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"In this article, we developed a resubmitted lot for group acceptance sampling plan to ensure the lifetime of the product quality assuming that the product lifetime follows the exponentiated half logistic distribution. The plan parameters are determined by fixing the experiment termination time and the number of testers at the specified producer?s and consumer?s risks both satisfy simultaneously. The proposed group sampling plan is compared with the ordinary group sampling plan. An example is given to illustrate the methodology."

"ABSTRAKAcceptance sampling merupakan salah satu bagian penting dalam bidang quality control dan digunakan untuk berbagai jenis inspeksi produk. Perencanaan acceptance sampling menyatakan kebutuhan jumlah sample dan kebutuhan kriteria menerima atau menolak sebuah lots. Penelitian ini memperkenalkan skema baru dalam perencanaan penerimaan sampling untuk data variable pada kasus resubmitted lots melalui informasi sampling yang berdasarkan proses kapabilitas indek Cpmk. Indeks kapabilitas Cpmk mengakomodasi konsep kualitas modern dalam peningkatan kualitas yang memperhatikan proses yield kesesuaian spesifikasi suatu proses dan proses loss variasi dari target suatu proses . Metode yang digunakan dalam penelitian ini untuk mencari kriteria jumlah sampel dan nilai kritikal penerimaan lots dari beberapa kombinasi level nilai kualitas, nilai resiko produsen dan nilai resiko konsumen menggunakan penyelesaian dua persamaan non-linear yang simultan mengikuti prosedur operasi serta aturan pembuatan keputusan resubmitted lots. Untuk mendapatkan kriteria tersebut, fungsi operasi dari pengambilan sampling resubmitted lots dibangun berdasarkan exact sampling distribution bukan approximation sehingga menghasilkan keputusan yang lebih akurat dan realistis. Penelitian ini memberikan sebuah contoh kasus dalam dunia industri untuk mengilustrasikan dan mendemonstrasikan bagaimana menggunakan perencanaan acceptance sampling untuk resubmitted lots berdasarkan indek kapabilitas Cpmk pada data variable serta melihat keuntungan-keuntungan yang didapat dari skema ini.

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ABSTRACTAcceptance sampling is one of the important parts of the field of quality control and used primarily for any kinds of inspection. Acceptance sampling plans state the required sample size and the required acceptance or rejection criteria for lots sentencing. This study introduces a new scheme in variables acceptance sampling plans for resubmitted lots based on the process capability index Cpmk. Cpmk capability index accommodate modern philosophy in improving the quality of attention to the process yield conformance specification of a process and the process loss variation of the target process . The method used in this study to search required sample size for inspection and critical acceptance value of various combinations of levels of quality values, producer rsquo s risk and consumer rsquo s risk are constructed by solving two non linear simultaneous equations. To obtain these criteria, the operation of the sampling function resubmitted lots are built based on the exact sampling distribution rather than the approximation for more accurate decisions and realistic results. This study provides an example of a case in the industrial world to illustrate and demonstrate how to use the variable sampling plans for resubmitted lots based on The Capability Index Cpmk and see the benefits gained from this scheme."

"Distribusi Transmuted Exponentiated Exponential merupakan generalisasi dari distribusi Exponentiated Exponential yang dibentuk dengan menggunakan metode quadratic rank transmutation maps (QRTM). Distribusi Transmuted Exponentiated Exponential merupakan salah satu distribusi kontinu yang mampu memodelkan data dengan hazard rate naik, turun, bathtub, dan non-monoton. Pada tugas akhir ini akan dibahas konstruksi dari distribusi Transmuted Exponentiated Exponential. Karakteristik-karakteristik distribusi yang meliputi fungsi kepadatan probabilitas, fungsi distribusi, dan hazard rate dari distribusi Transmuted Exponentiated Exponential juga dijelaskan lebih lanjut. Pada bagian akhir, diberikan suatu aplikasi dari distribusi Transmuted Exponentiated Exponential pada suatu data lifetime.

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Transmuted Exponentiated Exponential distribution is a generalization of Exponentiated Exponential distribution which formed using a method called quadratic rank transmutation maps (QRTM). Transmuted Exponentiated Exponential distribution is a continued distribution which can model increasing, decreasing, bathtub, and non-monotone hazard rate. In this paper, it will be explained how to form Transmuted Exponentiated Exponential distribution. Characteristics of distribution such as, probability density function, distribution function, and hazard rate of Transmuted Exponentiated Exponential distribution will be explained further. Finally, a set of lifetime data will be analyzed using Transmuted Exponentiated Exponential distribution as an illustration."

"Distribusi Gamma-Half Normal merupakan distribusi kontinu yang dapat memodelkan data yang unimodal atau bimodal. Distribusi Gamma-Half Normal merupakan hasil pengkombinasian antara distribusi Gamma dan distribusi Half Normal dengan menggunakan metode Transformed-Transformer. Pembahasan meliputi pembentukan distribusi Gamma-Half Normal, fungsi kepadatan probabilitas, fungsi distribusi, fungsi hazard, dan karakteristik-karakteristik distribusi Gamma-Half Normal lainnya. Penaksiran parameter-parameter dari distribusi Gamma-Half Normal menggunakan metode maksimum likelihood. Dua kelompok data dibangkitkan untuk memberikan ilustrasi penggunaan distribusi Gamma-Half Normal.

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Gamma-Half Normal distribution is a continued distribution which can model unimodal or bimodal data. Gamma-Half Normal distribution is derived from Gamma distribution and Half Normal distribution using the Transformed-Transformer method. It will be explained how to form Gamma-Half Normal distribution, probability density function, cumulative distribution function, hazard function, and other characteristics of Gamma-Half Normal distribution. Maximum likelihood method is used for estimating Gamma-Half Normal’s parameters. Two sets data are used to illustrate the applicability of Gamma-Half Normal distribution."

"Distribusi Exponentiated Exponential (EE) adalah pengembangan dari distribusi Exponential dengan cara menambahkan sebuah parameter bentuk alpha. Distribusi ini digunakan untuk mengatasi masalah ketidakfleksibilitas dari distribusi Exponential. Untuk melakukan inferensi mengenai permasalahan yang dimodelkan dengan distribusi EE, perlu dilakukan penaksiran parameter. Pada skripsi ini akan dibahas mengenai penaksiran parameter distribusi dari distribusi Exponentiated Exponential pada data tersensor kiri menggunakan metode Bayesian. Prosedur penaksiran meliputi penentuan distribusi prior yaitu digunakan distribusi prior konjugat, pembentukan fungsi likelihood dari data tersensor kiri, dan pembentukan distribusi posterior. Penaksir Bayes kemudian diperoleh dengan cara meminimumkan risiko posterior berdasarkan fungsi loss Squared Error Loss Function (SELF) dan Precautionary Loss Function (PLF). Kemudian setelah diperoleh perumusan penaksir Bayes, simulasi data dilakukan untuk membandingkan hasil taksiran parameter menggunakan fungsi loss SELF dan PLF yang dilihat dari nilai Mean Square Error (MSE) yang dihasilkan. Fungsi loss dikatakan lebih efektif digunakan dalam merumuskan penaksir Bayes apabila penaksir Bayes yang diperoleh menghasilkan nilai MSE yang lebih kecil. Berdasarkan hasil simulasi, fungsi loss PLF lebih efektif digunakan untuk alpha≤1, sedangkan fungsi loss SELF lebih efektif digunakan untuk alpha>1.

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Exponentiated Exponential (EE) distribution is the development of Exponential Distribution by adding alpha as a shape parameter. This distribution can solve unflexibility issue in Exponential distribution. In order to make inferences about any cases modeled with EE distribution, parameter estimation is required. This thesis will discuss about parameter estimation of Exponentiated Exponential distribution for left censored data using Bayesian method. Parameter estimation procedure are selection of prior distribution which is conjugate prior, likelihood construction for left censored data, and then forming posterior distribution. Bayes estimator can be obtained by minimize posterior risk based on Squared Error Loss Function (SELF) and Precautionary Loss Function (PLF). After Bayes estimator is obtained, simulation is done to compare the results of Bayes estimator using SELF and PLF which are seen from the result of Mean Square Error (MSE). Loss function is said to be more effective to obtain Bayes estimator if the resulting Bayes estimator yield smaller MSE. Based on simulation, PLF more effective for alpha ≤ 1, while SELF more effective for alpha>1."

"The Third Edition retains the general organization of the prior two editions, but it incorporates new material throughout the text. The book is organized into six parts: Part I covers basic sampling from simple random sampling to unequal probability sampling; Part II treats the use of auxiliary data with ratio and regression estimation and looks at the ideas of sufficient data, model, and design in practical sampling; Part III covers major useful designs such as stratified, cluster and systematic, multistage, and double and network sampling; Part IV examines detectability methods for elusive populations, and basic problems in detectability, visibility, and catchability are discussed; Part V concerns spatial sampling with the prediction methods of geostatistics, considerations of efficient spatial designs, and comparisons of different observational methods including plot shapes and detection aspects; and Part VI introduces adaptive sampling designs in which the sampling procedure depends on what is observed during the survey. For this new edition, the author has focused on thoroughly updating the book with a special emphasis on the first 14 chapters since these topics are invariably covered in basic sampling courses. The author has also implemented new approaches to explain the various techniques in the book, and as a result, new examples and explanations have been added throughout. In an effort to improve the presentation and visualization of the book, new figures as well as replacement figures for previously existing figures have been added. This book has continuously stood out from other sampling texts since the figures evoke the idea of each sampling design. The new figures will help readers to better visualize and understand the underlying concepts such as the different sampling strategies."

"ABSTRACTAs confirmed by marketing studies, customer demand sometimes increases with the amount of inventory available, depending on the nature of goods. This paper analyzes a two tier supply chain under such inventory dependent demand (IDD). The analysis of the paper for the supply chain is in two modes, as a vendor leading Stackelberg game and as its integrated counterpart, followed by the profit sharing or the holding cost sharing mechanism to further improve the vendors profit from the vendor leading mode. The analysis procedure is complicated by non zero fixed costs in the system such that the profit functions are non concave. The analysis is complete such that the optimal quantities and their sensitivities, the optimal ordering quantities, the optimal wholesale prices, etc., are given under IDD. The tradeoff between the profit sharing and the holding cost sharing mechanisms are given under the influence of the zero and non zero fixed costs in the system."