Desain Rangkaian Sensor dan Driver Motor pada Rancang Bangun Miniatur Pintu Garasi Otomatis

Sensor adalah suatu piranti konverter yang mengukur suatu besaran fisik dan mengubahnya ke dalam suatu sinyal yang dapat dibaca dari suatu pemgamatan.Untuk mengoperasikan suatu sistem rancang bangun miniatur pintu garasi yang bekerja secara otomatis dengan menggunakan Programable Logic Control, dalam hal ini perintah keluaran untuk mengeksekusi kerja dari suatu PLC, PLC tersebut membutuhkan sinyal input yang harus diberikan. Dalam hal ini maka dirancangan sistem input yang dapat bekerja secara otomatis terhadap objek yang akan dijadikan objek pengamatan. Dalam Perancangan sistem otomatis tersebut maka dirancang dan dibuat sistem sensor dengan menggunakan sistem pemancar dan sistem penerima. Sistem pemancar merupakan suatu peralatan yang memberi pengamatan terhadap objek yang akan di sensor dengan menggunakan Light Emisi Dioda (LED, kemudian sinyal diterima oleh sistem penerima untuk diteruskan ke bagian masukan Input PLC berupa Light Dependence Colektor (LDR). Sinyal dari LDR digunakan untuk mendriver relay untuk mengaktifkan kontak-kontak relay. Kontak-kontrak relay inilah yang memberi suatu perintah ke input PLC. Sinyal input dari PLC di proses dan keluaran berupa sinyal digital. Agar sinyal ini dapat digunakan maka diperlukan driver untuk menjalankan keluaran, dalam hal ini aktuator yang akan didrver adalah motor dc servo. Karena motor ini dimanfaatkan untuk membuka dan menutup pintu garasi secara otomatis, maka diperlukan suatu sistem penggerak motor sesuai yang diinginkan melalui rangkaian perintah yang saling interloking. Sementara objek output PLC adalah motor servo dc maka perintah interlocking dapat dilakukan dengan mengubah arah polaritas arus jangkar pada rotor mesin servo dc tersebut. Berdasarkan hasil pengujian sistem sensor input dan driver keluaran pada sisi output PLC yang telah dirancang dan dibuat mengindikasikan bahwa rancangan dan pembuatan rangkaian sensor dan driver penggerak motor dc servo bekerja dengan bai

A DEEP LEARNING MODEL IMPLEMENTATION BASED ON RSSI FINGERPRINTING FOR LORA-BASED INDOOR LOCALIZATION

LoRa technology has received a lot of attention in the last few years. Numerous success stories about using LoRa technology for the Internet of Things in various implementations. Several studies have found that the use of LoRa technology has the opportunity to be implemented in indoor-based applications. LoRa technology is found more stable and is more resilient to environmental changes. Environmental change of the indoor is a major problem to maintain accuracy in position prediction, especially in the use of Received Signal Strength (RSS) fingerprints as a reference database. The variety of approaches to solving accuracy problems continues to improve as the need for indoor localization applications increases. Deep learning approaches as a solution for the use of fingerprints in indoor localization have been carried out in several studies with various novelties offered. Let’s introduce a combination of the use of LoRa technology's excellence with a deep learning method that uses all variations of measurement results of RSS values at each position as a natural feature of the indoor condition as a fingerprint. All of these features are used for training in-deep learning methods. It is DeepFi-LoRaIn which illustrates a new technique for using the fingerprint data of the LoRa device's RSS device on indoor localization using deep learning methods. This method is used to find out how accurate the model produced by the training process is to predict the position in a dynamic environment. The scenario used to evaluate the model is by giving interference to the RSS value received at each anchor node. The model produced through training was found to have good accuracy in predicting the position even in conditions of interference with several anchor nodes. Based on the test results, DeepFi-LoRaIn Technique can be a solution to cope with changing environmental conditions in indoor localizatio

The Effect of Angiotensin-Converting Enzyme Gene Polymorphisms in the Coronary Slow Flow Phenomenon at South Sumatra, Indonesia Population

BACKGROUND: The coronary slow flow phenomenon (CSFP) is believed to be affected by endothelial dysfunction ruled by renin, angiotensin, aldosterone, and the angiotensin-converting enzyme (ACE). The gene of ACE has been characterized in humans by a major insertion (I)/deletion (D) polymorphism. Serum ACE levels were associated with I/D polymorphism in the ACE-encoding gene. AIM: This study explored and analyzed the role of ACE gene polymorphism risk factors with the incidence of CSFP in the population of South Sumatra, Indonesia. METHODS: This study was a cross-sectional analytic observational study. A total of 112 CSFP and non- CSFP patients participated in this study. Blood was obtained from the study subjects then processed. Angiotensin I and aldosterone levels were examined using the enzyme-linked immunosorbent assay. The Judkins method was used in the assessment of coronary angiography, which was carried out through the femoral artery. For the examination of ACE I/D polymorphisms, genome deoxyribonucleic acid was extracted from blood cells (leukocytes), using the Wizard’s purification system and examined using the polymerase chain reaction method. All data were evaluated through the Chi-square test, two samples t-test, and Mann–Whitney U-test. All tests used two-sided significance and p < 0.05 was considered statistically significant. RESULTS: ACE I/D gene polymorphism possessed a significant effect in increasing the risk of CSFP. Genotype II polymorphism increased the risk of CSFP as much as 6.9 times compared to individuals with ID/DD genotype. The existence of allele I increased the risk of CSFP 5.7 times compared to allele D. Levels of angiotensin I and aldosterone were increased significantly in patients with CSFP. CONCLUSION: ACE I/D gene polymorphism possessed a significant effect in increasing the risk of CSFP. Genotype of II was the risk factor for the development of CSFP in population of South Sumatra, Indonesia

Penerapan Sistem Informasi Kesehatan (Siketan) Berbasis Teknologi Digital Untuk Meningkatkan Keakuratan Laporan Bulanan Angka Penyakit Puskesmas Benteng

Tenaga Kesehatan yang ada di  Puskesmas Benteng selama ini membuat penulisan buku register rekam medis dan laporan bulanan (LB1)  secara manual  pada kertas, dan dimuat pada dokumen Microsoft Excel dan pengiriman laporan bulanan ke Dinas Kesehatan melalui email. Pembuatan LB1 dengan sistem manual membuat pekerjaan tenaga kesehatan membutuhkan waktu yang lama. Tim PKM menganalisis situasi mitra memerlukan teknologi dengan mengembangkan sistem informasi Kesehatan (Siketan) berbasis teknologi digital untuk meningkatkan keakuratan laporan bulanan angka penyakit di Puskesmas benteng. Tujuan dari Tim PKM adalah memberikan sosialiasasi terkait Sistem Informasi Kesehatan (Siketan) dan melakukan demonstrasi penggunaan sistem informasi Kesehatan kepada tenaga medis Puskesmas Benteng.  Metode yang digunakan dalam PKM adalah dengan cara persentase dan demontrasi Siketan kepada seluruh peserta yang merupkan tenaga medis Puskesmas Benteng. Pemberian Siketan terhadap UPT Puskesmas Benteng di sambut baik dengan harapan agar kedepan mampu memberikan kemudahan pada tenaga Kesehatan UPT Puskesmas Benteng dalam Menyusun Laporan bulanan (LB1)

Correlation of IL-17 Serum Levels with Carotid Intima-Media Thickness and Degree of Disease Activity in Rheumatoid Arthritis Patients at Dr. Mohammad Hoesin General Hospital Palembang, Indonesia

Background: Rheumatoid arthritis (AR) is an autoimmune disease characterized by chronic and progressive systemic inflammation, in which the joints are the main target. AR has long been associated with increased cardiovascular risk. Vascular inflammation plays an important role in atherosclerosis. In AR, there is an increase in IL-17, which accelerate the formation of atherosclerosis. In Indonesia alone, there is no data that publishes the correlation between IL-17 levels with carotid IMT and the severity of AR. Methods: This type of research is a descriptive observational study with a correlation test approach. A total of 31 subjects participated in this study who were AR patients and calculated a DAS score of 28. Carotid IMT was measured by high-resolution carotid Doppler ultrasound B-mode ultrasound machine (PHILIPS, iE33) equipped with an 11 MHz linear array transducer. IL-17 was measured by the ELISA method. Data analysis was performed with a correlation test with SPSS software version 25. Results: There was a strong positive correlation between IL-17 and the degree of disease activity in AR (DAS28 score) with r = 0.657; p = 0.0001; n=31. There was no significant correlation between carotid IMT and IL-17 levels (r= 0,207; p=0,264; n=31). Conclusion: There is a strong positive correlation between IL-17 and the degree of AR disease activity. There was no significant correlation between carotid IMT and IL-17 levels

The Association between Urinary Tissue Inhibitor Metalloproteinase 2 (TIMP-2) and Insulin-like Growth Factor Binding Protein 7 (IGFBP-7) and Renal Recovery in Acute Kidney Injury

Background. Acute kidney injury (AKI) is a common and serious medical condition associated with significant increases in morbidity, mortality, cost of care and non recovery of kidney function that leads to progression to chronic kidney disease. Cell cycle arrest is implicated in the pathogenesis and repair process following AKI. The urinary cell-cycle arrest markers tissue inhibitor of metalloproteinase-2 (TIMP-2) and insulin-like growth factor binding protein 7 (IGFBP-7) have been utilized to predict the risk of AKI in many studies from specific population with good performance. However, their use in predicting recovery is still lacking. The aim of this study was to determine the association between two novel AKI biomarkers, urinary TIMP2 and IGFBP7 and renal recovery after 7 days of treatment in AKI patients at Dr. Mohammad Hoesin Hospital Palembang. Method.  This was a prospective cohort study conducted in dr. Mohammad Hoesin Hospital Palembang from January 2021 until March 2021. Subjects enrolled in this study were patients whom diagnosed AKI based on KDIGO 2012 criteria. Urine samples were collected upon patients’ enrollment within 24 hours of AKI diagnosis. We utilized Sandwich Enzyme Linked Immunosorbant Assay (ELISA) method to detect urinary TIMP-2 and IGFBP-7 levels. The primary outcome is recovery from AKI after 7 days of treatment. Chi square test is used to analyze the association between urinary TIMP-2 and IGFBP-7 levels and renal recovery. Results. There were 70 subjects, only 22 of them were recovered after 7 days (31%). Median of urinary TIMP-2 and IGFBP-7 was 0,0047(0,0001-0,1439) [(ng/ml)2/1000]. There was significant association between urinary TIMP2 and IGFBP7 and renal recovery (p=0,027; OR 3,19; 95% CI 1,116-9,128). Conclusion. There was significant association between urinary TIMP2 and IGFBP7 and renal recovery in AKI patients

Electrocardiography Predictive Value on Coronary Slow Flow Phenomenon

Coronary Slow Flow Phenomenon (CSFP) is characterized by the slow flow of contrast in one or more epicardial coronary vessels without evidence of coronary artery stenosis during coronary angiography procedures. CSFP is fairly common at the time of elective angiography with an incidence of around 7% and accounts for about 4% of hospitalized unstable angina cases. Coronary angiography is currently still the only effective way to detect CSFP, but this procedure is an invasive procedure with high costs, there is a risk of allergy to contrast. Electrocardiography (ECG), as a widely available, inexpensive, and simple modality is felt to be an attractive alternative in early detection of this abnormality. The ECG parameters on CSFP discussed in this study include; p-wave dispersion, QT interval dispersion, QRS intrinsic (Tpeak-Tenddeflection duration), and QRS fragmentation. Further studies are needed on the ECG image in CSFP so that in the future ECG can be a cheaper and non-invasive diagnostic modality for CSFP compared to coronary angiography