Makna Religi Novel Ketika Cinta Bertasbih Karya Habiburrahman El Shirazy: Analisis Semiotik Dan Aplikasinya Dalam Pembelajaran Sastra Di Madrasah Aliyah

Makna Religi Novel Ketika Cinta Bertasbih karya Habiburrahman El Shirazy: Analisis Semiotik dan Aplikasinya dalam Pembelajaran Sastra di Madrasah Aliyah. Tesis, Surakarta: Magister Pengkajian Bahasa Universitas Muhammadiyah Surakarta, November 2011. Pembimbing I Dr. Ali Imron Al Ma’ruf, M.Hum. Pembimbing II Drs. Yakub Nasucha, M. Hum. Tujuan dari penelitian ini adalah untuk mendeskripsikan dan menjelaskan arti religi yang terkandung dalam Novel Ketika Cinta Bertasbih karya Habiburrahman El Shirazy. Penelitian ini menggunakan pendekatan deskriptif kualitatif. Sumber data yang digunakan adalah Novel Ketika Cinta Bertasbih karya dari Habiburrahman El Shirazy. Teknik pengumpulan data yang digunakan adalah purposive sampling. Teknik analisis data yang digunakan adalah content analysis. Penelitian ini menggunakan pendekatan semiotik yang terdiri atas pembacaan heoristik dan hermeneuti k . Berdasarkan analisis data penelitian dapat disimpulkan novel Ketika Cinta Bertasbih karya Habiburrahman El Shirazy, memiliki struktur yang utuh, dan unsur yang satu berkaitan dengan yang lain. Adapun makna religius yang terkandung dalam Novel Ketika Cinta Bertasbih karya Habiburrahman El Shirazy berisi tentang (1) taubatan nasuha, ( 2 ) wajib berusaha, berdoa dan berserah diri, (3) kekuasaan dan kebesaran Tuhan, (4) Tuhan Maha Pengampun dan tempat mohon pertolongan, (5) kehidupan manusia di dunia tidak lepas dari ujian dan cobaan, (6) larangan berbuat kerusakan di muka bumi, (7) kewajiban manusia mencari nafkah, (8) cinta tanah air dan perjuangan, ( 9 ) kehidupan di dunia yang tidak kekal, (10 ) amal ibadah sebagai bekal menghadap Tuhan, ( 11 ) kewajiban menggunakan kesempatan untuk beribadah, ( 12 ) larangan takabur, (13) belajar seumur hidup

Robust Estimation of a Linearized Nonlinear Regression Model with Heteroscedastic Errors:A Simulation Study

A simulation study is used to examine the robustness of some estimators on a linearized nonlinear regression model with heteroscedastic errors, namely the Linearized Ordinary Least Squares (LOLS), Transformed Generalized Least Squares (TGLS) , Linearized Reweighted Least Squares (LRLS) and Transformed Linearized Reweighted Least Squares (TLRLS). The latter is a modification of Reweighted Least Squares (RLS) based on Least Median of Squares (LMS). The empirical evidence shows that the first three estimators are not sufficiently robust when the percentage of outliers in the data increases. That is, they do not have a high breakdown point. On the other hand, the modified estimator (TLRLS) has a higher breakdown point than the other three estimators

Bootstrap Methods in a Class of Non-Linear Regression Models

In this paper, the performances of the bootstrap standard errors (BSE) of the Weighted MM (WMM) estimates were compared with the Monte Carlo (MCSE) and Asymptotic (ASE) standard errors. The properties of the Percentile (PB), Bias-Corrected Persentile (BCP), Bias and Accelerated (BC), Studentized Percentile (SPB) and the Symmetric (SB) bootstrap confidenceaintervals of the WMM estimates were examined and compared. The results of the study indicate that the BSE is reasonably close to the ASE and MCSE for up to 20% outliers. The BCa has attractive properties in terms of better coverage probability, equitailness and average interval length compared to the other methods

Character and conflict in Agatha Christie’s crooked house

Characters are the important element in the novel to build the story more interesting. Usually, the main characters in the novel have mental and physical similarities in the real life. The character is the person in a story, a character can also society, race, mental and moral attitude, quality of reason, famous person, figure in the literary work created by the author from what they do or what they say. The character fully displayed to represent the author’s own ideas as they occur in everyday life. This present study discusses the characters and conflicts in Crooked House novel aimed to find two things: 1) Character that exist in Crooked House novel. 2) The conflict that exists in Crooked House novel. The research data used the theory from E.M Forster who introduced the theory of flat and round characters to find character reflected in the novel Crooked House. Then, to analyze conflict used theory of Robert Stanton to know the conflict that exist in Crooked House novel. This study used qualitative descriptive method to find character and conflicts that exist in Crooked House novel. The researcher identifies the determination of analysis and conclusion to the research data. The result of this present study shows that there are fifty-one data which are divided into two types. Those are twenty-two data of flat character, there are Shopia Leonides, Charles Hayward, Magda Leonides, Philip Leonides, and Laurence Brown, and twenty-nine data of round characters, there are Brenda Leonides, Clemency Leonides, Roger Leonides, Edith de Haviland, Aristide Leonides, Josephine Leonides, Eustace Leonides, and Mr Gaitskill which describe how the characters in Crooked House novel. Then in the conflict found eight data which are divided into two types that is two data of internal conflict there are Charles Hayward and Eustace Leonides, and six data of external conflict there are Sophia Leonides, Josephine Leonides and Roger Leonides

Security techniques for sensor systems and the Internet of Things

Sensor systems are becoming pervasive in many domains, and are recently being generalized by the Internet of Things (IoT). This wide deployment, however, presents significant security issues. We develop security techniques for sensor systems and IoT, addressing all security management phases. Prior to deployment, the nodes need to be hardened. We develop nesCheck, a novel approach that combines static analysis and dynamic checking to efficiently enforce memory safety on TinyOS applications. As security guarantees come at a cost, determining which resources to protect becomes important. Our solution, OptAll, leverages game-theoretic techniques to determine the optimal allocation of security resources in IoT networks, taking into account fixed and variable costs, criticality of different portions of the network, and risk metrics related to a specified security goal. Monitoring IoT devices and sensors during operation is necessary to detect incidents. We design Kalis, a knowledge-driven intrusion detection technique for IoT that does not target a single protocol or application, and adapts the detection strategy to the network features. As the scale of IoT makes the devices good targets for botnets, we design Heimdall, a whitelist-based anomaly detection technique for detecting and protecting against IoT-based denial of service attacks. Once our monitoring tools detect an attack, determining its actual cause is crucial to an effective reaction. We design a fine-grained analysis tool for sensor networks that leverages resident packet parameters to determine whether a packet loss attack is node- or link-related and, in the second case, locate the attack source. Moreover, we design a statistical model for determining optimal system thresholds by exploiting packet parameters variances. With our techniques\u27 diagnosis information, we develop Kinesis, a security incident response system for sensor networks designed to recover from attacks without significant interruption, dynamically selecting response actions while being lightweight in communication and energy overhead

Diagnostic plot for the identification of high leverage collinearity-influential observations

High leverage collinearity influential observations are those high leverage points that change the multicollinearity pattern of a data. It is imperative to identify these points as they are responsible for misleading inferences on the fitting of a regression model. Moreover, identifying these observations may help statistics practitioners to solve the problem of multicollinearity, which is caused by high leverage points. A diagnostic plot is very useful for practitioners to quickly capture abnormalities in a data. In this paper, we propose new diagnostic plots to identify high leverage collinearity influential observations. The merit of our proposed diagnostic plots is confirmed by some well-known examples and Monte Carlo simulations

Robust nonlinear regression: case study for modeling the greenhouse gases, methane and carbon dioxide concentration in atmosphere

Four nonlinear regression models are proposed for the atmospheric carbon dioxide and methane gas concentrations data, reported by United Nation 1989. Among those considered, the Exponential with Intercept is the most preferred one to model methane data due to better convergence and lower correlation between parameters. On the other hand, the scale exponential convex model is appropriate for carbon dioxide data because besides having smaller standard errors of parameter estimates and smaller residual standard errors, it is numerically stable. Due to large range of data that goes back to history to 7000 years ago, there is a big dispersion in data set, so that it made us to apply robust nonlinear regression estimation methods to have a smoother model