability distribution. Stochastic VRPC model then solved using robust approach by looking for the highest demand under each scenario to be solve, therefore the solution generated deals with the minimum probability of unmet demand."

"Models that include a notion of time are ubiquitous in disciplines such as the natural sciences, engineering, philosophy, and linguistics, but in computing the abstractions provided by the traditional models are problematic and the discipline has spawned many novel models. This book is a systematic thorough presentation of the results of several decades of research on developing, analyzing, and applying time models to computing and engineering."