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All Journal International Journal of Health and Information System (IJHIS) Jurnal Kecerdasan Buatan dan Teknologi Informasi
Utomo, Adi Heru
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Computer Science & IT Health Professions Library & Information Science Medicine & Pharmacology Public Health

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Detecting Dehydration Based on Urine Color Using Fuzzy Logic Image Processing and Regulating Water Intake with an Automatic Water Pump According to Dehydration Level Using an IoT-Based Utomo, Denny Trias; Utomo, Adi Heru; Olivia, Zora; Maria, Nita; Rosidania, Nilla Putri
International Journal of Health and Information System Vol. 1 No. 3 (2024): January
Publisher : Indonesian Journal Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47134/ijhis.v1i3.32

Abstract

Dehydration is a condition where the body lacks the fluids it needs to carry out its functions optimally. Dehydration can cause various health problems, including decreased mental and physical performance, and can even cause death if not treated immediately. Therefore, it is important to be able to detect and treat dehydration early. One way to detect dehydration is through urine color analysis. Urine that is darker than normal can be a sign of dehydration. The classification of dehydration level according to urine color is as follows: 1-2: Hydrated, 3-4: Mildly dehydrated, 5-6: Dehydrated, 7-8: Very dehydrated. This research aims to develop an IoT-based dehydration detection system that can detect the level of dehydration in a person based on urine color and regulate water intake automatically using a water pump.  The novelty of this research is the method of integrating drinking water intake with dehydration detection based on real-time urine color based on IoT using the Fuzzy Logic method. The results of this research are used by the Jember State Polytechnic TeFa Nutrition Care Center (NCC) in serving patients. The methodology used in this research is Fuzzy Logic image processing to process urine color data and determine a person's level of dehydration. After carrying out this research, the following conclusions were obtained: Based on the literature study in this research, 8 levels of hydration status according to NSW Health were obtained, then from this literature a method was obtained to measure a person's hydration based on urine color using image processing using the Fuzzy Logic method.
ALAT UKUR TINGKAT PENCEMARAN UDARA (KARBON MONOKSIDA (CO) dan NITROGEN DIOKSIDA (NO2)) PADA SEKTOR PERTANIAN BERBASIS IoT Utomo, Adi Heru; Andrianto, Erwin; Utomo, Denny Trias
Jurnal Kecerdasan Buatan dan Teknologi Informasi Vol. 2 No. 1 (2023): January 2023
Publisher : Ninety Media Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69916/jkbti.v2i1.31

Abstract

Pencemaran udara saat ini terus meningkat karena aktivitas manusia yang yang membuat tingkat konsentrasi gas tinggi, salah satunya dari sektor pertanian yang menghasilkan gas rumah kaca. Sehingga, menyebabkan beberapa dampak buruk bagi kelangsungan makhluk hidup terutama manusia. Pertanian menyumbangkan gas rumah kaca sekitar 14% pada skala global dan 7% pada skala nasional. Hasil tersebut didapat dari pengukuran yang dilakukan oleh dinas pertanian dengan menggunakan sungkup menangkap gas pencemar udara dan laboratorium untuk mengukur konsentrasi gas pencemar udara. Namun, saat ini di Kabupaten Jember peralatan yang dibutuhkan untuk melakukan pengambilan sampel dan laboratorium untuk mengukur tingkat konsentrasi gas masih kurang memadai. Maka, untuk mengatasi permasalahan tersebut, Peneliti merancang sebuah sistem berbasis IoT yang dapat di mengukur tingkat pencemaran udara dengan menggunakan parameter antara lain gas CO dan gas NO2. Hasil dari pengujian, akurasi dari algoritma fuzzy sugeno pada penelitian saat ini sebesar 100%. Sedangkan tingkat error dari sensor CO sebesar 11,4% dan tingkat error dari sensor NO2 sebesar 6,66%. Kata Kunci : Internet of Things, Fuzzy Sugeno, Polusi Udara, Pertanian
Co-Authors Denny Trias Utomo, Denny Trias Erwin Andrianto Maria, Nita Olivia, Zora Rosidania, Nilla Putri