Center for Scientific Publication
Not a member yet
4029 research outputs found
Sort by
Spatial Extreme Value Analysis of Extreme Rainfall Using the Extremal-t Process
Full text linkIndonesia’s diverse topography, consisting of coasts, lowlands, highlands, and mountains, results in a wide range of weather and climate conditions, enabling various hydrological phenomena such as extreme rainfall, hurricanes, high temperatures, and storms. In recent years, global warming has emerged as a major environmental concern, with one of its significant impacts being climate change. This, in turn, increases the frequency and intensity of extreme hydrological events, potentially causing floods, transportation and communication disruptions, infrastructure damage, agricultural losses, and threats to human life. This study aims to identify the best model and estimate the return levels of extreme rainfall in Ngawi Regency from March 1990 to November 2022 using spatial extreme value analysis with max-stable processes and the extremal-t process. Daily rainfall data from 1990 - 2018 were used for model training, while data from 2018 - 2022 were allocated for model testing to validate predictive performance. Parameter estimation was conducted using Maximum Likelihood Estimation (MLE) and Maximum Pairwise Likelihood Estimation (MPLE), solved through the Broyden-Fletcher-Goldfarb-Shanno (BFGS) Quasi-Newton numerical iteration method. The analysis shows that the best trend surface model has average rainfall and variance influenced by latitude, while the distribution shape is unaffected by latitude or longitude, indicating isotropy. Furthermore, the return level prediction demonstrates higher accuracy when applied over a three-year period
Comparison Of KNN, Random Forest, And F-PSO Algorithms On Simple Feature Scaling for Agility Level Classification
Full text linkClassifying agility levels presents challenges due to variations in team members’ personalities, roles, and undesirable behaviors. This study aims to enhance classification accuracy by comparing the performance of three algorithms: K-Nearest Neighbors (KNN), Random Forest, and Fuzzy-Particle Swarm Optimization (F-PSO) in classifying agility levels using simple feature scaling as part of the data preprocessing. Simple feature scaling is employed to ensure that all parameters are on the same scale, thereby improving the model’s effectiveness in learning classification patterns. F-PSO was selected for its ability to perform adaptive global search optimization within a fuzzy environment, while KNN and Random Forest serve as benchmarks. The study involved 160 participants from various Scrum teams to evaluate the effectiveness of these algorithms. The parameters considered included team members’ personalities (based on the Keirsey model), roles within the team, and the identification of negative behavior patterns (antipatterns). The results indicated that the F-PSO algorithm significantly outperformed KNN and Random Forest in terms of accuracy, improving from an average accuracy of 25% before optimization to 93.75% after applying F-PSO. This approach enables Scrum teams to identify and address obstacles affecting agility, facilitating earlier problem prediction and resolution, leading to more adaptive and effective teams
Viscosity Modeling and Prediction of Amorphophallus oncophyllus and Sapindus rarak Using Machine Learning Methods
Full text linkViscosity plays an important role in regulating the mobility of fluids injected into the reservoir to increase the efficiency of oil sweeping. This study discusses the application of Machine Learning methods, namely ANN and ANFIS, to model the correlation of physical properties of Amorphophallus oncophyllus and Sapindus rarak solutions. The purpose of this study is to obtain a correlation to determine the viscosity of the polymer solutions. The data used include viscosity measurements for 21 samples of Amorphophallus oncophyllus and Sapindus rarak solutions with variations in concentration and salinity. The data is augmented by digitization for modeling. The results show that both Machine Learning methods can estimate viscosity values well. Very accurate results are achieved by applying ANN and ANFIS with average correlation coefficients of 0.997240 and 0.995124, respectively
NUMERICAL ANALYSIS OF SHEAR CAPACITY OF DOUBLE CORRUGATED WEB GIRDER INFILLED
Full text linkThis research investigates the shear capacity of double corrugated web steel I- girders filled with concrete using finite element analysis. The study examines the influence of the corrugation angle and the thickness of the concrete filling on the strength capacity of the girder beams. Four beams were designed to fail in shear along a 1500 mm span from the left support of the beam, enabling the determination of shear failure conditions. Each beam had identical properties with a flange width (B) of 250 mm, a web height (H) of 1000 mm, a span length of 3500 mm, a flange thickness (tf) of 15 mm, and a web thickness (tw) of 1 mm. The research employed a 3-point bending method, applying a single load point 1500 mm from the left support. The tests were conducted by varying the corrugation angles and the thickness of the concrete filling in the corrugated web, which served as the research variables. The study aimed to determine the peak load-deflection curve, the failure mode diagram, and the shear capacity of the girder beams. The results of the tests showed that the double corrugated web steel I-girder filled with concrete, with a corrugation angle of 45 degrees and a concrete thickness of 65 mm, exhibited the best load-bearing strength among the three variations tested. It demonstrated a 52.65% increase in load capacity and a 53.49% reduction in deflection compared to the finite element validation test values. In contrast, the other three variations showed a decrease in shear strength
Effect of the Increase in Vertical Web Member Stiffness on Lateral Buckling Strength of the Pony Steel Bridge
Full text linkIn half-through bridge or pony steel bridge, that is a bridge without upper wind bracing, strength of the bridge is determined mainly by the lateral buckling strength of its upper chord. Buckling strength of this chord is provided by the flexural stiffness of vertical web member, cross beam, and diagonal beam. In order to improve the stiffness of vertical web member, triangular steel profile that was quite high was added to the inner side of bridge for reducing the clearance width in bridge and disturbing traffic or pedestrian. In this research, stiffness of the vertical web member was improved by using the non-prismatic cross section and adding the triangular stiffener as high as the concrete deck. Finite Element Analysis for the lateral stiffness of bridge cross section used a 3D element model which has been validated by previous study. This numerical study was conducted to validate the Engesser theory for determining the lateral elastic stiffness from upper chord. Study shows the result that accuracy of 3D element model is extremely high, compared with analytic method. Lateral elastic stiffness of bridge in general increased along with the stiffness of vertical web member. However, it can be concluded that effect on the capability of lateral buckling in upper chord was not too significant, as a consequence of the increase in stiffness of vertical web member. Critical lateral buckling occurred in an inelastic range, in which the critical inelastic buckling stress was determined using small tangent modulus as alternative of modulus of elasticity
Analysis of Suitability and Carrying Capacity for Ecotourism Purposes in the Sepanjang Beach Tourism Area
Full text linkPantai Sepanjang menawarkan hamparan pasir yang luas dan panjang dengan sedikit karang dan bukit kapur yang telah berubah menjadi tebing. Melalui pemandangan alamnya, pengunjung menjadi tertarik untuk mengunjungi Pantai Seanjang. Tujuan dari penelitian ini adalah untuk menganalisis tingkat kesesuaian pariwisata untuk keberlanjutan. Sementara itu, penelitian terkait daya dukung kawasan dilakukan untuk mengetahui kemampuan sumber daya alam dalam mempertahankan fungsi dan kualitasnya untuk memberikan pengalaman rekreasi yang diinginkan pengunjung. Demi ketersediaan ekosistem, perlu diterapkan prinsip-prinsip ekowisata untuk memberikan batasan perilaku bagi manusia sebagai pelaku pariwisata untuk melakukan aktivitas rekreasi tanpa mengurangi kepuasan wisatawan. Teknik pengumpulan data kesesuaian pariwisata menggunakan 11 parameter: tipe pantai; lebar pantai; kedalaman air; material dasar air; kemiringan pantai; kecepatan arus; kecerahan perairan; penutupan daratan pantai; biota berbahaya; dan ketersediaan air tawar. sedangkan daya dukung kawasan dihitung dengan menghitung tingkat ekonomi masyarakat sekitar kawasan wisata; kontribusi masyarakat; aktivitas pengunjung; luas area yang dapat dimanfaatkan pengunjung; lama kunjungan; lamanya waktu kawasan wisata dibuka dalam satu hari. Hasil analisis kesesuaian wisata pada stasiun 1 adalah 2,32, stasiun 2 2,32, dan stasiun 3 2,2. Hasil menunjukkan daya tampung kawasan tersebut adalah 240 orang/hari untuk kegiatan penangkapan ikan dan 744 orang/hari untuk kegiatan rekreasi pengunjung
PENGUJIAN pH, GUGUS FUNGSI DAN AKTIVITAS ANTIBAKTERI KRIM BERBAHAN VIRGIN COCONUT OIL (VCO)
Full text linkThis study aims to determine the pH, determine the functional groups and determine the diameter of the inhibition zone of cream made from VCO. In this study, cream was made with 2 formulations, formula 1 with 15% VCO concentration and formula 2 with 20% VCO concentration. In making the cream, all the ingredients that will be used were weighed first. The oil phase (VCO, vaselin album, stearic acid, span 60, and propyl paraben) was heated to 70°C. The water phase (glycerin, methyl paraben, tween 80, and distilled water) was heated to 70°C. The water phase was gradually incorporated into the oil phase at 70°C. It was then homogenised at 2000 rpm for 15 minutes to cool. Both cream formulas were analysed for pH, functional groups and antibacterial activity. The pH of VCO-based cream in formula 1 has an average pH value of 5.91 and formula 2 has an average pH value of 6.03, so each cream sample has an acidity level with a range of 4.5-6.5. The functional groups found in VCO-based cream formulas 1 and 2 are: C-H bending, C=C stretch (aliphatic and aromatic); C=N, C=O stretch (acids, aldehydes, ketones, amides, esters, anhydrides), CΞC stretch; CΞN, C-H stretch: CH3; CH2, Stretch C-H: C-H; C=C-H; Ar-H. In the range of numbers 3750 - 3000 cm-1 there are functional groups O-H; N-H. Waves 3000-1000 cm-1 have a sharp band shape and strong intensity. The wavenumber 3700-3100 cm-1 has a wide band shape and strong intensity. F2 cream has a larger inhibition zone diameter than F1 cream. The diameter of the inhibition zone of cream F2 is largest at a concentration of 10%, the greater the concentration the less the diameter of the inhibition zone
Optimalisasi Desain Scaffolding: Studi Pengaruh Scaffolding dengan Penambahan Outrigger
Full text linkOutrigger sendiri pada scaffolding sudah cukup lama diperkenalkan sebagai tambahan pada scaffolding, namun di mayoritas pelaksanaan pembangunan, outrigger ini jarang sekali untuk digunakan dikarenakan efisiensi waktu dan biaya, usulan pada penelitian ini yaitu untuk melakukan studi analisis kekuatan scaffolding ditambahkan dengan outrigger dengan menggunakan Finite Element Analysis (FEA), dengan demikian dapat diketahui bagaimana pengaruh outrigger dalam scaffolding untuk memperkuat struktur sehingga meminimalisir kemungkinan terjadinya kecelakaan kerja. Di dalam proposal penelitian ini, scaffolding akan dilakukan pemodelan dengan beberapa variasi yaitu variasi satu lantai, dua lantai, dan tiga lantai dengan dua konfigurasi outrigger yaitu satu sisi dan dua sisi. Uji dorong (pushover test) akan dilakukan pada Finite Element Analysis dengan displacement controlled untuk mengetahui bagaimana performa scaffolding. Penggunaan perkuatan outrigger diharapkan dapat menurunkan defleksi (Δ) scaffolding. Sedangkan penerapan metode ini di lapangan diharapkan mampu memperpanjang waktu runtuh bangunan agar pekerja memiliki waktu lebih lama untuk melakukan evakuas
Prediction and Analysis of The Number of ARI Cases based on PM2.5 Concentration with Co-Kriging Approach
Full text linkAir quality significantly impacts global environmental health, influencing both human well-being and climate change. According to the World Health Organization (WHO), air pollution is one of the most substantial environmental threats to human health, with Indonesia experiencing particularly severe air quality issues. The World Air Quality Report ranks Indonesia 14th globally and 1st in Southeast Asia for poor air quality, with a notable increase in PM2.5 concentrations to 37.1 µg/m³ in 2023. Major sources of pollution include coal-fired power plants, motor vehicles, forest fires, and agricultural activities. In urban areas like Surabaya, PM2.5 levels have risen, contributing to high incidences of Acute Respiratory Infections (ARI). Spatial analysis reveals a correlation between PM2.5 levels and ARI cases, with spatial regression and co-kriging methods offering accurate estimation models. This study utilizes co-kriging, incorporating PM2.5 data from nine districts in Surabaya, to estimate ARI cases. The Exponential semivariogram model provided the most accurate predictions, with a MAPE value of 5.11%. The highest estimated ARI cases were in the Kenjeran district, highlighting the need for targeted interventions. Future research should expand observation points and consider additional influencing factors such as weather, population density, and socioeconomic conditions to enhance prediction accuracy and support effective public health strategies