Evaluasi Usability Aplikasi Elektronik-Kesehatan Ibu dan Anak (e-KIA)

Teknologi informasi sudah berkembang disemua bidang dan tidak terkecuali sudah diterapkan ke bidang kesehatan. Salah satu langkah awal penerapan teknologi informasi pada bidang kesehatan adalah dengan membangun aplikasi untuk memonitor kesehatan ibu dan anak yang disebut dengan e-KIA. Aplikasi e-KIA yang sudah dibangun saat ini masih belum diketahui tingkat usabilitas dari penggunaan aplikasi tersebut. Pengujian usability ini penting untuk dilakukan sebelum aplikasi tersebut digunakan oleh masyarakat secara luas dan dapat digunakan sebagai early warning untuk mendeteksi kemungkinan-kemungkinan kesalahan yang terjadi. Untuk mengatasi hal tersebut pengujian usability dilakukan pada aplikasi e-KIA. Pengujian usability dimulai dengan melakukan studi litearatur terkait. Kemudian dilakukan pemilihan evaluator sekaligus melakukan briefing proses evaluasi. Tahap selanjutnya adalah merancang instrumen untuk evaluasi dan merancang skenario evaluasi. Evaluasi usability yang dilakukan difokuskan pada 3 hal yaitu Severity Ranking (SR), Ease of Fixing Ranking (EFR), dan Kategori Masalah. Masalah yang ditemukan kemudian dikategorikan berdasarkan 10 prinsip heuristik Nielsen dan disederhanakan menjadi kategori Selection Driven Command (perbaikan interaksi), Content Organization (kelengkapan konten informasi), dan Visual Representation (pemilihan komponen desain yang tepat). Dari hasil evaluasi tersebut didapatkan temuan masalah Selection Driven Command (perbaikan interaksi) sejumlah 18 temuan, Content Organization (kelengkapan konten informasi) sejumlah 10 temuan, dan Visual Representation (pemilihan komponen desain yang tepat) sejumlah 7 temuan. AbstractInformation technology has emerged in all aspect including in the healthcare field. e-KIA is an application to monitor mother and child healthcare as initial steps in implementing information technology in the healthcare field. As a newly developed application, the usability level of e-KIA is not known yet. Usability testing is important steps to be taken before the application will be used by stakeholders. Usability testing could be used to identify problems that may occur in the early stage and could be used as early warning to application aspects need to be fixed. e-KIA Usability Testing is conducted to overcome the specified problems. Usability testing started by taking the literature review followed by evaluator selection and evaluation briefing. The next step is designing an evaluation instrument and evaluation scenario. The conducted usability testing is focus on Severity Ranking (SR), Ease of Fixing Ranking (EFR), and Problem Category. The identified problems are then categorized into Nielsen’s 10 Heuristic Principal. The identified problems are simplified to three categories of Selection Driven Command, Content Organization, and Visual Representation. The experiment has found 18 problems in Selection Driven category, 10 problem in Content Organization, and 7 problems in Visual Representation category.

APIs and Your Privacy

Application programming interfaces, or APIs, have been the topic of much recent discussion. Newsworthy events, including those involving Facebook’s API and Cambridge Analytica obtaining information about millions of Facebook users, have highlighted the technical capabilities of APIs for prominent websites and mobile applications. At the same time, media coverage of ways that APIs have been misused has sparked concern for potential privacy invasions and other issues of public policy. This paper seeks to educate consumers on how APIs work and how they are used within popular websites and mobile apps to gather, share, and utilize data. APIs are used in mobile games, search engines, social media platforms, news and shopping websites, video and music streaming services, dating apps, and mobile payment systems. If a third-party company, like an app developer or advertiser, would like to gain access to your information through a website you visit or a mobile app or online service you use, what data might they obtain about you through APIs and how? This report analyzes 11 prominent online services to observe general trends and provide you an overview of the role APIs play in collecting and distributing information about consumers. For example, how might your data be gathered and shared when using your Facebook account login to sign up for Venmo or to access the Tinder dating app? How might advertisers use Pandora’s API when you are streaming music? After explaining what APIs are and how they work, this report categorizes and characterizes different kinds of APIs that companies offer to web and app developers. Services may offer content-focused APIs, feature APIs, unofficial APIs, and analytics APIs that developers of other apps and websites may access and use in different ways. Likewise, advertisers can use APIs to target a desired subset of a service’s users and possibly extract user data. This report explains how websites and apps can create user profiles based on your online behavior and generate revenue from advertiser-access to their APIs. The report concludes with observations on how various companies and platforms connecting through APIs may be able to learn information about you and aggregate it with your personal data from other sources when you are browsing the internet or using different apps on your smartphone or tablet. While the paper does not make policy recommendations, it demonstrates the importance of approaching consumer privacy from a broad perspective that includes first parties and third parties, and that considers the integral role of APIs in today’s online ecosystem

Quest for Knowledge and Pursuit of Grades: Information, Course Selection, and Grade Inflation at an Ivy League School

This paper exploits a unique natural experiment — Cornell University’s 1996 decision to publish course median grades online - to examine the effect of grade information on course selection and grade inflation. We model students’ course selection as dependent on their tastes, abilities, and expected grades. The model yields three testable hypotheses: (1) students will tend to be drawn to leniently graded courses once exposed to grade information; (2) the most talented students will be less drawn to leniently graded courses than their peers; (3) the change in students’ behavior will contribute to grade inflation. Examining a large dataset that covers the period 1990-2004 our study provides evidence consistent with these predictions

A characteristics framework for Semantic Information Systems Standards

Semantic Information Systems (IS) Standards play a critical role in the development of the networked economy. While their importance is undoubted by all stakeholders—such as businesses, policy makers, researchers, developers—the current state of research leaves a number of questions unaddressed. Terminological confusion exists around the notions of “business semantics”, “business-to-business interoperability”, and “interoperability standards” amongst others. And, moreover, a comprehensive understanding about the characteristics of Semantic IS Standards is missing. The paper addresses this gap in literature by developing a characteristics framework for Semantic IS Standards. Two case studies are used to check the applicability of the framework in a “real-life” context. The framework lays the foundation for future research in an important field of the IS discipline and supports practitioners in their efforts to analyze, compare, and evaluate Semantic IS Standard

AQUA: an ontology driven question answering system

This paper describes AQUA our question answering over the Web. AQUA was designed to work over heterogeneous sources. This means that AQUA is equipped to work as closed domain and in addition to open-domain question answering. As a first instance, AQUA tries to answer a question using a Knowledge base. If a query cannot be satisfied over a knowledge base/database. Then, AQUA tries to find an answer on web pages (i.e. it uses as corpus the internet as resource). Our system uses NLP (Natural Language Processing), First order logic and Information Extraction technologies. AQUA has been tested using an ontology which describes academic life. Keywords Ontologies, Information Extraction, Machine Learnin