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Wahyutama Fitri Hidayat
Universitas Bina Sarana Informatika
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Engineering Library & Information Science

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Journal : Computer Science (CO-SCIENCE)

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Penerapan Model Design Thinking Pada Perancangan Aplikasi Informasi Desa Wisata Kabupaten Bantul Hidayat, Wahyutama Fitri; Malau, Yesni; Purnama, Rachmat Adi; Setiadi, Ahmad
Computer Science (CO-SCIENCE) Vol. 4 No. 2 (2024): Juli 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v4i2.3459

Abstract

Tourism actors in the current technological era have implemented information systems. With the rapid growth of tourist villages in Bantul Regency, there is a need for promotion and digital information delivery media. However, in developing digital media it is also necessary to pay attention to aspects of the users who are the target market. The design of the application called sidewi mobile (mobile tourist village information system) is based on user experience and needs, using the Design Thinking methodology which has five stages as follows: Empathize, Define, Ideate, Prototype, and Test. The design of the Sidewi mobile application was created using FIGMA software. This research has direct benefits, namely that it can be used as a benchmark for design needs before the development process. The results of the design are then tested using the usability testing method. Using a user friendly design approach and conducting testing using usability testing with the results of five users being able to complete the testing proves that when it was created using user experience there were no significant difficulties when used and it covered all needs.
Prediksi Kualitas Tidur: Pendekatan Machine Learning yang Mengintegrasikan Faktor Kesehatan dan Lingkungan Putra, Jordy Lasmana; Hidayat, Wahyutama Fitri
Computer Science (CO-SCIENCE) Vol. 4 No. 2 (2024): Juli 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v4i2.4737

Abstract

Sleep disorders significantly affect an individual's sleep quality, which can lead to serious health problems. For the elderly, poor sleep quality can drastically reduce life expectancy. The main problem is the lack of effective predictive tools to improve sleep quality among the elderly, compounded by the numerous factors that can influence their sleep quality. Therefore, analysis and prediction are necessary to enhance sleep quality. This study aims to develop and test a predictive model for sleep quality in the elderly by integrating health and environmental factors using a machine learning approach. The dataset used is a new one available on the website Kaggle.com, namely the National Poll on Healthy Aging (NPHA) data, which provides insights into health issues, healthcare, and health policies affecting Americans aged 50 and above. The aim is to improve sleep quality among the elderly. A machine learning method, specifically deep learning with the Random Forest algorithm, was used in this study and showed good results with an accuracy rate of 94.00% and a training data accuracy of 44.44%. The results of this study are expected to provide a predictive tool that can be used by healthcare practitioners to improve the sleep quality of the elderly, thereby positively impacting their health and life expectancy.
Penerapan Model Design Thinking Pada Perancangan Aplikasi Informasi Desa Wisata Kabupaten Bantul Hidayat, Wahyutama Fitri; Malau, Yesni; Purnama, Rachmat Adi; Setiadi, Ahmad
Computer Science (CO-SCIENCE) Vol. 4 No. 2 (2024): Juli 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v4i2.3459

Abstract

Tourism actors in the current technological era have implemented information systems. With the rapid growth of tourist villages in Bantul Regency, there is a need for promotion and digital information delivery media. However, in developing digital media it is also necessary to pay attention to aspects of the users who are the target market. The design of the application called sidewi mobile (mobile tourist village information system) is based on user experience and needs, using the Design Thinking methodology which has five stages as follows: Empathize, Define, Ideate, Prototype, and Test. The design of the Sidewi mobile application was created using FIGMA software. This research has direct benefits, namely that it can be used as a benchmark for design needs before the development process. The results of the design are then tested using the usability testing method. Using a user friendly design approach and conducting testing using usability testing with the results of five users being able to complete the testing proves that when it was created using user experience there were no significant difficulties when used and it covered all needs.
Prediksi Kualitas Tidur: Pendekatan Machine Learning yang Mengintegrasikan Faktor Kesehatan dan Lingkungan Putra, Jordy Lasmana; Hidayat, Wahyutama Fitri
Computer Science (CO-SCIENCE) Vol. 4 No. 2 (2024): Juli 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v4i2.4737

Abstract

ganguan tidur sangat mempengaruhi kualitas tidur seseorang yang dapat menyebabkan masalah kesehatan yang serius, untuk kalangan lansia kualitas tidur yang buruk dapat menyebabkan tingkat harapan hidup menurun drastis. Banyak sekali faktor-faktor yang dapat mempengaruhi kualitas tidur lansia, yang perlu dilakukan analisis dan prediksi agar dapat meningkatkan kualitas tidur yang baik. Penelitian ini bertujuan untuk melakukan prediksi kualitas tidur lansia dengan mengintegrasikan faktor kesehatan dan lingkungan menggunakan pendekatan machine learning, data set yang digunakan adalah data set baru yang ada di website kaggle.com yaitu data National Poll on Healthy Aging (NPHA) yang berisikan wawasan tentang isu kesehatan, perawatan kesehatan, dan kebijakan kesehatan yang memengaruhi orang Amerika berusia 50 tahun ke atas. Metode maching learning, yaitu deep learning dengan algoritma Random Forest digunakan pada penelitian ini dan menunjukkan hasil yang baik dengan nilai akurasi 94,00% dan 44,44% akurasi yang didapatkan dengan menggunakan data latih.
Co-Authors Ade Hendini Ahmad Setiadi Ali Mustopa, Ali Annida Purnamawati Bayu Pratama, Eri Destiana Putri Eri Bayu Pratama Fajar Sarasati Fajar Shidiq Fintri Indriyani Hermanto Hermanto Jordy Lasmana Putra Julianto, Muhammad Fahmi Kartika Handayani Khalila, Ayasha Noor Mochammad Imron Awalludin Muhamad Syarif Muhammad Fahmi Julianto Paulus Tofan Rapiyanta Rachmat Adi Purnama Rangga Sanjaya Taufik Asra Wawan Nugroho YANTO YANTO Yesni Malau