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All Journal PHARMACOLOGY, MEDICAL REPORTS, ORTHOPEDIC, AND ILLNESS DETAILS (COMORBID) TRANSPUBLIKA INTERNATIONAL RESEARCH IN EXACT SCIENCES (TIRES) Jurnal Pengabdian Masyarakat Bangsa Heca Journal of Applied Sciences Malacca Pharmaceutics Leuser Journal of Environmental Studies Ekonomikalia Journal of Economics Journal of Educational Management and Learning Infolitika Journal of Data Science Grimsa Journal of Science Engineering and Technology
Ghazi Mauer Idroes
Department Of Occupational Health And Safety, Faculty Of Health Sciences, Universitas Abulyatama, Aceh Besar 23372, Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Other

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Predicting Obesity Levels with High Accuracy: Insights from a CatBoost Machine Learning Model Maulana, Aga; Afidh, Razief Perucha Fauzie; Maulydia, Nur Balqis; Idroes, Ghazi Mauer; Rahimah, Souvia
Infolitika Journal of Data Science Vol. 2 No. 1 (2024): May 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijds.v2i1.195

Abstract

This study aims to develop a machine learning model using the CatBoost algorithm to predict obesity based on demographic, lifestyle, and health-related features and compare its performance with other machine learning algorithms. The dataset used in this study, containing information on 2,111 individuals from Mexico, Peru, and Colombia, was used to train and evaluate the CatBoost model. The dataset included gender, age, height, weight, eating habits, physical activity levels, and family history of obesity. The model's performance was assessed using accuracy, precision, recall, and F1-score and compared to logistic regression, K-nearest neighbors (KNN), random forest, and naive Bayes algorithms. Feature importance analysis was conducted to identify the most influential factors in predicting obesity levels. The results indicate that the CatBoost model achieved the highest accuracy at 95.98%, surpassing other models. Furthermore, the CatBoost model demonstrated superior precision (96.08%), recall (95.98%), and F1-score (96.00%). The confusion matrix revealed that the model accurately predicted the majority of instances in each obesity level category. Feature importance analysis identified weight, height, and gender as the most influential factors in predicting obesity levels, followed by dietary habits, physical activity, and family history of overweight. The model's high accuracy, precision, recall, and F1-score and ability to handle categorical variables effectively make it a valuable tool for obesity risk assessment and classification. The insights gained from the feature importance analysis can guide the development of targeted obesity prevention and management strategies, focusing on modifiable risk factors such as diet and physical activity. While further validation on diverse populations is necessary, the CatBoost model's results demonstrate its potential to support clinical decision-making and inform public health initiatives in the fight against the global obesity epidemic.
ANALYSIS OF THE HEAVY METAL CONTENT OF LEAD AND MERCURY IN FRESHWATER SEA SHELLS IN THE RIVER KRUENG SABEE ACEH JAYA Wahyuni, Srie; Yanti, Nova; Idroes, Ghazi Mauer
PHARMACOLOGY, MEDICAL REPORTS, ORTHOPEDIC, AND ILLNESS DETAILS Vol. 2 No. 3 (2023): JULY
Publisher : Transpublika Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55047/comorbid.v2i3.1105

Abstract

Gold mining in Aceh Jaya, specifically in Gunong Ujeun, results in the discharge of waste water containing heavy metals into nearby rivers. This can negatively impact the environment, particularly through contamination by lead and mercury. These heavy metals can be toxic to aquatic life, potentially disrupting the food chain. Kijing clams, a type of shellfish commonly found in freshwater rivers, are particularly susceptible to metal accumulation due to their filter feeding behavior. This research aims to assess the impact of lead and mercury levels in the Krueng Sabe river on the accumulation of these metals in shellfish, exceeding the threshold set for the river in Aceh Jaya Regency. The study will use Atomic Absorption spectroscopy (AAS) to measure the heavy metal content. The results show that the lead content in shellfish meat is 0.191 mg/kg, while the mercury content is 0.255 mg/kg. These levels are below the maximum limits set for heavy metals in food.
ANALYSIS OF HEAVY METAL CADMIUM (CD) CONTENT IN THE IE SEU’UM HIT WATER AREA IN ACEH BESAR Wahyuni, Srie; Idroes , Ghazi Mauer; Natasya, Natasya
PHARMACOLOGY, MEDICAL REPORTS, ORTHOPEDIC, AND ILLNESS DETAILS Vol. 3 No. 1 (2024): JANUARY
Publisher : Transpublika Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55047/comorbid.v3i1.1110

Abstract

The Ie Seu'um hot springs area is located in Ie Seu'um Village, Mesjid Raya District, Aceh Besar Regency which has hot springs which are visited and used by the local community and tourists as a place for recreation with the family, a bathing place, and a place to boil food. Egg. The aim of this research is to determine and test heavy metals, namely Cadmium (Cd), which may be contained in the Ie Seu'um hot springs. The research used the AAS (Atomic Absorption Spectrophotometer) method. This research method uses a purposive sampling method, while the samples in this study were taken at spring points, namely places where people carry out egg-boiling activities and in holding tanks before the water flows into the bathing tubs. The results obtained for Cadmium (Cd) metal contained in hot springs (A) Ie Seu'um were <0.0005#) and reservoirs (B) were 0.0005#). Based on the maximum standard for Cadmium (Cd) content according to the Regulation of the Minister of Health of the Republic of Indonesia Number 2 of 2023 in the Clean Water Requirements for heavy metals, this heavy metal does not exceed the threshold and is below the detection limit of the test method. It is hoped that the results of this research can become basic information for the public and tourists to always protect the ecosystem of the Ie Seu'um hot spring area and preserve local wisdom.
Edukasi dan Pelatihan Pertolongan Pertama Pada Kecelakaan (P3K) Siswi SMA Swasta Babul Maghfirah Kabupaten Aceh Besar Seni, Wildan; Zahara, Hafni; Karma, Taufiq; Kala , Pasyamei Rembune; Idroes, Ghazi Mauer; Yustiana, Yustiana; Bako, Winanda; Wangi, Putri Ayu Sekar; Anggi, Tiara; Fauziah, Niken
Jurnal Pengabdian Masyarakat Bangsa Vol. 2 No. 4 (2024): Juni
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v2i4.958

Abstract

Kecelakaan dapat terjadi kapan saja dan dimana saja, kecelakaan merupakan suatu kejadian yang terjadi secara mendadak sehingga mengakibatkan seseorang memerlukan penanganan dan_pertolongan secara cepat dan tepat. Tujuan penyelenggaraan kegiatan edukasi dan pelatihan ini adalah sebagai penguat keterampilan sehingga peserta mendapat bekal untuk dapat diaplikasikan kepada masyarakat. Pelaksanaan kegiatan ini dilaksanakan oleh mahasiswa dan dosen prodi Keselamatan dan Kesehatan Kerja Universitas Abulyatama Aceh dan sasaran dari kegiatan ini yaitu siswi SMA Swasta Babul Maghfirah Kabupaten Aceh Besar kelas X dan XI terdiri dari 1 70 siswi. Kegiatan pengabdian di awali dengan presentasi dan tanya jawab dilanjutkan dengan simulasi dan praktek oleh peserta. Metode yang di lakukan adalah dengan memberikan pretest dan posttest kepada 31 siswi kemudian menganalisis data dari lembar jawaban tersebut apakah peserta yang mengikuti penyuluhan tersebut mengalami peningkatan pemahaman yang signifikan atau tidak. Dari hasil penyuluhan terjadi peningkatan pemahaman dari sebelum dan sesudah pelatihan, diantaranya terjadi peningkatan pemahaman mengenai pengetahuan tentang Pertolongan Pertama Pada Kecelakaan (P3K) 25,8%, peningkatan pemahaman mengenai pemanfaatan mitela dan bidai pada korban kecelakaan 80,7%, dan pengetahuan mengenai cidera kepala dan penanganannya mengalami peningkatan sebesar 54,8%. Pengetahuan tentang cidera patah dan penanganannya 61%, transportasi korban kecelakaan 35,5%. Kegiatan ini sangat bermanfaat bagi semua peserta yang hadir karena ini merupakan bentuk edukasi tentang P3K dan penanganan korban.
Embrace, Don’t Avoid: Reimagining Higher Education with Generative Artificial Intelligence Noviandy, Teuku Rizky; Maulana, Aga; Idroes, Ghazi Mauer; Zahriah, Zahriah; Paristiowati, Maria; Emran, Talha Bin; Ilyas, Mukhlisuddin; Idroes, Rinaldi
Journal of Educational Management and Learning Vol. 2 No. 2 (2024): November 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/jeml.v2i2.233

Abstract

This paper explores the potential of generative artificial intelligence (AI) to transform higher education. Generative AI is a technology that can create new content, like text, images, and code, by learning patterns from existing data. As generative AI tools become more popular, there is growing interest in how AI can improve teaching, learning, and research. Higher education faces many challenges, such as meeting diverse learning needs and preparing students for fast-changing careers. Generative AI offers solutions by personalizing learning experiences, making education more engaging, and supporting skill development through adaptive content. It can also help researchers by automating tasks like data analysis and hypothesis generation, making research faster and more efficient. Moreover, generative AI can streamline administrative tasks, improving efficiency across institutions. However, using AI also raises concerns about privacy, bias, academic integrity, and equal access. To address these issues, institutions must establish clear ethical guidelines, ensure data security, and promote fairness in AI use. Training for faculty and AI literacy for students are essential to maximize benefits while minimizing risks. The paper suggests a strategic framework for integrating AI in higher education, focusing on infrastructure, ethical practices, and continuous learning. By adopting AI responsibly, higher education can become more inclusive, engaging, and practical, preparing students for the demands of a technology-driven world.
Artificial Neural Network–Particle Swarm Optimization Approach for Predictive Modeling of Kovats Retention Index in Essential Oils Kurniadinur, Kurniadinur; Noviandy, Teuku Rizky; Idroes, Ghazi Mauer; Ahmad, Noor Atinah; Irvanizam, Irvanizam; Subianto, Muhammad; Idroes, Rinaldi
Infolitika Journal of Data Science Vol. 2 No. 2 (2024): November 2024
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/ijds.v2i2.220

Abstract

The Kovats retention index is a critical parameter in gas chromatography used for the identification of volatile compounds in essential oils. Traditional methods for determining the Kovats retention index are often labor-intensive, time-consuming, and prone to inaccuracies due to variations in experimental conditions. This study presents a novel approach combining Artificial Neural Networks (ANN) with Particle Swarm Optimization (PSO) to predict the Kovats retention index of essential oil compounds more accurately and efficiently. The ANN-PSO hybrid model leverages the strengths of both techniques: the ANN's capacity to model complex nonlinear relationships and PSO's capability to optimize hyperparameters by finding the global optimum. The model was trained using a dataset of 340 essential oil compounds with molecular descriptors, with the performance evaluated based on Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE). Results indicate that a simpler ANN configuration with one hidden neuron achieved the lowest RMSE (80.16) and MAPE (5.65%), suggesting that the relationship between the molecular descriptors and the Kovats retention index is not overly complex. This study demonstrates that the ANN-PSO model can serve as an effective tool for predictive modeling of the Kovats retention index, reducing the need for experimental procedures and improving analytical efficiency in essential oil research.
A Review of the Ethno-dentistry Activities of Calotropis gigantea Ningsih, Diana Setya; Celik, Ismail; Abas, Abdul Hawil; Bachtiar, Boy Muhclis; Kemala, Pati; Idroes, Ghazi Mauer; Maulydia, Nur Balqis
Malacca Pharmaceutics Vol. 1 No. 1 (2023): June 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v1i1.31

Abstract

Calotropis gigantea is a medicinal herb that thrives in arid climates. All parts of this plant are rich in secondary metabolites, which are very beneficial for health. Phytochemicals of this plant include flavonoid, alkaloids, steroids, cardiac glycosides, and terpenoids, which have a wide range of pharmacological effects. The potential of metabolit compound from C. gigantea can be used in dental treatment. This review describes the potential use of C. gigantea in ethno-dentistry, specifically as anti-caries, soft tissue inflammation (periodontitis and gingivitis), degenerative diseases (tumor/cancer), and wound healing. This review provides general perspectives and basic literature on the use of C. gigantea in the field of etno-dentistry.
Antimicrobial Properties of Medicinal Plants in the Lower Area of Ie Seu-um Geothermal Outflow, Indonesia Fakri, Fajar; Harahap, Saima Putri; Muhni, Akmal; Khairan, Khairan; Hewindati, Yuni Tri; Idroes, Ghazi Mauer
Malacca Pharmaceutics Vol. 1 No. 2 (2023): October 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v1i2.44

Abstract

The lower area of the Ie Seu-um manifestation, located in Ie Seu-um village, Aceh Besar District, harbors several medicinal plants that exhibit potential for the treatment of infectious diseases. This study aims to assess the secondary metabolite content and in vitro antimicrobial activity against Staphylococcus aureus, Escherichia coli, and Candida albicans of medicinal plants inhabiting the geothermal region. Medicinal plants, namely Pluchea indica (L.) Less., Acrostichum aureum L., Acacia mangium L., and Calotropis gigantea (L.) Dryand., were collected within a range of 100-150 meters from the hot springs in the lower area. Methanol extracts of these medicinal plants underwent phytochemical screening and were tested for antimicrobial activity using the Kirby-Bauer disc diffusion method at a concentration of 50%. The results of phytochemical screening demonstrated positive variations in alkaloids, flavonoids, saponins, steroids, triterpenoids, and tannins for each medicinal plant. The antimicrobial activity of the methanol extracts noticeably inhibited the growth of S. aureus compared to E. coli and C. albicans. The largest inhibition zones were observed for the leaf part of A. mangium (12.70 ± 2.30 mm) against S. aureus, the aerial part of A. aureum (11.57 ± 2.01 mm) against E. coli, and the aerial part of P. indica (9.89 ± 1.11 mm) against C. albicans. Based on the research findings, medicinal plants originating from the lower area of the Ie Seu-um manifestation exhibit potential as antimicrobial agents, particularly against gram-positive bacteria.
Integrating Genetic Algorithm and LightGBM for QSAR Modeling of Acetylcholinesterase Inhibitors in Alzheimer's Disease Drug Discovery Noviandy, Teuku Rizky; Maulana, Aga; Idroes, Ghazi Mauer; Maulydia, Nur Balqis; Patwekar, Mohsina; Suhendra, Rivansyah; Idroes, Rinaldi
Malacca Pharmaceutics Vol. 1 No. 2 (2023): October 2023
Publisher : Heca Sentra Analitika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60084/mp.v1i2.60

Abstract

This study explores the use of Quantitative Structure-Activity Relationship (QSAR) studies using genetic algorithm (GA) and LightGBM to search for acetylcholinesterase (AChE) inhibitors for Alzheimer's disease. The study uses a dataset of 6,157 AChE inhibitors and their IC50 values. A LightGBM model is trained and evaluated for classification performance. The results show that the LightGBM model achieved high performance on the training and testing set, with an accuracy of 92.49% and 82.47%, respectively. This study demonstrates the potential of GA and LightGBM in the drug discovery process for AChE inhibitors in Alzheimer's disease. The findings contribute to the drug discovery process by providing insights about AChE inhibitors that allow more efficient screening of potential compounds and accelerate the identification of promising candidates for development and therapeutic use.
Penyuluhan Penanggulangan Kebakaran Menggunakan Karung Goni/Handuk Basah Pada Siswa SMA Swasta Babul Maghfirah Kabupaten Aceh Besar Seni, Wildan; Zahara, Hafni; Karma, Taufiq; Raisah, Putri; Idroes, Ghazi Mauer; Shofi, Shofi; Muksin, Muksin; Mirja, Mirja; Purnama, M. Risky; Jainury, Aldi; Diki, Diki; Irwana, Salman; Ifandi, Ilham; Jauna, Jauna; Sabri, Muhammad
Jurnal Pengabdian Masyarakat Bangsa Vol. 2 No. 10 (2024): Desember
Publisher : Amirul Bangun Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59837/jpmba.v2i10.1751

Abstract

Penyebab kebakaran selain karena faktor alam juga karena faktor manusia terutama kelalaian dan juga ketidaksiapan menghadapi kebakaran. Pelaksanaan Pengabdian Masyarakat ini dilatarbelakangi oleh kejadian kebakaran pada Pesantren Babul Maghfirah Kabupaten Aceh Besar pada tanggal 25 Januari 2024 sehingga kegiatan penyuluhan ini sangat relevan dilaksanakan di SMA Swasta Babul Maghfirah yang merupakan bagian dari Pesantren tersebut. Pelaksanaan kegiatan ini dilaksanakan oleh mahasiswa dan dosen prodi Keselamatan dan Kesehatan Kerja Universitas Abulyatama Aceh dengan jumlah peserta sebanyak 185 orang. Metode yang di lakukan adalah dengan memberikan pretest dan posttest kemudian menganalisis data dari lembar jawaban tersebut apakah peserta yang mengikuti penyuluhan tersebut mengalami peningkatan pemahaman yang signifikan atau tidak mengenai api, penyebab kebakaran dan cara penggunaan karung goni/handuk basah sebagai alat penanggulangan kebakaran. Sebelum diadakan kegiatan penyuluhan ini, para peserta kurang memahami tentang api dan kebakaran serta cara penanggulangannya. Kegiatan pelatihan ini dimulai dari pemaparan materi, praktek penggunaan karung goni/handuk basah untuk memadamkan kebakaran, dan terakhir adalah tanya jawab. Dari hasil penyuluhan terjadi peningkatan pemahaman sebelum dan sesudah penyuluhan, diantaranya terjadi peningkatan pemahaman mengenai konsep segitiga api sebesar 63,3%, peningkatan pemahaman pengetahuan penyebab atau pemicu kebakaran sebesar 36,7%, dan pemahaman pengetahuan penggunaan karung goni/handuk basah sebagai alat penanggulangan kebakaran mengalami peningkatan sebesar 53,3%. Kegiatan ini sangat bermanfaat bagi semua peserta yang hadir karena ini merupakan bentuk edukasi tentang kejadian kebakaran yang memang pernah dialami Pesantren tersebut.
Co-Authors Abas, Abdul Hawil Abd Rahman, Sunarti Ahmad, Noor Atinah Akmal Muhni Alfizar Alfizar Ali Bakri Anggi, Tiara Aprianto . Arkadinata, Teguh Asep Rusyana Azhar, Fauzul Bachtiar, Boy Muhclis Bahri, Ridzky Aulia Bako, Winanda Celik, Ismail Diah, Muhammad Diana Setya Ningsih, Diana Diana Setya Ningsih, Diana Setya Diki, Diki Eko Suhartono El-Shazly, Mohamed Emran, Talha Bin Faisal, Farassa Rani Fajar Fakri Fauziah, Niken Fazli, Qalbin Salim Hafni Zahara Harahap, Saima Putri Harera, Cheariva Firsa Hewindati, Yuni Tri Hizir Sofyan Idroes, Ghalieb Mutig Ifandi, Ilham Imelda, Eva Irvanizam, Irvanizam Irwana, Salman Jainury, Aldi Jauna, Jauna Kemala, Pati Khairan Khairan Khalijah Awang Kurniadinur, Kurniadinur Kusumo, Fitranto Lala, Andi Lukman Hakim Maria Paristiowati Marwan Marwan Maulana, Aga Maulydia, Nur Balqis Maysarah, Hilda Medyan Riza Mirda, Erisna Mirja, Mirja Misbullah, Alim Muhammad Adam, Muhammad Muhammad Ichsan Muhammad Ichsan Muhammad Sabri Muhammad Subianto Muhammad Yanis Muhammad Yusuf Mukhlisuddin Ilyas Muliadi Ramli Muslem Muslem, Muslem Musvira, Intan Natasya Natasya Nizamuddin Nizamuddin Nova Yanti Pasyamei Rembune Kala Patwekar, Mohsina Prasetio, Rasi Purnama, M. Risky Putri Raisah Raisah, Putri Raudhatul Jannah Razief Perucha Fauzie Afidh Rinaldi Idroes Rizkia, Tatsa Sasmita, Novi Reandy Shofi, Shofi Siti Maulina Rukmana Souvia Rahimah Suhendra , Rivansyah Suhendra, Rivansyah Suhendrayatna Suhendrayatna Surna, Muhammad Ipan Susanna Susanna Syamsiar, Syamsiar Taufiq Karma Teuku Rizky Noviandy Teuku Zulfikar Tjut Chamzurni TRINA EKAWATI TALLEI Wahyuni, Srie Wangi, Putri Ayu Sekar Wildan Seni, Wildan Wiwik Handayani Yandri, Erkata Yustiana Yustiana, Yustiana Zahriah, Zahriah Zuchra Helwani, Zuchra Zulkarnain Jalil