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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 551 Documents
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Liposome Photosensitizer with Enzyme from Black Soybean Tempeh: Formula Optimization and In Vitro Thrombolytic Activity Evaluation Azzahra, Farah Daffa; Mulyani, Laida Neti; Sabrina, Tia; Fithri, Najma Annuria
Science and Technology Indonesia Vol. 10 No. 3 (2025): 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.2025.10.3.903-915

Abstract

Stroke and myocardial infarction contributed significantly as the leading causes of global mortality rate, both commonly caused by thrombosis. Black soybean tempeh (BSBT), a traditional Indonesian food fermented with Rhizopus oligosporus fungus is rich in proteolytic enzymes, with potential to be utilized for thrombosis related ailments. Herein, we report the first findings of BSBT enzymatic activity and its subsequent formulation into liposomal system as a thrombolytic. Additionally, we incorporated photosensitizer dyes into the liposomes, phycocyanin and fluoresecein, creating a photothermally active therapeutic delivery system. Liposomes containing BSBTwere formulated using soy lecithin and tween 80, whichwere then subjected to evaluations including size, PDI, zeta potential, morphological, and stability studies. Furthermore, we observed their photothermal efficiency and thrombolytic activity using whole blood clot in vitro model. BSBT crude and purified extract produced satisfactory enzymatic activity, stable at neutral pH (∼7) and maintained stable activity at temperatures of ∼60◦C. Liposome formulation was spherical with a particle size of 607.8 nm; PDI of 0.339; and zeta potential of -24.2 mV. BSBT crude extract and purified enzyme at a concentration of 100% gave 51.28 and 56.05% thrombolytic activity. Based on the test results obtained, the optimum formula of photosensitizer liposomes produced had high encapsulation efficiency, with photothermal efficiency of 57.66 and 44.23% for Lip-Flu and Lip-Phy respectively. The formulations with laser exposure generated good thrombolytic activity (∼55-56%) comparable with nattokinase. Based on these findings, liposomal delivery of BSBT enzymes can maintain proteolytic activity, providing the first insights for thrombolytic purposes of BSBT enzymes.
Development of Nanofiber Made of Nanocellulose with Oil Encapsulation of Eucalyptus sp. Sari, Wida Fatma; Haryati, Sri; Mohadi, Risfidian
Science and Technology Indonesia Vol. 10 No. 4 (2025): October
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.2025.10.4.1074-1086

Abstract

The amalgamation of natural polymers derived from lignocellulosic waste with synthetic polymers is a potential avenue for producing high-value products through nanotechnological innovations. Nanofibers are a significant application of nanotechnology and is now being explored as an alternative method for treating lignocellulosic waste. Nanofiber is a fiber generated by an electrospinning device. Cellulose obtained from lignocellulose can be transformed into valuable products, including nanocellulose. This project entails the synthesis of nanofibers via the combination of natural and synthetic polymers, an innovative approach in the field. Natural polymers are derived from alginate and nanocellulose, whilst synthetic polymers are produced from Poly Vinyl Alcohol (PVA). This study employs nanofibrils in healthcare, specifically as a cartridge filter in masks infused with Eucalyptus sp. This study sought to identify the optimal method for producing nanofibers with a minimal pore size by varying the concentrations of PVA (4%, 8%, 12%, and 16%) and nanocellulose (2.5%, 5%, and 7.5%). This research employs a combination of methods to produce nanocellulose of suitable size, an innovative process. The pretreatment process utilizes a blend of chemical and physical methods. Nanocellulose is synthesized using varying concentrations of sulfuric acid (25%, 50%, and 75%) during the acid hydrolysis process. The optimal nanocellulose size was attained at a sulfuric acid concentration of 50% (40oC, 10 minutes), as evidenced by a mean diameter of 484.3 nm. The amalgamation of physical and chemical methods has demonstrated efficacy in generating a beneficial pore size distribution in nanocellulose. Nanofibers are synthesized utilizing 12% PVA, 0.5% alginate, 2.5% nanocellulose, and 1% Eucalyptus sp. over 30 hours (3 mL), resulting in an average diameter of 200 nm for the created nanofibers. Concurrently, the nanofiber produced in the absence of Eucalyptus sp. exhibited a diameter of 240 nanometers.
Manufacturing and Characterization of Bioplastic from Chitosan and Rambutan Seed (Nephelium lappaceum L.) Starch with the Addition of Sorbitol as Plasticizer Kusumaningsih, Triana; Firdaus, Maulidan; Handayani, Desi; Rahayu, Windi Vinata; Vegasty, Sabella; Ningsih, Dyah A F; Istiqomah, Annisa
Science and Technology Indonesia Vol. 10 No. 4 (2025): October
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.2025.10.4.990-998

Abstract

A bioplastic formulated from chitosan and rambutan seed starch (Nephelium lappaceum L.), with sorbitol added as a plasticizer, presents a promising innovation to reduce the reliance on conventional plastics, which contribute to an annual waste accumulation of 381 million tons. This study aims to produce bioplastic from chitosan and rambutan seed starch, to analyze its physical and mechanical properties, and to determine the optimal composition. The bioplastic was fabricated using the solution casting method, with heating at 85-95◦C and drying in an oven at 60◦C for approximately 24 hours. The resulting bioplastic exhibited favorable tensile strength and elongation, as well as rapid biodegradability in soil. FTIR analysis revealed functional groups including O-H, C-H, N-H, C-O, and C-C, indicating the presence of corresponding components. The best composition was achieved with a starch-to-chitosan ratio of 40:60% and 20% sorbitol, resulting in a thickness of 0.21 mm, density of 0.80 g/cm3, water absorptionof 41.17%, tensile strength of 52.53 N/mm2, elongation of 22.64%, and biodegradability of 36.67%. TGA analysis showed three degradation stages i.e. water dehydration, starch degradation, and chitosan degradation.
Potential of Tropical Seaweed Carageenan in Applications of Soft Capsule as a Replacement for Gelatin: A Review Hidayat, Taufik; Syamsu, Khaswar; Sunarti, Titi Candra; Nurilmala, Mala; Manalu, Lamhot
Science and Technology Indonesia Vol. 10 No. 4 (2025): October
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.2025.10.4.1288-1300

Abstract

Carrageenan, a natural sulfated polysaccharide extracted from red seaweed, has gained significant attention in the development of drug delivery systems, particularly as a capsule-forming material. With its biodegradable, biocompatible, and gel-forming properties, carrageenan offers great potential as a plant-based alternative to animal-derived gelatin. This review evaluates the potential of carrageenan, especially iota-carrageenan, in the production of soft capsules as a gelatin substitute, and compares the characteristics of carrageenan-based hard and soft capsules. Soft capsules are generally formulated with iota-carrageenan and plasticizers such as glycerol to achieve optimal flexibility, while hard capsules utilize kappa-carrageenan due to its stronger gel texture. Structural modifications, including depolymerization and polymer blending, have been reported to improve viscosity, elasticity, and disintegration time of carrageenan capsules. Nevertheless, limitations remain, such as high viscosity and slower disintegration compared to gelatin-based capsules. Therefore, formulation optimization and advanced extraction techniques are essential to enhance carrageenan capsule performance. Future research should emphasize cost-effective and high-purity extraction methods, engineered depolymerization processes, and the modification of kappa-carrageenan to exhibit iota-like flexibility. These strategies are expected to advance the feasibility of tropical seaweed-derived carrageenan as a sustainable and halal-compliant material for pharmaceutical capsule applications.
Extraction Optimization of Phenolic Compounds from Rimpang Lempuyang Gajah (Z. Zerumbet): Green Solvent (NADES-UAE) (Ultrasound-Assisted Extraction) and MAE (Microwave Assisted Extraction) Berghuis, Nila Tanyela; Nursanto, Eduardus Budi; Nanda, Elsa Vera; Maryana, Erma; Tjokrokusuma, Donowati; Kurniawati, Fitri
Science and Technology Indonesia Vol. 10 No. 4 (2025): October
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.2025.10.4.1179-1187

Abstract

The Lempuyang plant is one of the medicinal plants in Indonesia. One of the plants of the Lempuyang family that has not been widely researched is Lempuyang Gajah Zingiber zerumbet (L.). The commonly used method of extraction of phenolic compounds is maceration with organic solvents. The disadvantages are the amount of organic solvents that must be used and the long extraction time (days). An environmentally friendly solvent that has been successfully developed in the 21st century is eutectic or known as Natural deep eutectic solvent (NADES). In addition, NADES can also be used in conjunction with other extraction methods such as (UAE), and microwave aid (MAE). The results obtained were the synthesis of NADES with HBA (Choline Chloride) and HBD variations (Glucose, Lactic Acid, and Ethylene Glycol) with ratios of 1:1 and 1:2. In the maceration process, variations in time (2, 4, 6 hours) and variations in extraction methods (maceration, UAE and UAE-MAE) are carried out. The best TFC (Total Flavonoid Content) value data was obtained by NADES D (choline chloride: glycerol 1:2) of 697.24 mg QE/g extract through a combined ultrasonic and microwave method (UAE-MAE) while the best TPC (Total Phenolic Content) was NADES C (choline chloride: glycerol 1:1) of 2491.88 mg GA/g extract through a combined ultrasonic and microwave method (UAE-MAE). Meanwhile, the characterization of NADES synthesis to see the interaction of hydrogen bonds through FTIR analysis, and the content of phenolic compounds and flavonoids was carried out through HPLC-DAD.
Oil Palm Leaves as an In-situ Bio-silica Source in Sustainable Synthesis of V2O5-SiO2 Yudha S., Salprima; Adfa, Morina; Wibowo, Risky Hadi; Reagen, Muhamad Alvin
Science and Technology Indonesia Vol. 10 No. 4 (2025): October
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.2025.10.4.1148-1155

Abstract

Using ammonium vanadate and natural silica from oil palm leaves in situ at 900oC is a sustainable synthesis method for producing V2O5-SiO2 mixed oxides in the form of a brownish powder. Therefore, this study aims to investigate a more environmentally friendly alternative to synthesizing V2O5-SiO2 using oil palm leaves, a by-product from oil palm farming. The XRD analysis of the reaction products showed specific V2O5 peaks and broadened peaks, indicating the presence of amorphous silica. The Fourier transform infrared (FTIR) analysis, which revealed the presence of Si-O-Si and Si-O-V functional groups, also supported the characteristic assessment. In addition, X-ray fluorescence (XRF) analysis showed that V2O5 (46.70 mass%) and SiO2 (52.60 mass%) were present, along with small amounts of other possible metal oxides, such as P2O5, K2O, CaO, Fe2O3, Al2O3, and PdO.
The Kernel Function of Reproducing Kernel Hilbert Space and Its Application on Support Vector Machine Utami, Bernadhita Herindri Samodera; Warsono; Usman, Mustofa; Fitriani
Science and Technology Indonesia Vol. 10 No. 4 (2025): October
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.2025.10.4.1096-1108

Abstract

Reproducing Kernel Hilbert Space (RKHS) is a Hilbert space consisting of functions that can be represented or reproduced by a kernel function. The development of data science has made RKHS a method that refers to an approach or technique using the concept of reproducing kernels in certain applications, especially machine learning. Support Vector Machine (SVM) is one of the machine learning methods included in the supervised learning category for classification and regression tasks. This research aims to determine the form of linear kernel functions, polynomial kernel functions, and Gaussian kernel functions in Support Vector Machine analysis and analyze their performance in Support Vector Machine classification and regression. Application of the RKHS method in SVM classification analysis using World Disaster Risk Dataset data published by Institute for International Law of Peace and Armed Conflict (IFHV) from Ruhr-University Bochum in 2022 obtained results that are based on the results by comparing the predictions of training data and testing data using linear kernel functions, polynomial kernels and Gaussian kernels, it is recommended that classification using linear kernels provides the best prediction performance.
Decision Tree Algorithms in Water Quality Classification: A Comparative Study of Random Forest, XGBoost, and C5.0 Shofiana, Dewi Asiah; Caniadi, Melan; Sholehurrohman, Ridho; Aristoteles
Science and Technology Indonesia Vol. 10 No. 4 (2025): October
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.2025.10.4.999-1011

Abstract

Safe drinking water is more than a convenience; public health officials often call it a cornerstone of survival. United Nations International Children’s Emergency Fund (UNICEF) reported that, shockingly, roughly two billion people still drink water that is neither clean nor tested. Pathogenic bacteria from human feces and livestock waste taint roughly 70% of available sources, creating a silent epidemic. Scientists express water quality into five levels: poor, marginal, fair, good, and excellent – named as the Water Quality Index (WQI) designed by the Canadian Council of Ministers of the Environment (CCME). This research measured the performance of three decision-tree classifiers, including Random Forest, XGBoost, and C5.0 to predict water quality. The preprocessing pipeline was thorough, involving label encoding, use of synthetic minor over-sampling technique (SMOTE) for balancing imbalanced classes, and an exploratory phase to examine outliers and irregularities within the dataset. According to the findings, Random Forest finished at an impressive test result with 98% of accuracy. XGBoost and C5.0 follows close behind at about 96%, but the latter turned out to be the fastest, edging out both XGBoost and Random Forest, making C5.0 a preferable when a time-sensitive or emergency decision is needed. In short, this research highlights the importance of modern preprocessing tools combined with machine learning algorithms in monitoring water quality.
MgO Scattering Effects on CCT Uniformity and Lumen Strength of The Traditional White LED Packages De, Pham Van; Thinh, Dang Truong; Ho , Sang Dang
Science and Technology Indonesia Vol. 10 No. 4 (2025): October
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.2025.10.4.1280-1287

Abstract

Scattering of light within white light-emitting diodes (LEDs) is crucial for minimizing internal reflection and ensuring consistent color distribution. Among the array of scattering-induced nanoparticles, magnesium oxide (MgO) stands out for its distinctive scattering performance, positioning it as a promising material in the field of optic fiber sensing. This study investigates the integration of MgO nanoparticles into yellow phosphor films with the aim of augmenting the color uniformity and luminous efficiency of conventional white LEDs, specifically those excited by blue light. Light scattering is evaluated across varying concentrations of MgO within the phosphor layer. Results reveal that manipulation of MgO nanoparticle concentration enables precise control over correlated color temperature (CCT) regulation in white LEDs. Furthermore, the inclusion of MgO nanoparticles reduces the requisite amount of yellow phosphor for LED fabrication, thereby curbing production costs. Significantly, MgO exhibits potential in harmonizing CCT and luminosity in white LEDs. Additionally, there is a marginal improvement in color quality scale with increasing MgO concentration. The optimal MgO concentration for achieving a balance between CCT uniformity, luminosity, and color reproduction parameters is determined to be 7 wt.%.
MICE and ADASYN for Missing Data Imputation and Imbalanced Data Handling on Heart Disease Classification Desiani, Anita; Dewi, Deshinta Arrova; Amran, Ali; Pratiwi, Ananda; Andriani, Yuli; Cahyono, Endro Setyo
Science and Technology Indonesia Vol. 10 No. 4 (2025): October
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.2025.10.4.1020-1030

Abstract

The quality of data is determined by several things, namely the completeness and balance data. The heart disease dataset from the University of California, Irvine (UCI) has missing and imbalanced data, which if it is not handled, can lead to a lack of accuracy in the prediction model and errors in interpreting the data. To overcome missing data, several methods can be used, one of which is data imputation. Attributes with missing data of 5% or less are handled using imputation methods such as Mean, Mode, and MICE. Attributes with numeric types are handled by Mean. Attributes with categorical types are imputed byMode. Attributes with more than 5% missing data are imputed using the MICE method. Imbalanced data can be handled by applying an oversampling method using the Adaptive Synthetic Sampling Approach (ADASYN). The effect of imputing missing data and addressing class imbalance on heart disease classification performance was tested using Random Forest, Support Vector Machine (SVM), and Multi-Layer Perceptron (MLP) algorithms. After handling missing values and data imbalance, improvements were observed in the classification results. The accuracy, precision, recall, and F1-score showed excellent performance, above 90% on several classification methods. The results indicate that handling missing and imbalanced data through Mean, Mode, MICE, and ADASYN positively impacts the performance of classifiers on the UCI heart disease dataset.

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