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INDONESIA
Science and Technology Indonesia
Published by Universitas Sriwijaya
ISSN : 25804405     EISSN : 25804391     DOI : -
Core Subject : Science, Social, Engineering,
Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Environmental Science Materials Science & Nanotechnology Physics
An international Peer-review journal in the field of science and technology published by The Indonesian Science and Technology Society. Science and Technology Indonesia is a member of Crossref with DOI prefix number: 10.26554/sti. Science and Technology Indonesia publishes quarterly (January, April, July, October). Science and Technology Indonesia is an international scholarly journal on the field of science and technology aimed to publish a high-quality scientific paper including original research papers, reviews, short communication, and technical notes. This journal welcomes the submission of articles that covers a typical subject of natural science and technology such as: > Chemistry > Biology > Physics > Marine Science > Pharmacy > Chemical Engineering > Environmental Science and Engineering > Computational Engineering > Biotechnology Journal Commencement: October 2016
Arjuna Subject : -
Articles 616 Documents
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Modeling and Forecasting of Sulfur Dioxide (SO₂) Emissions in Several ASEAN Countries (Using State Space Multivariate Time Series Analysis) Mustofa Usman; Edwin Russel; Nurhanurawati; Faiz AM Elfaki; Nadya R. Ikhsana; Deta Erviana; Moni Dwi Fenski
Science and Technology Indonesia Vol. 11 No. 3 (2026): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2026.11.3.877-893

Abstract

Sulfur dioxide (SO2) emissions (ton/year) produced from coal combustion, household heating, motor vehicles, and volcanic eruptions, has been considered as a dangerous air pollutant that causes many respiratory diseases and increases the mortality rate. Many studies have been conducted generally in developed countries and industrialized countries that are aware of the adverse effects of increasing SO2 emissions in the air. Many studies have been conducted to measure the level of air pollution caused by SO2 emissions and research on the relationship of SO2 emissions with public health and mortality rates. The problem in this study is how to build the best State Space Multivariate Time Series model for SO2 emissions data in several ASEAN countries, Indonesia, Thailand, Philippines and Malaysia. This study aims to build the best State Space Multivariate Time Series model that fits the data and uses the best state space model for forecasting SO2 emissions for the next few years. The analysis method that will be used is State Space Multivariate Time Series Analysis (Autoregressive Vector modeling, and State Space Model). The results show that SO2 emissions in Indonesia are significantly influenced by emission conditions in Indonesia four years earlier and SO2 emissions in Malaysia two and four years earlier; SO2 emissions in Thailand are significantly influenced by SO2 emission conditions in Thailand and the Philippines one year prior; SO2 emissions in the Philippines are significantly influenced by SO2 emission conditions in Thailand one years prior and SO2 emission conditions in the Philippines four years prior; SO2 emissions in Malaysia are significantly influenced by SO2 emissions conditions in Indonesia two, three, and five years prior, SO2 emissions conditions in Malaysia four years prior, SO2 emissions conditions in Thailand and Philippines five years prior. Forecasting results using the state space model indicate a downward trend in SO2 emissions in Indonesia, Thailand, the Philippines, and Malaysia over the next ten years.
The Transportation Planning for Cost Optimization in Cold-Chain Distribution: A Case Study Chatchai Sutikasana; Sanit Pattane; Sasiwimon Wongwilai; Weenakorn Ieosanurak
Science and Technology Indonesia Vol. 11 No. 3 (2026): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2026.11.3.1079-1088

Abstract

Cold chain logistics for perishable goods faces increasing challenges in balancing product quality and cost efficiency. This study proposes a mixed integer linear programming (MILP) model that jointly optimizes transportation and inventory decisions in temperature-controlled supply chains by incorporating both transportation and perishability-related holding costs within a multi-node distribution network. A real-world case study based on a ten-node cold chain system in Thailand is used to validate the model. The results indicate that the proposed approach effectively determines routing structures, shipment quantities, and vehicle utilization while accounting for product deterioration. Compared with experience-based planning, the proposed model reduces total logistics cost by 8.02%, primarily through improved transportation efficiency. These findings demonstrate the importance of integrating routing decisions with perishability considerations and highlight the model’s potential as a practical decision-support tool for cold chain logistics operations.
Interlinkage of Drought, Fire Severity, Vegetation Degradation, and Hydrological Response in Peatland Ecosystems Mokhamad Yusup Nur Khakim; Azhar Kholiq Affandi; Erni; Mardia Ulfa
Science and Technology Indonesia Vol. 11 No. 3 (2026): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2026.11.3.1106-1126

Abstract

Peatlands, as fragile ecosystems, are vulnerable to deforestation and altered hydrological regimes. The objectives of this study were to evaluate the effects of deforestation on runoff, drought, and fire severity in nine Peat Hydrological Units (KHG) in South Sumatra, Indonesia, in 2014–2025. The deforestation map was created by analyzing the Landsat-8 image through Spectral Mixture Analysis (SMA) and the Normalized Difference Fraction Index (NDFI). The runoff was modeled using the Soil Conservation Service-Curve Number (SCS-CN) method based on downscaled land cover, CHIRPS, GLDAS, and MODIS data. The drought condition was evaluated using the Vegetation Health Index (VHI), and fire severity was evaluated based on the Relativized Burn Ratio (RBR). The findings indicate that in 2015, the most significant deforestation occurred with the value of NDFI decreasing by > 0.25. In 2015, the highest annual rainfall during the study was 1828 mm, with an anomaly of 1-m topsoil moisture reaching −11.35 mm. Extreme drought (VHI < 0.1) occurred in > 35% of the area of S. Merang – S. Ngirawan and S. Lalan – S. Merang watersheds. Also, the 2015 fires had the largest area of moderate and high (RBR > 0.27) compared to the 2019 and 2023 fires. Deforestation also increased hydrologic response in the watershed as the annual runoff coefficient increased from 13% in 2015 to 15% in 2016 due to a decrease in infiltration from vegetation loss. As a conclusion, this study showed that deforestation increased runoff, drought conditions and peat fires. Our findings are important for evidence-based strategies on fire mitigation and hydrological management in tropical peatlands.
Synergistic Integration of Multi-Sensor Satellite Data and Gradient Boosting Machine Learning for High-Resolution PM₂.₅ Estimation during Tropical Peatland Fires Dessy Gusnita; Iis Sofiati; Fadhlullah Ramadhani; Angga Yolanda Putra; Risyanto; Waluyo Eko Cahyono; Tatik Kartika; Muhammad Priyatna; Estiningtyas Kusumastuti
Science and Technology Indonesia Vol. 11 No. 3 (2026): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2026.11.3.1089-1105

Abstract

Tropical peatland and forest fires are critical contributors to regional haze and public health crises, yet ground-based monitoring in these regions remains sparse. This study develops a robust framework for estimating surface PM₂.₅ concentrations during extreme fire events (2021–2025) by integrating multi-sensor satellite observations with in-situ data through a Hist Gradient Boosting Regressor (HGBR) approach. To enhance predictive accuracy, we implemented advanced feature engineering, including 1–3 days of exogenous lags, rolling statistics (3 and 7-day windows), and aerosol–meteorological interaction variables. Our analysis of multiple pollutants (PM₂.₅, NO₂, SO₂, CO, HC, and O₃) reveals that during active fire periods, the Air Quality Index (AQI) frequently escalated to "Unhealthy" and "Hazardous" levels. The proposed HGBR model demonstrated high fidelity in representing spatiotemporal variability, achieving a coefficient of determination (R² = 0.72), with an RMSE of 14.26 μg/m³ and MAE of 8.49 μg/m³ (n = 339). These results validate the efficacy of machine learning-driven satellite monitoring in bypassing the limitations of fragmented ground station networks. This framework offers a scalable solution for operational air quality forecasting and early warning systems in fire-prone equatorial regions.
Nano-Enhanced Tri-Organotin (IV) Complexes from a Ciprofloxacin Hybrid: Synthesis, Characterization, and Superior Antifungal Activity Aliyaa Dhahir Mohsin; Angham G. Hadi; Rana A. K. Al-Refaia
Science and Technology Indonesia Vol. 11 No. 3 (2026): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2026.11.3.982-993

Abstract

Organotin (IV) compounds are of significant interest in both the chemical and medicinal sectors. Among these, tri-organotin (IV) derivatives (R3SnX) stand out due to their potent biological activity and their distorted trigonal bipyramidal geometry. The present study details the synthesis, nano-formulation, and improved antifungal activity of three new tri-organotin (IV) complexes. These complexes have been synthesized from a hybrid ligand, formed from ciprofloxacin and 5-aminosalicylic acid, followed by modification of the carboxylate functional group with chloroacetic acid. These compounds have been completely characterized by FT-IR, multinuclear NMR spectroscopy (¹H, ¹³C, ¹¹⁹Sn), and CHNS analysis. To enhance their biological activity, the synthesized complexes have been nano-formulated with triangular silver nanoparticles (AgTNPs). The antifungal activity of both pure and nano-formulated complexes has been investigated against Fusarium spp. In vitro antifungal assays against Fusarium spp. revealed that the triphenyltin complex (T3) was the most active among the pure compounds, achieving a 20% inhibition rate at 2 mg/mL, attributed to its high lipophilicity and aromatic content. Remarkably, the nano-formulated version (AgTNPs-T3) demonstrated a significant synergistic effect, increasing the inhibition rate to 55% at the same concentration, a 2.75-fold enhancement compared to the unmodified complex. This superior performance is attributed to the high surface area-to-volume ratio and sharp vertices of the AgTNPs, which facilitate better membrane penetration and ROS generation.
Physicochemical Properties and Water Filtration Performance of Electric Field Fabricated Polyvinylidene Fluoride Membranes Aneka Firdaus; Agung Mataram; Rahma Dani; Muhammad Satya Putra Gantada; Nukman; Irwin Bizzy; Ahmad Fauzi Ismail
Science and Technology Indonesia Vol. 11 No. 3 (2026): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2026.11.3.808-826

Abstract

This study investigated the use of an electric field-assisted phase inversion method (15 kV) to tailor the properties of PVDF membranes with a thickness of 3 mm. The electric field significantly altered membrane formation, producing porous structures compared to the dense morphology of untreated membranes. Increasing the PVDF concentration (25–35%) reduced the pore size from 11.54 µm to 5.27 µm, resulting in more uniform structures. Surface analysis indicated that the membranes remained relatively smooth, with smaller surface features at higher polymer concentrations. The mechanical properties improved substantially, with the tensile strength increasing from 12.28 MPa to 43.21 MPa and higher stiffness observed. FTIR results revealed enhanced β-phase formation under the electric field, indicating improved chain alignment, supported by increased crystallinity from XRD. In terms of filtration performance, the permeability reached 55.32 L/m2·h·bar, while turbidity rejection exceeded 90% for all treated membranes. These results demonstrate a promising approach for high-performance PVDF membranes and strong potential as composite base materials.
Root-Derived Phytochemicals from Inula confertiflora for Antioxidant and Antibacterial Activities Mohammad Budiyanto; Abere Habtamu Manayia; Esubalew Meku Godie; Minbale Gashu Tadesse; Fasih Bintang Ilhami; Sapti Puspitarini
Science and Technology Indonesia Vol. 11 No. 3 (2026): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2026.11.3.1176-1191

Abstract

Inula confertiflora, a medicinal herb indigenous to Ethiopia, often used in traditional treatments for inflammatory and pain-related conditions. The root of I. confertiflora was soaked with n-hexane, ethyl ether, and acetone solvents. The proportion of crude extracts derived from ethyl ether extracts was 1.4 times higher than that of n-hexane and 1.2 times higher than that of acetone. Analytical detection results of crude extracts confirmed that I. confertiflora contained a variety of different preliminary phytochemicals. The higher concentrations of total flavonoids and other polar phytoconstituents present in the ethyl ether extracts were associated with greater radical-scavenging effectiveness in the DPPH solution. More than half of the bacterial growth efficiency was restricted by phytochemicals derived from I. confertiflora root extracts using non-polar, medium-polar, and high-polar solvents. It is crucial to note that medium-polar extracts of I. confertiflora root decreased the inhibitory effect on the development of both gram-positive and gram-negative bacterial strains at a concentration of 100 μg/mL using acetone as the solvent. Additionally, they exhibited improved radical scavenging against a DPPH solution. Moreover, molecular docking simulation clearly revealed that I. confertiflora extracts have a strong binding affinity toward four key bacterial target proteins (LasB (-7.9kcal/mol), PBP2a (-8.0kcal/mol), FabH (-11.3kcal/mol), and MurA1 (-4.7kcal/mol)). Collectively, these findings suggest that I. confertiflora extracts exhibit substantial potential as antibacterial agents by targeting diverse and functionally important bacterial proteins.
Land Cover Classification Using LAPAN-A3 and Sentinel-2 Imagery in Google Earth Engine: A Machine Learning-Based Comparative Analysis Danang Budi Susetyo; Dewayany Sutrisno; Atriyon Julzarika; Agus Herawan; Patria Rachman Hakim; Ahmad Fauzi
Science and Technology Indonesia Vol. 11 No. 3 (2026): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2026.11.3.1164-1175

Abstract

Open-source satellite imagery such as Sentinel-2 has been widely proven reliable for various geospatial applications. However, achieving geospatial independence remains crucial for any country to reduce reliance on foreign data sources and strengthen national sovereignty in Earth observation capabilities. In this context, Indonesia initiated a microsatellite development program in 2007, which has now reached its third generation with LAPAN-A3. Despite these efforts, LAPAN-A3 is still considered an experimental satellite, and further evaluation is required before it can be fully adopted for operational applications. This study evaluates the performance of LAPAN-A3 imagery for land cover mapping using machine learning approaches and compares its performance with the well-established global dataset Sentinel-2. Two widely used classifiers, Random Forest (RF) and Support Vector Machine (SVM), were implemented within the Google Earth Engine (GEE) platform and tested using different combinations of spectral features. The results show consistent improvements in classification performance when additional spectral features are incorporated for both LAPAN-A3 and Sentinel-2 datasets. In all feature configurations, RF outperforms SVM, achieving higher Overall Accuracy (OA) and Kappa coefficients. Although Sentinel-2 generally yields slightly better results, LAPAN-A3 demonstrates promising performance despite its experimental nature. These findings highlight the potential of LAPAN-A3 as a national remote sensing asset that can contribute to Indonesia’s long-term goal of achieving geospatial independence and strengthening domestic Earth observation capabilities.
Initial Assessment of a Dual-Bioactive Hydrogel Incorporating Phagocytosis-Stimulating and Tissue-Regenerative Proteins for Enhanced Wound Healing Papassara Changklang; Tan Suwandecha; Somchai Sriwiriyajan; Jongdee Nopparat; Neelam Balekar; Teerapol Srichana
Science and Technology Indonesia Vol. 11 No. 3 (2026): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2026.11.3.1127-1137

Abstract

Wound healing is a complex process that can be impaired by various factors. Hydrogel is a recommended choice for keeping the skin moist and enhancing wound healing. Hydrogel can contain bioactive compounds to improve wound healing effectiveness further. Phagocytosis activating protein (PAP) and thrombospondin (TSP) can stimulate macrophage and promote cell proliferation. They had the potential to enhance wound healing when incorporated into a hydrogel. This study aims to evaluate the effect of PAP and TSP hydrogel on irritation and wound healing efficacy in a rat model. This experiment is conducted using a full-thickness wounds model in rats. The hydrogel formulations with PAP and/or TSP were applied to the wounds for 21 days. The wound contraction, histology, and TGF-β1 expression were measured. The results showed that low-dose PAP hydrogel had the best wound healing performance among all groups, with high TGF-β1 levels in the early phase and low levels in the late phase. Low-dose TSP hydrogel had similar but weaker effects than low-dose PAP hydrogel. There was no sign of skin irritation for all formulations. Hydrogel containing a low dose of PAP or TSP is a promising formula for further developing new wound dressing materials. It also opens an opportunity to cure some challenging to-treat wounds, such as diabetic and burn wounds.
Semiparametric Path Analysis with Truncated Spline: A Simulation Study with Double Resampling Inference Fachira Haneinanda Junianto; Adji Achmad Rinaldo Fernandes; Solimun; Ani Budi Astuti; Muhammad Hisyam Lee
Science and Technology Indonesia Vol. 11 No. 3 (2026): July
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2026.11.3.1054-1067

Abstract

This study proposes a semiparametric path analysis framework that integrates truncated spline modeling with resampling-based inference to capture both linear and nonlinear relationships within a unified structure. The motivation arises from the limitation of conventional path analysis, which relies on linearity assumptions that are often violated in empirical data, as indicated by the Ramsey RESET test. To address this issue, a truncated spline approach is employed to flexibly model nonlinear relationships, while statistical inference is conducted using double resampling techniques. A simulation study is performed to evaluate the performance of resampling methods under varying conditions. The results show that for a sample size of n=200 with a single nonlinear relationship, the double jackknife method provides more stable and efficient estimates compared to alternative approaches. This finding motivates its application in the empirical analysis. The empirical results, based on data from East Java, Indonesia, reveal that technology access has a significant direct effect on both financial knowledge and financial literacy. A nonlinear relationship is identified between technology access and financial literacy, characterized by a threshold effect captured through truncated spline modeling. However, the indirect effect through financial knowledge is found to be statistically insignificant. Overall, the proposed approach offers a flexible and robust framework for modeling complex causal relationships and improves inference accuracy in semiparametric path analysis.

Page 61 of 62 | Total Record : 616

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