On the power of traps and diversions in a document preparation language

Title (Bahasa Indonesia): Pengaruh kualitas layanan terhadap kepuasan pengguna jasa di Pelabuhan Perikanan Samudera (PPS) Bitung, Indonesia This study evaluates the effect of service quality on the service users’ utilization in the Ocean Fisheries Port (OFP) of Bitung, Indonesia. It employed 3 quantitative methods,Customer Satisfaction Index (CSI), Importance Performance Analysis and Gap Analysis. From 14 services, there were 13 services categorized as satisfactory services. It means that Ocean Fisheries Port of Bitung has performed well in most of its functions. The unsatisfactory one was clean water service. To increase the users’ level of satisfaction in the OFP of Bitung, improvement needs to be done in the services of ship arrival and departure document preparation, fishing vessel log book inspection, recommendation for subsidized fuel use, fish catch certification, port hygiene, entrance ticket, information building rental, electricity, clean water supply, equipment rental, and mooring. Penelitian tentang pengaruh kualitas layanan terhadap kepuasan pengguna jasa di Pelabuhan Perikanan Samudera (PPS) Bitung, Indonesia, telah dilakukan. Dengan mengunakan 3 metode kuantitatif, yaitu Customer Satisfaction Index (CSI), Importance Performance Analysis dan Gap Analisis, didapat hasil sebagai berikut: dari 14 layanan, terdapat 13 layanan yang mendapatkan predikat puas meskipun tidak ada yang sangat memuaskan. Ini dapat diartikan, bahwa PPS Bitung telah melakukan tugas pokok dan fungsinya dengan baik. Hanya ada satu pelayanan yang kurang memuaskan, yaitu pelayanan air bersih. Untuk meningkatkan kepuasan pengguna jasa/stakeholder di PPS Bitung, maka perbaikan perlu dilakukan terhadap pelayanan persiapan dokumen kedatangan dan keberangkatan kapal, log book penangkapan ikan, rekomendasi bahan bakar minyak solar subsidi, sertifikat hasil tangkapan ikan, kebersihan kolam pelabuhan dan kebersihan pelabuhan, pas masuk, sewa lahan bangunan informasi, jasa listrik, jasa air bersih, sewa peralatan, dan tambat labuh.

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Document Preprocessing with TF-IDF to Improve the Polarity Classification Performance of Unstructured Sentiment Analysis

Kinetik Game Technology Information System Computer Network Computing Electronics and Control ◽

10.22219/kinetik.v5i3.1066 ◽

2020 ◽

pp. 235-242

Author(s):

Farrikh Alzami ◽

Erika Devi Udayanti ◽

Dwi Puji Prabowo ◽

Rama Aria Megantara

Keyword(s):

Machine Learning ◽

Feature Extraction ◽

Random Forest ◽

Sentiment Analysis ◽

Classification Performance ◽

Document Preparation ◽

Learning Models ◽

Polarity Classification ◽

Negative Sentiment ◽

Machine Learning Models

Sentiment analysis in terms of polarity classification is very important in everyday life, with the existence of polarity, many people can find out whether the respected document has positive or negative sentiment so that it can help in choosing and making decisions. Sentiment analysis usually done manually. Therefore, an automatic sentiment analysis classification process is needed. However, it is rare to find studies that discuss extraction features and which learning models are suitable for unstructured sentiment analysis types with the Amazon food review case. This research explores some extraction features such as Word Bags, TF-IDF, Word2Vector, as well as a combination of TF-IDF and Word2Vector with several machine learning models such as Random Forest, SVM, KNN and Naïve Bayes to find out a combination of feature extraction and learning models that can help add variety to the analysis of polarity sentiments. By assisting with document preparation such as html tags and punctuation and special characters, using snowball stemming, TF-IDF results obtained with SVM are suitable for obtaining a polarity classification in unstructured sentiment analysis for the case of Amazon food review with a performance result of 87,3 percent.

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Medical Writing: Write your Way to Six-Figures and Beyond

The Senior Care Pharmacist ◽

10.4140/tcp.n.2021.273 ◽

2021 ◽

Vol 36 (6) ◽

pp. 273-275

Author(s):

Brittany Hoffmann-Eubanks

Keyword(s):

Medical Education ◽

Scientific Publication ◽

Medical Writing ◽

Document Preparation ◽

Regulatory Document ◽

Needs Assessments ◽

Broad Term ◽

Medical Journalism ◽

Journalism Research ◽

Medical Writers

Medical writing is a broad term for a vast 3-billion-dollar industry. The industry is large enough to accommodate all types of medical writers and health care communicators who can contribute in various ways. For example, some medical writers assist with medical education, such as continuing medical education (CME), slide-decks, textbooks, needs assessments, and patient education. Other medical writers may work in medical journalism, research documents, medical marketing, regulatory document preparation, or scientific publication and presentations. This article discusses ways for pharmacists to enter this field and is an extension of the ASCP provided webinar, which can be accessed here.

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