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Computer Science (CO-SCIENCE)
Published by Universitas Bina Sarana Informatika
ISSN : -     EISSN : 27749711     DOI : https://doi.org/10.31294/coscience
Core Subject : Science,
Computer Science & IT
Computer Science (CO-SCIENCE) pertama kali publikasi tahun 2021 dengan nomor ISSN (Elektonik): 2774-9711 yang diterbitkan oleh Lembaga Ilmu Pengetahuan Indonesia (LIPI). Computer Science (CO-SCIENCE) adalah jurnal yang diterbitkan oleh Program Studi Ilmu Komputer Universitas Bina Sarana Informatika. Computer Science (CO-SCIENCE) terbit 2 kali setahun (Januari dan Juli) dalam bentuk elektronik. Redaksi menerima naskah berupa artikel ilmiah dan penelitian pada bidang: Networking, Aplication Mobile, Software Engineering, Web Programming, Mobile Computing, Cloud Computing, Data Mining, dan Aplikasi Sains.
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 121 Documents
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Sistem Informasi Pendalaman Materi Berbasis Web Pada SMA Cengkareng 1 Menggunakan Model Waterfall Susafa'ati Susafa'ati; Nunung Hidayatun; Hidayanti Murtina
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.v3i2.1943

Abstract

Cengkareng 1 High school as an educational institution  providing senior secondary education in the city of West Jakarta. In every semester the school always conducts a study evaluation in the form of a written exam. The problem faced by the school is that the school wants to hold a deepening of the material for students to face the exam but is constrained by time, place, cost and teaching staff. From these problems, a system was created that could document the material, assignments and presentation of the questions as part of the implementation of deepening the material. Analysis and design by waterfall method. Research begins with conducting literature reviews, collecting data, analyzing systems and requirements, building system models using UML, designing application implementations, testing using black box testing, and maintaining system data. The results of this research are provided in the form of a web-based material immersion application. The application has the ability to provide materials, monitor student assignment uploads, and help students identify their limitations as they prepare for school and national exams.
Sistem Informasi Pengaduan Perbaikan Jalan Desa (Program SIG) Berbasis Web Hidayat Muhammad Nur; Vadlya Maarif
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.v3i2.1963

Abstract

Several damaged roads in the Kebasen area during the rainy season are continuous work for the government. As an effort to assist this public service, it provides an opportunity for the public to submit complaints or complaints when public facilities have not met expectations. The following is an alternative to the procedure for submitting complaints or complaints for road repairs online which can help better communication. This study aims to build a GIS web-based road repair complaint information system. The system prototype was designed in stages with the development of the waterfall model system and the PHP programming language. In making this system the author uses the framework CodeIgniter (Ci) and Object Oriented Analysis and Design (OOAD). The interface for connecting several applications uses the Google Application Programming Interface (API) and MySQL database. The results of this study are expected to be the system of choice for conveying the aspirations of the people up to date in complaints about road repairs, environmental conditions, traffic conditions, public road management conditions, security conditions, street lighting conditions and presenting information optimally
Metode Design Thinking Pada Sistem Informasi Presensi Pegawai Kejaksaan Negeri Kota Bogor Yuris Alkhalifi; Khairul Rizal; Amir Amir; Ainun Zumarniansyah; Destia Sari Rahmadhani Fadillah
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.v3i2.1968

Abstract

Employee presence is an important factor for an agency or company to achieve goals, this is related to discipline and has an impact on the performance of each employee. But in reality, there are still several agencies that still use manual absences that have not been computerized, one of which is the Kejaksaan Negeri Kota Bogor's Office. The system used by the Kejaksaan Negeri Kota Bogor in the attendance process is still manual, namely using a daily attendance book which affects the efficiency and effectiveness of data collection, data search, and calculations and requires a relatively long time. Therefore, it is necessary to have special data collection to record attendance and absence so that work activities can be recorded in real-time and properly, one of which is by using a computerized system with Information Systems. The information system built on a website basis uses the CodeIgniter 3 framework and MySQL. The method used is the Design Thinking Method which has 5 stages. The output of this study is known to be tested with usability testing by user on the Learnability aspect of 75%, then on the efficiency aspect of 100% and the memorable aspect of 66.77%. The average result of the test is quite good at 80.56%. So by making this information system, it can facilitate the process of being on time, searching for data, calculating and summarizing timeliness and minimizing errors when recording presence data.
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

Abstract

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.
Pendekatan Algoritma Klasifikasi Machine Learning untuk Deteksi Penyakit Demensia Muhammad Iqbal; Hendri Mahmud Nawawi; Muhammad Rezki; Abdul Hamid; Sri Rahayu
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.v3i2.1987

Abstract

Early detection of dementia through the use of machine learning classification algorithms is important for providing appropriate interventions to patients. In this context, this study aims to compare the performance of several machine learning classification algorithms in detecting dementia using the attribute selection method. In the early stages, patient data including medical history, cognitive test results, and other attributes were collected as input, an attribute selection algorithm was used to select the most informative attribute subset in detecting dementia. The subset of attributes used as input for training machine learning classification models, several classification algorithms such as Extra Trees (ET), Linear Discriminant Analysis (LDA), Random Forest (RF) and Ridge. In this study, accuracy is used as the main metric to compare algorithm performance. The evaluation results show that the Random Forest (RF) algorithm produces the best performance with an accuracy of 91.56%. The Extra Trees (ET) algorithm has an almost comparable accuracy of 91.44%, while Ridge and Linear Discriminant Analysis (LDA) have an accuracy of 90.44% respectively. In the context of dementia detection, the performance of the Random Forest algorithm with the attribute selection method proved to be the best with an accuracy of 91.56%. These results indicate that the developed model is capable of recognizing complex patterns and relationships between features that are relevant to dementia status. The use of the attribute selection method also contributes to increasing the accuracy and efficiency of the classification algorithm.
Penerapan Teknik Random Oversampling Untuk Memprediksi Ketepatan Waktu Lulus Menggunakan Algoritma Random Forest Diantika, Sri; Nalatissifa, Hiya; Maulidah, Nurlaelatul; Supriyadi, Riki; Fauzi, Ahmad
Computer Science (CO-SCIENCE) Vol. 4 No. 1 (2024): Januari 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v4i1.1996

Abstract

Punctuality of graduation is something that students yearn for, besides being important for students, punctuality of graduation is also very important for universities, this is because the aspect of student graduation is one aspect of assessment in an institutional accreditation process of a university to show its quality. One of the obstacles faced to find out whether a student can graduate on time or not is because the study period cannot be detected early, this will have an impact on late student graduation. To analyze this, a lot of research was conducted on the accuracy of student graduation, through the cumulative grade point average (GPA) obtained by students during their studies. This research on the prediction of student graduation timeliness uses a random forest algorithm model. The data used in this research object has an unbalanced number of data classes, to overcome this, a random oversampling (ROS) resampling technique is applied and also applies Split validation or division between learning data by 50% for test data and 50%. To evaluate the model built, the author uses evaluation metrics such as accuracy, recall, and precision. The results of the study showed that the proposed model can well predict compared to other models, namely with the results precision of 87.05%, accuracy test values of 90.04%, recall of 90.04%.From these results, it can be interpreted that the random forest algorithm is considered good in predicting the timeliness of a student's graduation
Perancangan Game Role-Playing sebagai Sarana Edukasi Sejarah Menggunakan Metode Game Development Life Cycle Hilmawan, Brian Nur; Yuniati, Trihastuti
Computer Science (CO-SCIENCE) Vol. 4 No. 1 (2024): Januari 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v4i1.2032

Abstract

Sejarah sebagai suatu kejadian yang telah terjadi di masa lampau dapat menjadi sebuah pelajaran di masa yang akan datang bagi umat manusia. Ironisnya, generasi muda jaman sekarang lebih condong untuk mengadopsi budaya global. Kemajuan teknologi yang pesat membuat pengetahuan dalam lingkup teknologi lebih diminati, namun, bukan menjadi suatu alasan bagi calon generasi masa depan untuk melupakan pondasi tempat ibu pertiwi berdiri. Salah satu fenomena yang tidak asing di dengar adalah video game. Melihat hal ini, pengembangan video game yang juga akrab di adopsi pada tujuan yang lebih serius seperti edukasi, mendorong penelitian ini, yaitu untuk merancang suatu sistem game yang memiliki nilai edukasi yang dapat menghibur dan memberikan pengetahuan kepada penggunanya tentang pesan yang ingin diberikan. Penelitian dilakukan menggunakan Metode Game Development Life Cycle yang dimulai dari tahap inisiasi untuk membentuk mindmap melalui brainstorming pengembang, pra-produksi guna membentuk low-fidelity prototype dan Game Document Design, produksi tahap dimana scene dibentuk, pengujian versi alpha oleh pengembang, hingga pengujian beta oleh pengguna potensial. Penelitian telah menghasilkan game “Keraton: Maja” yang berhasil dijalankan tanpa defect atau bug. Hasil pengujian kuesioner likert oleh beta tester mendapatkan rata-rata total nilai elemen sebesar 4,1 sehingga dapat disimpulkan bahwa sistem game dapat diterima dengan baik.
Peningkatan Jaringan Komunikasi Tertutup Berbasis Seluler Dengan Agregasi Multi Link : Studi Kasus PT. Solusi Media Semesta iman, Fadlul; Saputra, Elin Panca; Kusumo, Aryo Tunjung; Sismadi, Sismadi
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.v4i2.2372

Abstract

The increasing need for cellular-based closed communication networks in corporate environments has increasingly become a major focus for many organizations, including PT. Universal Media Solutions Jakarta. In the face of increasingly complex communication challenges and increasing data demands, the company is working to improve the efficiency and performance of its communications network. This study aims to investigate the potential of using multi-link aggregation as a solution to improve cellular communication networks at PT. Universal Media Solutions Jakarta. The multi-link aggregation method allows combining multiple communication lines to achieve increased network speed, availability, and consistency. The study will involve analyzing and testing various scenarios using multi-link aggregation technology in the company's cellular-based closed network environment. Network performance measurement will be carried out to radiate the effectiveness of the implemented solutions. In addition, technical and financial factors will also be considered to ensure the feasibility and efficiency of the proposed solution. The results of this study are expected to provide valuable insights for PT. Solusi Media Semesta Jakarta and other organizations in optimizing their closed communication network using multi-link aggregation technology. Thus, companies can increase productivity, reduce downtime, and improve service quality for their customers and internal users.
Pengukuran Kinerja Model Klasifikasi dengan Data Oversampling pada Algoritma Supervised Learning untuk Penyakit Jantung Masruriyah, Anis; Novita, Hilda; Sukmawati, Cici; Ramadhan, Angga; Arif, Siti; Dermawan, Budi
Computer Science (CO-SCIENCE) Vol. 4 No. 1 (2024): Januari 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v4i1.2389

Abstract

Heart disease remains a leading cause of death in Indonesia and worldwide. In the realm of data mining, class imbalance between heart disease and normal samples within datasets presents a significant challenge. This disparity can lead to model bias toward the majority class, resulting in suboptimal performance in identifying instances of heart disease. This study addresses this issue by implementing oversampling techniques, particularly Synthetic Minority Over-sampling Technique (SMOTE) and Adaptive Synthetic Sampling (ADASYN). The findings reveal that models without oversampling achieve accuracy and precision exceeding 80%, but exhibit poor class separation performance. In contrast, models employing oversampling, despite experiencing reductions in accuracy and precision, enhance their ability to distinguish between heart disease and normal classes. The top-performing model utilizing the Random forest algorithm with SMOTE attains an AUC value of 0.868, signifying a significant improvement in class separation. These discoveries provide essential guidance for the development of more effective and accurate heart disease classification models. The utilization of oversampling techniques, such as SMOTE, proves to be an effective strategy for mitigating class imbalances in heart disease data mining. While accuracy and precision may decrease, the model's capability to identify heart disease becomes more reliable, with notable outcomes assessed using AUC. This research contributes significantly to enhancing efforts in heart disease prevention and treatment through sophisticated and sustainable data mining techniques.  
Analisa Performasi Metode Client Side Rendering, Server Side Rendering, dan Incremental Static Regeneration dalam Proses Website Rendering Ardiyanto, Roni; Ardhianto, Eka
Computer Science (CO-SCIENCE) Vol. 4 No. 1 (2024): Januari 2024
Publisher : LPPM Universitas Bina Sarana Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31294/coscience.v4i1.2427

Abstract

Website telah menjadi bagian penting dari kegiatan bisnis, pendidikan, hiburan, maupun media sosial. Optimalisasi website menjadi penting saat proses pembuatannya. Hal ini disebabakan supaya pengguna website merasa nyaman. Akses website yang cepat dan ringan menjadi salah satu daya tarik pengguna. Metode pembuatan website pada bagian Front-End diklasifikasikan menjadi 3 macam, yaitu: metode render CSR (Client Side Rendering), metode render SSR (Server Side Rendering), dan metode render ISR (Incremental Static Regeneration). Penelitian ini menggunakan aplikasi website dengan framework Next.js sebagai website untuk pengujian. Dibuat dalam website satu halaman berisi list daftar berita dari API CNNIndonesia.com. Tujuan penelitian ini untuk mencari metode mana yang optimal digunakan dalam pengembangan website. Sebagai metrik performansi digunakan kecepatan dan ukuran website. Hasil yang diperoleh adalah bahwa metode ISR sangat cocok digunakan dalam pengembangan web frontend karena lebih ringan dan lebih cepat diakses dibanding metode SSR dan CSR. Dengan rekomendasi untuk pembuatan website, jika menginginkan kecepatan berarti dapat menggunakan metode ISR untuk peramban crome jika menggunakan mozilla SSR. Jika menginginkan generate yang ringan maka menggunakan metode ISR untuk mozilla dan ISR untuk chrome.

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