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"Dengan adanya revolusi Industri 4.0, pengembangan sistem monitoring menjadi tinggi dan sektor otomotif lah yang paling mendapatkan keuntungannya. Meskipun teknologi di bidang otomotif terus berkembang, ban tetap tidak tergantikan. Sebagai satu-satunya titik kontak dengan jalanan, kondisi ban hanya diawasi dengan tire pressure monitoring system, meskipun kondisi ban yang tidak optimal meningkatkan peluang terjadinya kecelakaan, ditambah hanya satu dari tiga pengemudi tidak mengetahui mengenai kapan sebuah ban harus diganti. Penelitian ini dilakukan dengan tujuan agar dapat membuat model matematis yang dapat mengestimasi sisa umur ban dengan baik. Untuk mendapatkan model matematis yang dapat digunakan, perlu melakukan eksperimen sebagai pembanding dan menggunakan data best practice sebagai acuan utama. Hasil analisa perbandingan akan dijadikan acuan untuk implementasi di perangkat lunak berbasis Python. Hasil penelitian yang didapatkan adalah tingginya efek dari perbedaan kecepatan dan percepatan dalam eksperimen maupun pembuatan model. Model matematis yang didapatkan memiliki akurasi rata-rata sebesar 15% saat dibandingkan dengan hasil eksperimen. Perbedaan dapat terjadi karena kurangnya perawatan kendaraan, kondisi eksperimen yang memiliki banyak kondisi, akurasi alat ukur, serta kondisi dari ban itu sendiri. Model matematis memiliki akurasi yang paling dekat terhadap eksperimen, maka perangkat lunak menggunakan model matematis sebagai dasar kalkulasi yang didapatkan.

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With the Industry 4.0 revolution, the development of monitoring system increases and automotive sector reaps most of the benefits. Despite the development in automotive technology, tires are still essential and unchangeable. As the only contact point with the road beneath, tires’ conditions are only monitored with tire pressure monitoring system and nothing else, but only one in three people knows when to change into new tires. The research’s purpose is to develop a mathematical model that can estimate the tire remaining life accurately. In order to obtain an accurate mathematical model, and experiment is required in order verify the mathematical model, with best practice data used as the reference. The analysis result will determine which model is the most accurate to be used as the mathematical model for a Python based application. The result when comparing the mathematical model with the experiment is Universitas Indonesia that there is a difference of about 15%. The difference may be caused by lack of maintenance, too many driving conditions, measuring tool accuracy, as well as the tires themselves. The initial mathematical model poses the most accurate result, hence why the application will use the mathematical model as its main function."

"This book provides a complete and comprehensive reference/guide to Pyomo (Python Optimization Modeling Objects). The text illustrates the breadth of the modeling and analysis capabilities that are supported by the software and support of complex real-world applications. Pyomo is an open source software package for formulating and solving large-scale optimization and operations research problems. The text begins with a tutorial on simple linear and integer programming models. A detailed reference of Pyomo's modeling components is illustrated with extensive examples, including a discussion of how to load data from data sources like spreadsheets and databases. Chapters describing advanced modeling capabilities for nonlinear and stochastic optimization are also included. The Pyomo software provides familiar modeling features within Python, a powerful dynamic programming language that has a very clear, readable syntax and intuitive object orientation. Pyomo includes Python classes for defining sparse sets, parameters, and variables, which can be used to formulate algebraic expressions that define objectives and constraints. Moreover, Pyomo can be used from a command-line interface and within Python's interactive command environment, which makes it easy to create Pyomo models, apply a variety of optimizers, and examine solutions. The software supports a different modeling approach than commercial AML (Algebraic Modeling Languages) tools, and is designed for flexibility, extensibility, portability, and maintainability but also maintains the central ideas in modern AMLs."

"Publisher Synopsis1. Introduction. 2. Data Types and Expressions. 3. Control Statements. 4. Strings and Text Files. 5. Lists and Dictionaries. 6. Design with Functions. 7. Simple Graphics and Image Processing. 8. Design with Classes. 9. Graphical User Interfaces. 10. Multithreading, Networks, and Client/Server Programming. 11. Searching, Sorting, and Complexity. (Online only) Appendices. Glossary. Inde"

"The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming."

"Introduces computer programming using the Python programming language."

"Penggunaan Python dipilih karena bahasa pemrograman ini bersifat open source dengan banyak tersedianya berbagai sumber dan Python juga diklaim sebagai bahasa yang menggabungkan kapabilitas, dengan kode sintaks yang sangat jelas, dan dilengkapi dengan bahasa yang besar dan komprehensif. Library Open CV juga tersedia secara gratis dan menyediakan banyak fungsi pemrosesan gambar. Pengoreksian citra CBCT yang dilakukan pada penelitian ini bertujuan untuk meningkatkan kualitas citra CBCT dengan melihat meningkatnya nilai yang didapat pada citra CBCT terkoreksi. Phantom CIRS 002LFC di-scan pada CBCT menggunakan half bow tie filter sesuai dengan protokol yang digunakan untuk scanning organ thorax. Penelitian ini menggunakan data citra pasien dengan diagnosa kanker paru dan laring masing-masing berjumlah dua dan satu orang. Hasil kalibrasi CBCT terhadap CT diperoleh bahwa nilai HU citra CBCT linier terhadap citra CT. Evaluasi PSNR dan SSIM digunakan pada penelitian ini sebagai parameter keberhasilan dari citra yang dikoreksi.

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Python was chosen because this programming language is open source with many sources available and Python is also claimed to be a language that combines capabilities, with very clear syntax code, and is equipped with a large and complete language. CV Open Library is also available free of charge and provides many drawing functions. CBCT image correction carried out in this study aims to improve the quality of CBCT images by looking at the value obtained in the corrected CBCT image. Phantom CIRS 002LFC was scanned on CBCT using a half bow tie filter according to the protocol used for scanning the thorax organs. This study uses image data of patients diagnosed with lung and laryngeal cancer, respectively, two and one person. The CBCT calibration results against CT showed that the HU value of CBCT images was linear to CT images. PSNR and SSIM evaluations were used in this study as the confidence parameters of the corrected image."

"Pengembangan sistem pendeteksi plagiarisme dibuat untuk mengatasi masalah plagiarisme yang kerap terjadi pada dunia akademis. Pada skripsi ini dibuat sistem pendeteksi plagiarisme otomatis pada karya tulis digital dwi bahasa Indonesia-Inggris dengan Bahasa Indonesia digunakan sebagai karya tulis yang akan diuji dan Bahasa Inggris sebagai karya tulis referensinya. Sistem menerapkan algoritma winnowing yang dilengkapi dengan metode penerjemah bahasa Googletrans API dan similar words. Algoritma winnowing merupakan algoritma yang dapat mendeteksi kesamaan antar teks dengan menggunakan fingerprint yang didapat dari proses hashing karakter teks. Penelitian dilakukan untuk meningkatkan akurasi sistem dan mengetahui metode penilai kesamaan teks yang akurat. Dari hasil penelitian, didapatkan bahwa parameter terbaik algoritma winnowing secara umum terdapat saat nilai k-window = 5 dan nilai basis bilangan prima bernilai 3. Parameter n-gram bernilai kecil akan lebih akurat pada teks yang memiliki jumlah kata lebih sedikit dan/atau tingkat plagiarisme tinggi dan sebaliknya. Tingkat akurasi sistem pendeteksi plagiarisme otomatis dwi bahasa yang dikembangkan berkisar antara 75.02 hingga 99.51. Metode Cosine Similarity menjadi metode penilai kesamaan teks terbaik dari hasil penelitian ini. Selain itu, metode penerjemahan Googletrans API juga memberikan kelebihan dalam hal akurasi dan kelengkapan data kamus dibandingkan dengan metode kamus terjemahan database.

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The development of plagiarism detection system is made to overcome the problem of plagiarism that often occurs in the academic world. In this thesis, an automatic plagiarism detection system on bilingual digital paper Indonesian English is created with Indonesian is used as the tested paper and English as the reference paper. The system implements the winnowing algorithm that comes with the Googletrans API language translator method and similar words. Winnowing algorithm is an algorithm that can detect similarity between text by using fingerprint obtained from hashing process of text character. The study was conducted to improve system accuracy and to know accurate method of text equality assessment.

From the study result, it is found that the best parameter of winnowing algorithm is generally occured when the value of k window 5 and the base value of the prime number is 3. The smaller value of n gram parameter will be more accurate in text that has fewer word counts and or high plagiarism levels and vice versa. The accuracy level of the automatic plagiarism detection system in the developed language ranged from 75.02 to 99.51 .

The Cosine Similarity method is the best method of text equality assessment according to results of this study. In addition, the Googletrans API translation method also provides advantages in terms of accuracy and completeness of dictionary data as compared to database translation dictionary method."