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Bakhtiyar Hadi Prakoso
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BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer
Published by Sinergis Asa Professional
ISSN : -     EISSN : 27220850     DOI : https://doi.org/10.37148/bios
Core Subject : Science,
Computer Science & IT
BIOS: Jurnal Teknologi Informasi dan Rekayasa Komputer (e-ISSN. 2722-0850) is a scientific journal in the field of information technology and computer engineering managed by the Asa Professional Research & Development Center (PUSLITBANG), Jember, East Java, Indonesia. This journal is managed by lecturers and practitioners who come from various university backgrounds in Indonesia, especially Jember, East Java.The BIOS journal is published 2 (two) times a year, namely every March and September. The BIOS journal published in each edition consists of 5-10 articles per volume. The focus and scope of this journal are in the field of Information Technology and others that are still knowledge related, including: Databases System Data Mining / Web Mining Data Warehouse Artificial Intelligence Business Intelligence Cloud & Grid Computing Decision Support System Human-Computer Interaction Mobile Computing & Application E-System Machine Learning Deep Learning Information Retrieval (IR) Computer Network Multimedia System Information System Geographic Information System (GIS) Accounting information system Database Security System & Network Security Cryptography Fuzzy Logic Expert System Image Processing Computer Graphic Computer Vision Semantic Web e-Health and others related to Information Technology and Computer Engineering.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 74 Documents
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Implementasi Machine Learning Untuk Prediksi Penyakit Jantung Menggunakan Algoritma Support Vector Machine Hidayat, Rahmat; Sy, Yandiko Saputra; Sujana, Teguh; Husnah, Mirdatul; Saputra, Haris Tri; Okmayura, Finanta
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 5 No 2 (2024): September
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v5i2.152

Abstract

Heart disease is currently a disease that has taken over many human lives. Data shows that more than 17 million people have died from heart disease. The high number of deaths, therefore, requires special handling to treat and prevent heart disease. In the development of technology, diagnosis of heart disease can be done with the help of information technology, one of which is through machine learning. This study aims to implement machine learning through the SVM algorithm to predict heart disease. The model formed by SVM produces an evaluation value indicated by an accuracy value of 0.85, a precision of 0.93, a recall of 0.76, and an f-1 score of 0.83. This model is used as training data to predict heart disease which is then successfully used to create a system through the Streamlit library which can be easily accessed via the website.
Analisis Sentimen Program Jaminan Kesehatan Nasional Menggunakan Multiclass Support Vector Machine Dasriani, Ni Gusti Ayu; Pariandi, Lalu Ahmad Gede; Dharma, I Made Yadi
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 6 No 1 (2025): March
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v6i1.136

Abstract

Optimizing the implementation on National Helath Insurance which requires the use of BPJS participant cards in various public services is one of the government policies that is widely discussed and has garnered many opinions in the community. Public opinion is expressed through social media, one of which is through Twitter. The aim of this research is to classify public opinion regarding the new regulations of the National Health Insurance Program as a form of government policy to implement Presidential Instruction Number 1 of 2022 using Twitter data. Public opinion as many as 1.179 tweets were labeled positive, negative and neutral sentiments, then TD-IDF wighting was carried out and analyzed using the multiclass SVM algorithm with the One Against All approach. The results of the analysis showed that Multiclass SVM with a linear kernel was able to classify with an accuracy level of 81% where the classification pf positive sentiment was17 (7.6%), negative sentiment was 115 (48.7%) and neutral sentiment are 104 (44.1%). This shows that public sentiment is dominated by negative sentiment or disagreement with the new regulations of the National Health Insurance Program.
Pengembangan Media Pembelajaran Berbasis Smart Apps Creator pada Mata Pelajaran Informatika Kelas X SMK Negeri 2 Tulungagung Ardiansyah, Afan Risqi; Indrakusuma, Abdul Haris
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 6 No 1 (2025): March
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v6i1.147

Abstract

This research focuses on improving the quality of teaching through the use of varied learning media at SMK Negeri 2 Tulungagung, which implements the Independent Curriculum. Even though technology such as projectors are available, the use of learning media is still dominated by printed books, which has an impact on the decline in students' interest in learning. The problem in learning Informatics at SMKN 2 Tulungagung is the lack of interactive learning media that is technology-based, especially in Computer Network and Internet materials. This research develops technology-based learning media using the Smart Apps Creator Application to increase interactivity and visualization. This study uses the Research & Development (R&D) method with the ADDIE (Analysis, Design, Development, Implementation, and Evaluation) model with the test subjects being students, lecturers as validators of media experts, and teachers as validators of material experts. Data collection instruments include interviews, observations, and questionnaires. The results of media validity obtained a score of 89.5% with the "Very Feasible" criterion and the validity of the material obtained a score of 89.2% with the "Very Feasible" criterion. The small group trial received a score of 76% with the "Feasible" criterion, while the large group trial obtained a result of 84.17% with the "Very Feasible" category. This AR media has proven to be effective in increasing students' understanding and motivation despite several technical obstacles.
Analisis Kualitas Website e-RKAM Menggunakan Metode WebQual 4.0 Febriyani, Risa; Syafrianto, Syafrianto
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 6 No 1 (2025): March
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v6i1.154

Abstract

Technological developments in the field of education have encouraged the implementation of the e-RKAM application to facilitate the preparation and reporting of School Operational Assistance funds digitally in madrasas. However, there are still some technical obstacles such as servers that often go down, errors in some menus, and delays in producing the latest report output (update), which has a significant impact on the quality of application services. This study aims to analyze the quality of the e-RKAM website using the WebQual 4.0 method, which includes three variables: usability quality, information quality, and service interaction quality, as well as its influence on user satisfaction. The results of the analysis showed that these variables together contributed 44.7% to user satisfaction, while the remaining 55.3% was influenced by other factors outside this study. The T-test showed that only the quality of information had a significant influence on user satisfaction (sig. value 0.000), while the quality of usability and the quality-of-service interaction had no significant effect (sig. values of 0.066 and 0.844, respectively). These findings highlight that the model used has not been fully comprehensive in explaining the variation in user satisfaction, so more research is needed to explore additional factors that may have an effect.
Optimasi Pembuatan Jadwal Perkuliahan Menggunakan Algoritma Genetika Berbasis Pendekatan Multivariat Rohim, Muhamat Abdul; Wiranto, Ferry; Fauziah, Difari Afreyna
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 6 No 1 (2025): March
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v6i1.160

Abstract

Penjadwalan perkuliahan merupakan salah satu aspek penting dalam manajemen akademik di perguruan tinggi. Proses penjadwalan yang dilakukan secara manual sering kali menghadapi berbagai kendala, seperti keterbatasan ruang, preferensi dosen, serta distribusi jadwal yang tidak merata. Penelitian ini bertujuan untuk mengoptimalkan proses penjadwalan perkuliahan menggunakan Algoritma Genetika (AG) agar lebih efisien dan mengurangi konflik jadwal. Data yang digunakan dalam penelitian ini meliputi 20 ruang kelas, 50 dosen, serta rata-rata 120 jadwal kuliah per semester. Implementasi sistem dilakukan menggunakan bahasa pemrograman PHP, dengan tahapan penelitian meliputi pengumpulan data, analisis kendala, perancangan algoritma, implementasi, dan evaluasi hasil. Hasil penelitian menunjukkan bahwa sistem berbasis AG mampu menghasilkan jadwal perkuliahan yang lebih merata, dengan waktu pemrosesan sekitar 1 hingga 5 menit dan tanpa adanya konflik jadwal. Dengan demikian, pendekatan ini terbukti lebih efektif dibandingkan metode manual yang sebelumnya digunakan.
Literature Review : Website sebagai Sarana Digital Marketing pada Sekolah Dasar dan Menengah di Era Cloud Computing Sari, Nove Kurniati; Syaddam, Syaddam; Zulkarnain, Riski
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 6 No 1 (2025): March
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v6i1.161

Abstract

Websites and cloud computing are strategic foundations for supporting digital marketing, education management, and marketing strategies in primary and secondary education schools. The website functions as an official information centre that conveys the achievements that have been achieved by the school, activities, and superior programs, as well as a marketing tool to build school branding. Cloud computing technology supports efficient data management, collaboration, and marketing optimization. This study aims to review the role of websites and integration of productivity suite platforms in supporting digital marketing for education management in primary and secondary education schools, as well as the implementation of effective marketing strategies for non-profit schools. With strong branding, effective marketing communications, and data-driven analytics, schools can increase visibility, public trust, and audience engagement. The integration of technologies such as productivity suite platforms further strengthens the operational efficiency and effectiveness of school marketing. This study is expected to provide valuable insights for stakeholders in the field of education regarding best practices and innovative strategies in utilizing websites and cloud computing technology to achieve school goals in the digital era.
Penerapan Algoritma K-Means Clustering untuk Segmentasi Nasabah Bank Irawan, Dudi; Wijaya, Guruh; Warisaji, Taufiq Timur
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 6 No 1 (2025): March
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v6i1.162

Abstract

Segmentasi nasabah merupakan strategi yang penting dalam industri perbankan untuk memahami karakteristik dan kebutuhan pelanggan secara lebih mendalam. Penelitian ini menerapkan algoritma K-Means clustering untuk mengelompokkan nasabah berdasarkan faktor demografi dan finansial, seperti usia, jenis kelamin, pendapatan, status pernikahan, dan kepemilikan aset perbankan. Data yang digunakan terdiri dari 600 record nasabah yang diambil dari sumber daring dan diproses menggunakan metode unsupervised learning dalam data mining. Proses clustering dilakukan dengan beberapa nilai k (jumlah cluster) untuk menentukan pengelompokan yang optimal. Validasi dilakukan menggunakan Within-Cluster Sum of Squares (WCSS) dan Davies-Bouldin Index guna mengukur kualitas hasil segmentasi. Hasil penelitian menunjukkan bahwa segmentasi dengan nilai k = 2 dan k = 4 memberikan pola yang lebih jelas dibandingkan k = 3, di mana setiap cluster memiliki karakteristik yang berbeda dalam hal profil risiko, preferensi produk, dan tingkat keterlibatan dengan layanan perbankan. Dengan pendekatan ini, bank dapat meningkatkan strategi pemasaran, manajemen risiko kredit, serta personalisasi layanan berdasarkan segmentasi yang dihasilkan. Selain itu, penelitian ini memberikan rekomendasi untuk pengembangan sistem berbasis data mining yang dapat membantu dalam pengambilan keputusan bisnis di sektor perbankan.
Sistem Deteksi Dini Stunting Pada Balita Menggunakan Teknik Klasifikasi Dengan Algoritma C4.5 Sebagai Upaya Penekan Angka Kasus Stunting Di Puskesmas Sumberjambe Kabupaten Jember Umam, Ahmad Busyronul; Pratama, Mudafiq Riyan; Prakoso, Bakhtiyar Hadi; Muflihatin, Indah
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 6 No 2 (2025): September
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v6i2.164

Abstract

Stunting is a condition of impaired growth in toddlers caused by chronic malnutrition, characterized by a height that is not appropriate for their age. According to SSGI 2022 data, Jember Regency has the highest stunting rate in East Java at 34.9%, exceeding the WHO standard (<20%). This study aims to design and develop an early detection system for stunting in toddlers at Sumberjambe Public Health Center using the C4.5 algorithm method. The type of research used is quantitative research with a data mining approach using the C4.5 algorithm and the prototyping method. The object of this study is secondary data obtained from maternal cohort books and Excel-based nutrition data from Sumberjambe Health Center, which includes data on children categorized as stunted and normal. The initial dataset consisted of 1,798 entries, and after going through a pre-processing stage, 130 clean data entries were obtained and used for analysis. The data mining process resulted in a Confusion Matrix accuracy of 83.33% and produced 34 rules that were used as knowledge for the early stunting detection system. The system was developed using the prototyping method, which includes several stages from initial planning and design to testing and user evaluation. In the construction of prototype stage, the system was built using PHP programming language with the Laravel 10 framework and tested using the black-box testing method. In the deployment, delivery & feedback stage, the system was directly tested by the nutrition team at Sumberjambe Health Center and received very positive responses. Users were satisfied with the appearance and performance of the system, with no revision requests, and fully approved the proposed prototype.
Penerapan Algoritma Support Vector Machine Berbasis Kernel Radial Basis Function dalam Klasifikasi Sel Kanker Arifin, Zainul; Rahman, Dhimas Fachri; Rintyarna, Bagus Setya; Daryanto, Daryanto
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 4 No 2 (2023): September
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v4i2.165

Abstract

Cancer is a leading cause of death globally, with over 10 million deaths reported in 2020, according to the World Health Organization (WHO). Early detection and accurate diagnosis are crucial to improving survival rates. However, conventional diagnostic methods such as biopsies and histopathological analysis have several limitations, including being invasive, time-consuming, and reliant on subjective interpretation by pathologists. With technological advancements, artificial intelligence (AI) and machine learning (ML) offer promising alternatives in cancer diagnosis. This study explores the effectiveness of the Support Vector Machine (SVM) algorithm in classifying cancer cells using the Breast Cancer Wisconsin dataset. The dataset consists of 699 cell samples obtained through fine needle aspiration, each described by 10 morphological features and labeled as benign or malignant. The results show that SVM with a Radial Basis Function (RBF) kernel can classify cancer cells with high accuracy. Data preprocessing, including cleaning and normalization, significantly improves model performance. Additionally, parameter optimization using grid search enhances the model’s reliability. This study highlights the strong potential of SVM as an efficient, accurate, and practical decision-support tool in medical diagnosis, particularly for cancer detection.
Implementasi Virtual Reality dalam Visualisasi Arsitektur Kampus Menggunakan Game Development Life Cycle (GDLC) Hidayat, Muhammad Hafid; Maulana, Oka Wahyu; Oktavianto, Hardian; Muharom, Lutfi Ali; Cahyanto, Triawan Adi; Saifudin, Ilham
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 6 No 2 (2025): September
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v6i2.169

Abstract

Campus promotions often still rely on conventional media such as brochures, mockups, or 2D videos which are less attractive to the digital generation. This presents a challenge in effectively conveying the university's image and excellence to prospective students, especially high school students. To overcome these problems, this research aims to develop a campus architectural visualization system based on Virtual Reality (VR) technology as a promotional media for Muhammadiyah University. This system was developed using the Game Development Life Cycle (GDLC) method, which includes initiation, pre-production, production, testing, and post-production stages. 3D models of the campus buildings were created using Blender and integrated into Unity to build an interactive VR environment. Key features include virtual campus navigation, detailed 3D visualizations, and interactive information presentation. Testing was conducted using the black-box method and usability evaluation. The results show that the VR application is able to provide an interesting and informative campus exploration experience. This system is expected to be an effective and modern promotional media, and is able to increase prospective students' interest in the campus.

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