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All Journal Journal of Information Technology and Computer Science (JOINTECS) MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer J-Dinamika: Jurnal Pengabdian Kepada Masyarakat ARTERI : Jurnal Ilmu Kesehatan J-REMI : Jurnal Rekam Medik dan Informasi Kesehatan Journal of Community Development BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer Jurnal Rekam Medik & Manajemen Informasi Kesehatan (RAMMIK) PEKAT : Jurnal Pengabdian Kepada Masyarakat DIANKES : Jurnal Pengabdian Teknologi Informasi dan Kesehatan Health & Medical Sciences JMMR (Jurnal Medicoeticolegal dan Manajemen Rumah Sakit) International Journal of Healthcare and Information Technology Manajemen Pelayanan Kesehatan
Mudafiq Riyan Pratama
Politeknik Negeri Jember
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Veterinary Other

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Perancangan dan Pembuatan Sistem Informasi KLPCM di Rumah Sakit Citra Husada Jember Mohammad Maulana Rifki Fadilah; Muhammad Yunus; Mudafiq Riyan Pratama; Demiawan Rachmatta Putro Mudiono
Jurnal Rekam Medik & Manajemen Informasi Kesehatan Vol. 4 No. 1 (2025): April
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/rmik.v4i1.1920

Abstract

Incomplete filling of medical records (KLPCM) is an indicator of the quality of nursing care. Citra Husada Hospital experienced an 83.5% medical record incompleteness rate in the fourth trimester of 2022, with the highest form of incompleteness occurring in the pre-surgical assessment at 59.68%. Furthermore, the KLPCM review process still relies on Excel, which presents several drawbacks, such as non-specific columns, a lack of user-friendliness, and the need for high precision due to small input fields. As a result, the KLPCM review process is time-consuming and prone to input errors. Based on these issues, a KLPCM information system is needed at Citra Husada Hospital in Jember. The system development method used is the Prototype method, with data collection techniques including interviews, observation, and documentation. The system is web-based, developed using the PHP programming language with the Laravel framework and a MySQL database. The system's features include user management, doctor management, form and form content management, patient management, KLPCM medical record analysis, reports, and incompleteness notifications. The system testing results, conducted using black box testing, showed that all functionalities work properly.
Analisis Implementasi SIMRS Registrasi Rawat Jalan dan UGD Metode HOT-FIT di RSU Penyangga Perbatasan Betun Benedicta Cherlyn Pera; Maya Weka Santi; Atma Deharja; Mudafiq Riyan Pratama
Jurnal Rekam Medik & Manajemen Informasi Kesehatan Vol. 4 No. 2 (2025): Oktober
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/rmik.v4i2.1921

Abstract

RSUPP Betun in Malaka Regency began implementing the Hospital Management Information System (HMIS) in June 2021 to support outpatient and emergency department (ED) registration. A preliminary study identified several issues, including a lack of staff training, technical disruptions with hardware and software, and network instability. This study aims to analyze the implementation of HMIS in the Outpatient Registration and ED units at RSUPP Betun using the HOT-FIT method. The research is qualitative, using interviews, observations, and documentation for data collection. The study's informants included seven individuals: the head of the medical records department, five registration staff, and one IT staff member. The results indicated that training improved user knowledge, but additional features, such as an alert system, are still required. Organizational support, funding, and inter-unit communication had a positive impact. However, the technological aspect revealed the need for better technical guidelines and higher-quality information. IT services were responsive, but the limited human resources hindered HMIS maintenance. Overall, HMIS has not yet fully improved service effectiveness due to suboptimal data integration. Recommendations include regular training, technical guidelines, a helpdesk feature, automatic logout, and SIMRS infrastructure updates.
Perancangan dan Implementasi Sistem Informasi Rekam Medis Elektronik Rawat Jalan Berbasis Web Di Puskesmas Umbulsari Jember Muhammad Misbahul Muttaqiin; Mudafiq Riyan Pratama; Muhammad Yunus; Dony Setiawan Hendyca Putra
Jurnal Rekam Medik & Manajemen Informasi Kesehatan Vol. 4 No. 2 (2025): Oktober
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/rmik.v4i2.1922

Abstract

The medical record at Umbulsari Jember Healthcare are still conducted manually leading to incomplete coding processes for patient diagnoses, with the completeness percentage falling below 100%, and the time required to provide medical records exceeding 10 minutes. This research aims to design and develop an electronic outpatient medical record system for Puskesmas Umbulsari Jember based on a web platform. Data collection was carried out through observation, interviews, documentation, and brainstorming. The system development method used is the prototype method, which includes the stages of requirement identification, prototype development, adjustment to user preferences, system development, and further adjustments. The first stage involves problem analysis, revealing that medical records are still handled manually. The next stage is prototype development, including the creation of Flowcharts, Data Flow Diagrams (DFD), Entity Relationship Diagrams (ERD), and interface designs. The system development process begins with gathering tools such as software, the Bootstrap 4 CSS Framework, the CodeIgniter Framework, and Visual Studio Code, followed by the system design phase. Once the system is complete, testing is conducted using the Black Box Testing approach, which shows that all system functions operate correctly
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 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.
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.
Analisis Klasifikasi Stadium Kanker Payudara Menggunakan Algoritma Naïve Bayes Berdasarkan Data Rekam Medis Mudafiq Riyan Pratama; Sefia Ayu Maharani; Mochammad Choirur Roziqin; Dony Setiawan Hendyca 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.v7i2.243

Abstract

Breast cancer is one of the leading causes of cancer-related mortality among women, highlighting the need for faster and more accurate approaches to support disease staging. The utilisation of electronic medical records through data mining techniques provides an alternative approach for breast cancer stage classification. This study aimed to analyse breast cancer stage classification using the Naïve Bayes algorithm based on electronic medical record data from patients at Baladhika Husada Level III Hospital, Jember. A quantitative approach was employed using secondary data consisting of 476 breast cancer medical records selected from a total of 1,082 records. The research stages included data selection, data cleaning, categorical encoding, model development using the Naïve Bayes algorithm, and model evaluation using a Confusion Matrix based on accuracy, precision, and recall. Model performance was evaluated using nine training-testing split scenarios ranging from 10:90 to 90:10. The experimental results showed that the 90:10 split scenario achieved the best performance, with an accuracy of 87.50%, precision of 86.36%, and recall of 86.36%. These findings indicate that the Naïve Bayes algorithm is capable of classifying breast cancer stages effectively based on patients' clinical characteristics recorded in electronic medical records. The proposed approach demonstrates the potential of integrating electronic medical records and the Naïve Bayes algorithm to support the development of clinical decision support systems for breast cancer stage classification.
Co-Authors Abdul Fatahillah Adhe Pandhu Dwi Prayogha Afrizal Himawan Alfianah, Adinda Bunga Alfiansyah, Gamasiano Alviani Rodyatul Agustina Alviyan Mahendra Amaliyah, Hikmah Andri Permana Wicaksono Angga Rahagiyanto Anisa Istiqomah Arleni Aulia Yunitasari Atma Deharja Bakhtiyar Hadi Prakoso Benedicta Cherlyn Pera Candra Irawan Dara Ayu Sadiyanti Rukmana Demiawan Rachmatta Putro Mudiono Dita Tinsi Riani dony setiawan hendyca putra Erna Selviyanti Faiz Robbani Faizatun Nikmah Firman Shalihin Gamasiano Alfiansyah Gandu Eko Julianto Suyoso Iqbal Ramadhan Suryawiyanto Iqbal Rhamadhan Suryawiyanto Irene Ratri Andia Sasmita Kartika, Ria Chandra Maya Weka Santi Mochammad Choirur Roziqin Mochammad Choirur Roziqin Mohammad Maulana Rifki Fadilah Mubarot Isa Muhammad Misbahul Muttaqiin Muhammad Yunus Muhammad Yunus Nindasari Okta Imelda Niyalatul Muna Novita Nuraini Nur Fadilatul Fitriyah Pramudya Rizkika Triwibowo Rachmawati, Ervina Ria Chandra Kartika Rossalina Adi Wijayanti Roziqin, Muhammad Choirur Sasmita, Irene Ratri Andia Sefia Ayu Maharani Selvia Juwita Swari Sulthan Muhammad Fauzan Laksono Suparmin Suparmin Suryana, Arinda Lironika Sustin Farlinda Swari, Selvia Juwita Veronika Vestine Vestine, Veronika