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INDONESIA
Jurnal Sains dan Teknologi
Published by Universitas Pendidikan Ganesha
ISSN : 23033142     EISSN : 25488570     DOI : -
Core Subject : Science, Education,
Computer Science & IT Education
Jurnal Sains dan Teknologi(JST) is a journal aims to be a peer-reviewed platform and an authoritative source of information. We publish original research papers, review articles and case studies focused on Mathematic, Biology, Physic, Chemistry, Informatic, Electronic and Machine as well as related topics. All papers are peer-reviewed by at least two referees. JST is managed to be issued twice in every volume.
Arjuna Subject : -
Articles 648 Documents
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Fuse Memproteksi Inverter dan Baterai BESS dalam Sistem Distribusi Listrik Jondra, I Wayan; Suryawan, I Ketut; I Putu Agus Satria Wibawa
JST (Jurnal Sains dan Teknologi) Vol. 14 No. 2 (2025): July
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jst-undiksha.v14i2.97954

Abstract

Keandalan sistem distribusi energi listrik sangat ditentukan oleh keberfungsian sistem proteksi, terutama dalam konteks penyaluran energi ke Battery Energy Storage System (BESS). Permasalahan terjadi ketika pemilihan kapasitas proteksi tidak sesuai dengan karakteristik teknis sistem, yang menyebabkan inverter dan baterai bekerja tidak optimal, sehingga menurunkan keandalan distribusi energi secara keseluruhan. Penelitian ini bertujuan untuk menganalisis secara mendalam kesesuaian spesifikasi fuse sebagai perangkat proteksi terhadap performa sistem distribusi energi listrik. Penelitian ini menggunakan pendekatan kuantitatif dengan desain studi kasus terapan. Subjek penelitian terdiri atas sistem proteksi fuse yang terpasang dalam jaringan. Data dikumpulkan melalui observasi teknis langsung, dokumentasi spesifikasi teknis fuse, inverter, dan baterai, serta pengukuran arus dan tegangan sistem distribusi. Instrumen penelitian mengacu pada indikator validitas teknis proteksi sistem tenaga listrik. Analisis data dilakukan secara matematis melalui perhitungan arus beban, arus hubung singkat, serta analisis efisiensi sistem distribusi terhadap karakteristik fuse yang digunakan. Hasil penelitian menunjukkan bahwa fuse tipe SQB 3 1000A mampu memberikan perlindungan terhadap inverter dan baterai dari arus lebih maupun arus hubung singkat. Kesimpulan dari penelitian ini menegaskan bahwa ketepatan pemilihan spesifikasi fuse sangat mempengaruhi keandalan dan efisiensi sistem distribusi energi pada sistem PLTS  hybrid berbasis BESS. Penelitian ini memberikan implikasi penting bagi perancang sistem tenaga berbasis energi terbarukan.
Skrining Fitokimia dan Kapasitas Antioksidan Tumbuhan Obat Papua Dillenia alata Pasaribu, Yenni Pintauli; Rifaldi; Kristyasari, Marantika Lia
JST (Jurnal Sains dan Teknologi) Vol. 14 No. 2 (2025): July
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jst-undiksha.v14i2.99185

Abstract

Pemanfaatan tumbuhan sebagai obat tradisional telah dilakukan oleh masyarakat untuk menyembuhkan berbagai penyakit. Dillenia alata (Dilleniaceae) digunakan oleh masyarakat tradisional Papua sebagai obat. Namun, informasi ilmiah tentang kandungan senyawa aktif dan bioaktivitas tumbuhan Dillenia alata masih sangat terbatas sehingga belum dapat dimanfaatkan secara luas.  Penelitian ini bertujuan mengetahui kandungan senyawa, kandungan fenolik dan flavonoid, serta aktivitas antioksidan kulit batang tumbuhan Dillenia alata. Subjek yang digunakan dalam penelitian ini adalah kulit batang Dillenia alata. Pengumpulan data menggunakan metode eksperimen laboratorium yang meliputi ekstraksi, uji kualitatif fitokimia, uji kandungan fenolik total (TPC), uji kandungan flavonoid total (TFC), dan uji antioksidan (DPPH, ABTS, FRAP). Data dianalisis menggunakan kurva standar untuk TPC, TFC, dan FRAP serta regresi linear untuk DPPH dan ABTS. Hasil temuan adalah ekstrak Dillenia alata mengandung senyawa golongan terpenoid, steroid, fenolik, flavonoid, alkaloid, dan saponin. Ekstrak metanol mempunyai nilai TPC dan TFC tertinggi yang menandakan ekstrak metanol memiliki kandungan/kadar senyawa fenolik dan flavonoid tertinggi. Ekstrak metanol juga menunjukkan kapasitas antioksidan tertinggi secara uji DPPH, ABTS, dan FRAP. Kesimpulannya adalah ekstrak polar kulit batang Dillenia alata mengandung senyawa-senyawa aktif yang mempunyai aktivitas antioksidan. Implikasinya adalah Dillenia alata berpotensi untuk dikembangkan sebagai agen antioksidan yang mendukung berbagai pengobatan alternatif. Dillenia alata juga berpotensi untuk diteliti lebih lanjut bioaktivitasnya sebagai antikanker dan antidiabetes yang berkorelasi positif dengan sifat antioksidan yang dimilikinya. Hasil riset ini juga membuka potensi riset lintas disiplin dalam mengungkap potensi etnobotani dan etnomedisin berbagai jenis tumbuhan obat Papua.
Integrasi Bagging dan Stacking Untuk Memperbaiki Kinerja Algoritma Klasifikasi C4.5 dan K-Nearest Neighbor(KNN) Syahrir, Moch.; Switrayana, I Nyoman; Darmawan, I Made Angga Wahyu
JST (Jurnal Sains dan Teknologi) Vol. 14 No. 2 (2025): July
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jst-undiksha.v14i2.100794

Abstract

Permasalahan utama dalam klasifikasi data berdimensi tinggi adalah lambatnya proses pemindaian dan inkonsistensi akurasi model, yang berdampak negatif terhadap kualitas informasi dan pengambilan keputusan berbasis data. Dalam konteks prediksi risiko keuangan, seperti kredit macet, keterbatasan ini dapat menghambat efektivitas sistem pendukung keputusan. Penelitian ini bertujuan untuk mengevaluasi dan mengembangkan kinerja algoritma klasifikasi dasar, yaitu C4.5 dan K-Nearest Neighbor (KNN), melalui integrasi teknik ensemble learning bagging dan stacking. Penelitian ini merupakan penelitian kuantitatif dengan desain eksperimen komparatif. Subjek penelitian adalah empat dataset publik yang merepresentasikan data keuangan, yaitu Bank Marketing (41188 record), Credit Card (1319 record), Credit Risk Assessment (32581 record), dan Credit Card Defaulter (10000 record). Data dikumpulkan dari repositori Kaggle, kemudian diolah menggunakan algoritma C4.5 dan KNN yang diintegrasikan dengan teknik ensemble. Instrumen penelitian berupa implementasi model klasifikasi menggunakan perangkat lunak Rapid Miner dan Python, dengan pengujian validitas melalui k-fold cross validation dan pengukuran reliabilitas menggunakan metrik akurasi. Teknik analisis data meliputi pengujian performa model berdasarkan nilai akurasi, presisi, recall, dan F1-score. Hasil penelitian menunjukkan bahwa bagging dengan algoritma C4.5 memberikan hasil terbaik pada tiga dari empat dataset, masing-masing dengan akurasi 91,21%, 97,73%, dan 92,11%. Sedangkan pada dataset keempat, kombinasi bagging dan KNN menghasilkan akurasi tertinggi sebesar 97,06%. Simpulan dari penelitian ini adalah bahwa teknik bagging secara signifikan mampu meningkatkan akurasi dan konsistensi model klasifikasi dasar. Implikasi dari hasil ini menunjukkan bahwa integrasi metode ensemble dapat menjadi solusi praktis dan teoretis untuk meningkatkan kualitas klasifikasi dalam domain keuangan, khususnya dalam memprediksi risiko kredit.
Perbandingan Kalman Filter dan Exponential Moving Average pada Sensor Ultrasonik dalam Sistem Smart Waste ATM Wijaya, Andy; Suhardi; Sari, Kartika
JST (Jurnal Sains dan Teknologi) Vol. 14 No. 2 (2025): July
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jst-undiksha.v14i2.101049

Abstract

Waste level monitoring is still often done manually, making it inefficient in preventing accumulation. Ultrasonic sensors are widely used because they are practical and affordable, but their accuracy is often affected by environmental and hardware conditions. This study aims to compare the Kalman Filter and Exponential Moving Average methods to improve the accuracy of ultrasonic sensor readings in an automated waste monitoring system. The type of research used is an experiment with a microcontroller-based system that is tested on various waste height variations. The Kalman Filter combines previous estimates with new data, while the Exponential Moving Average gives more weight to the most recent value. The performance of both methods is assessed based on measurement consistency and error rate.The data was then analyzed quantitatively using Root Mean Square Error (RMSE).The results show that the Kalman Filter produces lower errors and more stable data compared to the Exponential Moving Average or raw data. In conclusion, the Kalman Filter is more effective in improving the reliability and accuracy of the automated waste monitoring system. The implications of this research suggest that selecting the right sensor type can significantly improve system performance in detecting waste capacity in real time.
Nearpod-Based Animation Video Media on Increasing Learning Motivation and Understanding of Ecosystem Concepts in Elementary Schools Yulia Anggraeni; Abdul Muis; Rina Sugiarti Dwi Gita
JST (Jurnal Sains dan Teknologi) Vol. 14 No. 2 (2025): July
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jst-undiksha.v14i2.101626

Abstract

Learning motivation and conceptual understanding among elementary school students are still considered low. Difficulties in concentrating and understanding abstract material are factors that hinder the achievement of learning objectives. This study aims to analyze the effectiveness of using Nearpod-based animated video media in improving learning motivation and conceptual understanding of ecosystems among elementary school students. This research employed a quantitative approach with a quasi-experimental design using the one-group pretest-posttest method. The research subjects consisted of 20 students, who also served as trial participants. Data were collected through a learning motivation questionnaire and a conceptual understanding test that had been validated and tested for reliability. Data analysis was conducted using the non-parametric Wilcoxon Signed-Rank test because the data were not normally distributed. The results of the study showed that the use of Nearpod-based animated videos was effective in enhancing learning motivation while strengthening students’ conceptual understanding of ecosystems. Thus, this media can be concluded as an innovative and meaningful learning tool to address low learning motivation and difficulties in understanding abstract concepts among elementary school students. The implications of this study emphasize the importance of utilizing interactive learning technologies to create engaging, concrete, and supportive learning experiences in achieving educational goals.
Animation Media Based on Scratch 3.0 Software to Improve Student Understanding of Pronunciation Material at Junior High School Rofik; Eges Triwahyuni; Hariyanto
JST (Jurnal Sains dan Teknologi) Vol. 14 No. 2 (2025): July
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jst-undiksha.v14i2.101716

Abstract

The low ability of students in understanding pronunciation indicates that English learning still faces serious challenges. This occurs because innovative learning media have not been applied optimally, resulting in conventional and less interactive teaching. This study aims to develop and test the effectiveness of Scratch 3.0 as a learning medium in improving students’ pronunciation comprehension by analyzing, evaluating, and validating the media comprehensively. The type of research used is development research with the ADDIE model. The research subjects consist of two trial groups: an experimental class with 30 students and a comparison group with 32 students. Research data were collected through media expert validation, material expert validation, student response questionnaires, as well as learning achievement tests in the form of pretests and posttests. The research instruments included validation sheets, questionnaires, and test items to ensure the quality and effectiveness of the media. Data analysis was conducted using descriptive quantitative methods through validity tests, feasibility assessments, and calculations of students’ learning improvement. The results of the study show that Scratch 3.0 is proven to be valid, feasible, and effective in significantly improving students’ pronunciation comprehension. Thus, it can be concluded that the development of this media successfully addresses the problem of students’ low understanding of pronunciation. The implication of this research is that Scratch 3.0 can be used as an alternative innovative learning medium that encourages students to be more active, independent, and motivated in learning English.
Innovation in Antenna Testing: Development of an Automatic Measurement System for Gain and Radiation Pattern of a 4×1 Microstrip Array Antenna Junfithrana, Anggy Pradiftha
JST (Jurnal Sains dan Teknologi) Vol. 14 No. 2 (2025): July
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jst-undiksha.v14i2.102294

Abstract

The need for a more automated, precise, and integrated antenna measurement system has become urgent. The main objective of this research is to develop and test an automatic antenna measurement system based on LabVIEW that can improve the accuracy and efficiency of measuring the gain and radiation pattern of a 4x1 microstrip antenna. This research is a study of the development and validation of an experimental system using a 4×1 microstrip antenna array as the research subject, with an automatic measurement system based on an Arduino microcontroller (AT-Mega328) and stepper motor, as well as LabVIEW software for instrument control, data acquisition, real-time transmission, and user interface. Data collection was performed automatically via a roll-over-azimuth rotator. In data analysis, the results of the automatic system were quantitatively compared with CST simulation results and a semi-automatic system using 2D correlation coefficients and gain differences. At the same time, the benefits of improved time efficiency were also measured. The findings of this research indicate that the developed automatic measurement system provides a practical, efficient, and cost-effective solution for educational laboratories and industrial antenna testing, with potential for further development to support higher frequency ranges and three-dimensional measurements. The findings of this study have implications for improving the efficiency, accuracy, and flexibility of microstrip antenna testing and for offering practical and economical solutions for laboratory and industrial needs.
Using Gemini AI on the Interest and Learning Outcomes of Computer and Network Engineering Students in Vocational High Schools Tofan Dwi Tjahyono; Kustiyowati; Eges Triwahyuni
JST (Jurnal Sains dan Teknologi) Vol. 14 No. 2 (2025): July
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/jst-undiksha.v14i2.102807

Abstract

In the digital age and the 4.0 industrial revolution, the use of artificial intelligence (AI) technology in education has become increasingly urgent, particularly in technical vocational learning such as Network Security. This study aims to analyze the effect of using Gemini AI on students' interest and learning outcomes in Network Security at vocational high schools. This study employs a quantitative approach with a quasi-experimental design in the form of a non-randomized control group pre-test post-test design. The sample consists of two Grade XI TKJ classes at SMKN 1 Banyuanyar selected through purposive sampling. Data collection techniques include a questionnaire to measure learning interest and pre-test and post-test assessments to evaluate learning outcomes. Data were analyzed using the independent samples t-test, and effectiveness was assessed using Cohen’s d. The results showed a significant increase in both learning interest (d = 1.821) and learning outcomes (d = 3.560) in the experimental class after implementing Gemini AI, with a significance level of p < 0.001. These findings confirm that AI-based learning can be an effective solution in improving the quality of vocational education in the field of technology. This study contributes practically and theoretically to the development of adaptive learning methods and is recommended to be expanded to other contexts and subjects.

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