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Jurnal Informatika Medis (J-INFORMED)
Published by Universitas Muhammadiyah Muara Bungo
ISSN : -     EISSN : 29874661     DOI : https://doi.org/10.52060/im.v1i2
Core Subject : Health, Science,
Computer Science & IT Health Professions Library & Information Science Nursing Public Health Veterinary
Jurnal Informatika Medis sebagai menerima artikel ilmiah hasil penelitian, pemikiran dan kajian analisis-kritis mengenai penelitian di bidang penerapan TIK dalam layanan kedokteran dan kesehatan serta Pengembangan teknologi medis. Jurnal Informatika Medis memuat artikel yang relevan dengan area informatika kedokteran/kesehatan yang meliputi namun tidak terbatas pada topik : Pengolahan citra medis, Sistem informasi kedokteran/kesehatan, Bioinformatika kedokteran, Informatika kesehatan public, informatika untuk edukasi public, e-health, m-health, telemedicine, health care data mining, evaluasi dan pemanfaatan IT dibidang kedokteran/kesehatan serta topik lain terkait riset kedokteran/informasi di era informasi.
Arjuna Subject : Profesi Kesehatan - Teknologi Laboratorium Medis
Articles 44 Documents
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PENGEMBANGAN SISTEM INFORMASI BERBASIS ANDROID “VITA NUTRI HEALTH” PADA REMAJA OVERWEIGHT Chyntia Anggraini Putri
Jurnal Informatika Medis Vol. 3 No. 2 (2025): Jurnal Informatika Medis (J-INFORMED)
Publisher : Program Studi Informatika Medis Universitas Muhammadiyah Muara Bungo

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The current rapid development of technology, particularly in the field of information technology, aims to assist human activities. This is evident from the use of computers, mobile applications, various supporting applications, and the internet as a bridge for information exchange. According to the WHO, in 2022, more than 390 million children and adolescents aged 5-19 were overweight. The objective of this research was to develop the Android-based information system VitaNutriHealth as an educational tool for adolescents at high school in Malang. The Vita Nutri Health application was proven to significantly influence students' knowledge, attitudes, and eating behaviors. This study used a qualitative and quantitative approach. Based on statistical tests, the data on students' knowledge, attitudes, and food consumption behavior showed a significant change (p-value < 0.05) after the intervention with this application. Overall, the application was proven to be an effective nutritional education tool for overweight adolescents.
MODEL DEEP LEARNING UNTUK DETEKSI PNEUMONIA : STUDI EKSPERIMEN MENGGUNAKAN (CONVOLUTIONAL NEURAL NETWORK) ARSITEKTUR VGG16 Kurniawan, Ade Agung; Dwi Baharna, Haryan; Riko Muhammad Suri
Jurnal Informatika Medis Vol. 3 No. 2 (2025): Jurnal Informatika Medis (J-INFORMED)
Publisher : Program Studi Informatika Medis Universitas Muhammadiyah Muara Bungo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52060/im.v3i2.3847

Abstract

Pneumonia merupakan salah satu penyebab utama kematian pada anak usia di bawah lima tahun, terutama di negara dengan pendapatan rendah dan menengah. Keterbatasan tenaga kesehatan menyebabkan proses diagnosis sering terlambat, sehingga penanganan penyakit ini menjadi semakin sulit. Penelitian ini mengusulkan penerapan Convolutional Neural Network (CNN) dengan arsitektur VGG16 untuk melakukan deteksi pneumonia secara otomatis melalui citra rontgen dada. Metode ini dipilih karena kemampuannya dalam mengekstraksi fitur penting dari citra dengan efisien. Dataset yang digunakan berisi citra rontgen dada dengan dua kategori, yakni pneumonia dan normal. Model VGG16 diterapkan menggunakan teknik transfer learning guna mengatasi jumlah data pelatihan yang terbatas. Hasil pengujian menunjukkan bahwa model mencapai akurasi 96,42%, precision 96,36%, dan F1-Score 97,58%. Dibandingkan dengan penelitian terdahulu, performa model ini mengalami peningkatan yang signifikan, baik dari sisi akurasi maupun keseimbangan antara presisi dan recall. Selain itu, pendekatan ini mampu meminimalkan overfitting yang sering terjadi pada model lain, sehingga lebih stabil dan layak diterapkan dalam praktik. Dengan demikian, model VGG16 yang dikembangkan berpotensi menjadi solusi yang efektif untuk membantu tenaga medis dalam mendeteksi pneumonia secara cepat dan akurat, serta dapat diperluas untuk identifikasi penyakit paru-paru lainnya.
EVALUASI KINERJA DOSEN UNTUK PENENTUAN DOSEN TELADAN MENGGUNAKAN METODE MULTI FACTOR EVALUATION PROCESS (MFEP) Zulmi; Afianto, Dafit
Jurnal Informatika Medis Vol. 3 No. 2 (2025): Jurnal Informatika Medis (J-INFORMED)
Publisher : Program Studi Informatika Medis Universitas Muhammadiyah Muara Bungo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52060/im.v3.i2.3920

Abstract

This study aims to propose a lecturer performance evaluation model based on a Decision Support System using the Multi Factor Evaluation Process (MFEP) method, tailored to the Tri Dharma of Higher Education framework in regional private universities. Unlike conventional evaluation approaches that tend to be subjective, the proposed model integrates systematic criterion weighting and multi-criteria assessment to enhance objectivity and decision consistency. The evaluation criteria include teaching, research, community service, scientific publications, and discipline. The research data were collected from 13 lecturers of the Primary School Teacher Education Study Program over one academic year. The results indicate that the MFEP method is able to generate a measurable and transparent ranking of lecturer performance. This study provides a practical contribution in the form of a contextual and applicable lecturer performance evaluation model to support institutional decision-making in regional private higher education institutions.
PENGEMBANGAN SISTEM INFORMASI BERBASIS ANDROID “VITA NUTRI HEALTH” PADA REMAJA OVERWEIGHT Chyntia Anggraini Putri
Jurnal Informatika Medis Vol. 3 No. 2 (2025): Jurnal Informatika Medis (J-INFORMED)
Publisher : Program Studi Informatika Medis Universitas Muhammadiyah Muara Bungo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52060/im.v3i2.3619

Abstract

The current rapid development of technology, particularly in the field of information technology, aims to assist human activities. This is evident from the use of computers, mobile applications, various supporting applications, and the internet as a bridge for information exchange. According to the WHO, in 2022, more than 390 million children and adolescents aged 5-19 were overweight. The objective of this research was to develop the Android-based information system VitaNutriHealth as an educational tool for adolescents at high school in Malang. The Vita Nutri Health application was proven to significantly influence students' knowledge, attitudes, and eating behaviors. This study used a qualitative and quantitative approach. Based on statistical tests, the data on students' knowledge, attitudes, and food consumption behavior showed a significant change (p-value < 0.05) after the intervention with this application. Overall, the application was proven to be an effective nutritional education tool for overweight adolescents.
GAMBARAN PELAKSANAAN PENEMUAN KASUS DAN PENGOBATAN TUBERKULOSIS (TBC) DI SESI P2PM DI DINAS KESEHATAN KABUPATEN BUNGO Yessy Fitriani; Amelia Pebriani
Jurnal Informatika Medis Vol. 3 No. 2 (2025): Jurnal Informatika Medis (J-INFORMED)
Publisher : Program Studi Informatika Medis Universitas Muhammadiyah Muara Bungo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52060/im.v3i2.4052

Abstract

Tuberkulosis (TBC) merupakan penyakit menular yang masih menjadi masalah kesehatan masyarakat di Indonesia. Upaya pengendalian TBC dilakukan melalui program penemuan kasus dan pengobatan yang terintegrasi di fasilitas kesehatan. Penelitian ini bertujuan untuk menggambarkan pelaksanaan penemuan kasus dan pengobatan TBC pada bidang Pencegahan dan Pengendalian Penyakit Menular (P2PM) di Dinas Kesehatan Kabupaten Bungo. Metode yang digunakan adalah pendekatan deskriptif melalui kegiatan observasi, dokumentasi, dan keterlibatan langsung selama pelaksanaan Praktik Kerja Lapangan (PKL) yang berlangsung dari September hingga Desember 2025. Hasil kegiatan menunjukkan bahwa program penemuan kasus dilakukan melalui skrining suspek, pemeriksaan laboratorium seperti pemeriksaan mikroskopis dan Tes Cepat Molekuler (TCM), serta pencatatan dan pelaporan kasus melalui sistem surveilans. Pengobatan pasien TBC dilakukan dengan strategi DOTS (Directly Observed Treatment Short-course) yang terdiri dari fase intensif dan fase lanjutan. Namun, masih ditemukan beberapa kendala seperti keterbatasan sarana laboratorium, kurangnya koordinasi data antar fasilitas kesehatan, serta kasus pasien Lost to Follow Up (LTFU). Oleh karena itu diperlukan peningkatan koordinasi lintas sektor, penguatan sistem informasi kesehatan, serta peningkatan edukasi masyarakat untuk mendukung keberhasilan program eliminasi TBC.
SISTEM PENCATATAN RUJUKAN PUSKESMAS DALAM MENINGKATKAN EFISIENSI PELAYANAN KESEHATAN DI DINAS KESEHATAN  KABUPATEN BUNGO TAHUN 2025 Febri Ramanda; Milawati
Jurnal Informatika Medis Vol. 3 No. 2 (2025): Jurnal Informatika Medis (J-INFORMED)
Publisher : Program Studi Informatika Medis Universitas Muhammadiyah Muara Bungo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52060/im.v3i2.4055

Abstract

The referral system is an important component in ensuring effective and efficient health services. In Indonesia, the government has implemented the Integrated Referral Information System (SISRUTE) to facilitate communication between primary health facilities and referral hospitals. This study aims to analyze the referral recording system implemented in community health centers (Puskesmas) and its role in improving health service efficiency at the Bungo District Health Office. The research method used was descriptive analysis through observation, document analysis, and interviews with health office staff responsible for referral reporting. Data were collected from electronic referral records through SISRUTE and manual reports from health centers. The results show that the implementation of SISRUTE has improved the documentation and monitoring of patient referrals. However, several challenges were identified, including limited infrastructure, inadequate internet connectivity, and insufficient technical skills among health workers. The study also found discrepancies between manual and digital referral records in some health centers. Strengthening digital infrastructure, providing regular training for health workers, and developing standardized operational procedures are recommended to optimize the referral recording system. Overall, an integrated referral information system can significantly support the efficiency and coordination of healthcare services.
FORENSIC ANALYSIS OF TROJAN BACKDOOR (GACOR) ATTACKS ON PRIVATE CLOUD ENVIRONMENTS USING KUAD METHOD Hero Wintolo; Mohammad Faiq Badruz Zaman; Haruno Sajati; Imam Riadi; Anton Yudhana; Tri Rochmadi; Puspa Ira Dewi Candra Wulan
Jurnal Informatika Medis (J-INFORMED) Vol. 4 No. 1 (2026): Jurnal Informatika Medis (J-INFORMED)
Publisher : LPPM Universitas Muhammadiyah Muara Bungo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52060/im.v4i1.4196

Abstract

This research examines the impact of a Trojan Backdoor Attack, referred to as a Gacor attack, on the security and service integrity of a private cloud environment based on OwnCloud. The experimental environment was deployed ubuntu server 22.04 using OwnCloud version 10.15.2 and supported by a Mikrotik CCR1016-12G network device. Application level and network level activities were monitored through Apache web server logs and Snort Intrusion Detection System (IDS) version 2.9.15.1, respectively. The investigation adopts the knowledge Understanding assessment defence (KUAD) framework, which structures the analysis into initiation, acquisition, execution, mitigation, and digital evidence disposition stages. The attack scenario focuses on exploiting a file upload vulnerability in the OwnCloud service to deploy and execute a malicious PHP-based Trojan Backdoor. The results show that the Gacor attack demonstrates highly repetitive and centralized behaviour, originate from a limited number of highly active IP addresses. This behaviour exploits weaknesses in application security configuration and results in system takeover and service defacement. Correlation between log analysis and IDS alerts confirms 10 distinct attack events and reveals a structured intrusion pattern rather than random probing activity. The data visualization reveals a structured and centralized attack pattern, resulting in 100% defacement of the OwnCloud index page, which highlights the severe security risk faced by private cloud environments that lack a adequate file upload protection mechanisms. The findings demonstrate that the application of the KUAD method, when combined with log analysis and intrusion detection systems (IDS) is effective in identifying, analyzing, and systematically documenting Trojan Backdoor attacks in private cloud computing environments.
STUDI PERBANDINGAN ALGORITMA MACHINE LEARNING : SUPPORT VECTOR MACHINE, DECISION TREE DAN RANDOM FOREST DALAM KLASIFIKASI PENYAKIT DIABETES Muhammad Shodiq; Agus Priyono; Neni Purwati
Jurnal Informatika Medis (J-INFORMED) Vol. 4 No. 1 (2026): Jurnal Informatika Medis (J-INFORMED)
Publisher : LPPM Universitas Muhammadiyah Muara Bungo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52060/im.v4i1.4221

Abstract

Hyperglycemia, or elevated blood glucose levels, is a primary indicator of diabetes mellitus, a chronic metabolic disorder whose prevalence continues to rise globally according to reports from the World Health Organization (WHO). Early detection of diabetes risk is crucial for preventing severe long-term complications. This study aims to evaluate and compare the performance of three machine learning algorithms Support Vector Machine (SVM), Decision Tree, and Random Forest in classifying diabetes based on health indicators and lifestyle patterns. The dataset used was obtained from Kaggle, with preprocessing stages including handling missing values and normalization. Model performance was assessed using accuracy, precision, recall, and F1-score. The experimental results show that the SVM algorithm achieved the highest accuracy at 74.89%, followed by Decision Tree with 73.39%, and Random Forest with 72.41%. This research is expected to serve as a reference for developing early medical screening systems to intelligently and accurately detect diabetes risk.
ANALISIS KANDUNGAN PROTEIN, ZAT BESI DAN DAYA TERIMA BAKSO IKAN GABUS DENGAN PENAMBAHAN DAUN KELOR SEBAGAI ALTERNATIF MAKANAN TAMBAHAN IBU HAMIL KEK Dwi Ika Rahmayanti; Suriani Rauf; Mustamin
Jurnal Informatika Medis (J-INFORMED) Vol. 4 No. 1 (2026): Jurnal Informatika Medis (J-INFORMED)
Publisher : LPPM Universitas Muhammadiyah Muara Bungo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52060/im.v4i1.4388

Abstract

Kekurangan Energi Kronis (KEK) pada ibu hamil merupakan masalah gizi yang dapat meningkatkan risiko anemia, bayi berat lahir rendah (BBLR), dan stunting. Salah satu upaya untuk membantu memenuhi kebutuhan gizi ibu hamil adalah melalui pengembangan makanan tambahan berbasis pangan lokal. Penelitian ini bertujuan untuk menganalisis daya terima serta kandungan protein dan zat besi bakso ikan gabus dengan penambahan daun kelor sebagai alternatif makanan tambahan bagi ibu hamil KEK. Penelitian menggunakan desain pra-eksperimental dengan pendekatan One Shot Case Study pada tiga formulasi bakso ikan gabus dengan penambahan daun kelor. Uji daya terima dilakukan terhadap 30 panelis semi terlatih, sedangkan kandungan protein dan zat besi dianalisis di laboratorium. Hasil penelitian menunjukkan bahwa terdapat perbedaan yang signifikan pada aspek rasa dan tekstur (p<0,05), namun tidak terdapat perbedaan yang signifikan pada aspek warna dan aroma (p>0,05). Formulasi terbaik adalah F3 dengan kandungan protein sebesar 8.77% dan zat besi sebesar 13.44 µg/g. Disimpulkan bahwa bakso ikan gabus dengan penambahan daun kelor memiliki daya terima yang baik serta berpotensi menjadi alternatif makanan tambahan berbasis pangan lokal untuk membantu memenuhi kebutuhan protein dan zat besi ibu hamil Kekurangan Energi Kronik (KEK).
SMART-RME AI: SISTEM REKAM MEDIS ELEKTRONIK CERDAS BERBASIS ARTIFICIAL INTELLIGENCE UNTUK OPTIMALISASI OPERASIONAL KLINIK MANDIRI Ahmad Risman; Sidik Praptomo; Hendry Wibowo; Dafit Afianto
Jurnal Informatika Medis (J-INFORMED) Vol. 4 No. 1 (2026): Jurnal Informatika Medis (J-INFORMED)
Publisher : LPPM Universitas Muhammadiyah Muara Bungo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52060/im.v4i1.4392

Abstract

Digital transformation in the healthcare sector, particularly within independent clinics, still faces various obstacles such as unintegrated medical record keeping, inefficient administrative processes, and limitations in clinical and operational data analysis. These conditions lead to poor service quality, potential medical errors, and suboptimal managerial decision-making. Therefore, an Electronic Medical Record (EMR) system is required that is not only digital but also smart and adaptive to the needs of independent clinics. This study aims to develop Smart-RME AI, an artificial intelligence-based smart electronic medical record system capable of integrating medical and operational data in real-time, supporting clinic service efficiency, and assisting clinical and managerial decision-making. This system is expected to improve operational effectiveness, medical recording accuracy, and the quality of healthcare services in independent clinics. The research method used is Design Science Research (DSR), which includes the stages of problem identification, system requirements formulation, design and development of the Smart-RME AI artifact, as well as system evaluation through functional and user feasibility testing. Artificial Intelligence implementation is applied for patient data analysis, visit patterns, and decision support recommendations based on historical data. The targeted outputs of this research include: (1) a Smart-RME AI system prototype ready for implementation in independent clinics, (2) a scientific article publication in a SINTA 3 accredited national journal, and (3) Intellectual Property Rights (IPR) in the form of a copyright for the Smart-RME AI software. This research is expected to make a tangible contribution to the development of health information systems and accelerate the digital transformation of independent clinic services.

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