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All Journal Jurnal Abmas Negeri (JAGRI) Public Health and Safety International Journal (PHASIJ) Journal of Training and Community Service Adpertisi West Science Social and Humanities Studies JIMAD : Jurnal Ilmiah Multidisiplin Journal of Tecnologia Quantica Journal of Biomedical and Techno Nanomaterials Journal of World Future Medicine, Health and Nursing Journal Emerging Technologies in Education
Dito Anurogo
Universitas Muhammadiyah Makassar
Religion Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Dentistry Economics, Econometrics & Finance Education Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Physics Public Health Social Sciences Veterinary Other

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Edukasi Pemulihan Ekonomi Rumah Tangga dari Dampak Pandemi Covid-19 pada Disabilitas Desa Lamanda Kabupaten Bulukumba Sulawesi Selatan (PKM) Agusdiwana Suarni; Dito Anurogo; Faidul Adziem; Muhammad Nur Abdi; Andi Arifwangsa Adiningrat
JOURNAL OF TRAINING AND COMMUNITY SERVICE ADPERTISI (JTCSA) Vol. 1 No. 1 (2021): Okt 2021
Publisher : ADPERTISI

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1024.747 KB)

Abstract

Rumah tangga berasal dari sebuah keluarga. Keluarga berperan penting dalam pembangunankarakter anggotanya, tumbuh dalam keluarga yang harmonis adalah cita-cita semua orang,karna keluarga yang harmonis adalah awal dari peradaban masyarakat yang maju. Tapisayangnya tidak semua orang bisa merasakan hal tersebut. Masalah ekonomi merupakanpenyebab retaknya rumah tangga di banyak negara termasuk Indonesia. Negara Wuhan adalahnegara yang pertama kali terjangkit penyakit Covid-19 sejak 31 Desember 2019 (Sumber BBC2020), sehingga semua negara merasakan dampaknya dan salah satunya Indonesia, menyikapipernyataan WHO tentang wabah Covid-19 yang dinyatakan sebagai pandemi yang mejadimasalah global. Bagaimana halnya dengan Bapak/ibu yang telah berkeluarga dan merekaberkebutuhan khusus (disabilitas), apakah mereka dapat bertahan hidup dengan adanyapandemik ini khususnya dalam memenuhi kebutuhan hidupnya berdasarkan berita pedomanrakyat (2019) di kabupaten Bulukumba ada sekitar 1.223 penyandang catat. Olehnya itu,kegiatan pengabdian kepada masyarakat (PKM) ini bertujuan untuk memberikan edukasipemulihan Ekonomi rumah tangga dari dampak Pandemik Covid-19 bagi disabilitas di DesaLamanda Kabupaten Bulukumba Sulawesi Selatan. Metode yang di gunakan yakni memberikanedukasi dengan modul Ekonomi Rumah Tangga yang cakupan meterinya yaitu ilmuberwirausaha, pencatatan keuangan rumah tangga yang sederhana, dan ilmu kesehatan.Peserta kegiatan ini berjumlah 15 orang yakni bapak/ibu kepala rumah tangga disabilitas, danbeserta pejabat pemerintahan di daerah tersebut. Hasil kegiatan PKM ini, peserta yang hadirsudah ada bebarapa yang telah memulai bisnis akan tetapi mereka belum mengetahui caramarketing yang baik khususnya dalam bidang IT dan Pre test dan Post test yang kami adakanmenunjukan bahwa dengan adanya edukasi memberikan pengetahuan tambahan dan banyakilmu baru yang mereka belum kenal sebelumnya. Rekomendasi dari hasil kegiatan PKM ini,pemerintah turut berpartisipasi dalam memberikan akses permodalan kepada disabilitassehingga usaha yang mereka jalani tetap berjalan dan terus di lakukan pendampingan.
Desa Siaga Covid-19 Menuju Indonesia 5.0 Dito Anurogo; Agusdiwana Suarni; Andi Weri Sompa; Abdul Rahman Rahim
Jurnal Abmas Negeri (JAGRI) Vol. 1 No. 1 (2020): Volume 1 Nomor 1 Desember 2020
Publisher : Sarana Ilmu Indonesia (salnesia)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (453.747 KB) | DOI: 10.36590/jagri.v1i1.97

Abstract

Di masa pandemi Covid-19, peranan desa amat vital, terutama bagi pembangunan dan perekonomian bangsa. Masyarakat bersama pemerintah, akademisi, swasta, dan industri perlu bersinergi memberdayakan potensi 83.813 desa di Indonesia. Revolusi desa terkait erat dengan digitalisasi desa. Oleh karena itu, perlu adanya platform video digital berisi konsep desa Siaga Covid-19 yang multiperspektif dari pakar lintas-multidisipliner. Tujuan kegiatan pengabdian kepada masyarakat (PKM) daring ini adalah untuk merintis referensi atau platform digital (video) paripurna tentang desa Siaga Covid-19 yang multiperspektif dan berkelanjutan. Dengan diproduksinya sebelas video di channel Youtube Kampus Desa Indonesia, diharapkan tumbuh kesadaran masyarakat dan netizen sehingga dapat memberdayakan potensi desanya menjadi desa Siaga Covid-19 sebagai pondasi dasar kejayaan Indonesia.
Mapping Studies on Risk and Protective Factors for Mental Health in the Modern Era Dito Anurogo; Yocki Yuanti; Sri Kubillawati; Emdat Suprayitno; Gamar Abdullah
West Science Social and Humanities Studies Vol. 2 No. 01 (2024): West Science Social and Humanities Studies
Publisher : Westscience Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58812/wsshs.v2i01.621

Abstract

This bibliometric study delves into the extensive literature on risk and protective factors for mental health in the modern era, considering the complexities posed by technological advancements, socio-cultural shifts, and globalization. Utilizing bibliometric analysis, we identify clusters of literature, analyze trends over time, and explore potential research avenues. The network visualization reveals six distinct clusters, each representing thematic discussions related to mental health. Trend analysis highlights the evolution of research focus from early concerns to contemporary issues, with COVID-19 emerging as a prominent theme. Density analysis identifies research gaps and potential future topics. The collaboration network among authors suggests opportunities for interdisciplinary research. This analysis offers valuable insights for researchers, policymakers, and practitioners to inform evidence-based strategies for navigating the intricate landscape of mental health in the modern era.
Identifikasi Jamur Endofit Pada Tanaman Obat Tradisional Di Sulawesi Selatan Dito Anurogo; Rezqiqah Aulia Rahmat; Rahmat Pannyiwi
JIMAD : Jurnal Ilmiah Multidisiplin Vol. 3 No. 2 (2026): JIMAD : Jurnal Ilmiah Multidisiplin (January)
Publisher : Asosiasi Guru dan Dosen Seluruh Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59585/jimad.v3i1.862

Abstract

Endophytic fungi are microorganisms that live within plant tissues without causing disease symptoms. This study aimed to identify endophytic fungi associated with traditional medicinal plants in South Sulawesi that may produce bioactive compounds. The research was exploratory in nature, isolating fungi from leaves and stems using Potato Dextrose Agar (PDA) medium, and identifying them based on macroscopic and microscopic morphological characteristics. The results revealed the presence of several genera of endophytic fungi, including Aspergillus, Penicillium, Fusarium, and Trichoderma. These findings indicate the significant potential of endophytic fungi in the development of biotechnology-based traditional medicines.
Quantum Machine Learning for Drug Discovery: Accelerating the Simulation of Molecular Hamiltonians on Noisy Intermediate-Scale Quantum (NISQ) Devices Luis Santos; Maria Clara Reyes; Samantha Gonzales; Dito Anurogo
Journal of Tecnologia Quantica Vol. 2 No. 4 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/quantica.v2i4.2796

Abstract

Drug discovery increasingly relies on accurate simulation of molecular Hamiltonians, yet classical computational methods face exponential scaling barriers when modeling complex quantum systems. Recent advances in quantum machine learning (QML) and the availability of Noisy Intermediate-Scale Quantum (NISQ) devices offer new opportunities to accelerate molecular simulation despite hardware noise and qubit limitations. This study aims to evaluate the effectiveness of QML-based variational algorithms in improving the efficiency and accuracy of Hamiltonian simulation for drug-relevant molecules on NISQ platforms. A hybrid quantum–classical methodology was employed, combining variational quantum eigensolvers, noise-aware circuit optimization, and supervised learning models trained to predict energy landscapes. The results demonstrate that QML-enhanced variational circuits significantly reduce computational depth while maintaining competitive accuracy compared to classical methods, particularly for medium-sized molecular systems. The findings also reveal that noise-adaptive training improves algorithm robustness, enabling more reliable energy estimation under realistic quantum noise conditions. The study concludes that QML provides a promising pathway for accelerating early-stage drug discovery by enabling efficient molecular Hamiltonian simulation on current-generation quantum hardware.  
Determinasi Faktor yang Mempengaruhi Keberhasilan Inisiasi Menyusu Dini (IMD) pada Persalinan Normal: Studi Simulasi Berbasis Data Sintetis Dito Anurogo; Noorhani Dyani Laksmi; Ni Nyoman Sri Wirayuni; I Ketut Dian Lanang Triana
Public Health and Safety International Journal Vol. 6 No. 01 (2026): Public Health and Safety International Journal (PHASIJ)
Publisher : YCMM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55642/phasij.v6i01.1298

Abstract

Inisiasi Menyusu Dini (IMD) dilaporkan berasosiasi dengan penurunan kematian neonatal hingga 22% dan dipandang sebagai pintu masuk bagi keberhasilan ASI eksklusif. Cakupan IMD nasional 58,2% masih di bawah target Renstra 66%. Tujuan: Menganalisis faktor yang mempengaruhi keberhasilan IMD pada ibu bersalin normal dan menguji peran pengetahuan ibu sebagai mediator pada hubungan dukungan petugas kesehatan dengan keberhasilan IMD. Metode: Studi simulasi berbasis data sintetis yang membangkitkan 150 observasi ibu bersalin normal menggunakan distribusi parameter yang dikalibrasi dari literatur SDKI 2022 dan studi-studi cross-sectional terdahulu di Indonesia. Pembangkitan data dilakukan dengan R versi 4.3.1 (paket simstudy dan MASS), benih acak (random seed) ditetapkan untuk reproduksibilitas. Analisis meliputi chi-square, regresi logistik ganda dengan pemeriksaan multikolinearitas (VIF), dan uji mediasi bootstrap 5.000 sampel. Hasil: Keberhasilan IMD 61,3% (n=92). Faktor dominan: pengetahuan ibu (aOR=5,84; 95% CI: 2,28–14,95; p<0,001), dukungan petugas kesehatan (aOR=3,42; p=0,002), dukungan keluarga (aOR=2,89; p=0,008), pendidikan SMA ke atas (aOR=2,15; p=0,044), dan paritas multipara (aOR=1,98; p=0,047). Pengetahuan ibu memediasi 30,1% pengaruh dukungan petugas terhadap keberhasilan IMD. Simpulan: Dalam skenario simulasi, pengetahuan ibu muncul sebagai determinan utama sekaligus jalur mediasi penting. Kerangka analisis ini dapat digunakan sebagai dasar perencanaan studi empiris lanjutan dan perhitungan kekuatan statistik untuk evaluasi program edukasi prenatal terpadu di fasilitas kesehatan primer.
EVALUATE THE EFFECTIVENESS OF RNAI-BASED NANOPARTICLES AS THERAPY FOR PANCREATIC CANCER Dito Anurogo; Pong Krit; Siri Lek
Journal of Biomedical and Techno Nanomaterials Vol. 2 No. 1 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jbtn.v2i1.2019

Abstract

Pancreatic cancer is one of the most lethal cancers with limited effective treatment options. RNA interference (RNAi) offers a promising therapeutic approach, but efficient delivery systems are essential. To evaluate the effectiveness of RNAi-based nanoparticles as a therapy for pancreatic cancer, focusing on tumor inhibition and cell viability. A comprehensive study combining in vitro, in vivo, and clinical approaches was conducted. Pancreatic cancer cell lines (PANC-1, BxPC-3, AsPC-1) and mouse models with human pancreatic tumors were treated with RNAi-based nanoparticles. Characterization of nanoparticles included size, charge, and stability assessments using DLS and HPLC. RNAi-based nanoparticles inhibited tumor growth by 70% in mouse models and reduced cell viability by 60% in vitro. Nanoparticles demonstrated high stability and effective internalization into cancer cells, leading to significant gene silencing and apoptotic effects. RNAi-based nanoparticles show significant potential as an effective therapy for pancreatic cancer, demonstrating substantial tumor inhibition and cell viability reduction. Further clinical trials are necessary to confirm these findings and optimize nanoparticle formulations.
A 3D-PRINTED, GRAPHENE-REINFORCED HYDROGEL SCAFFOLD FOR ENHANCED OSTEOGENIC DIFFERENTIATION OF MESENCHYMAL STEM CELLS Dito Anurogo
Journal of Biomedical and Techno Nanomaterials Vol. 2 No. 5 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jbtn.v2i5.2761

Abstract

Bone tissue engineering requires scaffolds that replicate the mechanical stiffness and electroactive properties of native bone, features that conventional hydrogels lack. This study aimed to design, fabricate, and validate a 3D-printed graphene-reinforced hydrogel scaffold that enhances osteogenic differentiation of human mesenchymal stem cells (hMSCs) via combined mechanical and electrical stimulation. A composite bio-ink was developed by incorporating graphene nanoparticles (0, 0.1, 0.2, and 0.5% w/v) into a biocompatible hydrogel matrix, optimized for extrusion-based 3D printing. Scaffolds with a controlled pore size of 300 ?m were fabricated and analyzed for compressive strength, degradation kinetics, and electrical conductivity using a four-point probe. hMSCs were seeded onto the scaffolds and cultured under osteogenic conditions for 28 days. Osteogenic differentiation was assessed by alkaline phosphatase (ALP) activity (day 14), qPCR for RUNX2 and osteocalcin (OCN) (day 21), and Alizarin Red S staining for mineralization (day 28). Data were analyzed using ANOVA and regression modeling. The 0.2% w/v graphene-reinforced scaffolds showed optimal performance, with compressive strength of 35.0 MPa and electrical conductivity of 0.15 S/m, significantly higher than pure hydrogel controls. hMSCs cultured on these scaffolds exhibited increased ALP activity, upregulation of RUNX2 and OCN, and enhanced mineralization. At 0.5% w/v graphene, excessive viscosity hindered printability and reduced cell viability. Overall, the 3D-printed graphene-reinforced hydrogel scaffold at 0.2% w/v creates a synergistic electromechanical microenvironment, robustly promoting hMSC osteogenesis, and offers a scalable platform for next-generation bone tissue engineering.
The Role of Big Data Technology in Predicting and Managing the Spread of Infectious Diseases Loso Judijanto; Hermansyah Hermansyah; Kori Puspita Ningsih; Dito Anurogo; Mohamad Firdaus
Journal of World Future Medicine, Health and Nursing Vol. 2 No. 2 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/health.v2i2.757

Abstract

The spread of infectious diseases is a global problem that requires effective approaches for prediction and management. In recent years, Big Data technology has become a major concern in the healthcare field due to its ability to quickly collect, store and analyze large and diverse volumes of data. This opens up new opportunities to improve prediction and management of the spread of infectious diseases. This research aims to investigate the role of Big Data technology in predicting and managing the spread of infectious diseases. We want to identify effective methods for using big data to predict disease spread patterns and manage responses to them. The research method used in this research is a qualitative method in the form of literature analysis about the use of Big Data technology in the health sector, case studies of the implementation of Big Data systems to predict the spread of disease. The research results show that Big Data technology can improve predictions of the spread of infectious diseases by integrating data from various sources, including clinical, geographic, demographic and social data. Integrated Big Data systems can provide a better understanding of the factors that influence the spread of disease and enable faster and more effective decision making in responding to outbreaks. The conclusion of this research is that it confirms that Big Data technology has great potential in improving the prediction and management of the spread of infectious diseases. By effectively leveraging big data, we can improve our understanding of the dynamics of disease spread and implement more timely and efficient intervention strategies. Therefore, further investment and development in Big Data technology in the health sector is essential to strengthen capacity to face global health challenges.
Effect of a Low Carbohydrate Diet on Weight Loss in Obese Patients: Meta-Analysis Sisilia Prima Yanuaria Buka; Dito Anurogo; Nur Hasanah; Jeane L.I. Sumarauw; Muntasir Muntasir
Journal of World Future Medicine, Health and Nursing Vol. 2 No. 2 (2024)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/health.v2i2.760

Abstract

Obesity is a rapidly increasing global health problem and requires effective intervention strategies. Low-carbohydrate diets have become a major concern in obesity management, but previous studies have provided mixed results. This study aims to conduct a meta-analysis to evaluate the effect of a low-carbohydrate diet on weight loss in obese patients. The research method used in this research is meta analysis. A literature search was conducted through electronic databases for studies that met the inclusion criteria. Data from selected studies were then analyzed using meta-analysis methods to determine the effects of low-carbohydrate diets on weight loss. The results of this study stated that the meta-analysis involved data from 10 studies that met the inclusion criteria. The results showed that a low-carbohydrate diet significantly contributed to weight loss in obese patients. The average weight loss achieved was significantly higher in the group on a low-carbohydrate diet compared to the control group. The conclusion of this study, namely from this meta-analysis, shows that a low-carbohydrate diet is effective in reducing weight in obese patients. The clinical implication of these results is that low-carbohydrate diets may be an effective therapeutic option in the management of obesity. However, further research needs to be done to understand in more depth the long-term effects and safety of this low-carbohydrate diet. Through this research, it is hoped that it can provide a deeper understanding of the effectiveness of a low-carbohydrate diet as an obesity management strategy.
Co-Authors Abdul Rahman Rahim Adiningrat, Andi Arifwangsa Andi Weri Sompa Clara Mendes Emdat Suprayitno Faidul Adziem Gamar Abdullah Hermansyah Hermansyah I Ketut Dian Lanang Triana Jeane L.I. Sumarauw Loso Judijanto Lucas Lima Luis Santos Maria Clara Reyes Mohamad Firdaus Muhammad Nur Abdi Muntasir, Muntasir Ni Nyoman Sri Wirayuni Nong Chai Noorhani Dyani Laksmi Nur Hasanah Pedro Silva Pong Krit Rahmat Pannyiwi Rezqiqah Aulia Rahmat Roshonah, Adiyati Fathu Roya Zahir Rustiyana, Rustiyana Samantha Gonzales Siri Lek Sisilia Prima Yanuaria Buka Sri Kubillawati, Suarni, Agusdiwana Yocki Yuanti