Trijurnal E-Journal Universitas Trisakti
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    PENGARUH KONSENTRASI LARUTAN GARAM NATRIUM KLORIDA SEBAGAI MEDIA PEMISAH TAILING TIMAH DENGAN METODE SHAKING TABLE

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    Tailing merupakan limbah hasil pengolahan bijih yang masih dapat berpotensi menghasilkan manfaat jika diolah sebaik mungkin. Tailing timah berupa pasir biasanya mengandung mineral-mineral pengikut salah satunya yaitu zirkon. Zirkon merupakan salah satu senyawa kimia yang bersifat stabil. Zirkon sering ditemukan mengandung unsur radioaktif yang terdapat dalam struktur kristalnya. Terdapatnya kandungan zirkon dalam tailing timah menandakan masih adanya manfaat dari tailing timah tersebut. Penelitian ini menggunakan metode shaking table untuk memisahkan tailing timah dengan media pemisah larutan NaCl guna meningkatkan kadar zirkon dalam sampel tailing timah. Sampel yang digunakan dalam penelitian menggunakan tailing timah yang diperoleh dari PT Timah Tbk site Toboali, Bangka Selatan. Metode penelitian yang dilakukan dalam penelitian ini menggunakan metode eksperimental, untuk melihat pengaruh konsentrasi NaCl terhadap pemisahan bijih timah dengan metode shaking table. Konsentrasi NaCl yang digunakan dalam penelitian ini yaitu, 2,5; 3,76; dan 7,5 M, dengan kemiringan 0,9° yang dimana masing-masing variabel menggunakan sampel berukuran +100 mesh sebanyak 4000 gram. Sampel awal sebelum penelitian dilakukan uji kandungan mineral (XRD) dan uji kadar zirkon (XRF), lalu pada konsentrat hasil pengolahan dilakukan uji kadar zirkon (XRF), sehingga dapat mengetahui dan memperhitungkan perolehan dari setiap pengujian yang dilakukan

    LITERATURE STUDY: GROUND SURFACE SETTLEMENT DUE TO PIPE INSTALLATION WORKS USING THE PIPE JACKING METHOD

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    Trenchless technology has been applied to minimize traffic, social, and commercial disruptions caused by construction works such as pipe installation. This technology includes pipe jacking, an underground boring method using hydraulic power. Soil disturbance due to pipe installation using the pipe jacking method is an element that must be considered and monitored during the construction and design process, because excessive ground surface settlement can potentially damage structures near the construction area. Over time, methods for predicting surface settlement continues to develop, including finite element and analytical method such as Peck’s, Verruijt’s, and Pinto’s formula. The variety of methods also encourages the growth of new characteristics and features in ground surface settlement due to pipe jacking, including the non-symmetrical ground surface settlement to the pipe axis in curved pipe jacking, the significant impact of jacking force magnitude and shield machine movement, to grouting as the impact mitigation of construction work damages.

    META-ANALYSIS OF LAND VALUE UPLIFT FROM TOD PROJECTS: IMPLICATIONS FOR URBAN DEVELOPMENT AND POLICY

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    Aim: This study aims to systematically quantify the average land value appreciation (LVU) associated with Transit-Oriented Development (TOD) initiatives globally and present standardized reference values for the efficient design of Land Value Capture (LVC) measures. Methodology and results:                The employed meta-analysis using evidence from multiple empirical studies of different urban settings and transit modes. Fixed Effect and Random Effect Models were used to statistically robust estimate LVU measures against heterogeneity of methodologies, locations, and transit systems. Publication bias and variance estimation approaches (DL, REML, PM) were tested for providing reliable results. Analysis in our study finds average TOD-related LVU between 4.2% and 39.4%, and an overall effect size of 14% (95% CI: 8% - 20%) within 1km of transit stations. Conclusion, significance and impact study: Meta-analysis documents substantial but heterogeneous LVU from TOD initiatives, confirming the economic return of transit investments and highlighting the relevance of local contextual determinants of the size of uplift. The research provides essential standardized LVU comparisons for policymakers, urban planners, and researchers creating effective LVC programs to achieve sustainable urban growth. Findings confirm evidence-based investment decisions in infrastructure and contribute to theory for transit-induced land value relations, making it possible to make more accurate financial estimates for future TOD projects globally

    PENGARUH PENAMBAHAN CANGKANG KERANG SEBAGAI ADITIF PENYEMENAN

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    Keberhasilan proses pemboran sumur minyak tergantung pada kualitas dan campuran semen pemboran. Perencanaan komposisi pembuatan bubur semen yaitu air, bahan tambahan, atau campuran tambahan lainnya perlu dianalisa untuk menghasilkan sifat-sifat bubur semen yang diinginkan. Tujuan penelitian adalah untuk mengetahui komposisi dan sifat fisik bubur semen dengan penambahan zat adiktif cangkang kerang pada tiga variasi suhu waktu pengentalan, kuat tekan, dan rheologi bubur semen. Metodologi penelitian, desain penelitian kuantitatif menguji pengaruh penambahan aditif terhadap berbagai sifat fisik bubur semen. Pelaksanaan sesuai dengan protokol penelitian yang telah disusun. Analisis dengan mengukur waktu penebalan, kuat tekan, dan reologi bubur semen menggunakan peralatan vicat, dengan memperhatikan kondisi tekanan dan suhu standar API 10A. Hasil penelitian, pengujian semen kelas G dengan aditif kerang pada kadar air 44% menunjukkan hasil penurunan kuat tekan dengan setiap penambahan konsentrasi aditif. Penambahan aditif clamshell pada kadar air 44% dengan tiga variasi temperatur yaitu 80°F, 140°F, dan 200°F waktu perendaman selama 24 jam dan 8 jam. Suhu memiliki pengaruh yang besar terhadap uji waktu pengentalan sampel semen dan waktu perendaman akan berpengaruh lebih besar terhadap penambahan aditif kerang. Hasil uji waktu pengentalan semen kelas G dengan penambahan aditif cangkang kerang pada substitusi cangkang kerang 0%, 15%, 20%, 25% dan 50%, menunjukkan bahwa semakin banyak substitusi cangkang kerang maka semakin cepat waktu pengeringan pada pembacaan vicat dan hasil yang sama Ditemukan juga pada uji kuat tekan ekosemen pada substitusi cangkang kerang 0%, 15%, 20%, 25% dan 50% menunjukkan penurunan nilai kuat tekan dengan semakin banyak substitusi shell ditambahkan

    HUBUNGAN PROFIL LIPID, INDEKS MASSA TUBUH DAN ANKLE BRACHIAL INDEX PADA PEREMPUAN BERUSIA ≥ 50 TAHUN

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    Penyakit arteri perifer merupakan salah satu jenis penyakit pada pembuluh darah, yang dapat ditemukan pada usia lanjut, penderita obesitas, hipertensi dan diabetes. Salah satu cara yang dapat digunakan untuk menentukan penyakit arteri perifer adalah dengan mengukur ankle brachial index. Penelitian ini bertujuan untuk menganalisa hubungan antara profil lipid, indeks massa tubuh, dan tekanan darah dengan ankle brachial index. Sebanyak 78 perempuan berusia ≥50 tahun yang bertempat tinggal di Kecamatan Mampang dipilih sebagai subjek penelitian. Subjek dengan riwayat infak miokardium dan nilai ankle brachial index > 1,4 tidak diikutsertakan dalam penelitian. Hasil penelitian diperoleh sebesar 5,13% dengan nilai ankle brachial index ≤0,9; 65,38% dengan kadar kolesterol total ≥200mg/dL; 61,54% dengan kadar kolesterol low-density lipoprotein ≥130mg/dL; 34,62% dengan kadar kolesterol high-density lipoprotein <50mg/dL; 17,95% dengan kadar trigliserida ≥150mg/dL; 76,92% indeks massa tubuh ≥23,00; 52,56% dengan tekanan darah sistolik tinggi; dan 37,18% dengan tekanan darah sistolik tinggi. Analisa statistik dengan uji Fisher menunjukan bahwa tidak terdapat hubungan antara profil lipid, indeks massa tubuh, dan tekanan darah dengan ankle brachial index (p>0,05).  Temuan pada penelitian ini menunjukan bahwa profl lipid, indeks massa tubuh, dan tekan darah bukan merupakan faktor yang menentukan nilai ankle brachial index. Subjek dengan nilai ankle brachial index ≤0,9 tidak banyak, sehingga perlu dilakukan penelitian lebih lanjut dengan membandingkan berbagai faktor tersebut pada kelompok penderita penyakit arteri perifer dengan kelompok normal

    CSR Perceived by Employees and Organizational Citizenship Behaviors in mutual insurance companies: The mediating role of job involvement.

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    This study aims to explain the mechanism through which employees\u27 attitudes toward corporate social responsibility (CSR) in social enterprises influence organizational citizenship behaviors (OCBs), with job involvement considered as a mediating factor. Based on a sample of 532 employees from Tunisian mutual insurance companies, structural equation modeling confirms the direct positive links between perceived CSR and OCBs. Indirect effects through job involvement reveal that CSR fosters OCBs oriented toward the organization (civic virtue and team spirit), but not those directed toward individuals (mutual help). While existing literature supports the link between CSR and OCBs, few studies have examined the mediating processes involved. This study addresses this gap by demonstrating how CSR perceptions can enhance job involvement, which in turn promotes specific forms of organizational citizenship behaviors. Its findings offer practical implications for managers seeking to leverage CSR to enhance employee engagement, foster citizenship behaviors, and promote sustainable performance

    UI/UX Development for Tour Ticketing on Pari Island using User Centered Design

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    UI/UX Development of UCD-Based Tourism Tour Ticketing on Pari Island, which currently feels like the method of ordering tourism services on Pari Island is still too conventional, especially in the tourism sector. In fact, purchasing tourism tour tickets with methods that follow technological developments greatly influences efficiency in handling the surge of tourists coming to Pari Island, especially on weekends and other holidays. On Pari Island, purchasing tickets for tourism such as homestays, catering, snorkeling equipment rentals, bicycles, and motorbikes is still considered conventional where tourists who come to Pari Island must look for homestays and book tickets directly on the spot, in this study an application was created with a simple and attractive ticket purchasing concept (E-Ticket) which aims to improve the UCD-based tourism tour ticket ordering system on Pari Island

    Development of Osteoporosis Prediction System on Femur and Tibia Bones with Convolutional Neural Network

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    Osteoporosis and osteopenia are conditions that commonly affect bone health significantly, this is characterized by decreased bone density causing the risk of fractures especially in the femur and tibia. The prevalence rate of these diseases is calculated from 103,334,579 people between the ages of 15 and 105 years, with an overall prevalence of 18.3%. Fast and accurate detection is needed for the first line of defense for osteoporosis patients and potential patients. This study provides the development of a Convolutional Neural network (CNN) model trained to predict osteoporosis and osteopenia from x-ray radiographs of femur and tibia bones. The proposed model has satisfactory performance on all metrics namely average accuracy 90%, average recall 90%, average F1 score 90%. From these performance results, alternative detection methods using CNN can be considered by medical parties or parties who can utilize the first diagnosis of osteopenia to osteoporosis bone disease handling compared to conventional methods

    Analysis of CNN for Detecting Footsteps in Physical Traces App

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    Step detection is an essential feature in promoting healthy living through mobile applications. This study evaluates the accuracy of a Convolutional Neural Network (CNN) model implemented in the Physical Traces application for detecting steps based on accelerometer and gyroscope sensor data. Data were collected through experimental activities where 60 participants walked 20 steps and ran 10 meters, repeated three times each. The results show average accuracy exceeding 100%, indicating a tendency for overcounting. Evaluation was performed using Absolute Error, Relative Error, Symmetric Accuracy, and SMAPE. Statistical analysis (Mann-Whitney, Kruskal-Wallis), reliability test (Cronbach’s Alpha = 0.9178), and validity test (positive correlations) revealed significant differences by gender and age group. These findings indicate that CNN-based step detection works effectively, but improvements are necessary to address individual variability and real-world conditions

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