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Sensors and Transducers for Stroke Detection Systematic Literature Review Iswanto Suwarno; Rezarta Lalo; Elena Costru-Tasnic; Jan van der Merwe; Husitha Vanguru
Sunan Kalijaga Journal of Physics Vol. 5 No. 1 (2023): Sunan Kalijaga Journal of Physics
Publisher : Prodi Fisika Fakultas Sains dan Teknologi UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/physics.v5i1.4242

Abstract

Along with changes in lifestyle, stroke is not only a disease that attacks the elderly population, but also often attacks people of productive age. Actions are proposed to the public to control risk factors, such as changing lifestyle behavior or taking medication, and variations in stroke risk are tracked by evaluating stroke risk annually. The symptom of stroke that is currently widely known by the public is paralysis, even though many stroke symptoms often appear without realizing it. So it is necessary to detect stroke using sensors and transducers to detect it. The aim of this research is to examine sensors and transducers for stroke detection. This research uses a systematic literature review using Preferred Reporting Items for Systematic Reviews (PRISMA). The results of article screening and selection found 84 potential articles that met the inclusion criteria. The research results show that the development of sensors and transducers for stroke detection is currently starting to develop through artificial intelligence based on the internet of thought which uses sensors and transducers within it. Judging from the production of tools that use sensors and transducers for stroke detection. Optimization of sensors and transducers for stroke detection must be carried out with appropriate use, detailed regulatory supervision, and continuous innovation of sensors and transducers for stroke detection which is useful in reducing the number of strokes in the world
A Artificial Intellegent algorithms for Tumor Disease Detection: systematic Literature Review Muhammad Hafid Alkarim; Iswanto Suwarno; Muhammad Ahmad Baballe; Mukhtar Ibrahim Bello
Sunan Kalijaga Journal of Physics Vol. 5 No. 2 (2023): Sunan Kalijaga Journal of Physics
Publisher : Prodi Fisika Fakultas Sains dan Teknologi UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/physics.v5i2.4275

Abstract

A Tumor is a swelling in the body caused by cells that multiply abnormally. Tumors or neoplasms consisting of benign tumors and malignant tumors. Benign tumors can grow larger but do not spread to other body tissues. Malignant tumors are cancers that attack the entire body and are uncontrollable. Comparison between the cell nucleus with the cytoplasm of malignant tumors, while benign tumors are the same as normal cells. Cancer cells can develop rapidly. These cells attack and damage body tissues through the bloodstream and lymph vessels so that they can grow in new places. One way to detect tumor disease is by utilizing Artificial intelligence algorithms for tumor Disease Detection. The purpose of this paper is for the development of Artificial Intellegent algorithms for the detection of tumor Diseases and optimization of Artificial Intellegent algorithms for the detection of tumor Diseases. This research uses systematic literature review by using preferred Reporting Items for Systematic Review (PRISMA). The results of screening and selection of articles obtained 64 potential articles that have met the inclusion criteria. The results showed that with earlier detection, a person can check tumor disease earlier using the help of Artificial intelligence algorithms. The results of research on the development of Artificial intelligence algorithms for detection of tumor Diseases have found Artificial intelligence algorithms that can be used to reduce the risk of tumor disease. Optimization of Artificial Intelegency algorithms for tumor classification, performing new data processing methods such as artificial intelligence can be selected to provide the accuracy of classification and diagnosis, exploration of detection limits is a very important aspect in tumor diagnosis based on SERS, finding improved and suitable nanoparticle substrates so as to significantly improve the original Raman signal.
Improving Health Protocols and Marketing of Baked Bread Umkm Products in Diro Hamlet, Bantul Idiani Darmawati; Ratna Indriawati; Iswanto Suwarno
Jurnal Pengabdian dan Pemberdayaan Masyarakat Indonesia Vol. 3 No. 7 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jppmi.v3i7.211

Abstract

Micro, Small and Medium Enterprises (MSMEs) are one of the fields that make a significant contribution to spurring Indonesia's economic growth. This is because the absorption capacity of MSMEs for a workforce is very large and close to the small people. Toast is one food that is quite popular at all ages. Consumers can choose a variety of flavors that suit their tastes. This type of food can be found in several places, including in the hamlet of Diro Bantul. One of the toast seller groups is chaired by Mr. Pungki Priawan, who has been selling toast since 2016. The problems faced are during this pandemic, sales turnover has decreased drastically, the lack of an understanding of the importance of carrying out an online marketing strategy, has not been able to adjust to the pandemic conditions which must implement health protocols according to government recommendations, so that business results cannot reach the maximum. . The UMY Service Team aims to improve the skills of SME players so that they can create digital promotional media to market products online and help provide education on Health protocols, so that they are more hygienic and increase sales turnover. The target of this community service is in the form of increasing discipline in implementing health protocols and helping create digital promotions for online sales through social media accounts. The method used is direct online and offline assistance as well as providing health protocol education. The results obtained during the mentoring were very significant, where since an online marketing strategy was created, sales turnover has increased rapidly, and since the education from the service team, business actors are more disciplined in implementing health protocols.
Production Rate Analysis of Citronella Essential Oil Using Distillation Method Novi Caroko; Lilis Kurniasari; Novi Diah Wulandari; Iswanto Suwarno
Jurnal Pengabdian dan Pemberdayaan Masyarakat Indonesia Vol. 3 No. 10 (2023)
Publisher : Peneliti Teknologi Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59247/jppmi.v3i10.216

Abstract

Semoyo is one of the districts located in Gunungkidul Regency. The community engages in the cultivation of traditional medicinal plants. One of the area's widely cultivated traditional medicinal plants is citronella. The community produces a significant amount of citronella, but it has yet to be processed into high-value economic products. Currently, citronella has emerged as a promising commodity because it can be used as a raw material to produce essential oil. The production of citronella essential oil is carried out through steam-hydro distillation. This research aimed to test the distillation characteristics to determine the potential production of citronella essential oil. The research aimed to determine the rate and capacity of essential oil production using citronella as the raw material. Based on the test results, the optimal duration for the distillation process of 2,000 grams of citronella was 60 minutes, with a maximum duration of 90 minutes. The yield of citronella essential oil obtained from this test was 0.414%. The resulting citronella essential oil has a density of 0.920 grams/mL, a clear appearance, a distinctive lemongrass aroma, and a light yellow color. These criteria meet the SNI 3953:2019 for citronella essential oil