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INDONESIA
Jurnal Fisika Unand
Published by Universitas Andalas
ISSN : 23028491     EISSN : 26862433     DOI : https://doi.org/10.25077/jfu
Core Subject : Science, Engineering,
Earth & Planetary Sciences Electrical & Electronics Engineering Energy Materials Science & Nanotechnology Physics
Makalah yang dapat dipublikasikan dalam jurnal ini adalah makalah dalam bidang Fisika meliputi Fisika Atmosfir, Fisika Bumi, Fisika Intrumentasi, Fisika Material, Fisika Nuklir, Fisika Radiasi, Fisika Komputasi, Fisika Teori, Biofisika, ataupun bidang lain yang masih ada kaitannya dengan ilmu fisika.
Arjuna Subject : Fisika dan Astronomi - Fisika Nuklir dan Molekuler, dan Ooptik
Articles 6 Documents
 1 
Search results for , issue "Vol 15 No 2 (2026)" : 6 Documents clear
Analisis Spatiotemporal Dinamika Garis Pantai Dan Pemetaan Zona Bahaya Tsunami Di Kota Padang Menggunakan Penginderaan Jauh dan Sistem Informasi Geografis Musra, Faizah; Namigo, Elistia Liza
Jurnal Fisika Unand Vol 15 No 2 (2026)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jfu.15.2.132-139.2026

Abstract

The city of Padang is one of Indonesia's coastal areas that is highly vulnerable to tsunamis due to its location directly facing the Mentawai–Sumatra megathrust subduction zone. This study aims to analyze coastal dynamics using multitemporal satellite imagery and examine its relationship with tsunami hazard zoning based on the physical characteristics of the area. The methodology includes digitizing the coastline for 2013 and 2025, analyzing the rate of coastline change using the Digital Shoreline Analysis System (DSAS), and combining spatial parameters such as elevation, slope, distance from the coastline, and proximity to rivers to produce a tsunami hazard zone map. Overlay analysis indicates that areas with low elevation, gentle slopes, and proximity to river mouths and coastlines fall into the category of high tsunami vulnerability. The results of the study show spatial variations in coastal dynamics in Padang City, with significant abrasion observed in Koto Tangah District (-1.754 m/year) and Padang Selatan (-1.051 m/year), while notable accretion was recorded in Bungus Teluk Kabung (+1.470 m/year). This study proves that the integration of remote sensing data and Geographic Information Systems (GIS) provides a comprehensive spatial framework to support coastal disaster mitigation efforts and risk-based spatial planning.
Analisis Efektivitas Filtrasi Sederhana terhadap Kualitas Fisik-Kimia Air Sumur Bor dan Sungai Kahayan untuk Mitigasi Dampak Lingkungan Iashania, Yunida; Agustiani , Reni; Fridtriyanda, Asri; Waruwu, Valentinus; Enzelina Silaban, Yunita
Jurnal Fisika Unand Vol 15 No 2 (2026)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jfu.15.2.140-146.2026

Abstract

The purpose of this study was to determine the effectiveness of the filter before and after filtration so that the water complies with water quality standards. The research method used a quantitative method with a field and laboratory experimental approach to test changes in air quality after going through a filtration process using a simple system designed. Based on research obtained from the laboratory, there was an increase in the effectiveness of well water quality of 95.65%, dissolved manganese (mn) of 83.87%, the color looked clearer with an increase of 68.47%, dissolved iron (Fe) of 14.63%, air acidity (pH) of 7.16%, nitrite (NO2) of 1.43%. While for river water the TSS value was 40.82%, dissolved oxygen (DO) of 121.03%, chemical oxygen demand (COD) of 14.16%, biological oxygen demand (BOD) of 12.82% and an increase in pH of 4.17%. The filter designed in this study is effective for use in water wells because it is able to filter and improve the quality of groundwater because it complies with water quality standards, namely PP No. 22 of 2021, while for river water it is still less effective in addressing air quality, especially in TSS and BOD values.
Optimalisasi Potensi Limbah Alat Gelas sebagai Adsorben Limbah Logam Berat Fe, Cd, Pb dan Mn Skala Laboratorium Gusthia, Melisa Weno; Nurmi, Fatiyah Aghni Yati; Rahmatunisa, Sefina; Muldarisnur, Mulda
Jurnal Fisika Unand Vol 15 No 2 (2026)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jfu.15.2.125-131.2026

Abstract

Chemical laboratory activities produce liquid waste containing hazardous materials, including heavy metals such as Fe, Cd, Pb, and Mn, which have the potential to pollute the environment if not managed properly. This study aims to optimize the use of laboratory glassware waste as an environmentally friendly alternative adsorbent to reduce heavy metal levels in laboratory-scale liquid waste. The research stages include collecting glassware waste from various laboratories, grinding, sieving, and activating the adsorbent through chemical treatment (HNO₃ and HCl-HNO₃), drying, calcination, and adding NaOH to open the adsorbent pores. Material characterization was carried out using SEM, FTIR, and BET to observe the morphology and surface area of the pores. Initial results showed that the three-stage activation was able to improve the quality of the adsorbent pores so that it was ready for use in the adsorption process. In the next stage, heavy metal adsorption tests were carried out with variations in time and mass of the adsorbent, then analyzed using Flame AAS and re-characterized with SEM-EDX, FTIR, and BET. The results using FTIR can be proven that the adsorbent contains SiO2 compounds that have the potential to have pores due to the structure of the compound. The results of the BET characterization obtained a surface area value of 0, which proves that the adsorbent has a very small pore size, also called micropores. The results of Flame AAS measurements show that the adsorbent is able to adsorb heavy metals with an adsorption percentage above 85%.
Identification Of Subsurface Lithological Units Using Electrical Resistivity Modelling In A Landslide-Prone Area Of Dlingo, Bantul, Yogyakarta Rahmawati Fitrianingtyas; Amri, Chairul; Khafidh Nur Aziz; Hilma Lutfiana; Rial Dwi Martasari; Uli Ulfa
Jurnal Fisika Unand Vol 15 No 2 (2026)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jfu.15.2.155-163.2026

Abstract

The Dlingo area in Bantul Regency, Yogyakarta, is characterized by steep slopes and volcanic deposits that contribute to high landslide susceptibility, as evidenced by destructive events in 2021. This study aims to characterize subsurface conditions controlling slope instability using electrical resistivity modeling. Geoelectric data were acquired using the Wenner configuration along four survey lines, consisting of three slope-parallel profiles and one slope-perpendicular profile, each 225 m long with 15 m electrode spacing. Apparent resistivity data were processed and inverted using Res2Dinv to generate two-dimensional (2D) resistivity sections. The results consistently reveal three principal resistivity zones across all profiles: (1) a high-resistivity unit (approximately 33,9–642 Ωm) interpreted as relatively compact to slightly weathered tuff, (2) a moderate-resistivity layer (1.79–33.9 Ωm) corresponding to weathered volcanic deposits, and (3) a low-resistivity zone (<1.79 Ωm) interpreted as water-saturated or highly conductive material developed along the lower slope. The recurrent resistivity contrast between the weathered layer and the underlying conductive zone suggests a hydrogeological boundary that may facilitate pore-water accumulation and contribute to slope instability. These findings provide a geophysically constrained conceptual model of subsurface controls on slope instability in volcanic terrains.
Stabilisasi Sterik Polimer Non-Ionik Tween 80 pada Nanopartikel Senyawa Bioaktif Buah Kapulaga Saragih, Horasdia
Jurnal Fisika Unand Vol 15 No 2 (2026)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jfu.15.2.164-173.2026

Abstract

The bioactive compounds in cardamom fruit are highly beneficial to health, as they possess anticancer, antioxidant, antibacterial, anti-inflammatory, and antibiotic properties. Therefore, they have great potential to be developed as oral medicines in the future. However, they are highly hydrophobic and consequently insoluble in water. This poses an obstacle to their development. To overcome this problem, bioactive compounds from cardamom fruit have been synthesized into nanometer-sized particles (13.13-19.75 nm) and encapsulated with the nonionic polymer surfactant Tween 80. The results show that Tween 80 surfactant not only acts as an encapsulant for nanoparticles so that they can be dispersed in an aqueous medium, but also acts as a steric stabilizer so that the nanoparticles can remain stable for a long time. Four concentrations of bioactive compounds from cardamom fruit were used, namely: 6, 8, 10, and 12 mg to observe their effect on size stability. All nanoparticles produced from the four concentrations had excellent size stability.
Development of an Integrated Artificial Intelligence Model for Bottle Inspection Using Geometric Feature Extraction and ROI-Based Statistical Analysis Dewi Anggraeni; Santoso, Rikho Adi; Naba, Agus; Sakti, Setyawan Purnomo; Rianto, Sugeng
Jurnal Fisika Unand Vol 15 No 2 (2026)
Publisher : Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jfu.15.2.147-154.2026

Abstract

In the era of Industry 4.0, the demand for manufacturing systems that are fast, precise, and efficient has become increasingly urgent. This drives the adoption of artificial intelligence (AI) technologies as a promising solution, including in the field of automatic bottle sorting. However, many industries still use manual bottle sorting systems, which often have significant drawbacks. This study presents an integrated artificial intelligence (AI)-based inspection model for automated bottle inspection in the context of smart manufacturing. The proposed approach integrates geometric feature extraction with region-of-interest (ROI)-based statistical image analysis to improve classification accuracy and robustness. Geometric features extracted from bottle contours are combined with optimized ROI selection to enhance feature relevance prior to classification using a Random Forest algorithm. The dataset consists of four bottle types: plastic, glass, cans, and cardboard, captured under controlled imaging conditions. Experimental results show that the proposed integrated method achieves classification accuracy ranging from 96% to 97.72%. The findings confirm that ROI optimization significantly influences statistical feature characteristics and improves overall model performance. This integrated framework is suitable for implementation in automated visual inspection systems supporting Industry 4.0 applications.

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