Article Per Year (5 Year)
p-Index From 2021 - 2026
2.39
P-Index
This Author published in this journals
All Journal Jurnal MIPA Jurnal Penelitian Fisika dan Aplikasinya (JPFA) Jurnal Fisika Unand JURNAL ILMIAH PENDIDIKAN FISIKA AL BIRUNI PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Buana Information Technology and Computer Sciences (BIT and CS) Jurnal Fisika dan Terapannya Journal of Engineering, Computer Science and Information Technology (JECSIT) Jurnal Lentera: Penelitian dan Pengabdian Masyarakat
Afrioni Roma Rio
Sam Ratulangi University
Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Health Professions Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Physics Public Health Social Sciences Other

Published : 14 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 14 Documents
Search

 1   2 
Pemetaan Zona Iklim di Sulawesi Utara Berdasarkan Kelembaban dan Presipitasi Menggunakan K-Means Clustering Afrioni Roma Rio
Jurnal Lentera: Penelitian dan Pengabdian Masyarakat Vol. 6 No. 1 (2025): Jurnal Lentera: Penelitian dan Pengabdian Masyarakat
Publisher : Yayasan Bina Lentera Insan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.57207/xhf69j50

Abstract

Klasterisasi kelembaban dan presipitasi di Sulawesi Utara dilakukan dalam rangka memetakan pola curah hujan di wilayah tersebut. Kelembaban relatif dan presipitasi adalah dua parameter penting dalam meteorologi yang sering digunakan untuk memprediksi pola curah hujan. Dalam penelitian ini, data yang digunakan adalah data dalam rentang lima tahun dari tahun 2020 hingga tahun 2024 yang diambil dari 171 kecamatan di Sulawesi Utara. Metode k-means clustering digunakan untuk mengelompokkan kecamatan-kecamatan di Sulawesi Utara berdasarkan rata-rata kelembaban relatif dan presipitasi. Dalam analisis ini, empat klaster kecamatan berhasil dihasilkan. Meskipun rata-rata kelembaban relatif tidak menunjukkan perbedaan yang signifikan antara keempat klaster, namun terdapat perbedaan signifikan dalam sebaran data presipitasi antara klaster-klaster tersebut. Klaster 1 merupakan klaster dengan tingkat presipitasi tertinggi, diikuti oleh klaster 2 dan klaster 3. Klaster 4 merupakan klaster dengan tingkat presipitasi paling rendah dibandingkan dengan klaster-klaster yang lain. Analisis ini dapat menjadi dasar bagi pemerintah dan lembaga terkait dalam memetakan pola curah hujan di Sulawesi Utara dan membantu dalam perencanaan dan pengelolaan sumber daya air. Selain itu, informasi tentang sebaran data presipitasi pada setiap klaster dapat menjadi pedoman dalam memetakan potensi bencana banjir dan tanah longsor di wilayah tersebut. Penelitian ini juga dapat menjadi acuan bagi penelitian lanjutan tentang pola curah hujan di Sulawesi Utara.
Biomass-Derived Activated Carbon via Na₂CO₃, KOH, and ZnCl₂ Activation: A Comparative Physicochemical Study toward Energy Storage Electrodes Bakti, Andi Ikhtiar; Rio, Afrioni Roma; Mosey, Handy Indra Regain; Jumriadi, Jumriadi
Jurnal Ilmiah Pendidikan Fisika Al-Biruni Vol 14 No 2 (2025): Jurnal Ilmiah Pendidikan Fisika Al-Biruni
Publisher : Universitas Islam Negeri Raden Intan Lampung, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24042/jipfalbiruni.v14i2.29076

Abstract

This study investigates the fabrication of granular activated carbon (AC) from biomass waste using three chemical activating agents: sodium carbonate (Na₂CO₃), potassium hydroxide (KOH), and zinc chloride (ZnCl₂), to evaluate their effects on structural, morphological, and electrical properties relevant to energy storage applications. An experimental laboratory-based method with a comparative activation approach was employed. The resulting activated carbon samples were characterized by X-ray diffraction (XRD), scanning electron microscopy coupled with energy-dispersive spectroscopy (SEM–EDS), and iodine adsorption and electrical measurements. XRD analysis revealed that all samples predominantly exhibit amorphous or turbostratic carbon structures with partial structural ordering, with ZnCl₂-activated samples showing higher short-range ordering than those activated with the other activators. SEM observations indicated qualitative differences in surface morphology and pore development, with more pronounced pores in the KOH-activated carbon. EDS analysis confirmed carbon-rich surfaces with minor residual inorganic elements originating from the activating agents and biomass precursor. Iodine adsorption results, used as a proxy indicator of microporosity, showed that the KOH-activated carbon exhibited the highest iodine number (630.70 mg/g). Electrical measurements, reported as apparent electrical conductivity under the applied packed-bed measurement conditions, also indicated the highest value for the KOH-activated sample (1724.10 S/m). Based on the parameters measured in this study, KOH activation produced the most favorable combined iodine adsorption and apparent electrical conductivity among the activation routes investigated. Therefore, KOH-activated biomass-derived carbon is identified as the most promising candidate for subsequent electrochemical validation toward supercapacitor electrode applications.
Pelatihan Sistem Pertanian Cerdas Berbasis Internet of Things di Desa Kaasar, Minahasa Utara: Training on Internet of Things-Based Smart Farming System in Kaasar Village, North Minahasa Andi Ikhtiar Bakti; As'ari As'ari; Afrioni Roma Rio; Jumriadi Jumriadi; Rachma Rahim
PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat Vol. 11 No. 7 (2026): PengabdianMu: Jurnal Ilmiah Pengabdian kepada Masyarakat
Publisher : Institute for Research and Community Services Universitas Muhammadiyah Palangkaraya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33084/pengabdianmu.v11i7.11540

Abstract

The smart farming system training based on the Internet of Things (IoT) in Kaasar Village, North Minahasa, North Sulawesi, successfully enhanced farmers' understanding and skills in operating smart farming technology. The pre-test results indicated that 80% of participants were unfamiliar with the technology, but after the training, 90% demonstrated a good understanding of how to use the system. Additionally, the training on business strategy and digital marketing improved farmers' skills in promoting their products through Google Business and social media. However, some challenges were encountered, such as the limited number of devices available, which required participants to take turns using them. This program has had a significant positive impact on the sustainability of agricultural businesses in Kaasar Village, although some technical aspects need improvement to enhance the effectiveness of future training sessions.
The Effect of Myopia on Brain Signals: Insights from EEG Studies Ernawatil Gani; Afrioni Roma Rio; Mahendra Kusuma Nugraha; Freddy Haryanto
Jurnal Penelitian Fisika dan Aplikasinya (JPFA) Vol. 14 No. 1 (2024)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/jpfa.v14n1.p19-32

Abstract

Refractive vision disorders, such as myopia, can significantly influence an individual's cognitive performance, particularly their ability to perceive and interpret visual stimuli. Myopia, a common refractive error affecting children and adults, can be assessed using various methods, including electroencephalography (EEG). The primary objective of this investigation was to identify distinctive brain signals associated with myopia. This study delves into analyzing brain signals in myopic individuals by employing EEG data and spectral entropy analysis through MNE-Python. EEG data were collected from five myopic participants during a 10-minute session, both with and without their corrective glasses. The collected data underwent preprocessing and power spectral density calculations. Subsequently, spectral entropy analysis was employed to assess the complexity and distribution skewness of EEG frequency patterns. The results of this study revealed notable differences in brain activity, particularly in the occipital region, between individuals wearing glasses and those without them. This variance could be attributed to the enhanced visual clarity experienced by individuals wearing glasses, enabling them to perceive better and process the visual stimuli presented in the study videos. Specifically, spectral entropy values were lower in children without glasses (averaging 1.0) than those with glasses (averaging 3.5), indicating a higher degree of irregularity in the brain activity of myopic children who do not wear corrective eyewear. In conclusion, this study indicates an increase in brain activity irregularities among children without glasses. The findings suggest that specific factors, such as blinking and hand movements, play a role in exacerbating this irregularity. These findings reveal how myopia affects brainwave patterns and indicate that EEG and spectral entropy analysis can enhance our understanding of refractive vision disorders.
Co-Authors As'ari As'ari Bakti, Andi Ikhtiar Ernawatil Gani, Ernawatil Freddy Haryanto Handy I. R. Mosey Jayawarsa, A.A. Ketut Jumriadi Mahendra Kusuma Nugraha Maria Daurina Bobanto Nurwijayanti Rachma Rahim Salsabila, Unik Hanifah