Jurnal Universitas Siliwangi
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Studi Analisis Pengaliran Pipa Air Bersih di Perumahan Bumi Lestari dengan Menggunakan Epanet
Get PDFPerumahan Bumi Lestari terletak di kelurahan Sambongjaya, Kecamatan Mangkubumi, Kota Tasikmalaya, menggunakan sumber air bersih yaitu sumur dengan ketinggian muka airnya adalah 6 meter, mengalami keterlambatan pasokan air jika dialirkan ke hunian rumah yang elevasinya lebih tinggi dari mata air sumur tersebut dan dialirkan secara gravitasi. Beberapa rumah tidak mendapatkan pasokan air bersih karena tinggi energi air pada pipa tidak cukup untuk mengalirkan aliran air ke rumah yang elevasinya jauh lebih tinggi dari reservoir (sumur) sehingga tujuan penelitian ini yaitu mengidentifikasi arah aliran dan menganalisis tinggi energi pada saluran pipa menggunakan epanet. Metode penelitian dimulai dengan studi literatur kemudian pengumpulan data berupa data elevasi setiap junction, diameter dan panjang pipa serta data alur distribusi air dengan kebutuhan debit setiap titik layanan setelah itu data dimasukan kedalam program epanet untuk mencari tinggi energi. Kesimpulan dari penelitian ini diantaranya yaitu identifikasi arah aliran dimulai dari sumber air dimana terdapat 2 sumur dan 2 tandon. Pada tandon 1 mengalirkan air ke blok C dengan 28 titik layanan. Untuk tandon 2 pompa 1 mengalirkan air pada blok D dan C dengan 17 layanan. Pada tandon 2 pompa 2 mengaliri blok A dan B dengan 10 titik layanan sedangkan pada tandon 2 pompa 3 mengaliri blok A dan B dengan 13 titik layanan. Tinggi energi pada saluran pipa yang disimulasikan dengan menggunakan epanet semua mengalir dengan normal kecuali pada saluran pipa di blok D dan C berjumlah 16 hunian dan blok C berjumlah 20 hunian yang mengalami negative head atau kekurangan pasokan air
Pengaruh Risiko Likuiditas, Risiko Operasional, Risiko Bisnis, Risiko Pasar Terhadap Kinerja Keuangan Perusahaan Sub Sektor Kosmetik Yang Terdaftar di BEI Periode 2019-2023
Get PDFPenelitian ini bertujuan menganalisis pengaruh risiko likuiditas, risiko operasional, risiko bisnis, dan risiko pasar terhadap kinerja keuangan (ROA) 5 perusahaan sub-sektor kosmetik di Indonesia berdasarkan total aset periode 2019-2023. Data yang digunakan diperoleh dari laporan keuangan yang tercatat pada Bursa Efek Indonesia. Sampel penelitian dipilih menggunkan teknik Purposive Sampling sehingga diperoleh 5 sampel perusahaan sub-sektor kosmetik yang sesuai kriteria dari total 8 populasi. Metode analisis yang digunakan yaitu Analisis Regresi Data Panel dengan pendekatan Random Effect Model (REM) yang diuji dengan softwere EViews 12. Hasil penelitian menunjukkan bahwa, secara simultan risiko likuiditas, risiko operasional, risiko bisnis, dan risiko pasar berpengaruh signifikan terhadap kinerja keuangan (ROA). Secara parsial, risiko likuiditas berpengaruh negatif dan signifikan terhadap kinerja keuangan (ROA); risiko operasional berpengaruh positif dan signifikan terhadap kinerja keuangan (ROA); risiko bisnis berpengaruh positif dan tidak signifikan terhadap kinerja keuangan (ROA); dan risiko pasar berpengaruh negatif dan tidak signifikan terhadap kinerja keuangan (ROA) pada perusahan sub-sektor kosmetik yang terdaftar BEI periode 2019-2023
Analisis Faktor–Faktor yang Mempengaruhi Profitabilitas Perusahaan Tambang dan Energi Dalam Indeks ISSI Tahun 2019–2023
Get PDFThis study aims to analyze the factors that influence the profitability of mining and energy companies listed in the Indonesian Sharia Stock Index (ISSI) in the period 2019–2023. The variables used as measurements in this study include Green Investment, Enterprise Value (EV), Capital Expenditure (CAPEX), and Shares Outstanding, in determining profitability. This study uses a quantitative approach with a panel data regression method to analyze secondary data obtained from financial statements and company environmental performance reports. The results of the analysis show that green investment has a significant positive effect on company profitability, indicating that the implementation of sustainable investment can improve competitiveness and operational efficiency. The Enterprise Value variable also has a significant positive effect, while Capital Expenditure shows a significant negative effect on profitability, reflecting the potential impact of financial burdens in the short term. Meanwhile, Shares Outstanding also shows a significant negative effect on profitability. This study provides an important contribution to the literature related to sustainable investment, especially in strategic sectors such as mining and energy. The results of this study also provide practical recommendations for investors and policy makers to further encourage the implementation of green investment as a strategy towards economic and environmental sustainability
Studi Integrasi Eko-Enzim dan Ekobrik dalam Mengurangi Limbah dan Meningkatkan Kualitas Lingkungan (studi kasus Kelurahan Silae Kota Palu)
No full textSampah merupakan masalah yang dirisaukan oleh semua kalangan bahkan dunia. Begitupun dengan Kota Palu, sampah makanan mencapai 71% dengan komposisi sampah terbanyak didominasi oleh rumah tangga. Tujuan dari tulisan ini meliputi dua yakni, pertama memberikan edukasi berbasis lingkungan tentang pemanfaatan sampah plastik dan organik, dan kedua mengetahui cara pengelolaan sampah yang efisien dan berkelanjutan lingkungan di Kota Palu. Metode yang digunakan adalah PRA (Participatory Rural Appraisal), dengan metode ini melibatkan masyarakat dalam proses progam kerja. Hasil kegiatan pengabdian masyarakat di Kelurahan Silae bahwa pendampingan pemanfaatan sampah menjadi ekobrik dan ekoenzim efektif dalam pengurangan jumlah sampah yang masuk ke Tempat Pembuangan Sampah. Terciptanya produk ekobrik menjadi meja dan kursi pojok baca di setiap kelas Sekolah Dasar dan produk ekoenzim sebagai pengganti sabun berbahan kimia menjadi sabun ramah lingkungan. Di Kelurahan Silae juga sudah memiliki TPS 3R, hal ini sangat membantu dalam program pengolahan sampah plastik dan organik
Pola konsumsi ultra processed food dan kejadian gizi lebih pada remaja
Get PDFOvernutrition among adolescents is a growing public health concern both globally and nationally. It is closely associated with high consumption of ultra-processed foods (UPF) and low levels of physical activity. Adolescents tend to prefer convenient, energy-dense foods and lead sedentary lifestyles, which can trigger an energy imbalance and lead to fat accumulation. Objective: This study aimed to analyze the differences in UPF consumption patterns and physical activity based on overnutrition status among adolescents. Methods: This quantitative study used a cross-sectional design. The sample consisted of 87 students from grades VII and VIII at SMP Negeri 8 Tasikmalaya, selected using proportionate stratified random sampling. UPF consumption was measured using the Semi Quantitative Food Frequency Questionnaire (SQ-FFQ), and physical activity was assessed using the Global Physical Activity Questionnaire (GPAQ). Nutritional status was determined by measuring body weight (kg) and height (cm), and assessed using BMI-for-age based on Z-scores. Data analysis was conducted using univariate and bivariate analysis with the Mann-Whitney test. Results: There were significant differences in the amount of UPF consumption (p=0.000), frequency of UPF consumption (p=0.000), and physical activity (p=0.002) based on overnutrition status. Conclusion: There are significant differences in the amount and frequency of UPF consumption and levels of physical activity based on overnutrition status among adolescents. Educational efforts and targeted interventions are needed to reduce UPF intake and promote physical activity to prevent overnutrition in adolescents.Gizi lebih pada remaja merupakan masalah kesehatan masyarakat yang semakin meningkat secara global maupun nasional. Gizi lebih berhubungan dengan tingginya konsumsi ultra processed food (UPF) dan rendahnya aktivitas fisik. Remaja cenderung memilih makanan yang praktis dan tinggi energi, serta menjalani gaya hidup sedentari, yang dapat memicu ketidakseimbangan energi dan menyebabkan penumpukan lemak tubuh.Tujuan: Penelitian ini bertujuan untuk menganalisis perbedaan pola konsumsi UPF dan aktivitas fisik berdasarkan kejadian gizi lebih pada remaja. Metode: Penelitian ini merupakan penelitian kuantitatif dengan menggunakan desain penelitian cross sectional. Sampel pada penelitian ini berjumlah 87 siswa kelas VII dan VIII di SMP Negeri 8 Tasikmalaya yang diambil menggunakan teknik proportionate stratified random sampling. Variabel pola konsumsi UPF diukur menggunakan kuesioner Semi Quantitative Food Frequency Questionnaire (SQ-FFQ), sedangkan variabel aktivitas fisik diukur menggunakan kuesioner Global Physical Activity Questionnaire (GPAQ). Status gizi diukur dengan penimbangan berat badan (kg) dan tinggi badan (cm) dan ditentukan menggunakan IMT/U berdasarkan Z-score. Analisis data dilakukan secara univariat dan bivariat menggunakan uji Mann Whitney. Hasil: Terdapat perbedaan antara jumlah konsumsi ultra processed food berdasarkan kejadian gizi lebih pada remaja (p=0,000), terdapat perbedaan antara frekuensi konsumsi ultra processed food berdasarkan kejadian gizi lebih pada remaja (p=0,000), terdapat perbedaan antara aktivitas fisik berdasarkan kejadian gizi lebih pada remaja (p=0,002). Kesimpulan: Terdapat perbedaan signifikan antara jumlah dan frekuensi konsumsi UPF serta aktivitas fisik berdasarkan kejadian gizi lebih pada remaja. Diperlukan upaya edukasi dan intervensi untuk menurunkan konsumsi UPF serta meningkatkan aktivitas fisik guna mencegah gizi lebih pada remaja
MEMBANGUN LOYALITAS PELANGGAN TOKOPEDIA: PERAN E-SERVICE QUALITY, PERCEIVED VALUE, DAN CUSTOMER TRUST
Get PDFThis study aims to examine the influence of e-service quality and perceived value on customer loyalty, both partially and simultaneously. The population of this study were active students of Siliwangi University who had shopped at Tokopedia, with a sample of 388 students. The research method used was verification analysis, with data analysis techniques in the form of multiple linear regression. The results of the study showed three main findings, namely E-service quality and perceived value together have a positive influence on customer loyalty. E-service quality has a positive influence on customer loyalty. Perceived value has a positive influence on customer loyalty
Analisis Dampak Pertumbuhan Ekonomi, Indeks Pembangunan Manusia, dan Kemiskinan dengan Pengangguran sebagai Variabel Moderasi di Sulawesi Selatan
Get PDFPoverty in developing nations, including Indonesia, is a complex issue stemming from inequalities in access to education, healthcare, and economic resources. This study examines the connections between economic growth, the Human Development Index (HDI), and poverty, with unemployment serving as a moderating factor in South Sulawesi from 2019 to 2023, employing panel data and the Fixed Effect Model (FEM). The findings indicate that the HDI significantly reduces poverty, underscoring the importance of enhancing education, healthcare, and income for poverty alleviation. Conversely, unemployment significantly worsens poverty, yet it does not influence the relationship between economic growth and HDI in relation to poverty. Economic growth itself also does not have a direct impact, suggesting the necessity for inclusive growth policies. The study highlights the critical role of HDI and unemployment reduction in addressing poverty, offering policy recommendations focused on enhancing HDI, generating employment, and ensuring a fairer distribution of the benefits of growth. Kemiskinan di negara berkembang termasuk Indonesia merupakan masalah yang kompleks dan terkait dengan ketidakmerataan akses terhadap pendidikan, kesehatan, dan ekonomi. Penelitian ini mengkaji hubungan antara pertumbuhan ekonomi, Indeks Pembangunan Manusia (IPM), dan kemiskinan, dengan pengangguran sebagai variabel moderasi di Provinsi Sulawesi Selatan tahun 2019-2023, menggunakan data panel dan Fixed Effect Model (FEM). Hasil penelitian menunjukkan bahwa IPM berperan signifikan dalam mengurangi kemiskinan, hal yang perlu diperhatikan pentingnya peningkatan sektor pendidikan, kesehatan, dan pendapatan. Sementara itu, pengangguran berkontribusi positif terhadap peningkatan kemiskinan, namun tidak mempengaruhi hubungan antara pertumbuhan ekonomi dan IPM terhadap kemiskinan. Selain itu, pertumbuhan ekonomi tidak menunjukkan pengaruh signifikan secara langsung, yang menunjukkan perlunya kebijakan pertumbuhan yang lebih inklusif. Penelitian ini menekankan pentingnya peningkatan IPM dan pengurangan pengangguran dalam upaya pengentasan kemiskinan, dengan saran kebijakan yang fokus pada peningkatan IPM, penciptaan lapangan kerja, dan pemerataan manfaat pertumbuhan
A Clustering-Based Artificial Intelligence Approach for Minimizing of Ionizing Radiation Exposure in Uyo Metropolis Nigeria
Get PDFElectromagnetic Field (EMF) radio frequency exposure is a growing concern due to its impacts on public health and the environment. This study aims to develop a data-driven framework for clustering and analyzing long-term far-field EMF exposure in Uyo Metropolis, Nigeria, with a focus on identifying exposure patterns and assessing their implications. Data were measured at multiple locations using smart meter strategically deployed across three major roads in uyo metropolis to capture variations in exposure levels. The preprocessing steps involved data cleaning and normalization to enhance data quality and reliability for meaningful analysis. Four clustering algorithms, namely, K-Means, Hierarchical Clustering, DBSCAN, and Gaussian Mixture Model (GMM), were employed to analyze the distribution of radiation levels. The Silhouette score was used to evaluate the different clustering methods with respect to cohesion within clusters and separation from other clusters. The best results were obtained by Hierarchical Clustering and GMM, each achieving a mean Silhouette score of 0.81, indicating well-defined and highly contrasting clusters. K-Means performed moderately well, with an average Silhouette score of 0.73, while DBSCAN, due to its sensitivity to noise and parameter settings, achieved a lower score of 0.62. These findings highlight significant spatial variability in EMF exposure across different urban zones, emphasizing the need for targeted regulatory measures. The study underscores effectiveness of machine learning and offers a scalable approach for characterizing EMF exposure. Results reported offer scalable and data-driven framework for characterizing exposure patterns, with important implications for public health policies, urban planning strategies, and regulatory interventions
Classification Of The Maturity Level Of Glutinous Rice Tape Fermentation Using Convolutional Neural Network
No full textStiky tape is a popular snack in Indonesia made from fermented ketan rice. One of the main benefits of eating white cheddar rice is to trigger the digestive system. Excessive consumption can result in a decrease in sweetness and inappropriate texture. Therefore, it is necessary to classify the maturity level of the tape, so that there is no excessive maturity that results in adverse effects on the body and the quality of the tapes.The study aims to test the accuracy of the white tape maturity classification program as well as design and implement a classification system using the Convolutional Neural Network (CNN) method with the VGG16 architecture. The white tape image data set was obtained with the iPhone X camera in jpg format, covering three maturity classes: raw, ripe, and rotten, each consisting of 400 images. The data set is divided into 768 training data, 192 validation data, and 240 test data, then processed through preprocessing stages including resize, augmentation, and rescale. The CNN model was implemented with the VGG16 architecture and tested on various Epochs, producing an accuracy of 0.98 on Epoches 20 and 30, and reaching 0.99 on the 40th. The results of the research showed that the CNN method with VGG-16 architecture was effective in classifying the maturity level of the tape, achieving high accuration and significant consistency as the number of Epochs increased. This implementation is expected to preserve the quality of the tapes and extend the application of modern technology in traditional industries
Integration of SMOTE and Ensemble Models for Predicting Airline Passenger Satisfaction
No full textThe high public interest in air transportation has become a polemic for airline companies that are competing to maintain their existence by continuously improving their services. The passenger satisfaction survey data collected has several problems such as unbalanced data, missing values, noise, difficulty finding significant patterns and biased data. Imbalanced class causes the classification results to lean more towards the majority class, this can reduce the performance of the prediction model. SMOTE is one of the over-sampling methods to balance the dataset by increasing the number of samples in the minority class based on k-nearest neighbors to approach the same class. Boosting is a machine learning strategy that combines many very fragile and poor prediction rules to produce very accurate prediction rules. In this study, we conducted a model experiment by integrating the SMOTE and AdaBoost ensembles with the classification algorithm to obtain the best performance metrics. The results showed that the performance of integrating the DT + SMOTE and DT + SMOTE + AdaBoost models produced an accuracy of 91.88%, this performance is superior to the traditional DT model. Significant performance improvements also occur in the integration of NB+SMOTE+AdaBoost and NB+AdaBoost, which is an increase of around 5% compared to NB. However, the application of SMOTE to NB decreases accuracy because SMOTE produces synthetic samples that can disrupt the independence assumption of NB. The results of this study demonstrate the superiority of our proposed method, a robust ensemble learning compared to traditional machine learning classifiers. Both techniques are very efficient in improving classification capabilities, especially in cases of complex and imbalanced data. AdaBoost, Customer satisfaction prediction, Data mining, Ensemble learning, Imbalanced data, SMOTE.