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All Journal Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Jurnal Eksplora Informatika Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) JAREE (Journal on Advanced Research in Electrical Engineering) Journal of Medicine and Health Technology
Adhi Dharma Wibawa, Adhi Dharma
Departemen Teknik Komputer Institut Teknologi Sepuluh Nopember
Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Health Professions Immunology & microbiology Medicine & Pharmacology Neuroscience

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Evaluation of The Poedji Rochjati Score Card (PRSC) on Digital Platform @hamilku.id Based on The Delphi Method Fadli, Sonny; Wibawa, Adhi Dharma; Eljatin, Dwinka Syafira
Jurnal Eksplora Informatika Vol 14 No 1 (2024): Jurnal Eksplora Informatika
Publisher : Institut Teknologi dan Bisnis STIKOM Bali

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30864/eksplora.v14i1.1108

Abstract

The number of cases and deaths of mothers and babies in Indonesia is increasing, which is mediated by low-risk detection in early pregnancy, and a lack of knowledge resulting in the dissemination of pregnancy-related information tends to be poorly understood. As a solution to this problem, the purpose of this study was to analyze the effectiveness and usability of the Poedji Rochjati Score Card (PRSC) feature on the @hamilku.id Digital Platform based on the Delphi method. Qualitative research methods with technical observations were carried out online by obstetricians and gynecologists. The main focus of this research was usability testing involving 46 pregnant women who used the application and 9 randomly selected respondents. The assessment and evaluation were guided by the Delphi method, which involved two rounds of testing by six obstetricians and gynecologists. The results were descriptively analyzed. The findings showed that pregnant female respondents aged between 17 and 34 years had a higher education level, were dominated by people without jobs/housewives, were domiciled in Sidoarjo, had undergone antenatal care (ANC) ≤ 6 times, and had undergone ≥ 5 pregnancies. According to the PRS, 52.2% of pregnant women were classified as having high-risk pregnancies (HRPs). Based on the evaluation of the application from the usability aspect, 83.3% of the participants stated that the information was comprehensive and that the medical terminology was easy to understand. However, only half of them considered visualization in the form of images or animations to be very helpful in illustrating pregnancy risks. Delphi testing with obstetricians and gynecologists revealed that the digital PRSC features generated positive ratings, indicating that the tool is accurate, informative, easy to understand, and effective at improving the quality of health services. The second round showed an improvement in the quality and relevance of the digital PRSC features, with more diverse feedback from the respondents providing a broader perspective for future research and feature development. As a result, the digital PRSC feature can help individuals precisely and accurately identify pregnancy risks.
Leveraging Text-Mining Techniques On Electronic Medical Records to Analyze National Drug-insured Medication Use Wibawa, Adhi Dharma; Ramadhani, Prio Adi; Buntoro, Ghulam Asrofi; Hariadi, Ridho Rahman; Siswanto, Putri Alief; Sabilla, Shoffi Izza
Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Vol. 8, No. 2, May 2023
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/kinetik.v8i2.1695

Abstract

Processing electronic medical record (EMR) data has become a common practice among scientists for extracting valuable insights and studying diseases. Given the large volumes of text data in EMRs, efficient computerized text-mining techniques are necessary. As academics, we recognize that drug-used analysis from EMR data in Indonesia is currently limited. This study focuses on obtaining meaningful insights from EMR data to make positive recommendations for hospitals. The proposed method uses pattern-based Regular Expressions (regex) to extract drug names and a Levenshtein distance algorithm to check their compatibility. We developed the pattern based on analyzing Indonesia EMR data. The extracted drug names were compared to a list of selected drugs (National Drug-Insured/Fornas) that are required and must be provided at healthcare facilities in Indonesia. The Levenshtein distance threshold was set to two to decide whether the extracted drug names belonged to nationally drug-insured or not. Only about 11.09 – 16.11% of medications given by doctors are listed in the Fornas drug list. Between 2019 and 2021, there was an inaccuracy in the writing of prescriptions for Fornas drugs, with as many as 57.53% to 63.21% of drug names being written incorrectly. The results of this study indicate that the Levenshtein distance algorithm has promising potential for implementation in the Ministry of Health of Indonesia, with a precision rate of 97.07%.
Optimizing Diabetic Neuropathy Severity Classification Using Electromyography Signals Through Synthetic Oversampling Techniques Purnawan, I Ketut Adi; Wibawa, Adhi Dharma; Kurniawati, Arik; Purnomo, Mauridhi Hery
Jurnal Nasional Pendidikan Teknik Informatika : JANAPATI Vol. 13 No. 3 (2024)
Publisher : Prodi Pendidikan Teknik Informatika Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/janapati.v13i3.85675

Abstract

Electromyography signals are electrical signals generated by muscle activity and are very useful for analyzing the health conditions of muscles and nerves. Data imbalance is a prevalent issue in EMG signal data, especially when addressing patients with varied health conditions and restricted data availability. A major difficulty for machine learning models is class imbalance in datasets, which frequently leads to biased predictions favoring the dominant class and neglecting the minority classes. The data augmentation method employs the Synthetic Minority Over Sampling Technique (SMOTE) and Random Over Sampling (ROS) to address data imbalances and enhance the performance of classification models for underrepresented classes. This study employs an oversampling technique to enhance the efficacy of the XG Boost model. SMOTE exhibits better efficacy relative to competing methods; the application of appropriate oversampling techniques allows models to integrate patterns from both majority and often neglected minority data.
Diagnostic and Therapeutic Alternative Medicine in Healthcare Practice: A Comprehensive Review Wibawa, Adhi Dharma; Risaldi, Randi Achtiar; Kartowirejo, Faiz Arrafi; Suryani, Siti Dwi; Kendenan, Valentino; Ahmad, Naufal; Sianipar, Cintya Melati; Zuhrotul Laili, Nazwa
Journal of Medicine and Health Technology Vol. 2 No. 1 (2025)
Publisher : Direktorat Riset dan Pengabdian Kepada Masyarakat, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j30466865.v2i1.2338

Abstract

Treatment that combines local wisdom and modern knowledge is increasingly developing. This treatment is known as alternative medicine, which differs from conventional medicine because it is intended for therapy or diagnosis and has a close relationship with cultural practices such as community spirituality. This review aims to comprehensively understand alternative medicine, including its background, reasons for its use and debates about its effectiveness and safety. In addition, this review aims to improve readers' understanding of alternative medicine so that they can make better decisions in choosing the right treatment. This review compares two types of alternative medicine, diagnostic and therapeutic medicine. Diagnostic alternative medicine focuses on identifying imbalances in the body that are believed to cause disease. In contrast, therapeutic alternative medicine is based on traditional beliefs, is empirical, or has been used for centuries. The debate about the credibility of these two alternative medicine methods is ongoing, and strong scientific evidence is needed to support their effectiveness and safety. In addition, it is important to discuss the regulation and standardization of practice for practitioners of these alternative medicines. This review emphasizes the importance of consulting a specialist before starting any alternative treatment to ensure its safety and suitability for the patient's health condition. This review helps to increase readers' understanding of alternative medicine, so they can make better decisions in choosing the right treatment.
A Stress Level Monitoring System for Rescue Teams During Search and Rescue Operations Based on Electroencephalography hariyadi, dedy; wibawa, adhi dharma; wirawan, wirawan
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 9, No 2 (2025): July
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v9i2.437

Abstract

Search and Rescue (SAR) officers work in high-risk conditions that require physical and mental resilience. Prolonged stress can affect the performance and success of SAR operations. This study evaluates the effectiveness of Electroencephalography (EEG) coherence analysis as a method for monitoring stress in SAR personnel. Using the OpenBCI EEG device and electrodes in the F3 and F4 areas, the brain activity of SAR personnel was recorded in two conditions, office activity (baseline) and rescue operations (SAR condition). The data collection for this research involved the same participants in both baseline and SAR operation conditions, resulting in 30 raw EEG data for further analysis. Data collection on operational conditions was carried out while the rescue officers conducted a search and rescue operation for a capsized boat in the Bengawan Solo River, Ngadirejo Village, Tuban Regency. Data analyzed based on coherence values obtained through the Power Spectral Density (PSD) features of alpha, beta, and gamma sub-band to detect changes related to stress levels. The results showed an increase in coherence in the alpha sub-band by 85.5%, beta sub-band by 92.9%, and gamma sub-band by up to 94.9% during moderate stress conditions, reflecting increased attention, alertness, and intensive information processing required in emergency situations. These findings indicate that EEG coherence analysis can be an effective tool for monitoring stress in SAR personnel in real-time.
Co-Authors Abdurahman Abdurrahman Ahmad, Naufal Arik Kurniawati Dwinka Syafira Eljatin Evi Septiana Pane, Evi Septiana Fadli, Sonny Fitriani, Fatimah Nur Ghulam Asrofi Buntoro Haykal, Muhammad Nazhif Hedianto, Tri Hidayah, Rizka Nurul Imam Susilo Indriani, Ratri Dwi Indriastuti, Endah Karimah, Rumman Kartowirejo, Faiz Arrafi Kendenan, Valentino Mauridhi Hery Purnomo Njoto, Edwin Nugroho Pamungkas, Yuri Parlindungan, Putra Gelar Purnawan, I Ketut Adi Putra, Gumilar Fardhani Ami Putri Alief Siswanto Putri, Atina Irani Wira Ramadhani, Prio Adi Rangkuti, Rahmah Yasinta Ridho Rahman Hariadi Ridhoi, Ahmad Risaldi, Randi Achtiar Sabilla, Shoffi Izza Sakina Sianipar, Cintya Melati Suryani, Siti Dwi Syulthoni, Zain Budi Wirawan Wirawan Zuhrotul Laili, Nazwa