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"Directional multiscale systems, particularly shearlets, are now having the same dramatic impact on the encoding of multidimensional signals. Since its introduction about five years ago, the theory of shearlets has rapidly developed and gained wide recognition as the superior way of achieving a truly unified treatment in both a continuous and a digital setting. By now, it has reached maturity as a research field, with rich mathematics, efficient numerical methods, and various important applications."

"Lapangan M merupakan lapangan gas yang terletak di Cekungan Sumatera Selatan dan sudah dikembangkan dengan pemboran 5 sumur pengembangan dari reservoar paparan karbonat Formasi Baturaja, dengan rata-rata produksi sebesar 4 MMCFPD per sumur. Berdasarkan hasil interpretasi seismik dan analog dengan lapangan minyak disebelah utara lapangan M, yaitu lapangan A, masih terdapat potensi reservoar minyak (oil rim) yang terletak downdip dari reservoar gas yaitu daerah yang belum dikembangkan di antara batas kontak gas dan minyak dengan batas kontak minyak dan air. Data produksi minyak sumur-sumur di lapangan A berkisar antara 100 - 800 BOPD per sumur. Hasil studi ini diharapkan dapat mengidentifikasi zona prospek minyak tersebut dan juga untuk pengembangan lebih lanjut zona gas. Menggunakan data seismik 3D dan data sumur, dilakukan evaluasi melalui metode dekomposisi spektral Continuous Wavelet Transform (CWT) data seismogram sintetik sumur dan data tras seismik yang melewati sumur, kemudian hasilnya disebarkan ke seluruh lapangan untuk mengidentifikasi penyebaran lateral keberadaan zona anomali frekuensi rendah. Hasil analisa dekomposisi spektral CWT pada data sumur dan data tras seismik yang ditunjukkan pada crossplot antara Amplitudo CWT dengan Frekuensi memperlihatkan korelasi yang cukup bagus. Sumur gas menunjukkan nilai amplitudo CWT paling tinggi pada frekuensi 10 ? 13 hz dan sumur minyak pada frekuensi 17 - 22 hz. Nilai amplitudo menurun pada frekuensi yang lebih tinggi. Pada sumur air, nilai amplitudo CWT selalu paling rendah pada frekuensi rendah hingga tinggi, sehingga dari crossplot tersebut dapat disimpulkan bahwa cut-off amplitudo zona air adalah pada 1,0+E09. Berdasarkan hasil analisis CWT dari data sumur ini, analisa dekomposisi spektral CWT kemudian disebarkan ke seluruh lapangan untuk bisa mengidentifikasi zona prospek. Selain itu, hasil crossplot antara nilai amplitudo CWT dengan nilai Saturasi air (Sw) pada zona reservoir memperlihatkan adanya hubungan yaitu nilai amplitudo CWT yang tinggi berkorelasi dengan nilai saturasi air yang rendah, begitupun sebaliknya.

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Field M is a gas field located in the South Sumatra Basin and has been developed by the drilling of five development wells from carbonate platform reservoir of Baturaja Formation, with average production of 4 MMCFPD per well. Based on the result of seismic interpretation and its analog to the oil field located to the north of field M, namely field A, there is still potential of oil reservoir (oil rim) located downdip from the gas reservoir The potential area is limited in the area that has not been developed between gas and oil contact and between oil and water contact. The production of oil wells in the field A ranges between 100-800 BOPD per well. The result of this study is expected to identify the oil zone and other prospects for further gas development.

Based on 3D seismic data and well data, the evaluation was carried out using one of spectral decomposition methods, the Continuous Wavelet Transform (CWT). The analysis was done using both well synthetic seismogram data and seismic trace that crossing-through the wells. Then CWT was run on both data. Referring to the result of the analysis, CWT was distributed across the field to identify the presence of low-frequency zone.

The results of the CWT analysis from well data and seismic trace data are shown on the crossplots between the amplitude and the frequency. They show a fairly good correlation. Gas zone shows the highest value of CWT amplitude at a frequency of 10-13 Hz and oil zone shows the highest value at a frequency of 17- 22 Hz. Amplitude values decreased in the higher frequencies. In the water zone, the value of the CWT amplitude is always lower in low to high frequencies. From the crossplot it can be concluded that the cut-off amplitude value for water zone is at 1.0 + E09. In any frequency, the CWT amplitudes below that value is nonhydrocarbon or water.

The result of spectral decomposition that is based the above analysis and distributed throughout the field is able to identify zones of prospects. In addition to that, the crossplot between the CWT value and the water saturation (Sw) in each oil, gas and water zone shows a correlation. High CWT amplitudes correlate to low water saturation, and vice versa."

"Multivariate Analysis for the Social Sciences provides clear guidelines combined with the insight needed to understand the methods and applications of multivariate statistics. This easy-to-follow book provides students in social, behavioral, and health science-whose focus is not primarily in mathematics-with an abundance of chapter-ending questions and answers, including: conceptual questions about the meaning of each method; questions that test the reader?s ability to carry out the computational procedures on simple datasets; and data analysis questions for using analytical packages to analyze both simplest case data and also to practice with more realistic datasets."

"For over 30 years, this text has provided students with the information they need to understand and apply multivariate data analysis. This text provides an applications-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to students how to understand and make use of the results of specific statistical techniques. In this revision, the organization of the chapters has been greatly simplified. New chapters have been added on structural equations modeling, and all sections have been updated to reflect advances in technology, capability, and mathematical techniques."

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Keberhasilan ekonomi merupakan suatu indikator yang baik dari sebuah masyarakat yang kaya. Meskipun demikian, ada banyak faktor lain yang memengaruhi kekayaan dan kesejahteraan masyarakat suatu negara seperti tingkat kebebasan pribadi, lingkungan hidup, dan pendidikan, yang merupakan elemen penting dalam menciptakan suatu masyarakat yang makmur. Penelitian ini bertujuan untuk mengidentifikasi faktor-faktor yang membentuk kemakmuran 149 negara di dunia selama tahun 2018. Dalam penelitian ini 74 variabel yang diambil dari Legatum Prosperity IndexTM digunakan, kecuali variabel-variabel yang berasal dari Gallup World Poll karena ketidaktersediaan data. Data dianalisis menggunakan Analisis Faktor, dan direduksi menjadi 13 faktor yang menggambarkan tentang berbagai aspek penting dalam kehidupan. Seratus empat puluh sembilan negara tersebut dikelompokkan berdasarkan skor faktor masing-masing negara menggunakan pengklasteran metode Ward menjadi 4 kelompok berbeda dengan masing-masing klaster beranggotakan negara-negara yang memiliki karakteristik yang serupa. Diperoleh bahwa Klaster 1 merupakan kelompok negara-negara yang secara keseluruhan makmur, Klaster 2 merupakan kelompok negara-negara yang cukup makmur dalam hal masyarakat yang inklusif, Klaster 3 merupakan kelompok negara-negara dengan tingkat kemakmuran yang cukup, dan Klaster 4 merupakan kelompok negara-negara yang cukup makmur dalam hal masyarakat yang berdaya serta ekonomi yang bebas.

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Economic achievement is a good indicator of a wealthy society. Nevertheless, there are many other factors that affect in shaping the wealth and well-being of the people in a country, such as the level of personal freedom, the environment, and education which are important elements in creating a prosperous society. The aim of this study is to identify the factors that shape the prosperity of 149 countries in the world during 2018. In this study 74 variables taken from the Legatum Prosperity IndexTM are used, excluding variables originating from the Gallup World Poll due to data unavailability. The data is reduced using Factor Analysis into 13 factors that describe various aspects of life. The 149 countries are clustered based on their factor scores using Wards Clustering into 4 distinct groups of countries with similar features. It is revealed that Cluster 1 consists of countries that are overall prosperous, Cluster 2 consists of countries that are quite prosperous in terms of an inclusive society, Cluster 3 consists of countries with sufficient levels of prosperity, and Cluster 4 consists of countries that are quite prosperous in terms of an empowered society and a free economy.

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