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EFFECT OF BABY MASSAGE AND KANGAROO MOTHER CARE TO WEIGHT GAIN ON LOW BIRTH WEIGHT (LBW) Arief, Windhy Lathifah; Rita, Rauza Sukma; Oktova, Rafika
Indonesian Journal for Health Sciences Vol 8, No 2 (2024): September
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/ijhs.v8i2.6813

Babies with low birth weight (LBW) require more complex treatments. Baby massage and kangaroo method treatment are additional treatments that can be given so that babies experience weight gain. Weight gain is an indicator of growth in babies with LBW. This study aims to determine the effect of infant massage and kangaroo methods on weight gain in LBW babies. Method: Narrative literature review through databases: ScienceDirect, PubMed and Google Scholar using inclusion and exclusion criteria. Results: 20 journals were obtained for analysis. Baby massage carried out by parents for 7 days (3 times a day, for 15 minutes) affected weight gain in low birth weight babies with an average weight gain of 15 grams/day. The kangaroo method, for a minimum of 4-6 hours and carried out directly by the baby's mother, had a more significant effect on weight gain in low birth weight babies with an increase of 6 grams/day. Infant massage interventions and kangaroo methods also had a better effect on weight gain in babies with low birth weight with an average weight gain of 11-23 gr/day. This study concludes that infant massage and kangaroo methods affect weight gain in babies born with LBW.

Analisa Detak Jantung dengan Metode Heart Rate Variability (HRV) untuk Pengenalan Stres Mental Berbasis Photoplethysmograph (PPG) Novani, Nefy Puteri; Arief, Lathifah; Anjasmara, Rima
JITCE (Journal of Information Technology and Computer Engineering) Vol. 3 No. 02 (2019)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.3.02.90-95.2019

Emotions influence individual behavior and there is no emotional experience that has a stronger influence than stress. Prolonged stress has a direct negative influence on physical and emotional conditions. For that reason, it is important to know a person's mental stress state, so that further action can be taken later, so as not to have a serious impact on physical and mental health. In this study, the photoplethysmograph (PPG) approach is used to recognize mental stress conditions based on Heart Rate Variability (HRV) frequency domain analysis. In this study stress was identified by SVM classifier using LF, HF and LF / HF Ratio from HRV frequency domain analysis. The LF results were increased in mild stress conditions, HF increased in conditions of mild stress and medium stress and the LF / HF Ratio slowly increased from mild stress to severe stress. The training data obtained 80 data with 95% mild stress accuracy from 19 data, medium stress accuracy 96% from 49 data and 99% severe stress accuracy with 12 data.

Sistem Pendeteksi Gejala Awal Tantrum Pada Anak Autisme Melalui Ekspresi Wajah Dengan Convolutional Neural Network Novani, Nefy Puteri; Salsabila, Dini Ramadhani; Aisuwarya, Ratna; Arief, Lathifah; Afriyeni, Nelia
JITCE (Journal of Information Technology and Computer Engineering) Vol. 5 No. 02 (2021)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jitce.5.02.93-106.2021

Tantrums are outbursts of anger and they can occur at any age. An attitude tantrum or what is commonly referred to as a temper tantrum is a child's outburst of anger that often occurs when a child shows negative behavior. Emotional outbursts of tantrums that occur in children with autism are not only to seek the attention of adults, but also as an outlet for a child's feelings for parents and those around him on a whim or feeling he is feeling, but the child cannot convey it. For this reason, researchers propose a system for detecting early symptoms of tantrums in children with autism through facial expressions with CNN. The CNN method is one of the deep learning methods that can be used to recognize and classify an object in a digital image. Then the preprocessing process is carried out using labeling on the data. Then the CNN architecture is designed with input containing 48x48x1 neurons. The data was then trained using 357 epochs with an accuracy rate of 72.67%%. Then tested using test data for children with autism to get an average accuracy value of 72.67%%.

Evaluation of Cloud-Based Ethereum Network Performance Sundara, Tri; Arief, Lathifah
The Indonesian Journal of Computer Science Vol. 11 No. 3 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/IJCS.V10I2.446

Ethereum, that enable development of decentralized applications, will likely to leverage cloud computing. In this research, we evaluate the performance of a cloud-based Ethereum network. We researched 3 Ethereum networks, namely: Ethereum mainnet, Ethereum testnet Ropsten, and Ethereum testnet Rinkeby. We analyze the computational resource utilization required to run an Ethereum node for a month as well as the costs involved. Research shows that the utilization of computing resources on the Main Net is generally higher than on the Test Net network. Computing resources used in the cloud cost thousands of dollars and this will increase as the number of nodes running to support the Ethereum network.

EFFECT OF BABY MASSAGE AND KANGAROO MOTHER CARE TO WEIGHT GAIN ON LOW BIRTH WEIGHT (LBW) Arief, Windhy Lathifah; Rita, Rauza Sukma; Oktova, Rafika
Indonesian Journal of Health Science Vol 8 No 2 (2024): September
Publisher : Universitas Muhammadiyah Ponorogo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24269/ijhs.v8i2.6813

Babies with low birth weight (LBW) require more complex treatments. Baby massage and kangaroo method treatment are additional treatments that can be given so that babies experience weight gain. Weight gain is an indicator of growth in babies with LBW. This study aims to determine the effect of infant massage and kangaroo methods on weight gain in LBW babies. Method: Narrative literature review through databases: ScienceDirect, PubMed and Google Scholar using inclusion and exclusion criteria. Results: 20 journals were obtained for analysis. Baby massage carried out by parents for 7 days (3 times a day, for 15 minutes) affected weight gain in low birth weight babies with an average weight gain of 15 grams/day. The kangaroo method, for a minimum of 4-6 hours and carried out directly by the baby's mother, had a more significant effect on weight gain in low birth weight babies with an increase of 6 grams/day. Infant massage interventions and kangaroo methods also had a better effect on weight gain in babies with low birth weight with an average weight gain of 11-23 gr/day. This study concludes that infant massage and kangaroo methods affect weight gain in babies born with LBW.

Condition Monitoring System and Automatic Air Cleaning in the Toilet of Firebase-Based Andalas University Lecture Building Multri Okta Ilham, Randa; Hadelina, Rizka; Hersyah, Mohammad Hafiz; Arief, Lathifah
CHIPSET Vol. 6 No. 02 (2025): Journal on Computer Hardware, Signal Processing, Embedded System and Networkin
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/chipset.6.02.117-123.2025

Maintaining the cleanliness and comfort of toilets in lecture buildings is very important for the quality of the campus environment. This study develops a Firebase-based Automatic Air Condition Monitoring and Cleaning System in the restrooms of Andalas University lecture halls. The main problem identified is the lack of direct monitoring, which leads to the appearance of unpleasant odors and potential health problems. A survey showed that 64.8% of respondents sometimes felt unpleasant odors, while 59.3% indicated a lack of adequate air circulation.To solve this problem, the designed system is able to detect and monitor toilet conditions in real-time through gas measurements such as ammonia, hydrogen sulfide, and carbon monoxide using MQ-135, MQ-136, and MQ-7 sensors, the results of which can be monitored through a website. The system not only monitors, but also controls air quality by turning on the exhaust fan when the gas level exceeds a certain. Tests show that the system is accurate in detecting gas, with sensor precision above 90% and an average data transmission time of 1.74 seconds. However, the humidity measurement showed an error rate of 32.36%. The system effectively improves the hygiene monitoring of restrooms, thereby improving comfort and health on campus

Portable Cough Classification System Based on Sound Feature Extraction Using Tiny Machine Learning Arief, Lathifah; Risky, Mutiah; Derisma; Kasoep, Werman; Puteri, Nefy
The Indonesian Journal of Computer Science Vol. 11 No. 1 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v10i2.3001

Cough is one of the most common markers that can provide information in diagnosing a disease. More specifically, cough is a common symptom of many respiratory infections. There are several types of cough, including: dry cough, wet cough (cough with phlegm), croup cough and whooping cough. This study aims to create a system that can classify the sounds of coughing up phlegm, dry cough, whooping cough and croup cough. The system development uses the concept of tiny machine learning. In the system built, Arduino Nano 33 BLE Sense is used as a control device and LED is used as an output device. In this study, the classification of dry cough, wet cough, croup cough and whooping cough was performed using the MFCC voice feature extraction. In the process of classifying coughing sounds using the Neural Network Classifier, the system has a percentage of dataset training accuracy from a total of 5 classes (croup, dry, noise, wet, whooping) of 97.1% by applying an epoch value of 500, window size 3000ms and a window increase of 500ms.

Penerapan YOLO Untuk Identifikasi Dan Penayangan Informasi Peralatan Laboratorium Dalam Mendukung Merdeka Belajar Arief, Lathifah; Muhammad, Fauzan
The Indonesian Journal of Computer Science Vol. 11 No. 1 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v10i2.3015

Computer Laboratory serves as the place to conduct experimentation in regards to Computer System. During the practical or experimentation, it is not rare to see the confusion or misunderstanding of what to do or what is needed. This problem comes from lack of knowledge and how one or more dsvice is identical to another. With the development of technology, the new method using machine learning is made for soving these problems. The system with You Only Look Once method will detect the device on camera, and then showing the file that contains datasheet explaining what that device is and how to use it. This system can also be used at anytime so everyone can learn through it and improves the efficieny of the study.

Utilizing Machine Learning and Cloud Services to Improve Disaster Information Systems Arief, Lathifah; Sundara, Tri
The Indonesian Journal of Computer Science Vol. 11 No. 1 (2022): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v11i1.3090

Cloud services have enabled various information system developments. In this paper, we explore the use of Amazon Sagemaker cloud services and AWS Data Exchange in disaster information systems. We proposed cloud architecture for a disaster information system and found some of the datasets provided on AWS Data Exchange could be leveraged for such system.

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