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Rancang Bangun Aplikasi Pembelajaran Bahasa Arab Untuk Siswa Madrasah Ibtidaiyah Berbasis Android Waeisul Bismi; Musriatun Napiah; Jordy Lasmana Putra; Fajar Shidiq
Computer Science (CO-SCIENCE) Vol. 1 No. 2 (2021): Juli 2021
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v1i2.256

With the increasingly open mindset of society today, especially Indonesia, it makes it easy for us to accept new things and implement them in our lives, these new things appear in many aspects such as one of which is education. In terms of education, it is better if it is carried out at an early age, especially in terms of learning a second foreign language or a foreign language substituting for English, this is what elementary school teachers have realized and has begun to be implemented recently, to do this elementary schools need tools to create methods. this learning becomes effective. Therefore the authors make an Arabic learning application that will make it easier for elementary school teachers to effectively introduce basic Arabic such as the recognition of the names of the day for elementary school children, which is equipped with sounds and images that can attract children's interests. This application can be run on an Android smartphone with a minimum Android OS 5.0 (Lollipop) and a maximum Android OS is 8.1 (Oreo).

Perancangan Sistem Informasi Dengan PHP Dan MYSQL Untuk Pendaftaran Sekolah Di Masa Pandemi Mugi Raharjo; Musriatun Napiah; Rian Septian Anwar
Computer Science (CO-SCIENCE) Vol. 2 No. 1 (2022): Januari 2022
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v2i1.689

During the current Covid-19 pandemic, a platform such as a website is needed to facilitate the process and activities of new student admissions in the field of education, the activity in question is holding a selection of new student admissions in schools. In the process of admitting new students, there are still a lot of schools that still use the system manually or face to face in the admissions process, so that the level of efficiency and security in order to maintain health protocols can be met. In this design, the author conducted a case study in one of the kindergartens in Jakarta which still applies a manual system so that in this pandemic era it is very effective. Students don't need to be bothered to come to school during this pandemic. In terms of education on the website, we provide guidance to parents on how to use the website via whatsapp video call or Zoom Meeting to make it easier. For that we tried to make the website, which is an information system that is used for new student admissions based on the website to make it easier for parents to register for school for their children. And the selection of the website platform was chosen to make it easier for parents to open this service without having to install applications that would normally take up memory on smartphone devices, we created this website with Php and My Sql. The results of this study indicate that this system is able to manage the process of accepting new students for this school.

Komparasi Algoritma Machine Learning untuk Klasifikasi Gejala Coronavirus Disease 19 (Covid-19) Musriatun Napiah; Rachmawati Darma Astuti; Eka Kusuma Pratama
Computer Science (CO-SCIENCE) Vol. 3 No. 2 (2023): Juli 2023
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v3i2.1984

COVID-19 or Corona Virus Disease 19 is a member of the extended family of coronaviruses that cause a spectrum of illnesses from mild to severe, including MERS and SARS. While the cause of COVID-19 transmission has not been confirmed, it is believed that the virus is transmitted from animals to humans, causing various symptoms such as cough, runny nose, fever, sore throat and loss of smell. Research was conducted to classify COVID-19 symptoms into low, medium, and high categories in patients. This study aims to classify patient data and determine the risk of COVID-19 infection based on the severity of symptoms, namely mild, moderate, and high. Machine learning methods, including Decision Tree and SVM algorithms, are introduced and compared with K-Nearest Neighbor (K-NN), Neural Network (NN), Random Forest (RF), and Naive Bayes. The dataset used contains 127 patient records from kaggle.com. The test results showed that SVM achieved 54% accuracy, while Decision Tree achieved 98%. This research provides important insights into the risk assessment of COVID-19 infection based on symptom severity, and the use of machine learning techniques is expected to improve analysis and prediction capabilities in the face of the COVID-19 pandemic.

Analisis Sentimen Ulasan Pelanggan Menggunakan Algoritma Naive Bayes pada Aplikasi Gojek Heristian, Sujiliani; Napiah, Musriatun; Erawati, Wati
Computer Science (CO-SCIENCE) Vol. 5 No. 1 (2025): Januari 2025
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v5i1.7775

Transportation is a means that a person uses to move from one place to another. One mode of transportation that is popular among the public is online motorcycle taxis, such as Gojek. Gojek continues to innovate to meet customer needs more effectively, as well as expand the scope of its services. This research aims to identify the number of positive and negative sentiments in the user review dataset, evaluate the performance of the algorithm used, and measure the level of customer satisfaction with Gojek services. Analysis was carried out on 6,485 customer reviews, which resulted in 4,387 positive sentiments and 2,098 negative sentiments. The classification model used, namely Naive Bayes, shows an accuracy of 88.5%, precision of 88.1%, and recall of 89.0%. The results of this research indicate that the Naive Bayes method provides good performance in analyzing the sentiment of user reviews of Gojek services

Analisis Sentimen Ulasan Pelanggan Menggunakan Algoritma Naive Bayes pada Aplikasi Gojek Heristian, Sujiliani; Napiah, Musriatun; Erawati, Wati
Computer Science (CO-SCIENCE) Vol. 5 No. 1 (2025): Januari 2025
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v5i1.7775

Transportation is a means that a person uses to move from one place to another. One mode of transportation that is popular among the public is online motorcycle taxis, such as Gojek. Gojek continues to innovate to meet customer needs more effectively, as well as expand the scope of its services. This research aims to identify the number of positive and negative sentiments in the user review dataset, evaluate the performance of the algorithm used, and measure the level of customer satisfaction with Gojek services. Analysis was carried out on 6,485 customer reviews, which resulted in 4,387 positive sentiments and 2,098 negative sentiments. The classification model used, namely Naive Bayes, shows an accuracy of 88.5%, precision of 88.1%, and recall of 89.0%. The results of this research indicate that the Naive Bayes method provides good performance in analyzing the sentiment of user reviews of Gojek services

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