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"Laporan tahunan merupakan dokumen resmi yang dipublikasikan oleh perusahaan, organisasi, ataupun Lembaga kementrian untuk menyajikan informasi terkait kinerja dan kondisi organisasi. Menganalisis laporan tahunan memerlukan banyak waktu karena dokumen memuat jumlah halaman dan kata yang sangat banyak. Maka dari itu terdapat metode yang dapat menganalisis dengan cepat dan objektif dengan bidang ilmu big data yaitu topic modelling. Metode topic modelling yang digunakan adalah Latent Dirichlet allocation (LDA) untuk menganalisis laporan tahunan Kementrian Kelautan dan Perikanan(KKP) Indonesia dari tahun 2015-2022. Metrik evaluasi yang digunakan dengan menghitung nilai koherensi dari setiap model yang dibuat pada setiap tahun laporan. Sehingga dapat menghasilkan topik-topik utama dari laporan tahunan KKP. Diharapkan hasil dari topic modelling dari laporan tahunan dapat menjadi informasi berharga terkait potensi perikanan dan kelautan di Indonesia.

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Annual reports are official documents published by companies, organizations, or ministries to present information related to the performance and condition of the organization. Analyzing the annual report takes a lot of time because the document contains a very large number of pages and words. Therefore, there is a method that can analyze quickly and objectively with the field of big data science, namely topic modeling. The topic modeling method used is Latent Dirichlet allocation (LDA) to analyze the annual report of the Ministry of Marine Affairs and Fisheries (KKP) Indonesia from 2015- 2022. The evaluation metric using the coherence score of each model created in each year of the annual report. So that it can produce the main topics of the KKP annual report. It is expected that the results of topic modeling from annual reports can be valuable information related to the potential of fisheries and marine in Indonesia."

"Persaingan pasar yang ketat membuat pengelola aplikasi XYZ harus dapat menghadirkan keunggulan dari produknya. Untuk itu, pengelola XYZ melakukan analisis terhadap ulasan yang diberikan oleh penggunanya. Namun, pengelola aplikasi XYZ mengalami kesulitan dalam melakukan analisis ulasan karena menggunakan cara yang manual dan tidak efisien. Penelitian ini dilakukan untuk mengetahui sentimen dari aspek-aspek mobile service quality (M-S-QUAL) dan topik-topik yang sering dibicarakan oleh pengguna aplikasi XYZ pada review Google Playstore. Data ulasan yang digunakan merupakan ulasan dari bulan Januari 2023 hingga Agustus 2024, data ini berjumlah 13,364 data. Terdapat 5,000 data yang dianotasi. Data tersebut kemudian dibersihkan dan digunakan untuk melakukan analisis sentimen berbasis aspek (ABSA) dan pemodelan topik. Hasil penelitian menunjukkan dari sembilan aspek M-S-QUAL, terdapat tiga aspek yang dieliminasi karena kekurangan data, dan terdapat empat aspek yang dieliminasi karena model machine learning yang dilatih memiliki performa yang kurang baik dengan F1-score dibawah 0.7. Model yang layak digunakan untuk scoring hanya ada pada aspek billing dan system availability yaitu model XGBoost dengan teknik oversampling synthetic minority over-sampling technique (SMOTE) untuk kedua aspek. Performa dari model-model ini adalah 0.758 pada aspek billing, dan 0.802 pada aspek system availability. Dari 4,006 ulasan relevan pada aspek billing, 6.44% adalah sentimen positif, 90.81% adalah sentimen negatif, dan 2.75% adalah sentimen netral. Dari 2,410 ulasan relevan pada aspek system availability, 7.88% memiliki sentimen positif, 86.76% memiliki sentimen negatif, dan 5.35% memiliki sentimen netral. Hasil ini menunjukkan bahwa sentimen dominan pada ulasan yang relevan dengan aspek billing dan system availability adalah sentimen negatif. Pemodelan topik dilakukan untuk masing-masing sentimen positif dan negatif pada aspek billing dan system availability. Pemodelan topik aspek billing menghasilkan 3 topik untuk sentimen positif, 3 topik untuk sentimen negatif. Pemodelan topik aspek system availability menghasilkan 2 topik untuk sentimen positif, dan 2 topik untuk sentimen negatif. Topik-topik ini yang dapat dijadikan poin perbaikan dan peningkatan aplikasi XYZ.

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The intense competition in the market forces the XYZ management to offer competitive advantages in their product. To achieve this, they analyze user reviews. However, they face challenges in analyzing user reviews because they still use manual methods, which makes the process inefficient. This study aims to understand the sentiment of aspects of mobile service quality (M-S-QUAL) and the popular topics from XYZ app users in Google Play Store reviews. The data used in this study was 13,364 reviews from January 2023 to August 2024, with 5,000 of them manually labeled. The data was cleaned and used for aspect-based sentiment analysis (ABSA) and topic modeling. The results showed that, out of nine M-S-QUAL aspects, three were excluded due to insufficient data, and four more were excluded because the machine learning models performed poorly, with F1-scores below 0.7. Only the billing and system availability aspects had decent models. The models for these aspects used the XGBoost algorithm combined with synthetic minority over-sampling technique (SMOTE). The models’ performance scores were 0.758 for billing and 0.802 for system availability. For the billing aspect, out of 4,006 relevant reviews, 6.44% had positive sentiment, 90.81% were negative, and 2.75% were neutral. For system availability, out of 2,410 relevant reviews, 7.88% were positive, 86.76% were negative, and 5.35% were neutral. This shows that most users had negative sentiment about billing and system availability. Topic modeling was conducted separately for positive and negative sentiments in both the billing and system availability aspects. For the billing aspect, topic modeling resulted in three topics for positive sentiment and three topics for negative sentiment. For the system availability aspect, two topics were identified for both positive and negative sentiments. These topics can serve as key areas for improving and enhancing the XYZ application."

"In the past few years the authors of this 5th edition, as teachers and research supervisors in academic and top-clinical facilities, have been able to closely observe the latest developments in the field of clinical data analysis, and they have been able to assess their performance. The novel methods are explained using practical examples and step-by-step analyses readily accessible for non-mathematicians. All of the novel chapters have been internationally published by the authors in peer-reviewed journal, including the American Journal of Therapeutics, the European Journal of Clinical Investigation, The International journal of Clinical Pharmacology and therapeutics, and other journals, and permission is granted by all of them to use this material in the current book. They firmly believe that any reader can benefit from this clinical approach to statistical data analysis."

"Tugas akhir ini ditulis dalam rangka mengkaji mengenai gratitude yang berperan sebagai elemen spasial yang dapat memberikan respon terhadap isu kelangkaan, lingkungan, dan ekonomi. Scarcity merupakan isu kompleks antara sebab dan akibat yang terjadi pada dunia saat ini. Salah satu hal yang merupakan alasan utama terjadinya scarcity adalah sumber daya yang terbatas untuk memenuhi kebutuhan populasi manusia yang tidak terbatas, ketidakseimbangan ini yang menjadi satu dari banyak faktor pemicu scarcity. Metode pengumpulan data yang digunakan dalam penulisan kajian ini berupa pengkajian literatur dari buku dan jurnal yang membahas tentang scarcity, gratitude, & sensory spatial elements. Gratitude dalam merespon scarcity. Gratitude pada kehidupan keseharian, dan bagaimana gratitude hadir dalam ruang dan waktu. Selain itu terdapat studi kasus terkait aplikasi gratitude yang disintesakan oleh penulis dengan isu wabah Covid-19 yang terjadi di Kota Wuhan, China.Berdasarkan hasil penelitian, didapatkan kesimpulan bahwa elaborasi antara elemen simbolisme spasial seperti cahaya, suara, temparatur, dan skala pada ruang dapat menimbulkan emosi pada manusia dan merefleksikan memori yang terjadi saat pandemic melalui kualitas ruang. Museum pada area pasar ikan Huanan di pusat kota wuhan merupakan bentuk manifestasi arsitektur yang di desain oleh penulis.

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The Final project was written in order to examine gratitude which acts as a spatial element that can provide responses to scarcity, environmental and economic issues. Scarcity is a complex issue between cause and effect that occurs in the world today. One of the main reasons for scarcity is limited resources to meet the needs of an unlimited human population, this imbalance which is one of the many triggers for scarcity.

Data collection methods used in writing this study in the form of a literature review from books and journals that discuss scarcity, gratitude, & sensory spatial elements. Gratitude in responding to scarcity. Gratitude in everyday life, and how gratitude is present in space and time. In addition there is a case study related to the application of gratitude that was synthesized by the author with the issue of the Covid-19 outbreak that occurred in Wuhan City, China.

Based on the results of the study, it was concluded that the elaboration between elements of spatial symbolism such as light, sound, temperature and scale in space can cause emotions in humans and reflect the memory that occurs during a pandemic through the quality of space. The museum in the Huanan fish market area in downtown wuhan is a form of architectural manifestation designed by the author."

"The pace of therapeutic advances in the treatment of cardiovascular diseases is rapid, and new clinically–relevant information appears with such frequency that it can be extremely challenging for clinicians to keep up. Still, knowledge and interpretation of major clinical trials is crucial for the range of clinicians who manage cardiovascular patients, especially since important trial evidence often needs to be implemented soon after it is published. Confidently apply gold standard treatment for 10 of the most critical areas of cardiology Written by an international team of experts, Cardiovascular clinical trials : putting the evidence into practice, provides a succinct overview of recent major clinical trials, the gold standard for all medical treatment, across all the major cardiovascular subspecialties, to ensure you’re up–to–date on the most critical findings Guides cardiology trainees and clinicians on how cardiovascular clinical trials are designed and conducted, including statistical methodology."

"Contents : Overview of the client education model -- Thinking and learning -- Theories and principles of learning -- Learner and setting assessment -- The child learner -- The adult learner -- The older learner -- The culturally diverse learner -- Learning objectives -- Teaching strategies -- Instructional materials -- Formative evaluation -- Summative evaluation."

"This book will examine current issues and controversies in the design of clinical trials, including topics in adaptive and sequential designs, the design of correlative genomic studies, the design of studies in which missing data is anticipated. Each chapter will be written by an expert conducting research in the topic of that chapter. As a collection, the chapters would be intended to serve as a guidance for statisticians designing trials."