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All Journal Indonesian Journal of Tropical and Infectious Disease Jurnal Pengabdian Magister Pendidikan IPA Indonesian Physical Review Indonesian Journal of Electrical Engineering and Computer Science Indonesian Applied Physics Letters ABSYARA: Jurnal Pengabdian Pada Masyarakat Jurnal Info Sains : Informatika dan Sains
Alfian Pramudita Putra
Bachelor Of Biomedical Engineering Study Program, Faculty Of Science & Technology, Universitas Airlangga, Surabaya
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Physics Public Health Other

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The Utilization of Achatina fulica Mucus in Alginate Membrane as Wound Healing Accelerator and Anti- Infection Material Rahmawati, Fatkhunisa; Mayasari, Dita Ayu; Adhitioso, Satrio; Putra, Alfian Pramudita; Kuntjoro, Eko Budi; Widiyanti, Prihartini
Indonesian Journal of Tropical and Infectious Disease Vol 5, No 1 (2014)
Publisher : Institute of Topical Disease

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

Abstract

Wound should be covered with bandage that is called wound dressing. Most people use synthetic materials such as gauze dressing. Gauze has high absorption of NaCl, which is often used to cleanse the wound. However, discomfort and pain arise since the gauze becomes sticky on the wound. Therefore, we need other alternatives instead of gauze to cover wound. One such alternative is the alginate membrane. This study used alginate membrane with mixture of mucous of the snail Achatina fulica, which contain proteins such as proline, serine asparagine, glycosaminoglycan, hydroxylysine, trionin and so forth, to activate the growth factor. Alginatepowder and carboxymethl cellulose (CMC) was dissolved in distilled water mixed with mucus of the snail Achatina fulica in four variations (4:0; 4:1, 4:2, 4:3) through a magnetic stirrer, and casted on a baking sheet covered with sterile gauze. High Performance Liquid Chromatography (HPLC) test showed that the glycosaminoglycan content was found on the mucous of Achatina fulica. This was indicated by the appearance of peak at 325–350 second. The most optimum alginate and mucus composition was in ratio of 4:2. This ratio resulted in a wound dressing that was still able to absorb the exudate and optimally accelerated wound healing.
Pelatihan Rancang Bangun Alat Deteksi Kelelahan Berbasis Audiovisual untuk Meningkatkan Kualitas Kerja Dan Kesehatan di SMK 3 Pancasila Kecamatan Ambulu Kabupaten Jember Provinsi Jawa Timur Khusnul Ain; Riries Rulaningtyas; Alfian Pramudita Putra
Jurnal Pengabdian Magister Pendidikan IPA Vol 4 No 1 (2021)
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (213.173 KB) | DOI: 10.29303/jpmpi.v4i1.594

Abstract

Kelelahan adalah salah satu permasalahan serius yang sering dialami pekerja sehingga bisa mengancam nyawa jika kurang mendapat perhatian. Organisasi Buruh Dunia melaporkan sebanyak 2 juta/tahun pekerja melayang nyawanya akibat kecelakaan kerja yang disebabkan oleh kelelahan.  Di Indonesia jumlah kecelakaan kerja mengalami peningkatan tiap tahunnya hingga 5%. Data dari BPJS ketenagakerjaan menunjukkan bahwa pada tahun 2016 terjadi 116.850 kasus kecelakaan kerja sedangkan pada tahun 2017 jumlah kasus meningkat menjadi 123.000 kasus. Banyak penelitian menunjukkan bahwa kelelahan adalah salah satu faktor yang berkontribusi sebagai penyebab kecelakaan. Salah satu cara untuk mengurangi resiko tersebut adalah mengukur kelelahan yang dialami pekerja. Kelelahan dapat dideteksi dengan mengukur waktu respon terhadap rangsangan yang diberikan. Waktu respon umpan balik sebagai tanggapan dari rangsangan yang diberikan merupakan parameter utama yang digunakan untuk menentukan tingkat kelelahan seseorang. Berdasarkan analisis situasi tersebut, maka melalui kegiatan pengabdian masyarakat Program Kemitraan Masyarakat ini, dapat diberikan bekal keahlian kepada siswa Sekolah Menengah Kejuruan (SMK) yang sudah memiliki bekal keilmuan elektronika dasar dan mikrokontroller untuk diberikan pelatihan pembuatan alat kesehatan dengan mempelajari dan mengembangkan instrumentasi medis sederhana berbasis elektronika dan mikrokontroller sederhana yaitu alat ukur tingkat kelelahan pekerja. Para siswa SMK diharapkan setelah lulus mampu mengembangkan produksi dan pengadaan alat kesehatan secara mandiri di Indonesia. Hasil kegiatan pengabdian masyarakat terlihat bahwa peserta pelatihan sangat antusias terhadap pelaksanaan kegiatan karena mendapatkan pengetahuan baru terkait dasar elektronika dan mikrokontroler
Pelatihan Rancang Bangun Sistem Monitoring Kondisi Air Tambak Berbasis Internet of Things (IoT) di SMK Perikanan dan Kelautan Kecamatan Puger Kabupaten Jember Alfian Pramudita Putra; Riries Rulaningtyas; Franky Chandra Satria Arisgraha
Jurnal Pengabdian Magister Pendidikan IPA Vol 4 No 4 (2021)
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (425.918 KB) | DOI: 10.29303/jpmpi.v4i4.1007

Abstract

Kualitas air tambak atau kolam budidaya ikan atau udang merupakan aspek eksternal yang harus diperhatikan. Permasalahan utama dalam kegagalan produksi ikan atau udang adalah buruknya kualitas air selama masa pemeliharaan, terutama pada tambak intensif. Sebagian besar pekerjaan monitoring telah dibantu teknologi informasi untuk memudahkan dalam pelaksanaan pemantauan. Salah satunya adalah dengan penggunaan Internet of Things (IoT). Sistem IoT ini dapat digunakan para petambak untuk memantau kondisi perarian tambak sehingga produksi mereka bisa meningkat. Melalui kegiatan pengabdian masyarakat Program Kemitraan Masyarakat ini, sistem yang dapat memantau suhu dan pH dari perariran secara kontinu telah dibuat dengan memanfaatkan IoT. Hal ini bermanfaat untuk para siswa SMK sehinga mereka dapat meningkatkan kemampuan di bidang teknologi yang tetap berkaitan dengan perikanan dan kelautan. Peserta pelatihan sangat antusias terhadap pelaksanaan kegiatan karena mendapatkan pengetahuan baru terkait mikrokontroler dan IoT. Selain itu, Siswa SMK dapat memiliki tambahan kemampuan dan pengetahuan yang berguna untuk bersaing di dunia kerja, khususnya pada era revolusi industri 4.0.
Pelatihan pembuatan sensor medis berbasi IoT sebagai pengenalan smart medical devices Riries Rulaningtyas; Alfian Pramudita Putra; Osmalina Nur Rahma; Katherine Katherine; I Made Mas Dwiyana Prasetya Wibawa; Kezia Sarahsophia Immanuel Ryadi
ABSYARA: Jurnal Pengabdian Pada Masayarakat Vol 4 No 1 (2023): ABSYARA: Jurnal Pengabdian Pada Masyarakat
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/ab.v4i1.6989

Abstract

Cardiovascular disease (CVD) is a leading cause of death globally, resulting in approximately 17.9 million deaths each year (WHO, 2017), with estimates projecting a rise to 23.3 million deaths by 2030 (Pusdatin Kemenkes RI, 2014). Early detection of heart disease plays a crucial role in CVD prevention, with heart rate (bpm) being a key indicator to assess heart function, ranging from 60 to 100 beats per minute. To address the need for early detection, a practical heart rate monitoring device utilizing the Internet of Things (IoT) and Smart Medical Devices (SMDs) was developed. This research aimed to provide training on IoT-based heart rate detection to high school students in Trenggalek. The training encompassed lectures and hands-on practice, successfully enhancing participants' knowledge of IoT, as demonstrated by improved test scores. Moreover, the training resulted in a prototype of an IoT-based heart rate monitoring system that utilizes Arduino and a heart rate sensor. Post-training evaluations showed the majority of participants were satisfied with the quality of materials and organization, indicating the positive impact of this engagement on the partners. The results support the potential of this IoT training to equip high school students with essential skills, fostering self-reliance in medical device production and reducing dependence on imports in the face of ASEAN Economic Community challenges. Ultimately, this initiative contributes to building a competent healthcare workforce in Indonesia.
Application of ANFIS-based Non-Linear Regression Modelling to Predict Concentration Level in Concentration Grid Test as Early Detection of ADHD in Children Sayyidul Istighfar Ittaqillah; Delfina Amarissa Sumanang; Quinolina Thifal; Akila Firdausi Harahap; Akif Rahmatillah; Alfian Pramudita Putra; Riries Rulaningtyas; Osmalina Nur Rahma, S.T., M.Si.
Indonesian Applied Physics Letters Vol. 4 No. 1 (2023): June
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/iapl.v4i1.48153

Abstract

Concentration is the main asset for students and serves as an indicator of successful learning implementation. One of the abnormal disturbances that can occur in a child's concentration development is attention deficit hyperactivity disorder (ADHD). The prevalence of ADHD in Indonesia in 2014 reached 12.81 million people due to delayed management in addressing ADHD. Therefore, early detection of ADHD is necessary for prevention. ADHD detection can be done by testing the level of concentration using a concentration grid. However, a method is needed that can be applied to uncooperative young children who are not familiar with numbers. Therefore, research was conducted with an innovative approach using a combination of EEG-ECG to classify concentration levels. The data used in this study were primary data from 4 participants with 5 repetitions. The data were processed in the preprocessing stage, which involved noise filtering and Butterworth filtering. The features used in this study were BPM (beats per minute), alpha, theta, and beta EEG signals, which would later become inputs for the Adaptive Neuro-Fuzzy Inference System (ANFIS). The output shows that the combination of EEG-ECG has the potential to predict concentration test results. Using BPM, alpha, theta, and beta signals can serve as parameters for predicting the concentration grid test values using ANFIS effectively. In the ANFIS model with 4 features, an accuracy of 99.997% was obtained for the training data and 80.2142% for the testing data. This result could be developed for early detection of ADHD based on concentration levels so the learning implementation could be more effective.
Brain-computer interface-based hand exoskeleton with bidirectional long short-term memory methods Osmalina Nur Rahma; Khusnul Ain; Alfian Pramudita Putra; Riries Rulaningtyas; Khouliya Zalda; Nita Lutfiyah; Nafisa Rahmatul Laili Alami; Rifai Chai
Indonesian Journal of Electrical Engineering and Computer Science Vol 34, No 1: April 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v34.i1.pp173-185

Abstract

It takes at least 3 months to restore hand and arm function to 70% of its original value. This condition certainly reduces the quality of life for stroke survivors. The effectiveness in restoring the motor function of stroke survivors can be improved through rehabilitation. Currently, rehabilitation methods for post-stroke patients focus on repetitive movements of the affected hand, but it is often stalled due to the lack of professional rehabilitation personnel. This research aims to design a brain-computer interface (BCI)-based exoskeleton hand motion control for rehabilitation devices. The Bidirectional long short-term memory (Bi-LSTM) method performs motion classification for the ESP32 microcontroller to control the movement of the DC motor on the exoskeleton hand in real-time. The statistical features, such as mean and standard deviation from the sliding windows process of electroencephalograph (EEG) signals, are used as the input for Bi-LSTM. The highest accuracy at the validation stage was obtained in the combination of mean and standard deviation features, with the highest accuracy of 91% at the offline testing stage and reaching an average of 90% in real-time (80%-100%). Overall, the control system design that has been made runs well to perform movements on the hand exoskeleton based on the classification of opening and grasping movements.
Automatic Detection of Escherichia coli Bacteria from Tryptic Soy Agar Image Using Deep Learning Method Yonanda, Yusril Putra; Putra, Alfian Pramudita; Purwanti, Endah
Indonesian Applied Physics Letters Vol. 4 No. 2 (2023): December
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/iapl.v4i2.46793

Abstract

Escherichia coli is a normal bacterial flora that lives in the human intestine, is harmless and is part of a healthy digestive tract. However, there are several strains of pathogenic Escherichia coli that can cause infections in the digestive tract, namely diarrhea. Diarrheal disease in Indonesia needs treatment and study because most of the diagnoses are still based on clinical diagnosis. Conventional methods used for the detection of Escherichia coli bacteria include culture methods, biochemical tests, and serological tests. This method has the disadvantage of requiring a long time, a large number of samples, and a relatively high error in reading the results. Therefore, the detection process needs to be done automatically using the Faster R-CNN deep learning method. In this research, we used Faster R-CNN with Inception v2 and ResNet-50 architecture and added augmentation and Image Enhancement to the Tryptic Soy Agar image dataset. The test results show that the addition of Image Enhancement greatly affects model performance and the model that has the best performance and is most appropriate to use is the Faster R-CNN ResNet-50 architecture with the addition of Contrast Stretching and Gaussian Filters to the image dataset. This model has 91% accuracy, 90% precision, 95% recall, and 92% F-1 score.
The Utilization of Achatina fulica Mucus in Alginate Membrane as Wound Healing Accelerator and Anti- Infection Material Rahmawati, Fatkhunisa; Mayasari, Dita Ayu; Adhitioso, Satrio; Putra, Alfian Pramudita; Kuntjoro, Eko Budi; Widiyanti, Prihartini
Indonesian Journal of Tropical and Infectious Disease Vol. 5 No. 1 (2014)
Publisher : Institute of Topical Disease Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (444.895 KB) | DOI: 10.20473/ijtid.v5i1.209

Abstract

Wound should be covered with bandage that is called wound dressing. Most people use synthetic materials such as gauze dressing. Gauze has high absorption of NaCl, which is often used to cleanse the wound. However, discomfort and pain arise since the gauze becomes sticky on the wound. Therefore, we need other alternatives instead of gauze to cover wound. One such alternative is the alginate membrane. This study used alginate membrane with mixture of mucous of the snail Achatina fulica, which contain proteins such as proline, serine asparagine, glycosaminoglycan, hydroxylysine, trionin and so forth, to activate the growth factor. Alginatepowder and carboxymethl cellulose (CMC) was dissolved in distilled water mixed with mucus of the snail Achatina fulica in four variations (4:0; 4:1, 4:2, 4:3) through a magnetic stirrer, and casted on a baking sheet covered with sterile gauze. High Performance Liquid Chromatography (HPLC) test showed that the glycosaminoglycan content was found on the mucous of Achatina fulica. This was indicated by the appearance of peak at 325–350 second. The most optimum alginate and mucus composition was in ratio of 4:2. This ratio resulted in a wound dressing that was still able to absorb the exudate and optimally accelerated wound healing.
Design Of A Fiber Optic Sensor-Based Respiration Monitoring System Qulub, Fitriyatul; Alvie Aditya, Shabrina; Ama, Fadli; Pramudita Putra, Alfian
Jurnal Info Sains : Informatika dan Sains Vol. 14 No. 03 (2024): Informatika dan Sains , Edition July - September 2024
Publisher : SEAN Institute

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Abstract

Human breathing rate is an essential marker for assessing one's health, especially regarding respiratory issues. Precise breathing measurements are vital in medicine as they help detect problems early and devise effective treatment plans. The use of fiber optic sensors to monitor breathing offers excellent potential in health monitoring, both medically and independently. Such sensors have advantages such as ease of manufacturing, high sensitivity, compact size, and affordable cost. In this study, a Singlemode-Multimode-Singlemode (SMS) optical fiber-based breathing sensor was designed by fitting it as a belt around the abdomen to measure abdominal breathing. This SMS sensor has variations in multimode length and wavelength used. Tests were conducted in sitting and standing positions, and the results showed the best performance of the SMS sensor at a multimode length of 3.5 cm with an accuracy rate of 99.2525%, linearity of 0.9997, and sensitivity of 2.9725 Hz/dBm. In addition, the standing body position provides 96.5% accuracy with a multimode length of 3.5 cm, while the sitting position provides 96.8% accuracy with a multimode length of 2 cm.
THE APPLICATION OF PLASTIC FIBER OPTIC SENSOR AS BLOOD PRESSURE MONITORING Fadli Ama; Agus Muhamad Hatta; Katherin Indriawati; Frans R Agustiyanto; Shofi Afghania Usamah; Alfian Pramudita Putra; Sigit Dani Perkasa
Indonesian Physical Review Vol. 8 No. 1 (2025)
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/ipr.v8i1.395

Abstract

Continuous blood pressure monitoring is essential for early hypertension prevention and cardiovascular disease diagnosis. Traditional methods are unsuitable for long-term use due to discomfort and limited portability. This study presents a tapered plastic fiber optical sensor (PFOS) as a sustainable, non-invasive solution for continuous monitoring. The PFOS system employs a light modulator based on mechanical waves to detect arterial pressure changes, utilizing an infrared light source (940 nm). The cuffless design includes four configurations: Bend, Bend with 1 Scratch, Bend with 3 Scratches, and Straight with 3 Scratches. The Bend with 1 Scratch configuration demonstrated superior performance, achieving 99.84% accuracy, a mean absolute error (MAE) of 0.1564, a linearity of 0.9999, and a sensitivity of 2.9997 Hz/dBm. Experimental validation involved testing radial and brachial arteries. Blood pressure estimates from Pulse Transit Time (PTT) were compared to a standard sphygmomanometer. On the radial artery, the Bend with 1 Scratch configuration achieved the best results, with the lowest MAE (1.72 for SBP, 2.39 for DBP) and highest accuracy (98.30% for SBP, 96.56% for DBP). The Straight with 3 Scratches configuration performed best on the brachial artery, with an MAE of 2.81 for SBP and 5.11 for DBP, and accuracies of 97.21% for SBP and 92.67% for DBP. The PFOS system offers a promising option for continuous monitoring in clinical and home settings.  
Co-Authors Agus Muhamad Hatta Akila Firdausi Harahap Alvie Aditya, Shabrina Ama, Fadli Delfina Amarissa Sumanang Dita Ayu Mayasari, Dita Ayu Eko Budi Kuntjoro, Eko Budi Fadli Ama Fatkhunisa Rahmawati, Fatkhunisa Fitriyatul Qulub Franky Chandra Satria Arisgraha Frans R Agustiyanto I Made Mas Dwiyana Prasetya Wibawa Katherin Indriawati Katherine Katherine Kezia Sarahsophia Immanuel Ryadi Khouliya Zalda Khusnul Ain Nafisa Rahmatul Laili Alami Nita Lutfiyah Osmalina Nur Rahma Prihartini Widiyanti Quinolina Thifal Rahmatillah, Akif Rifai Chai Riries Rulaningtyas Satrio Adhitioso Sayyidul Istighfar Ittaqillah Shofi Afghania Usamah Sigit Dani Perkasa Solly Aryza Yonanda, Yusril Putra