Blended learning adalah kolaborasi atau kombinasi antara pembelajaran tradisional (pembelajaran dengan tatap muka secara langsung) dan pembelajaran menggunakan teknologi atau e-learning. Universitas Brawijaya sebagai penyelenggara pendidikan tinggi juga telah memfasilitasi penggunaan teknologi untuk blended learning. Namun pada penerapan blended learning masih terdapat beberapa permasalahan Pada penelitian ini digunakan Unified Theory of Acceptance and Use of Technology (UTAUT) sehingga mampu menutupi kekurangan dari penelitian sebelumnya. Faktor-faktor yang dapat diidentifikasi dengan UTAUT diwakili 2 faktor yaitu perilaku penggunaan (Use Behavior) serta perilaku keinginan dalam menggunakan sistem (Behavioral Intention). Masing-masing dari kedua faktor ini dipengaruhi oleh 4 faktor yaitu harapan kinerja sistem (performance expectancy), harapan usaha yang dikeluarkan untuk mengoperasikan sistem (Effort Expectancy), pengaruh sosial (Social Influence) serta kondisi fasilitas yang mendukung operasional sistem (Facilitating Conditions). Sedang 4 faktor ini ditentukan oleh gender, umur, pengalaman dalam menggunakan sistem kesukarelaan penggunaan sistem dari pengguna. Dengan menggunakan UTAUT ternyata didapatkan hasil evaluasi bahwa faktor-faktor yang memiliki pengaruh terhadap penggunaan sistem blended learning di
<p>Penelitian bertujuan untuk mengevaluasi kesuksesan implementasi sistem informasi kesehatan (Homedika.com). Pengukuran dilakukan berdasarkan DeLone & McLean Model. Pengumpulan data dilakukan melalui kuesioner yang telah lolos uji validitas dan reliabilitas. Sampel penelitian berjumlah 30 responden yang dipilih dengan menggunakan teknik <em>purposive sampling</em> dan data dianalisis dengan statistik jenis deskriptif. Hasil analisis kesuksesan pada variabel <em>system quality, information quality</em>, <em>service quality</em>, <em>user satisfaction</em>, dan <em>net benefits</em> masuk ke dalam kategori Tinggi, dan variabel <em>use</em> masuk ke dalam kategori Cukup Tinggi. Kesuksesan implementasi sistem informasi kesehatan dapat ditingkatkan dengan cara melakukan perbaika pada variabel <em>use</em> dengan indikator <em>frequency of use</em>.</p><p><strong><em>Abstract</em></strong></p><p class="Judul2"><em>The study aims to evaluate the success of health information systems (Homedika.com) implementation. Measurements are carried out based on DeLone & McLean Model. Data collection was done through questionnaire that had passed the validity and reliability test. The research sample consisted of 30 respondents who were selected using purposive sampling technique and ata were analyzed using descriptive statistics formula. The results of success analysis in the system quality, information quality, service quality, user satisfaction, and net benefits</em><em> variable</em><em> </em><em>categorized as</em><em> High, and use variable </em><em>categorized as </em><em>Quite High. The success of the implementation of health information systems can be improved by improving the use variable with frequency of use</em><em> indicator</em><em>.</em></p><p><strong><em><br /></em></strong></p>
Vocational High School with ICT major need an intelligent computing system that could predict the student learning achievement. The system used fifteen achievement indicators and Naïve Bayes algorithm in data processing. Testing on student achievement data produces the conclusion that is the highest intelligent accuracy values in 53% with lowest accuracy value in 48% based on Naïve Bayes algorithm processing. The result of mining process using Naïve Bayes algorithm can be used to classify the 3rd year student achievement to five categories. These categories are Very Good, Good, Fair, Poor, and Failed. The system testing result showed that this intelligent computing system function was fitted with Vocational High School’s system requirement, system design, and system implementation.
Instead of thermometer, an infrared camera could be uti-lized to scan body temperature instantly and non-contact. This paperproposed a non-contact measurement of human body temperature by au-tomatically locating inner-chantus on thermal images. The inner-canthuswere detected in both eyes individually. It located inner-canthi based ontemperature where inner-canthi has the highest temperature in face area.A Thresholding based on 9-highest temperature were applied to detectcandidates of inner-canthus' blob as it must have minimum 9 pixel areaaccording to the Standard. Three knowledge based on characteristic ofeye were also applied in the algorithm as several spot in face usuallyfalls within the temperature threshold. The result show accuracy of al-gorithm to detect eye is 82% whether the eyelids were open or closed.There is no signicant dierent of temperature between closed and openeyes based on paired t-test. The algorithm also showed similar result tothermometer measurement based on paired t-test.
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