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Implementation of Clustering Time Series with DTW to Clustering and Forecasting Rice Prices Each Provinces in Indonesia
No full textIndonesia faces a significant imbalance between domestic supply and demand, leading to escalating rice prices and pronounced regional disparities. To elucidate underlying price patterns and forecast future trends, this study employed Hierarchical Clustering Time-Series with DTW and ARIMA modelling at both individual and cluster levels. Comprehensive analysis, incorporating visualization and threshold comparisons, identified Central Kalimantan as an outlier. Individual ARIMA models demonstrated exceptional performance, with MAPE values below 10%. The clustering time-series correlation using Cophenetic coefficient, reached 0.68 for ward linkages. Two clustering approaches were explored: (1) ignoring the outlier province, (2) excluding Central Kalimantan and incorporating it into a separate cluster. Optimal cluster measurement, the Elbow, Silhouette, Calinski-Harabasz, and Davies-Bouldin, yielded 6-7 clusters for the former approach and 3-5 clusters for the latter. Comparative analysis of individual and cluster forecasts, coupled with paired t-tests, revealed that Ward linkage in the second approach produced the most favorable results, with 27/34 provinces exhibiting cluster MAPE values less than or equal totheir individual MAPE. This finding underscores the efficacy of cluster-based modeling in generating accurate and representative estimates for a substantial portion of provinces. A 12-period rice price forecast indicates a prevailing trend of rising prices in most regions of Indonesia
Ensemble Physics of the Weather Research and Forecasting (WRF) Model for Predicting Heavy Rainfall in the Bandung area, West Java
Get PDFThe complex topography of the Bandung region, with the presence of mountains and valleys, can affect air flow patterns and rainfall distribution. Accurate weather predictions and spatial precision are crucial for anticipating the impacts of heavy rainfall. This study aims to evaluate the capability of the WRF physics ensemble prediction system in forecasting heavy rainfall events in the Bandung region. The use of an ensemble prediction system is a viable approach to quantifying uncertainty in numerical weather prediction and provide more reliable information. The case study used is the heavy rainfall event that caused flooding on October 4, 2022, in the Pagarsih area. Global Forecasting System (GFS) data with a spatial resolution of 0.25 x 0.25 and a temporal resolution of three hours were used as input for downscaling in the WRF-ARW model. This study used 9 configuration schemes of the WRF-ARW model parameterization as ensemble members. The results of the study indicate that the WRF model (a combination of the Purdue Lin, Yonsei University Scheme, and Betts-Miller-Janjic Scheme) provided the most accurate heavy rainfall prediction, with an RMSE value of 2.13. The probability maps of rainfall products can effectively identify peak heavy rainfall between 1:00 PM- 4:00 PM. This is indicated by the large area with a greater than 90% probability of rainfall exceeding 10 mm. The ensemble mean product of rainfall predictions tends to underestimate heavy rainfall in the Pagarsih area. The ensemble mean product of surface air temperature can effectively identify the pattern of observational f luctuations with a low RMSE value (0.77), and the ensemble mean product of surface layer air humidity can identify the pattern of observational fluctuations with a relatively high RMSE value (13.28)
Overflow Analysis on the FO Purifier of KM Tanto Sukses Vessel
Get PDFThis research aims to analyze the factors that cause overflow in the fuel oil purifier system and to identify measures that can be taken to address this issue using the Failure Mode and Effect Analysis (FMEA) method. Overflow in the fuel oil purifier can disrupt the fuel purification process, which is crucial for engine performance. Therefore, understanding the causes and appropriate solutions is essential. The analysis results indicate that the factors causing overflow include leakage or wear of vital components such as O-rings, gravity discs, belts, bowls, main seal rings, ball bearings, nozzles, and pilot valves, as well as improper installation of components or blockages due to debris obstructing the flow. Overflow can be managed through regular inspections of components prone to wear or damage, routine cleaning of components that are susceptible to clogging, and continuous monitoring and calibration of the system to ensure the purifier operates optimally. By implementing these measures, the fuel oil purifier system is expected to function efficiently, reduce the risk of overflow, and enhance the reliability of the fuel purification process
A Participatory Risk-Matrix Framework for User-Centered Validation of a Manual Standing Wheelchair
Get PDFThis study presents a participatory, risk-based validation framework for a manually actuated standing wheelchair. The standing function offers both physical and psychosocial benefits, including greater independence, improved social interaction, and better access to vertical space. However, adoption of such devices remains limited, especially in low-resource settings, due to concerns about usability, comfort, and safety. Rather than emphasizing technical novelty, the contribution of this study lies in applying a user-centered risk-matrix approach to systematically translate stakeholder concerns into design priorities. Through engagement with eight stakeholders, including direct users and institutional representatives, the study collected qualitative feedback on user experience. This feedback was organized into eight thematic risk categories. Among them, stability during transitions and the level of physical effort required were identified as the most pressing concerns. Each risk type was then evaluated using a qualitative 5×5 matrix to assess its likelihood and potential impact. This structured process enabled the design team to prioritize and implement targeted improvements, effectively reducing the likelihood of tipping-related risks. However, physical accessibility, particularly for users with limited upper-body strength, remained a high, unmitigated risk due to inherent limitations of manual operation. The study highlights the importance of integrating structured risk analysis with real user input to inform assistive technology development that is not only functional, but also contextually responsive
The Effect of Electric Field on Antioxidant Extraction from Avocado (Persea Americana) Seed
Get PDFAvocado seeds have gained attention as a promising natural ingredient for various applications. Utilizing avocado seeds reduces food waste and improves sustainability. Avocado seed contains a high concentration of bioactive chemicals as natural antioxidants that scavenge free radicals. This study investigates the impact of electric field (EF) treatment on avocado seed extraction enhancement. The effect of electric field strength ranging from 2.5 to 7.5 kV/cm with a treatment time of 5 minutes was investigated. Extraction yield, FTIR analysis, antioxidant activity (via the DPPH radical scavenging assay), and IC₅₀ values were obtained from the experimental data. The data were analyzed to evaluate extraction performance and to determine free radical scavenging activity. The result indicates that the value of E influences the extraction result. The best extraction conditions was achieved at an electric field strength of 7.5 kV/cm. The highest performance was obtained using an electric field of 7.5 kV/cm with extraction yield 13.29%, antioxidant activity of 95%, and an IC50 concentration of 120 µg/mL. The FTIR spectrum shows several peaks at 3206, 2937, 1603, 1402, 1021, and 879 cm-1 representing OH, C-H stretch, C=C, -C-H stretch, C-O stretch, and in-plan deformation vibration CH, respectively, to indicate the presence of antioxidants. This study demonstrates that electric field-assisted extraction serves as an eco-friendly alternative to conventional methods for obtaining natural bioactive compounds from avocado seeds
The Application of the K-Medoid Classification Method for Analyzing Crime Rates in South Sulawesi
Get PDFThis research employs the k-medoid clustering method to analyze districts and cities in South Sulawesi based on their crime rates. As the population grows, employment opportunities tend to diminish, which can increase stress levels and, consequently, the likelihood of criminal behavior. To evaluate the distribution of criminal incidents across South Sulawesi, the k-medoid method is used to cluster regions. Unlike other clustering methods, k-medoid utilizes the median as the cluster center (medoid), which enhances its robustness against outliers. Specifically, the Partitioning Around Medoids (PAM) algorithm is applied, where initial objects are randomly selected to represent clusters. If the error value is high, the cluster centers are adjusted until the error is minimized. The dataset comprises crime incidence data for South Sulawesi in 2020, focusing on various types of crime. The analysis identified an optimal number of three clusters based on the Silhouette coefficient. Cluster 1 includes 11 regions, Cluster 2 consists of 8 regions, and Cluster 3 contains 5 regions. These clusters provide a comprehensive overview of the crime conditions across different regions within each cluster
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No full textJurnal Manajemen Aset Infrastruktur & FasilitasVolume 9, Nomor 4, Oktober 2025 (e) ISSN 2615-1847 (P) ISSN 2615-1839JMAIF, Vol. 8, Nomor 1, Januari 2024 Analisis Skema Kerja Sama Pemerintah dan Badan Usaha (KPBU) sebagai Alat Pengadaan Jaringan dan Telekomunikasi di Indonesia (Studi Kasus: Palapa Ring)Farah Sabila & Willy Wijaya Analisis Kondisi Fasilitas Pasar Andir Bayongbong Kabupaten GarutCitrawati Citrawati & Tri SetyowatiEvaluasi Batasan Penggunaan Kolom Pipih pada Hunian Konsep MinimalisIka Rahmawati Suyanto & M Alif KurniawanAnalisis Kondisi Sarana dan Prasarana Pasar Ciwastra Kota BandungSiti Alya Kamila & Tri SetyowatiRoad Embankment Stability Analysis on Soft Soil, Case Study : City of Palembang Boundary / Banyuasin Regency Boundary - Tanjung Api-Api Road STA 60+450Hegi Hermawan Maulana, Mohamad Khoiri & BudiaminEvaluasi Kinerja Aset Gudang Tertutup PT Kansai Prakarsa CoatingsPutri Dewi Purnama & Halla Nur AzizahJMAIF, Vol. 7, Nomor 4, Desember 2023Evaluasi Kualitas Fasilitas Jalur Pedestrian Bagi Disabilitas Di Jalan Pajajaran Kota BandungRadilla Lailatussalma Sayyidina & Moch. Yusup Evaluasi Aset Fisik Dan Fungsi Pada Fasilitas Penumpang Di Terminal BekasiAnanda Suherlan & Moch. YusupAnalisis Kebutuhan Sistem Informasi Inventarisasi Aset Spasial Berupa Pemetaan Bangunan Heritage Jalan BragaNur Annisa Noviyanti Keberlanjutan Infrastruktur Pengolahan Minyak Jelantah Menjadi Biodiesel dalam Upaya Zero Waste untuk Pedagang KecilMarsono, Ariyanti Sarwono & I Wayan Koko SuryawanPerencanaan Sistem Jaringan Distribusi Air Bersih Berdasarkan Debit Andalan dan Kebutuhan Air di Perumahan Bridge Town MalangVasha Yusren Fadlillah, Anie Yulistyorini & Gilang Idfi Identifikasi Dampak Risiko pada Pembangunan Jalan Tol Trans Sumatera Ruas Lubuk Linggau–Curup-BengkuluDwi Jenita Maharani, Suryo Hapsoro Tri Utomo & Muh. Fauzie Siswanto
Produk dan Layanan Utama Perbankan Syariah
Get PDFSistem perbankan syariah merupakan entitas perbankan yang menjalankan operasionalnya berlandaskan pada ketentuan-ketentuan syariat Islam, dengan penekanan utama pada pengharaman riba, gharar, dan maisir. Ragam produk serta layanan primer yang disediakan oleh perbankan syariah mencakup skema pembiayaan, fasilitas simpanan, dan berbagai jasa keuangan lainnya yang telah diselaraskan dengan hukum Islam. Skema pembiayaan yang ditawarkan meliputi akad murabahah, musyarakah, mudharabah, dan ijarah, sementara fasilitas simpanan terdiri atas tabungan wadiah serta deposito mudharabah. Di samping itu, perbankan syariah turut menyajikan layanan perbankan digital, konsultasi keuangan berbasis syariah, dan instrumen investasi melalui sukuk. Implementasi produk dan layanan tersebut bertujuan untuk menghadirkan manfaat ekonomi yang berkeadilan, transparan, dan selaras dengan etika syariah, sekaligus mendorong inklusi keuangan bagi seluruh lapisan masyarakat
Corrosion Detection on Ship Hull Using ROV Based on Convolutional Neural Network
Get PDFThe Remotely Operated Underwater Vehicle (ROV) has several inspection functions. One of them is the inspection function for hull damage. The damage that often occurs in the hull is corrosion. The corrosion can cause a decrease in the strength of the hull plate, reduce the speed of the ship, and decrease the quality of the safety level of ships and passengers. This study aims to classify the level of corrosion intensity on ship hulls by implementing a Convolutional Neural Network (CNN). Identification is carried out on images taken by underwater cameras via a Remotely Operated Vehicle (ROV). The intensity of the area affected by corrosion is identified so that the level of corrosion intensity can be classified and it can be considered that the ship needs maintenance to prevent even greater losses due to corrosion. The dataset used is 240 image data divided into 3 classification categories: low, medium, and high corrosion intensity. The accuracy of the real-time testing of the CNN method on the dataset plate when conditions outside the water reached 91.1% and on the dataset plate when conditions underwater reached 86.6%.
Optimization of Ship Stability through Response Surface Methodology: Enhancing Safety and Performance via Cross Curve Analysis
Get PDFOptimizing the cross curves of ship stability through the application of Response Surface Methodology (RSM) requires a complex interplay between factors such as hull shape, beam, and draft significantly influences a ship's stability, which is crucial for the safety of the crew, passengers, and cargo. By employing RSM, this research systematically examines these factors, developing a second-order polynomial model to describe their relationship with stability metrics. The experiments were conducted using Design-Expert 13® software, which facilitated the design of experiments, data collection, model development, and validation. The optimized model revealed that while the overall impact of individual factors might not be significant, their combined interactions provide a robust predictive capability for ship stability. The results demonstrated that the optimized input variables led to improved stability outcomes, minimizing moment trim while maximizing longitudinal and transverse metacentric heights, thereby ensuring better performance and safety across various sea conditions