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Nyayu Latifah Husni, Nyayu Latifah
State Polytechnic of Sriwijaya
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Revolutionizing IV Infusions: Empowering Care with the DripControl+ App for Real-Time Monitoring and Precision Management Markinashella, Deva; Risma, Pola; Husni, Nyayu Latifah
International Journal of Advanced Health Science and Technology Vol. 3 No. 4 (2023): August
Publisher : Forum Ilmiah Teknologi dan Ilmu Kesehatan (FORITIKES)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35882/ijahst.v3i4.280

Abstract

The demand for an effective and precise monitoring and control system for intravenous infusion therapy has increased due to concerns regarding medication errors and inefficiencies associated with current manual monitoring methods employed by nurses, particularly when caring for multiple patients across different rooms. This research aims to enhance intravenous infusion therapy by developing a real-time monitoring and control system. The system utilizes IoT technology and advanced sensors, including the load cell sensor for infusion volume detection, the FC-33 optocoupler sensor for precise infusion drop monitoring, and also a servo motor as an actuator to bend the infusion hose. Integrated with the NodeMCU ESP32 microcontroller, the system empowers healthcare professionals with the user-friendly DripControl+ app to remotely monitor and cont rol the infusion process. The results indicate a seamless collaboration among the system components. The FC-33 Optocoupler sensor exhibits an outstanding accuracy rate of 99.39%. The load cell sensor achieves an impressive 99.61% accuracy. The servo motor precisely follows predetermined positions. These outcomes effectively highlight the system's ability to accurately control the infusion drip rate with exceptional precision. The FC-33 optocoupler sensor and servo motor play crucial roles in achieving this accuracy. With an impressive average accuracy of 97.99%, the system has proven to be highly efficient. However, it should be noted that sudden changes in infusion speed could impact the accuracy of the readings. The future research could focus on refining the system's ability to respond to abrupt changes in infusion speed through advanced algorithms, such as machine learning.
Sistem Smart Infus Berbasis Android dan Website Kinasih, Ayu Antika Sekar; Handayani, Ade Silvia; Hadi, Irawan; Husni, Nyayu Latifah; Chodijah, Siti
Jurnal RESISTOR (Rekayasa Sistem Komputer) Vol. 6 No. 2 (2023): Jurnal RESISTOR Edisi Agustus 2023
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/jurnalresistor.v6i2.1482

Abstract

Penelitian ini menyajikan sebuah sistem smart infus berbasis aplikasi Android dan website yang bertujuan untuk memonitoring dan mengontrol infus dari jarak jauh. Sistem infus yang inovatif ini berhasil menampilkan hasil monitoring infus dari setiap ruangan pasien yang memiliki parameter seperti berat infus, kecepatan tetesan infus, estimasi infus dan kondisi infus melalui website dan hasil pengontrolan setiap tetesan infus pada aplikasi Android. Kelebihan dari sistem ini adalah memudahkan pelayanan tenaga medis dalam melakukan pemantauan dan pengontrolan infus dari jarak jauh tanpa harus memantau dan mengontrol secara langsung dari ruangan ke ruangan.
Navigasi Garbage Robot (G-Bot) Menggunakan Environment Mapping Riansyah, Rici; Amperawan, Amperawan; Al Rasyid, Johansyah; Husni, Nyayu Latifah; Rasyad, Sabilal
TEKNIKA Vol. 14 No. 1 (2020): Teknika Januari - Juni 2020
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.13347597

Abstract

AbstrakSampah merupakan salah satu sumber permasalahan yang sangat serius jika tidak ditangani dengan benar. Beberapa hal yang ditimbulkan akibat tumpukan sampah yang berlebihan yaitu lingkungan yang kotor, bau tidak sedap, gangguan kesehatan, permukiman yang kumuh dan hal-hal lainnya yang diakibatkan oleh sampah yang kurang diperhatikan. Kurangnya pemantauan terhadap tempat penampungan sampah menjadi salah satu faktor penyebab menumpuknya sampah pada lokasi pembuangan. Untuk mengatasi permasalahan tersebut pada penilitian ini akan dirancang sebuah Garbage Robot yang mampu bernavigasi secara otomatis. Sistem kecerdasan pada Garbage Robot dibuat agar robot dapat berpindah dari suatu tempat ke tempat yang lain. Perancangan Garbage Robot menggunakan mikrokontroler Arduino Mega 2560 yang dilengkapi modul ESP8266 sehingga bisa terkoneksi dengan internet, Sensor Gps untuk mengetahui posisi robot serta sensor kompas, sensor jarak dan sensor warna untuk pendukung navigasi robot. Kata kunci— Sampah, Garbage Robot, Navigasi Robot, Arduino Mega 2560, Raspberry Pi, Sensor Kompas, Sensor Jarak, Sensor Gps dan Sensor Warna. Abstract            Garbage is one source of very serious problems if it is not handled properly. Some of the things that are caused by excessive pile of garbage are dirty environment, unpleasant odors, health problems, slums and other things that are caused by waste that is not considered. Lack of monitoring of rubbish dumps is one of the factors causing the accumulation of garbage at the disposal site. To overcome these problems in this study, a Garbage Robot will be able to navigate automatically. The intelligence system in the Garbage Robot is made so that the robot can move from one place to another. The design of Garbage Robot uses the Arduino Mega 2560 microcontroller which is equipped with ESP8266 module so that it can be connected to the internet, Gps Sensor to determine the position of the robot as well as compass sensors, proximity sensors and color sensors to support robot navigation.Keywords— Garbage, Garbage Robot, Navigation Robot, Arduino Mega 2560, Raspberry Pi,                 Compass Sensor, Proximity Sensor, Gps Sensor and Color Sensor.
Perancangan Deteksi Suara Paru Paru Berbasis DSP TMS320C6416T dan Module Wireless Meranda, Arganda; Alfarizal, Niksen; Husni, Nyayu Latifah; Pratama, Destra Andika; Irdayanti, Yeni; Handayani, Ade Silvia
TEKNIKA Vol. 14 No. 2 (2020): Teknika Juli - Desember 2020
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.13368220

Abstract

AbstrakParu-paru merupakan organ tubuh pada manusia dalam menjalankan sistem respirasi (pernapasan), dan berfungsi sebagai bertukarnya oksigen dan karbondioksida. Untuk mendeteksi suara paru-paru diperlukan stetoskop sebagai alat untuk mendengarkan suara pada paru-paru. Teknik ini disebut sebagai auskultasi, dimana pada teknik ini banyak batasan dan kekurangan. Untuk mengatasi permasalahan tersebut maka pada penelitian ini diusulkan sebuah teknik auskultasi yang dimodifikasi dengan electret condenser microphone untuk menangkap suara pada paru-paru. Tipe yang digunakan electret condenser microphone yaitu unidirectional (cardioid). Sinyal listrik yang dihasilkan oleh electret condenser microphone dikuatkan lagi menggunakan pre-amplifier karna sinyal listrik yang dihasilkan electrets condenser microphone sangat kecil. Pre-amplifier yang digunakan yaitu tube ultragain mic100. Sinyal yang dikuatkan dengan pre-amplifier masih berbentuk sinyal listrik, sinyal listrik ini akan diproses di DSP untuk mengubah sinyal menjadi data diskrit untuk mengubah sinyal suara ke sinyal listrik analog. Sinyal analog akan diubah melalui unit ADC agar dapat berubah menjadi sinyal digital kemudian DSP akan menerima sinyal digital dan memproses data digital tersebut yang kemudian sinyal disimpan dalam bentuk  file .wav. File .wav yang disimpan kemudian dipindahkan ke android melalui RobotDyn UNO+WIFI sebagai media komunikasi. RobotDyn UNO+WIFI yang digunakan yaitu tipe  ATmega328p+ESP8266 CH340G, file .Wav diproses dan diputar untuk dapat divisualisasikan pada android sehingga mempermudah dokter dalam menganalisa suara paru-paru pasien.  Kata kunci:  Suara paru-paru, Stetoskop, Electret Condenser Microphone, Pre-Amplifier dan DSP TMS320C6416T, dan RobotDyn UNO+WIFI ATmega328p+ESP8266 CH340G. AbstractThe lungs are organs in the human body in carrying out the respiratory system (breathing).  It function as the exchange of oxygen and carbon dioxide. To detect lung sounds, a stethoscope is needed as a tool to listen the sounds in the lungs. This technique is called auscultation.  In this technique, there are many limitations and disadvantages. Thus, to overcome this problem, this study proposed an auscultation technique modified with an electret condenser microphone to capture sounds in the lungs. The type used by the electret condenser microphone is unidirectional (cardioid). The electrical signal generated by the electret condenser microphone is amplified using a pre-amplifier because the electrical signal generated by the electrets condenser microphone is very small. The pre-amplifier used is the mic100 ultragain tube. The signal that is amplified by the pre-amplifier is still in the form of an electrical signal, this electrical signal will be processed on the DSP to convert the signal into discrete data to convert the sound signal to an analog electrical signal. The analog signal will be converted through the ADC unit so that it can be transformed into a digital signal then the DSP will receive a digital signal and process the digital data which is then stored in the form of a .wav file. The saved .wav file is then transferred to android via RobotDyn UNO + WIFI as a communication medium. RobotDyn UNO + WIFI used is the type ATmega328p + ESP8266 CH340G, .Wav files are processed and played so that it can be visualized on Android making it easier for doctors to analyze the sound of a patient's lungs. Keywords:  Lung sounds, Stethoscope, Electret Condenser Microphone, Pre-Amplifier and DSP TMS320C6416T, and RobotDyn UNO + WIFI ATmega328p + ESP8266 CH340G.
Penerapan Sistem Pengolahan Citra Digital Pendeteksi Warna pada Starbot Aditya, M Rizky Vira; Husni, Nyayu Latifah; Pratama, Destra Andika; Handayani, Ade Silvia
TEKNIKA Vol. 14 No. 2 (2020): Teknika Juli - Desember 2020
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5281/zenodo.13368229

Abstract

AbstrakSTARBOT (Smart trash can robot) merupakan robot kotak sampah yang dapat bergerak secara otomatis berdasarkan perintah yang diberikan user dan akan bergerak menuju suatu ruangan yang telah ditentukan. Robot ini menggunakan otak pengoperasian Raspberry Pi dan dilengkapi dengan penangkap citra Webcam yang dapat mengenali objek masing-masing ruangan dengan bentuk dan warna yang berbeda. Citra yang ditangkap oleh Webcam diproses menggunakan metode HSV. Nilai HSV didapatkan melalui proses sampling warna, konversi algoritma transformasi ruang warna secara perhitungan, dan simulasi menggunakan trackbar. Proses pengolahan citra yang ditangkap kamera juga memanfaatkan metode radius untuk menentukan jarak minimum antara tanda yang terdapat pada masing-masing ruangan dengan robot. Penggunaan metode HSV dipilih untuk mempermudah pendeteksian warna dalam berbagai kondisi baik dengan intensitas cahaya yang rendah maupun yang tinggi. Kata kunci—3-5 Smart Trash Can, HSV, radius, raspberry pi  AbstractSTARBOT (Smart trash can robot) is a trash box robot that can move automatically based on instructions given by the user and will move to a predetermined room. This robot uses the Raspberry pi as the operating brain and is equipped with a webcam image capture that can recognize objects in each room with different shapes and colors. The image captured by the webcam is processed using the HSV method. The HSV value is obtained through a color sampling process, calculation of the color space transformation algorithm conversion, and simulation using a trackbar. The image processing process captured by the camera also utilizes the radius method to determine the minimum distance between the marks contained in each room and the robot. The use of the HSV method was chosen to facilitate color detection in various conditions, both with low and high light intensity. Keywords—3-5 Smart Trash Can, HSV, radius, raspberry pi
Anxiety Detection for Autism Children through Vital Signs Monitoring using a Socially Assistive Robot Prihatini, Ekawati; Damsi, Faisal; Husni, Nyayu Latifah; Muslimin, Selamat; Marniati, Yessi; Ramadhan, M. Daffa
Computer Engineering and Applications Journal Vol 14 No 1 (2025)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/comengapp.v14i1.493

Abstract

Socially Assistive Robot (SAR) to detect anxiety levels in children with Autism Spectrum Disorder (ASD), a condition often accompanied by difficulties in recognising and expressing emotions, including anxiety. Early recognition of anxiety in children with Autism Spectrum Disorder (ASD) is crucial as it can affect their behaviour and social interactions. This SAR monitors vital signs namely blood pressure, heart rate and body temperature. This study involved children with Autism Spectrum Disorder (ASD) with two conditions, namely Asperger Syndrome and Classical Autism who interacted with a Socially Assistive Robot (SAR) equipped with a tensimeter (MPS20N0040D sensor) for blood pressure, MAX30100 sensor for heart rate, and MLX90614 sensor to measure body temperature. Results show that the Socially Assistive Robot (SAR) is able to measure vital signs with high accuracy and provide an indication of anxiety levels effectively, as vital signs correlate with anxiety levels. These findings demonstrate the potential of the Socially Assistive Robot (SAR) as a reliable tool in anxiety monitoring in children with ASD, with important implications for the development of future therapeutic interventions
Development of a Littering Behavior Detection Using 3D Convolutional Neural Networks (3D CNN) Husni, Nyayu Latifah; Prihatini, Ekawati; Ulandari, Monica; Handayani, Ade Silvia
Computer Engineering and Applications Journal Vol 14 No 1 (2025)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18495/comengapp.v14i1.1246

Abstract

Littering has become a significant problem that negatively impacts public health and environmental cleanliness. This research introduces an innovative solution using 3D Convolutional Neural Networks (3D CNN) technology to automatically detect littering behavior through real-time CCTV recordings. Two models were developed and tested. Model 1, which employs Conv3D, Batch Normalization, and Dropout, showed high training accuracy but exhibited fluctuations in validation accuracy, indicating potential overfitting. In contrast, Model 2, designed with a simpler structure without Batch Normalization and Dropout, achieved higher classification accuracy and efficiency. Both models significantly contribute to addressing littering in public areas, increasing awareness, and supporting environmental law enforcement. The integration of 3D CNN technology in detecting littering behavior demonstrates its potential to reduce pollution and promote environmentally responsible behavior.
Sistem Monitoring Kesehatan Dalam Penentuan Kondisi Tubuh Dengan Metode Fuzzy Mamdani Plowerita, Sanyyah; Handayani, Ade Silvia; Hadi, Irawan; Husni, Nyayu Latifah
PROtek : Jurnal Ilmiah Teknik Elektro Vol 8, No 2 (2021): Protek : Jurnal Ilmiah Teknik Elektro
Publisher : Program Studi Teknik Elektro Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/protk.v8i2.3341

Abstract

In this study, designing a health monitoring system with an Android-based Application of Health Detector (AHD) application. The data displayed is an input for multi-sensor readings from the detection of body health. From the detected health, it will provide a determination of the body's health condition, using the fuzzy mandani algorithm. The variables calculated were age, gender, heart rate, body temperature, systolic blood pressure, diastolic blood pressure, and blood oxygen levels. The stages of the fuzzy mamdani method in determining body health conditions include the formation of fuzzy sets, application of implications functions, and composition of rules. From the results of this study, it was found that the age factor affects health conditions. Older people tend to have indications of health conditions, only some of them have indicated health conditions, and almost all of them have healthy health conditions. The level of accuracy of the fuzzy mamdani method in this study was 85.18%. This is because in this study many variables are used which causes many rules to be made so that they are prone to errors.
Performance Evaluation on Applied Low-Cost Multi-Sensor Technology in Air Pollution Monitoring Handayani, Ade Silvia; Husni, Nyayu Latifah; Permatasari, Rosmalinda
Computer Engineering and Applications Journal (ComEngApp) Vol. 11 No. 3 (2022)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research aims to discuss the application of multi-sensor network technology for the monitoring of indoor air pollution. Indoor air pollution has become a severe problem that affects public health, especially indoor parking. The indoor air pollution monitoring system will provide information about vehicle exhaust emission levels. We have improved the system to identify six parameters of the vehicles' gas emissions within a different location at once. This research aimed to measure the parameter of Carbon Monoxide (CO), Carbon Dioxide (CO2), Hydro Carbon (HC), temperature and humidity, and levels of particulates in the air (PM10). The performance of this system shows good ability to compare the results of measurements of air quality measuring professionals. In this study, we investigated the performance of a custombuilt prototype developed under the android-based application to detect air pollution levels in the parking area. Our objective was to evaluate the suitability of a low-cost multi-sensor network for monitoring air pollution in parking and the other area. The benefit of our approach is that its time and space complexity make it valuable and efficient for real-time monitoring of air pollution.
Littering Activities Monitoring using Image Processing Husni, Nyayu Latifah; Handayani, Ade Silvia; Passarella, Rossi; Abdurrahman; Rahman, A.; Felia, Okta
Computer Engineering and Applications Journal (ComEngApp) Vol. 12 No. 3 (2023)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Littering is a human behavior that become a habit since childhood. Even though there are rules that prohibit this behavior, the community still continues to do so. In order to limit this bad behavior, a device that can monitor and provide notifications is needed. In this research, proposed device can identify human activities by utilizing webcam-based image processing. It is processed by machine learning using the Recurrent Neural Network (RNN). The monitoring device produced in this research works by comparing the captured image data with dataset. The captured image data are extracted into figures and form several coordinate points on the human body. Then, the system classifies the human activities into two categories, i.e., normal or littering. This device will provide an output in the form of a ewarning every time the activity of littering is detected.
Co-Authors A. Rahman Abdurahman Abdurrahman Ade Silvia Handayani Aditya, M Rizky Vira Ahmad Taqwa Al Rasyid, Johansyah Alfarizal, Niksen Amperawan Amperawan, Amperawan Andika, Destra Angguna, Welan Mauli Asriyadi Asriyadi Caesandra, Wahyu DWI RAMADHANI Evelina Evelina Faisal Damsi, Faisal Faris, Fakhri Al Felia, Okta Ganza Handayani, Ade S Silvia Hetty Meileni Irawan Hadi Irdayanti, Yeni Irsyadi Yani Kinasih, Ayu Antika Sekar Kusumanto, Kusumanto Leni Novianti Markinashella, Deva Marniati, Yessi Meranda, Arganda Moch Hikmal Abrar1 Muslimin, Selamat Niksen Alfarizal Permatasari, Rosmalinda Plowerita, Sanyyah Pola Risma Pratama, Destra Andika Prihatini, Ekawati Putra, Yogie Dwi Rahman, M. Arief Ramadhan, M. Daffa Rasyad, Sabilal Riansyah, Rici Rizkiyanti, Shally Rossi Passarella Sepulau, Ifroh Intan Siti Chodijah Siti Nurmaini Sitompul, Carlos R Sobri, M. Ulandari, Monica Vira, Rizky Wahyu Caesarendra