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Bakhtiyar Hadi Prakoso
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Perum. Griya Mangli Indah Blok AF-18 RT. 02 RW. 04, Kel. Mangli, Kec. Kaliwates, Kab. Jember, Jawa Timur, 68136
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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 94 Documents
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Pengembangan Dashboard Monitoring dan Pengingat Imunisasi Balita dengan Metode Scrum Bakhtiyar Hadi Prakoso; Gandu Eko Julianto Suyoso; Veronika Vestine; Muhammad Yunus
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 7 No 1 (2026): March
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v7i1.195

Abstract

The national coverage rate for complete basic immunization in Indonesia is high. However, several regions in Indonesia have under-performed targets. Several factors contribute, including a lack of parental awareness of the importance of immunization, suboptimal program planning and management, and manual recording processes. These factors contribute to inaccurate decision-making. This research aims to create a dashboard system for monitoring and reminding toddlers about immunizations for decision support systems. The system development method used was the Scrum method. The results indicate that this system meets the standard requirements for immunization monitoring. Further development of the system can include the addition of a web service feature to facilitate access across multiple platforms.
Rancang Bangun Aplikasi VitaMind untuk Skrining Awal HIV Pada Remaja Sebagai Kelompok Risiko Dia Bitari Mei Yuana; Afis Asryullah Pratama; Tegar Wahyu Yudha Pratama; Nilam Puspitasari; Nurina Aprilya; Faiqatul Hikmah
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 7 No 1 (2026): March
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v7i1.196

Abstract

Human Immunodeficiency Virus (HIV) remains a public health problem, particularly among adolescents who are in the social exploration phase and at risk of experiencing psychological distress. Social stigma, anxiety, and fear of diagnosis often prevent HIV-risk groups from accessing mental health services. Unfortunately, psychological screening has not been optimally integrated into primary health care. This study aims to develop VitaMind, a conversation-based psychological screening application that integrates a rule-based system and generative artificial intelligence (AI) to support early detection of psychological conditions in adolescents at risk of HIV. The research method used a Research and Development (R&D) approach with a Waterfall software development model, including needs analysis, system design, implementation, and testing. The results show that VitaMind is able to provide interactive, safe, and easily accessible self-psychological screening, equipped with sexual health education features and psychologist consultation registration. The integration of the rule-based system and generative AI produces adaptive and empathetic responses, thereby increasing user comfort. The VitaMind application has the potential to become a digital innovation to strengthen mental health services and support HIV prevention efforts among adolescents.
Pemetaan Literatur Sistem Digital Pemantauan Anak: Menyusun Kerangka Kebutuhan untuk Platform E-Kesehatan Terintegrasi di Indonesia Erna Selviyanti; Gandu Eko Julianto Suyoso; Mudafiq Riyan Pratama; Muhammad Yunus
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 7 No 1 (2026): March
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v7i1.197

Abstract

Background: Child growth and development monitoring is a fundamental intervention in preventing stunting and developmental delays. Although various digital systems have been developed, fragmentation between physical growth and child development monitoring remains a major challenge. Objective: This study aims to map the research landscape of digital systems for child growth and development monitoring and identify gaps and the most frequently appearing system requirements in the literature. Method: A systematic mapping study was conducted on six data sources consisting of direct access and Publish or Perish searches, including Scopus, Scopus via PoP, PubMed, PubMed via PoP, IEEE Xplore, and Web of Science via PoP for the 2020-2025 period. A total of 16 research articles were analyzed using VOSviewer for bibliometric mapping and thematic analysis for system requirements identification. Results: The mapping revealed six research clusters with digital health positioned peripherally. Temporal analysis showed a shifting focus toward mental health integration, stunting prevention, and digital tool utilization. Three main gaps were identified: the peripheral position of digital health, separation between growth and development domains, and dominance of observational studies. The most dominant functional requirements were growth monitoring (12 articles) and developmental screening (11 articles), while usability (9 articles) was the main non-functional priority. Conclusion: Integration of growth and development monitoring in a single platform remains understudied. The resulting requirements list can serve as an initial reference for future integrated system development.
Sistem Deteksi Dini Diabetes Mellitus Berdasarkan Rekam Medis Menggunakan Algoritma K-Nearest Neighbor Arleni Aulia Yunitasari; Mudafiq Riyan Pratama; Muhammad Yunus; Gandu Eko Julianto Suyoso
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 7 No 1 (2026): March
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v7i1.204

Abstract

At RSD dr. Soebandi Jember, 51% of Diabetes Mellitus (DM) patients are diagnosed after complications occur, and DM is the third leading cause of death among non-communicable diseases, accounting for 13.6%. This situation indicates a high rate of delayed case identification. Delayed diagnosis significantly increases patient mortality and morbidity rates, emphasizing the urgent need for an effective, integrated early, and detection system. This study developed a web-based early detection system for DM using the K-Nearest Neighbor (K-NN) algorithm with the Waterfall development method, consisting of the stages of communication, planning, modeling, construction, and deployment. The data comprised from 342 inpatient medical records, and after preprocessing, 164 clean data were obtained with variables including age, gender, family history, blood pressure, random blood sugar, and body mass index. The data were split using stratified sampling (50:50), with K=5 value selected based on the best performance. Blackbox testing was conducted to ensure the system’s functionality, while performance testing compared the system’s classification results with the test data. The performance of the K-NN algorithm for DM detection was evaluated using a Confusion Matrix, resulting in an accuracy of 97.56%, precision of 100%, and recall of 95.83%, which were consistent with the results from the WEKA tool. This system is expected to serve as an early screening tool and support DM prevention efforts.
Sistem Deteksi Dini Diabetes Melitus Dengan Teknik Klasifikasi Algoritma C4.5 Berdasarkan Rekam Medis di RS Tk. III Baladhika Husada Jember Alviani Rodyatul Agustina; Mudafiq Riyan Pratama; Muhammad Yunus; Ervina Rachmawati
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 7 No 1 (2026): March
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v7i1.203

Abstract

Diabetes Mellitus (DM) is a chronic disease condition that occurs when the pancreas cannot produce insulin or when the body cannot use insulin effectively. At Baladhika Husada Jember Hospital, DM ranks among the top 10 diseases with the highest mortality rate of 6.99% in 2024. In efforts to prevent and control DM, a website-based early detection system was developed using the C4.5 algorithm classification technique with the Waterfall method. The research stages included creating C4.5 algorithm classification rules using RapidMiner tools, followed by development using the Waterfall method, which consists of the communication, planning, modeling, construction, and deployment stages. The classification rules were developed using preprocessed data from a total of 240 datasets, resulting in 172 clean datasets obtained from medical records at Baladhika Husada Jember Hospital. The training and testing data ratio was 50:50 using stratified sampling. Performance testing using the Confusion Matrix method yielded accuracy, precision, and recall values of 100% each, along with 8 classification rules that were subsequently implemented in the system. Based on the research results, random blood sugar is the most influential risk factor for DM, as it achieved the highest gain ratio. Recommendations for future researchers include increasing the amount of data and expanding the variety of data to help the system learn more complex patterns.
Evaluasi Keamaan Sistem Informasi pada Dinas Pendidikan dan Kebudayaan Kota Balikpapan Menggunakan Indeks KAMI 5.0 Rara Krisna Adi Susilo; Dwi Arief Prambudi
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 7 No 1 (2026): March
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v7i1.206

Abstract

The Balikpapan City Education and Culture Office is a regional government tasked with managing, developing, and advancing the fields of education and culture in accordance with Government Regulation Number 19 of 2005 concerning National Education Standards. Documents managed by the Balikpapan City Education and Culture Office include personal data of students and parents, personal data of teachers, and data from various schools in Balikpapan City. The security of these documents must be maintained to protect public privacy and comply with PDP Law Number 27 of 2022 concerning the protection of personal data. Based on the interview results, the Balikpapan City Education and Culture Office has never conducted an evaluation of information security either internally or externally through the National Cyber and Crypto Agency (BSSN). The use of the KAMI Index acts as an assessment tool that assesses every aspect of the KAMI Index 5.0 with the ISO/IEC 27001:2022 standard. At this research stage, an assessment of the SE Category, an assessment of the KAMI Index area, analysis and discussion of the results, and recommendations for improvement were carried out. From the evaluation results, the Electronic System Category value was obtained as 42 and the Evaluation Results showed the status of "Not Eligible" with a value of the level of completeness of information security of 264. There are 129 recommendations for improvement provided and are expected to help the Balikpapan City Education and Culture Office in identifying various threats and vulnerabilities that can affect information security in providing procedures and reducing the risks that have been identified.
Perbandingan Algoritma Decision Tree dan K-Nearest Neighbor untuk Klasifikasi Penyakit ISPA Marchell William Putra Pakpahan; Bayu Angga Wijaya; Marsaulina Lumbantoruan; Ambarsius Samosir; Mikhael Rafael
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 7 No 2 (2026): September (In Progress)
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v7i2.215

Abstract

Acute Respiratory Infection (ARI) is one of the most common respiratory diseases with diverse and overlapping clinical symptoms, making initial identification challenging and necessitating a systematic, data-driven classification approach. This study aims to compare the performance of the Decision Tree and K-Nearest Neighbor (KNN) algorithms in classifying ARI-related disease categories. The novelty of this research lies in the specific construction of ARI labels into five distinct categories from the Pediatric Respiratory Infections dataset, coupled with a rigorous feature selection process to handle mixed data types and address class imbalance using weighted evaluation metrics. The dataset consisted of 801 patient records with 91 initial attributes. The classification label was constructed from the Main diagnostic column and grouped into five categories: Asthma/Bronchospasm/Wheezing, Pneumonia/Pneumopathy, Bronchiolitis, Laryngeal/Upper Respiratory, and Other. After feature selection to remove noise and redundancy, 54 features were used, consisting of 24 numerical and 30 categorical features. The research stages included preprocessing, label construction, missing value handling, categorical encoding, KNN normalization, 80:20 train-test splitting, and model evaluation. The results show that Decision Tree achieved higher performance with 67.08% accuracy and 69.12% weighted F1-score, while KNN achieved 65.84% accuracy and 64.18% weighted F1-score. Thus, Decision Tree demonstrates superior performance and interpretability for this specific dataset.
Analisis Kesiapan Penerapan Rekam Medis Elektronik dengan Metode DOQ-IT di Puskesmas Kendit Situbondo Sabran Sabran; Nabila Agustina; Maya Weka Santi; Gamasiano Alfiansyah
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 7 No 2 (2026): September (In Progress)
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v7i2.209

Abstract

Kendit Public Health Center currently uses paper-based medical records and has only recently begun implementing electronic medical records (EMR) in several service areas. However, this implementation faces numerous challenges, including data duplication, file damage, and the accumulation of 9,424 physical records. This situation highlights the importance of accelerating the comprehensive implementation of Electronic Medical Records (EMR) to enhance the efficiency of patient data management. This study aims to analyze the readiness for EMR implementation using the DOQ-IT method. This descriptive research involved 53 respondents, with data collected through questionnaires. The results showed that organizational alignment readiness was in the “very ready” category with a score of 31.72 out of a maximum score range of 45. The subvariables included culture (mean: 3.56), leadership (mean: 3.53), and strategy (mean: 3.47) on a 1 – 4 scale. Meanwhile, organizational capacity readiness was in the “moderately ready” category with a score of 59.77 out of a maximum score range of 100. The subvariables included information management (mean: 3.11), clinical and administrative staff (mean: 3.07), training (mean: 3.42), workflow process (mean: 2.92), accountability (mean: 2.75), budgeting (mean: 3.12), patient involvement (mean: 2.58), IT management (mean: 3.06), and IT infrastructure (mean: 2.80) on a 1 – 4 scale. Improvements are needed in organizational capacity, particularly in patient involvement, accountability, and IT infrastructure.
Analisis Prediksi Permintaan Produk FMCG menggunakan Model LSTM dan DES Untuk Optimalisasi Operasional Gudang Distribusi Tanti Cahya Herdiyani; Taswanda Taryo; Kahfi Heryandi Suradiradja; Zafira Salsabilah
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 7 No 2 (2026): September (In Progress)
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v7i2.213

Abstract

The Fast-Moving Consumer Goods (FMCG) sector is characterized by rapid product turnover and short shelf lives, requiring effective inventory management. Companies such as PT Macrosentra Niagaboga face challenges in maintaining stock availability. Although the inventory system has been integrated, stock verification is still conducted manually, requiring adaptive management to minimize the risk of overstock and stockout. Therefore, this study aims to develop a demand forecasting model using the Long Short-Term Memory (LSTM) algorithm integrated with Discrete-Event Simulation (DES) to optimize inventory management. The study utilized historical shipment data from May 2025 to January 2026. Preprocessing included data cleansing, date validation, and aggregation into daily and weekly data. Forecasting results were subsequently used as inputs for the DES simulations to determine optimal inventory policies. The results demonstrated that weekly LSTM aggregation was more accurate and stable than daily aggregation, as evidenced by a reduction in WAPE from 49.9% to 16.94% for high-demand products. Furthermore, integration with DES reduced stock levels by more than 30% using a safety stock ratio of 0.7 without compromising service levels. Finally, the proposed model was implemented in a web-based dashboard serving as a decision support system for monitoring forecasting and inventory policy recommendations.
Sistem Sistem Informasi Akreditasi Online Multi-LAM untuk Manajemen Dokumen Program Studi Eko Wahyu Wibowo; M. Iman Wahyudi; Angga Kurnia Putra
BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Vol 7 No 2 (2026): September (In Progress)
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/bios.v7i2.214

Abstract

Study-program accreditation requires supporting evidence to be organised in a valid, current, and traceable manner. This need becomes more complex when study programs within one faculty are evaluated by different independent accreditation agencies, such as LAMSAMA and LAM INFOKOM. This study develops a web-based multi-accreditation-agency information system for managing accreditation documents at a Faculty of Science and Technology. The system was developed using the System Development Life Cycle, which consists of requirements analysis, design, coding, testing, and maintenance. The results show that the system supports three user roles, document mapping by study program, accreditation agency, and criteria, as well as upload, download, validation, revision, and monitoring functions. Black-box testing indicates that the main functional scenarios run as expected. The proposed system contributes an adaptive document management model that can be updated when accreditation criteria or agency schemes change.

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