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All Journal Jurnal Manajemen Informasi Kesehatan Indonesia (JMIKI) J-REMI : Jurnal Rekam Medik dan Informasi Kesehatan Journal of Community Development BIOS : Jurnal Teknologi Informasi dan Rekayasa Komputer PEKAT : Jurnal Pengabdian Kepada Masyarakat International Journal of Health and Information System (IJHIS) International Journal of Healthcare and Information Technology
Rahagiyanto, Angga
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Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Environmental Science Health Professions Library & Information Science Mathematics Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Implementasi Sleepiness EWS Pada TRC BPBD Jember Sebagai Usaha Pengurangan Risiko Kecelakaan Kerja Prakoso, Bakhtiyar Hadi; Suyoso, Gandu Eko Julianto; Vestine, Veronika; Hartanto, Sugeng; Rahagiyanto, Angga
Journal of Community Development Vol. 5 No. 1 (2024): August
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/comdev.v5i1.236

Abstract

The Quick Response Team (TRC) of BPBD Jember plays an important role in disaster management. Among their emergency response activities are the mobilization of personnel for victim assistance and the distribution of aid to disaster victims. The nature of TRC's work demands both physical and mental effort. This poses a risk of work fatigue, one manifestation of which is microsleep, which can lead to traffic accidents as experienced by the TRC in 2019. The objective of this community service activity is to implement artificial intelligence that can monitor driver activity to reduce the risk of traffic accidents. The method of this service activity involves the installation of a sleepiness early warning system (EWS) in TRC BPBD Jember vehicles. The device is mounted on the dashboard, facing the driver, and powered by a 12-volt car battery. Based on interviews, the implementation of the sleepiness EWS in the operational vehicles of TRC BPBD Jember has been able to enhance driving safety by providing warnings to drivers when they begin to lose concentration, whether due to fatigue or distractions. Although there were challenges in implementing the device, such as slow response time and limited detection range, the community service team overcame these issues by recalibrating the device's response time and selecting drivers with similar anthropometric measurements to avoid the need for frequent adjustments when changing drivers.
Analisis Prediksi Kebutuhan Kapasitas Media Penyimpanan RME dengan Metode Least Square RSUPN Dr. Cipto Mangunkusumo Jakarta Wulandari, Savira Puteri; Rahagiyanto, Angga; Nuraini, Novita
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.v5i2.133

Abstract

The implementation of electronic medical record services is supported by PMK RI Number 24 of 2022, Article 3, Paragraph 1, which mandates that every health service facility must organize Electronic Medical Records (EMR). Therefore, hospitals need to transition from manual to electronic records. One necessary step is determining the storage capacity needed for the server. Additionally, according to Article 39, EMRs must be stored for 25 years, requiring a prediction of storage needs over that period. This study discusses predicting the storage capacity needs for EMRs using the Least Square method, which analyzes time series data trends. Hospital data shows 130,712 medical records with a size of 261,424 MB from September 2022 to March 2023. The predicted storage needs from April to December 2023 are 781,490 MB, and for the next 25 years (until 2048) is 8,974,669 MB or 9 TB. The accuracy of the prediction, tested using MAPE, is 6.34%, which is considered very good. RSUP Nasional Dr. Cipto Mangunkusumo has provided 6 TB of server storage and 71 TB of NAS as backup. With 80 GB used per month as of March 2023, the hospital is advised to provide storage according to the prediction. Additionally, the maximum upload size in the HIS needs to be increased beyond 2 MB per medical record to maximize scanning quality and efficiency
Implementation of Risk Factor Detection System Using k-NN Method to Reduce Maternal Mortality Rate at Sumbersari Primary Health Centre Prakoso, Bakhtiyar Hadi; Yunus, Muhammad; Rahagiyanto, Angga; Vestine, Veronika; Suyoso, Gandu Eko Julianto; Deharja, Atma
International Journal of Health and Information System Vol. 2 No. 3 (2025): January
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/ijhis.v2i3.49

Abstract

The Maternal Mortality Rate has become a major issue for the Indonesian government as it can be used to measure the reproductive health level of a country. In 2023, the maternal mortality rate in Jember Regency was recorded at 150 per 100,000 live births. Sumbersari Primary Heath Centre is one of Primary Health in Jember, located in the city. Still had cases of maternal mortality, with two recorded cases The Jember Regency government has implemented various interventions, including the implementation of integrated antenatal care (ANC), the preparation of emergency obstetric and neonatal management guidelines, and collaboration with educational institutions to support pregnant women, strengthen maternal and neonatal referrals, and enhance the PONED and PONEK maternity teams. In line with these programs, there is a need for synergy in utilizing information technology to support the Jember government’s efforts to reduce maternal mortality rates through the creation of an early detection system to predict maternal deaths. This research will develop an early detection system for maternal mortality using the KNN method. The attributes used include gestational age, weight, haemoglobin, blood pressure A, blood pressure B, facial swelling, stillbirth, breech birth, bleeding during pregnancy, hydramnios, post-term pregnancy, transverse presentation, preeclampsia/eclampsia, anaemia, tuberculosis, malaria, and heart failure. The system development will utilize the prototype method. The test results show that the system can be used to predict maternal mortality with an accuracy
A Prototype of MyoWare (Electromyography Muscle Sensor) for Measuring People’s Muscle Strengths Rahagiyanto, Angga; Suyoso, Gandu Eko Julianto; Vestine, Veronika; Iskandar, Abdullah
International Journal of Health and Information System Vol. 1 No. 1 (2023): May
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/ijhis.v1i1.9

Abstract

Human-Computer Interaction (HCI) becomes a solution to help humans connect with computers. Research and tools related to HCI have been developed by many researchers. HCI is able to help humans connect between humans and computers and humans with humans at a considerable distance. One of HCI model is applied to the MyoWare tool that can capture hand muscle movements using an electromyograph (EMG) sensor. This article describes how to assemble and identify the raw data generated from the MyoWare tool. Using MyoWare on the hand could produce EMG data output. MyoWare only used the EMG sensor and generated data in the form of Envelope EMG and Raw EMG which differed in scale and size. This required a extraction features process to make the data uniform. This study uses the Moment Invariant method to extract features and min-max to normalize each data generated on the MyoWare sensor. Testing was done by doing simple hand movements. The test results showed that the differences in gestures were recognized well even though they were performed in different positions.
Perbandingan Kinerja Algoritma KNN-DT-RF-SVM untuk Deteksi Dini Risiko Kematian Ibu Rahagiyanto, Angga; Prakoso, Bakhtiyar Hadi; Yunus, Muhammad; Vestine, Veronika; Suyoso, Gandu Eko Juliato; Deharja, Atma
J-REMI : Jurnal Rekam Medik dan Informasi Kesehatan Vol 6 No 2 (2025): March
Publisher : Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/j-remi.v6i2.5658

Abstract

Maternal Mortality Rate (MMR) in Indonesia remains a significant health issue, with data indicating a mortality rate far exceeding the Sustainable Development Goals (SDGs) target. This study aimed to explore and compare the performance of K-Nearest Neighbors (KNN), Decision Tree (DT), Random Forest (RF), and Support Vector Machine (SVM) algorithms in detecting maternal mortality risk. Using a medical dataset of pregnant women from Sumbersari Community Health Center, models were developed to classify three pregnancy risk categories: low risk (KRR), high risk (KRT), and very high risk (KRST). Model evaluation was conducted based on accuracy, precision, recall, and F1-score metrics. The results showed that the Random Forest algorithm achieved the highest performance with an accuracy of 76.7%, followed by Decision Tree and SVM with 70%, while KNN had the lowest accuracy at 50%. The main challenge encountered was data imbalance in the classification of very high-risk cases. This study suggests the use of data balancing methods such as SMOTE and additional data augmentation to enhance model performance. These findings can serve as a foundation for Puskesmas to implement machine learning-based early detection systems to reduce maternal mortality rates.
Analysis of Factors Causing Delays in Inpatient Medical Record Returns at Hospital X Alfiansyah, Gamasiano; Anindhitya, Lutfi; Nurmawati, Ida; Rahagiyanto, Angga
International Journal of Healthcare and Information Technology Vol. 2 No. 2 (2025): January
Publisher : P3M Politeknik Negeri Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25047/ijhitech.v2i2.6164

Abstract

The delay in the return of inpatient medical records at Hospital X reached 71.23% in February 2022. This indicates a persistently high delay rate that does not comply with the standard for returning inpatient medical records, which is 2 x 24 hours. The purpose of this study was to analyze the factors contributing to the late return of inpatient medical records using the WHO behavior theory. This research employed a qualitative approach, with data collected through interviews, observations, and documentation. The results showed that for the Thoughts and Feelings variable, the contributing factors were the lack of staff knowledge regarding the standard return time for inpatient medical records, as well as the fact that some staff had never attended training or seminars related to medical records. The Personal Reference variable was not identified as a contributing factor. For the Resources variable, there were no supporting facilities available in the medical record return process in each room, the SOPs did not include related units, had not been re-socialized, and were not available in every inpatient room. Regarding the Culture variable, incorrect knowledge was considered correct, and staff had to wait for the doctor’s schedule to complete signature requirements. In conclusion, delays in the return of inpatient medical records were influenced by staff knowledge, training, availability of supporting facilities, incomplete or poorly disseminated SOPs, and habitual practices among hospital personnel during the record return process.
Implementasi Transfer Knowledge Pemanfaatan Teknologi Tanin Urea Molases Block (TUMB) Ternak Sapi Perah di Kelompok Ternak Damar Wulan Nurfitriani, Rizki Amalia; Anwar, Saiful; Muhamad, Nur; Brillyantina, Septine; Utomo, Budi; Bachri, Syaiful; Rahagiyanto, Angga
PEKAT: Jurnal Pengabdian Kepada Masyarakat Vol. 4 No. 2 (2025): Oktober
Publisher : Puslitbang Sinergis Asa Professional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37148/pekat.v4i2.71

Abstract

Defisiensi mineral menjadi permasalahan khusus peternakan sapi perah salah satunya di Kelompok Ternak Damar Wulan. Penyebab permasalahan tersebut yaitu tidak pahamnya peternak akan pentingnya pemberian mineral dalam ransum. Solusi yang diberikan yaitu implementasi Transfer Knowledge pemanfaatan Teknologi Tanin Urea Molases Block (TUMB) Ternak Sapi Perah. Sasaran dari kegiatan ini yaitu peternak sapi perah di Kelompok Ternak Damar Wulan. Tujuan dari pelaksanaan kegaiatan ini yaitu untuk mengetahui peningkatan pengetahuan Kelompok Ternak Damar Wulan mengenai TUMB. Metode yang digunakan terdiri dari koordinasi awal, persiapan materi, kegiatan sosialisasi pemanfaatan  TUMB, pengisian survey, dan evaluasi hasil kegiatan sosialisasi TUMB. Pelaksanaan implementasi ini dalam bentuk sosialisasi dengan partisipasi aktif. Hasil kegiatan yaitu koordinasi awal dilakukan dengan memastikan kesiapan baik dari tim pelaksana maupun dari Kelompok Ternak Damar Wulan yang dilihat dari lokasi serta sarana prasarana. Pelaksanaan sosialisasi berjalan dengan baik dibuktikan dengan aktifnya peternak bertanya dan merespon selama proses sosialisasi tersebut berlangsung. Pengisian survey dilaksanakan sebelum dan sesudah pelaksanaan sosialisasi TUMB. Penyampaian materi sistem partisipasi aktif terbukti mampu meningkatkan pemahaman peternak dari sebelumya 5 peternak menjadi 35 peternak atau sebesar 94,59%.
Evaluasi RME Rawat Jalan Menggunakan Metode EUCS di RSUD Ngudi Waluyo Wlingi Wijayanti, Rossalina Adi; Rohman, Nur Cholis Abdul; Rachmawati, Ervina; Rahagiyanto, Angga
Jurnal Manajemen Informasi Kesehatan Indonesia (JMIKI) Vol 13 No 2 (2025)
Publisher : Asosiasi Perguruan Tinggi Rekam Medis dan Informasi Kesehatan Indonesia- APTIRMIKI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33560/jmiki.v13i2.728

Abstract

Obstacles were found in the development of RME at Ngudi Waluyo Wlingi Regional Hospital, namely that there were registration form items that were not used, x-ray results sometimes did not appear resulting in doctors looking at the printed results, and there was no RME user manual. This study aims to evaluate outpatient RME using the EUCS method. This research is a quantitative descriptive study using the end-user computing satisfaction method. The total sample was 54 respondents using the Lemeshow formula. The data collection technique is by distributing questionnaires. User satisfaction analysis, namely the results of respondents' answers, is calculated for each variable, namely content, accuracy, format, timeliness, ease of use. The results are compared between expectations and the reality received by the user. Users are very satisfied if reality is greater than expectations. Users are satisfied if reality is the same as expectations. Users are dissatisfied if expectations are greater than reality. The research results showed that 38.89% of respondents were dissatisfied with content, 37.04% of respondents were dissatisfied with accuracy, 27.78% of respondents were dissatisfied with format, 29.63% of respondents were dissatisfied with timeliness, there were 42, 59% of respondents were not satisfied with ease of use. The suggestions given are for Ngudi Waluyo Wlingi Regional Hospital to review the output produced by RME, add validation warnings when input duplication occurs, develop the RME interface, and create a manual book for using RME.
Co-Authors Alfiansyah, Gamasiano Anindhitya, Lutfi Budi Utomo Deharja, Atma Hartanto, Sugeng Ida Nurmawati, Ida Iskandar, Abdullah MUHAMAD, NUR Muhammad Yunus Muhammad Yunus Nuraini, Novita Prakoso, Bakhtiyar Hadi Rachmawati, Ervina Rizki Amalia Nurfitriani Rohman, Nur Cholis Abdul Saiful Anwar Septine Brillyantina Suyoso, Gandu Eko Julianto Suyoso, Gandu Eko Juliato Syaiful Bachri Vestine, Veronika Wijayanti, Rossalina Adi Wulandari, Savira Puteri