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All Journal Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Jurnal Cendekia : Jurnal Pendidikan Matematika MAJAMATH: Jurnal Matematika dan Pendidikan Matematika Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa Dan Inovasi Abdimas Singkerru International Journal of Applied Sciences and Smart Technologies
Sofia Debi Puspa
Universitas Trisakti
Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Public Health Social Sciences

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Study Characteristic Thermal Electric Generator (TEG) Type SP1848 27145 SA Sofia Debi Puspa; I Putu Budi Dharma; Sentot Novianto; Supriyadi; M. Alfian Gibran
Jurnal Asiimetrik: Jurnal Ilmiah Rekayasa Dan Inovasi Volume 6 Nomor 1 Tahun 2024
Publisher : Fakultas Teknik Universitas Pancasila

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35814/asiimetrik.v6i1.5561

Abstract

The TEG component, which operates on the Seebeck principle like a thermocouple, is widely used in the market, with TEG SP1848 27145 SA being one of the most common types. However, experiments must be conducted to determine its Seebeck coefficient, voltage, and power output when used with different heat and cold sources. This research aims to observe how the Seebeck coefficient, voltage, and power output of TEG SP1848 27145 SA change with variations in system temperature. To experiment, TEG SP1848 27145 SA is tested with a heater, and water flow rates are varied for cooling. Furthermore, the correlation between output voltage and ΔT has been determined through statistical analysis. The experiment results showed that the voltage output ranged from 0.54–1.03 V at a heater temperature of 86°C and an ΔT system value of 70.5-75°C. The Seebeck value was between 1,551.7-2,998.5 µV, and the power output was 43.5-67.7 mW. Additionally, the statistical analysis found a significant correlation between the temperature variable and output voltage variable, with an adjusted r square value of 89.2% for zero water flow rate and increasing to 95.8% for maximum water flow rate.
Convergence and Empirical Performance of Tanh-Based Adaptive Particle Swarm Optimization Joko Riyono; Aina Latifa Riyana Putri; Sofia Debi Puspa; Supriyadi Supriyadi; Christina Eni Pujiastuti; Fayza Nayla Riyana Putri
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 10 No 3 (2026): June 2026
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v10i3.7247

Abstract

Particle Swarm Optimization (PSO) is a widely used population-based optimization method but faces challenges in premature convergence, leading to suboptimal solutions. To address this issue, this study proposes a Tanh-Based Acceleration Coefficient PSO (TB-PSO), where the acceleration coefficients are modified using the hyperbolic tangent (tanh) function. The smooth and continuous behavior of tanh enables gradual coefficient updates, limits excessive particle velocities, and maintains swarm diversity, thereby improving convergence stability and balancing exploration and exploitation. The convergence theorem analysis confirms that TB-PSO meets stability criteria before being evaluated on unimodal and multimodal benchmark functions in 10 and 30 dimensions. Its performance is compared against several PSO variants, including TVAC-PSO, SCAC-PSO, NDAC-PSO, and SAC-PSO. In the 10-dimensional experiments, TB-PSO achieves the best overall final ranking based on the average and standard deviation of best solution, ranking first for functions f₃ and f₅, second for f₂ with only a marginal difference from the best-performing method, and remaining competitive for f₁ and f₄. These results indicate superior solution quality and stable convergence. For the 30-dimensional benchmark functions, TB-PSO ranks first for f₂, second for f₅, and third for f₁, f₃, and f₄ based on the same evaluation criteria. Although its ranking decreases compared to the 10-dimensional case, TB-PSO remains competitive, reflecting the increased complexity of high-dimensional optimization problems. Overall, the results demonstrate that the tanh-based acceleration coefficient modification effectively enhances PSO performance, particularly in lower-dimensional search spaces, while maintaining robustness in higher-dimensional scenarios.
Development of an Arduino-Based Water Rocket Launcher in Physics Experiments Larasati Putri; Fakhrizal Arsi; Kiar Vansa Febrianti; Sentot Novianto; Ika Wahyu Utami; Muhammad Najih; Sofia Debi Puspa; Muhammad Gilang Ramadhan; Harry Munandar
International Journal of Applied Sciences and Smart Technologies Vol. 8 No. 1 (2026): Volume 08, Issue 1, June 2026
Publisher : Faculty of Science and Technology, Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24071/5qcv4a36

Abstract

The effective science education requires practical methods that allow students to explore complex physics concepts. One promising approach is the use of physics experiment as an interactive media. This research focuses on the development of water rocket launcher using an Arduino as an innovative physics experiment. Arduino in water rocket launcher is used for making the precise control and relevant measurement of variables, such as angle of projection, speed of launch, maximum altitude of launch, and air pressure. The research process followed the ADDIE instructional design model and involved hardware, software prototyping, work testing, and user instruction. The launcher’s performance was tested with 33 engineering students and assessed by 5 experts. Expert evaluations rated the relevance, design, and usability of the kit highly (3.4–4.0 on a 4-point Likert scale). User responses from 33 students indicated strong agreement on ease of use and engagement (mean scores 3.79–3.91), with a high reliability (Cronbach’s alpha = .964). Experimental launches, using three and four finned rockets, showed maximum height percentage differences between theoretical and observed values ranging from 0.0%–52.6% (three fins) and 1.2%–51.8% (four fins); range errors were 3.4%–36.8% (three fins) and 2.1%–42.7% (four fins). The findings confirm that the Arduino-based water rocket launcher provides effective, interactive learning, though further refinement in data accuracy and instructional materials is recommended to maximize its classroom impact and is needed for improved accuracy.
Simulasi Clustering Provinsi di Indonesia dalam Penyebaran Covid-19 Berdasarkan Indikator Kesehatan Masyarakat Menggunakan Algoritma Gaussian Mixture Model Joko Riyono; Sofia Debi Puspa; Christina Eni Pujiastuti
MAJAMATH: Jurnal Matematika dan Pendidikan Matematika Vol. 5 No. 1 (2022): Vol. 5 No. 1 Maret 2022
Publisher : Prodi Pendidikan matematika Universitas Islam Majapahit (UNIM), Mojokerto, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36815/majamath.v5i1.1699

Abstract

Gaussian Mixture Model adalah suatu metode yang mengkontruksikan Clustering suatu dataset menjadi beberapa kelompok data yang memiliki distribusi Gaussian atau Normal. Pada penelitian ini akan dibahas gagasan untuk menentukan Clustering penyebaran Covid-19 pada 34 provinsi di Indonesia menggunakan Gaussian Mixture Model berdasarkan nilai indikator kesehatan masyarakat. Mengingat masih berlangsungnya pandemi Covid-19 di beberapa provinsi di Indonesia hingga saat ini, penelitian ini dipilih dengan tujuan sebagai masukan kepada pemerintah selaku pembuat kebijakan untuk bahan acuan penanganan pandemi Covid-19 sehingga program-program pencegahan penyebaran Covid-19 di tiap provinsi dapat tertangani secara lebih optimal. Hasil analisis data diperoleh 6 cluster optimal yaitu cluster yang berpotensi sangat tinggi berisi 1 provinsi, tinggi 4 provinsi, sedang 13 provinsi, cukup rendah 4 provinsi, rendah 2 provinsi, sangat rendah 10 provinsi dalam penyebaran Covid-19.
Co-Authors Achdianto Adit Waisal Aina Latifa Riyana Putri Christina Eni Pujiastuti Fakhrizal Arsi Fani Puspitasari Fayza Nayla Riyana Putri Harry Munandar Hary Munandar I Putu Budi Dharma Ika Wahyu Utami Jesika Erventy Osman Joko Riyono Joko Riyono Kiar Vansa Febrianti Larasati Putri Larasati Rizky Putri M. Alfian Gibran Muhammad Gilang Ramadhan Muhammad Hasan Muhammad Najih Sentot Novianto Supriyadi Supriyadi Supriyadi Syaifudin Triyono