Studi Literatur Review : Integrasi Kurikulum Pembelajaran Cerdas Biosensor Menggunakan Teknologi Internet of Things
Abstract
Penelitian ini bertujuan untuk menganalisis pengembangan teknologi biosensor di era industri 4.0 untuk memperluas wawasan siswa dalam pengembangan kerjasama antar bidang keilmuan. Metode yang digunakan berdasarkan studi literature review ini mencari kutipan tentang aplikasi biosensor dan pemanfaatannya, pentingnya teknologi digitalisasi, internet of things dan big data untuk pengembangan analisis biosensor sehingga dapat menciptakan produk inovatif secara berkelanjutan dan ringan secara finansial. Kajian analisis ini menghasilkan temuan penting bahwa perlu dilakukan kolaborasi kurikulum bidang teknik, kesehatan dan bidang keilmuan lain sehingga siswa dapat memahami interkoneksi konten antara disiplin ilmu yang berbeda terkait smart learning biosensor dan menerapkan pembelajaran mereka ke lingkungan industri.
References
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[2] Wang L, Zhang Y, Wu A, Wei G. Designed graphene-peptide nanocomposites for biosensor applications: A review. Analytica chimica acta. 2017 Sep 8;985:24-40.
[3] Siontorou CG, Batzias FA. A methodological combined framework for roadmapping biosensor research: a fault tree analysis approach within a strategic technology evaluation frame. Critical reviews in biotechnology. 2014 Mar 1;34(1):31-55.
[4] Patel SK, Parmar J, Trivedi H, Zakaria R, Nguyen TK, Dhasarathan V. Highly sensitive graphene-based refractive index biosensor using gold metasurface array. IEEE Photonics Technology Letters. 2020 May 6;32(12):681-4.
[5] Rahman MM, Rana MM, Rahman MS, Anower MS, Mollah MA, Paul AK. Sensitivity enhancement of SPR biosensors employing heterostructure of PtSe2 and 2D materials. Optical Materials. 2020 Sep 1;107:110123.
[6] Garzón V, Pinacho DG, Bustos RH, Garzón G, Bustamante S. Optical biosensors for therapeutic drug monitoring. Biosensors. 2019 Dec;9(4):132.
[7] Sawant SN. Development of biosensors from biopolymer composites. InBiopolymer composites in electronics 2017 Jan 1 (pp. 353-383). Elsevier.
[8] Haleem A, Javaid M, Singh RP, Suman R, Rab S. Biosensors applications in medical field: A brief review. Sensors International. 2021 May 13:100100.
[9] Bariya M, Nyein HY, Javey A. Wearable sweat sensors. Nature Electronics. 2018 Mar;1(3):160-71.
[10] Salim A, Lim S. Recent advances in noninvasive flexible and wearable wireless biosensors. Biosensors and Bioelectronics. 2019 Sep 15;141:111422.
[11] Akinwande D, Kireev D. Wearable graphene sensors use ambient light to monitor health.
[12] Kassal P, Steinberg MD, Steinberg IM. Wireless chemical sensors and biosensors: A review. Sensors and Actuators B: Chemical. 2018 Aug 1;266:228-45.
[13] Hao Z, Pan Y, Shao W, Lin Q, Zhao X. Graphene-based fully integrated portable nanosensing system for on-line detection of cytokine biomarkers in saliva. Biosensors and Bioelectronics. 2019 Jun 1;134:16-23.
[14] Wang J, Han K, Chen Z, Alexandridis A, Zilic Z, Pang Y, Lin J. A software defined radio evaluation platform for WBAN systems. Sensors. 2018 Dec;18(12):4494.
[15] Parthasarathy P, Vivekanandan S. A typical IoT architecture-based regular monitoring of arthritis disease using time wrapping algorithm. International Journal of Computers and Applications. 2020 Apr 2;42(3):222-32.
[16] Umar Ibrahim A, Pwavodi PC, Ozsoz M, Al-Turjman F, Galaya T, Agbo JJ. Crispr biosensing and Ai driven tools for detection and prediction of Covid-19. Journal of Experimental & Theoretical Artificial Intelligence. 2021 Aug 4:1-7.
[17] Yu Z, Jung D, Park S, Hu Y, Huang K, Rasco BA, Wang S, Ronholm J, Lu X, Chen J. Smart traceability for food safety. Critical Reviews in Food Science and Nutrition. 2020 Oct 7:1-2.
[18] Kharel J, Reda HT, Shin SY. Fog computing-based smart health monitoring system deploying lora wireless communication. IETE Technical Review. 2019 Jan 2;36(1):69-82.
[19] Ghonoodi A, Salimi L. The study of elements of curriculum in smart schools. Procedia-Social and Behavioral Sciences. 2011 Jan 1;28:68-71
[20] Ellahi RM, Khan MU, Shah A. Redesigning Curriculum in line with Industry 4.0. Procedia computer science. 2019 Jan 1;151:699-708
[21] Al-Arimi AM. Distance learning. Procedia-Social and Behavioral Sciences. 2014 Oct 7;152:82-8
[22] Shah UV, Chen W, Inguva P, Chadha D, Brechtelsbauer C. The discovery laboratory part II: A framework for incubating independent learning. Education for Chemical Engineers. 2020 Apr 1;31:29-37.
[23] Ike Yuni Wulandari, Ema, A Ana, Narwikant Indroasyoko, Heni Puspta, Andriana, Rahmad HIdayat. Learning Antenna Simulation To Enhance Technical Competency Of Avionics Students. Journal of Engineering Science and Technology. 2021 Feb;16(1):251-8
[24] Armstrong R, Hall BJ, Doyle J, Waters E. ‘Scoping the scope’of a cochrane review. Journal of public health. 2011 Mar 1;33(1):147-50.
[25] Pla L, Santiago-Felipe S, Tormo-Mas MÁ, Ruiz-Gaitán A, Pemán J, Valentín E, Sancenón F, Aznar E, Martínez-Máñez R. Oligonucleotide-capped nanoporous anodic alumina biosensor as diagnostic tool for rapid and accurate detection of Candida auris in clinical samples. Emerging microbes & infections. 2021 Jan 1;10(1):407-15.
[26] Zhao Y, Bu S, Wang C, Ma C, Li Z, Zhang W, Wan J. Dual Aptamer-Copper (II) Phosphate Nanocomposite-Based Point-of-Care Biosensor for the Determination of Escherichia coli O157: H7 through Pressure Monitoring with a Hand-Held Barometer. Analytical Letters. 2020 Sep 10;54(10):1603-15.
[27] Miao L, Li Z, Chen Y, Gao Y, Di J. A sensitive photoelectrochemical biosensor for pesticide detection based on BiVO4. International Journal of Environmental Analytical Chemistry. 2021 Jun 12:1-4.
[28] Pal K, Asthana N, Aljabali AA, Bhardwaj SK, Kralj S, Penkova A, Thomas S, Zaheer T, Gomes de Souza F. A critical review on multifunctional smart materials ‘nanographene’emerging avenue: nano-imaging and biosensor applications. Critical Reviews in Solid State and Materials Sciences. 2021 May 27:1-7.
[29] Olejnik B, Kozioł A, Brzozowska E, Ferens-Sieczkowska M. Application of selected biosensor techniques in clinical diagnostics. Expert review of molecular diagnostics. 2021 Sep 2;21(9):925-37.
[30] Chui, K.T., Liu, R.W., Lytras, M.D. and Zhao, M., 2019. Big data and IoT solution for patient behaviour monitoring. Behaviour & Information Technology, 38(9), pp.940-949.
Rajan Jeyaraj P, Nadar ER. Smart-monitor: patient monitoring system for IoT-based healthcare system using deep learning. IETE Journal of Research. 2019 Aug 9:1-8.
[31] Dwipriyoko, E. (2018). Literature Review on New Generation Cooperative Enterprise Architecture. Jurnal Tiarsie, 14(2), 51-56.
Published
2021-09-30
How to Cite
WULANDARI, Ike Yuni et al.
Studi Literatur Review : Integrasi Kurikulum Pembelajaran Cerdas Biosensor Menggunakan Teknologi Internet of Things.
Jurnal Tiarsie, [S.l.], v. 18, n. 3, p. 97-102, sep. 2021.
ISSN 2623-2391.
Available at: <https://jurnalunla.web.id/tiarsie/index.php/tiarsie/article/view/109>. Date accessed: 17 may 2026.
doi: https://doi.org/10.32816/tiarsie.v18i3.109.
Section
Articles
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
