cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Said Fachry Assagaf
Contact Email
said.fachry.assagaf@unm.ac.id
Phone
-
Journal Mail Official
sainsmat@unm.ac.id
Editorial Address
Unit Publikasi Lantai 3 Gedung ICP FMIPA UNM Jln. Daeng Tata, Kampus UNM Parangtambung, Makassar, Indonesia 90224
Location
Kota makassar,
Sulawesi selatan
INDONESIA
SAINSMAT: Jurnal Ilmiah Ilmu Pengetahuan Alam
Published by Universitas Negeri Makassar
ISSN : 20866755     EISSN : 2579568     DOI : https://doi.org/10.35580/sainsmat112330232022
Core Subject : Science, Education,
Biochemistry, Genetics & Molecular Biology Chemistry Decision Sciences, Operations Research & Management Education Physics
The objective of this journal is to publish original, fully peer-reviewed articles on a variety of topics and research methods in both sciences, mathematics, its education, and applied science. The journal welcomes articles that address common issues in mathematics, sciences, education, applied science and cross-curricular dimensions more widely.
Arjuna Subject : Umum - Umum
Articles 269 Documents
 23   24   25   26   27 
Green Chemistry Integrated Teaching Module Design To Optimize High School Students Critical Thinking Skills (Study On The Main Topic Of Acid and based) Halisah, Nur; Jusniar, Jusniar; Auliah, Army
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 14, No 2 (2025): September
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat142717772025

Abstract

This development research aims to produce a valid and practical integrated green chemistry teaching module using the ADDIE model, which includes analysis, design, development, implementation, and evaluation. The instrument used to measure validity is the validation sheet. The instrument for practicality is the observation sheet of lesson implementation and the teacher and student perception questionnaires. The research was conducted at SMAN 8 Makassar in August 2024. The results of the module's validity obtained a very valid average score of 3.70 with a consistency between rates of 1.00. The practicality of the module based on lesson implementation was 99.21%. The positive perceptions of teachers and students were 93.18% and 93.83%, respectively, both in the very practical category. The conclusion drawn is that the developed integrated green chemistry teaching module meets the validity and practicality criteria for use in teaching.
Kinetics Photodegradation of Methylene Blue Dye Using ZnO-Montmorillonite Composite Putri, Suriati Eka; Pratiwi, Diana Eka; Ria, Tiara Anugrah
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 14, No 2 (2025): September
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat142761972025

Abstract

The purpose of this study was to determine the degradation kinetics of methylene blue dyes using ZnO-Montmorillonite (MMT) composites. This study is an experimental research covering several stages, namely the preparation and purification of MMT samples, the synthesis of ZnO-MMT composites by impregnation method, the characterization of ZnO-MMT composites, and the determination of optimal conditions for the degradation of methylene blue (MB) dyes using the UV-Vis instrument. The results of the  ZnO-MMT composite research were able to degrade MB dyes irradiated by UV light with an optimal time of 150 minutes with a photodegradation rate of 4.199 minutes-1.Keywords: Kinetics, Reaction Rate, Photodegradation, MB Dye, ZnO-MMT.
Forecasting The Value of Non-Oil and Gas Exports in Indonesia Using Triple Exponential Smoothing Sulastri, Sri; Ramadhani, Inas Wulan
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 14, No 2 (2025): September
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat142764142025

Abstract

Peramalan nilai ekspor nonmigas di Indonesia sangat penting, karena prediksi ini memberikan gambaran tentang potensi penerimaan devisa, pertimbangan penting bagi pemerintah dalam merumuskan kebijakan ekonomi. Studi ini menyajikan hasil peramalan yang optimal menggunakan metode Triple Exponential Smoothing. Data tersebut terdiri dari angka ekspor nonmigas di Indonesia dari Januari 2020 hingga Desember 2024, yang diperoleh dari Badan Pusat Statistik (BPS). Tujuannya adalah untuk menentukan nilai ekspor nonmigas di Indonesia untuk tahun 2025, yang akan menjadi dasar bagi pemerintah untuk merumuskan kebijakan untuk tahun mendatang. Dari pemodelan yang dilakukan, diperoleh model terbaik dengan nilai parameter optimal = 0,3, = 0,1, = 1, dan nilai MSE sebesar 3,770563, serta nilai RMSE sebesar 864,4194. Prakiraan ekspor nonmigas Indonesia tahun 2025 menunjukkan fluktuasi tahunan, dengan bulan Maret diperkirakan memiliki nilai ekspor tertinggi dan bulan Mei diproyeksikan lebih rendah dari tahun sebelumnya.
Integration of Ensemble Stacking in Machine Learning for Thermal Stability Prediction of Metal-Organic Frameworks (MOF) Pratama, Ananta Surya; Umam, Taufiqul; Irnanda, Muhammad Diva; Nugroho, Dandy Prasetyo; Azies, Harun Al
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 14, No 2 (2025): September
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat142759682025

Abstract

This study aims to develop a predictive model for the thermal stability of Zinc-based Metal-Organic Frameworks (Zn-MOFs), which are crucial in high-temperature applications. The approach used is stacking ensemble learning, which integrates several base models, including Ridge Regression, Lasso Regression, K-Nearest Neighbors (KNN) Regression, Support Vector Regression (SVR), Linear Regression, RANSAC (Random Sample Consensus), Huber Regression, and Gaussian Process Regression, with the meta-model TheilSenRegressor. Experimental results indicate that the stacking model delivers high-accuracy predictions, evidenced by a Root Mean Squared Error (RMSE) of 0.0025 and a coefficient of determination (R²) of 0.9993 on the training data, and an RMSE of 0.0023 and an R² of 0.9994 on the test data, demonstrating the model's excellent generalization capability. A comparison with the Robust Regression model shows that the stacking model is more stable and consistent in providing accurate predictions for both the training and test sets. These findings suggest that the machine learning-based stacking ensemble learning approach can serve as a more efficient and faster alternative to conventional experimental methods in predicting the thermal stability of Zn-MOFs.
Analysis Of Student Perceptions Of The Use Of Artificial Intelligence In Science Learning In Elementary School Wirawan, Zose; Arwien, Rizki Trisnawaty; Muriati, St.
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 13, No 2 (2024): September
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat132657652024

Abstract

The aim of this research is to analyze students' perceptions regarding the application of artificial intelligence in science learning materials. The research method used in this study is a descriptive quantitative approach to evaluate the perceptions of elementary school students towards the implementation of artificial intelligence (AI) in science education in Makassar in June 2024. Data analysis techniques involve descriptive statistics. The subjects of the study consisted of 26 students, with instrument being a 24-item questionnaire using a Likert scale from 1 to 5. This questionnaire was designed to assess students' learning experiences, interests, motivation, benefits, impacts, as well as challenges and expectations. The results indicate that the use of AI in science learning has a significant positive impact, enhancing students' learning experiences, interests, and motivation. The majority of students reported that AI aided them in understanding the material, exam preparation, and learning outcomes. However, there were some challenges such as technical issues and adaptation that need to be addressed. Students have high expectations for the sustainability of this technology. To optimize the benefits of AI and overcome challenges, technical support, training, and adequate infrastructure are needed so that all students can equitably benefit from this technology.
Optimal Control of a Mathematical Model for Monkeypox Transmission in Indonesia Using the Pontryagin Maximum Principle Musfira, Musfira; Side, Syafruddin; Abdy, Muhammad; Ridho, Andi Muhammad; Supriadi, Supriadi
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 14, No 2 (2025): September
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat142763342025

Abstract

Abstract: The re-emergence of Monkeypox poses significant public health challenges in Indonesia. This disease continues to spread due to its zoonotic nature and the high frequency of human-animal interactions. This study aims to model the transmission dynamics of Monkeypox using the SIQR (Susceptible, Infectious, Quarantined, Recovered) framework and apply optimal control strategies through the Pantryagin Maximum Principle (PMP). Data from the Indonesian Ministry of Health were utilised for model parameterisation, with numerical simulations conducted using the fourth-order Runge-Kutta method. Control strategies included quarantine, tecovirimat, and public education. The simulation results revealed that implementing optimal control reduced the infected population by up to 75% within the first 10 months compared to scenarios without control. The basic reproduction number () was successfully reduced from 2.5 to below 1, indicating that the outbreak was controlled. Additionally, the recovery rate increased by 30%, with the susceptible population achieving a disease-free equilibrium by the eighth month. These findings highlight that mathematically-driven interventions can provide effective solutions for managing infectious diseases. It is recommended that these strategies be integrated into public health policies to optimise resource allocation. Further research is necessary to evaluate the scalability of this approach for other zoonotic diseases.
SITR Model of Tuberculosis Spread in Makassar City Fadhilah, Helisyah Nur; Annur, Ahmad Ihda Falah; Oktavia, Eka Putri
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 13, No 2 (2024): September
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat132641622024

Abstract

ABSTRACTTuberculosis or TBC is a type of chronic infectious disease caused by bacteria called Mycobacterium tuberculosis. The disease poses a serious threat to health regardless of age or gender. Individuals infected with this disease will experience symptoms such as coughing with sputum or blood, chest pain, and high fever. Transmission occurs through aerosols and droplets, allowing the bacteria to spread through the air and requires a minimum of 6 months of treatment for recovery. Therefore, The SITR (Suspectible-Infective-Treatment-Recovered) mathematical model with the Euler method is appropriately used in this article to describe the condition where infected individuals need treatment for recovery. The data analyzed comes from tuberculosis case reports collected by the South Sulawesi Regional Health Agency in 2015. This research has important relevance in understanding the dynamics of TB spread and provides a basis for the development of disease spread strategies. By using mathematical models, key factors affecting the spread of tuberculosis can be identified. Keywords: Mathematical Model, SITR Model, Dynamics of Spread, Tuberculosis.
Time Series Intervention Analysis With Gradual Impact Function A Case Study Of Railway Passenger Volume In Java Island Zulhijrah, Zulhijrah; Isnaini, Mardatunnisa; Angraini, Yenni; Notodiputro, Khairil Anwar; Mualifah, Laily Nissa Atul
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 14, No 2 (2025): September
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat142774742025

Abstract

Java Island has been significantly impacted by the COVID-19 pandemic, which started in March 2020. This study aims to analyze the impact of the pandemic on the volume of railway passengers’ volume with a time series approach using an interventional ARIMA model. The data used is the number of monthly passengers from 2015 to 2024. Initial modeling on data before the pandemic produced the best model, namely ARIMA (0,2,1). To measure the impact of the pandemic, a gradual step intervention function is used which represents the gradual effect of the event. The estimation results show that the ARIMA (0,2,1) model with a gradual step intervention function is able to provide more accurate forecasting results, with a MAPE value of 18.39%. This model effectively captures changes in mobility patterns due to the pandemic, especially in the post-intervention recovery phase. The findings make an important contribution to transportation policy evaluation and future strategic planningKeywords: Time Series, ARIMA  Intervention, Gradual Function, Railway 
The Effect Of Using Stem-PJBL Toward Science Literacy Ability And Collaboration Skill Of Prospective Science Teachers: Study On Subject Of Matter And Energy Yunus, Sitti Rahma; Arif, Rifda Nur Hikmahwati; Yanto, Nurfitra; Sarina, Sarina; Pertiwi, Andini; Alim, Muhammad Harisah
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 13, No 2 (2024): September
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat132667682024

Abstract

This research aims to analyze the level of science literacy ability and collaboration skill of prospective science teachers in the course of Matter and Energy and analyze the influence of STEM-PJBL learning on literacy abilities science and collaboration skills. This research is a pre-experiment with the research design used was One-Shot Case Study. In this design, students are given treatment, then observations are made about collaboration skill and they are given a scientific literacy ability test. The population in this study were all students of the faculty of Mathematics and Natural Science, Universitas Negeri Makassar at the Science Education Study Program in the even semester of the 2022/2023 academic year, while the sample in this study was students in the regular class of the 3rd semester of the 2022/2023 academic year which consisted of 2 classes that programmed the course of Matter and Energy. The regular class 01 as an experimental class and regular class 02 as a replication class. The research instruments used to measure collaboration skills are non-test instruments in the form of collaboration skills observation sheets and scientific literacy test instruments in the form of multiple choices. The results of descriptive statistical analysis show that the level of scientific literacy skills is in high category and the level of collaboration skills of prospective science teachers is in the very high category. The results of the inferential analysis show that the application of STEM-PJBL influences the scientific literacy abilities and collaboration skills of prospective science teachers in substance and energy courses. These results show that STEM-PJBL learning can be applied to other subjects because it can improve scientific literacy skills and collaboration skills of prospective teachers. It can be implemented to examine the effectiveness of this model in similar variables on the other subjects.
Analisis Keterampilan Proses Sains pada Pembelajaran IPA Setelah Pandemi Covid-19: Literatur Review Arsyad, Arie Arma; Muhiddin, St. Mutia Alfiyanti; Yanto, Nurfitra; Syakur, Akhmad
Sainsmat : Jurnal Ilmiah Ilmu Pengetahuan Alam Vol 13, No 2 (2024): September
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/sainsmat132669792024

Abstract

Keterampilan proses sains merupakan salah satu dari capaian pembelajaran pada kurikulum merdeka pada pembelajaran IPA. Penelitian ini menggunakan literatur review pada sejumlah artikel yang telah diterbitkan pada jurnal pendidikan IPA di Indonesia setelah pandemi covid-19 tahun 2021-2024 dengan keterampilan proses sains pada pembelajaran IPA di SMP sebagai fokus penelitian. Artikel yang dikumpulkan melalui database google scholar dan dipublikasikan melalui jurnal terakreditasi Kemendikbudristek. Terdapat 17 data jurnal yang menjadi sampel. Teknik analisis data yang digunakan adalah teknik PRISMA. Berdasarkan hasil analisis penelitian diperoleh bahwa terdapat beberapa model pembelajaran yang dapat melatihkan keterampilan proses sains dengan baik dan membantu peserta didik dapat menyelesaikan masalah sehari-hari.Kata kunci: keterampilan proses sains, literatur review, teknik PRISMA, pembelajaran IPA.

Page 26 of 27 | Total Record : 269

 23   24   25   26   27 

Filter by Year

2012 2025


Reset
Filter By Issues
All Issue Vol 14, No 2 (2025): September Vol 14, No 1 (2025): Maret Vol 13, No 2 (2024): September Vol 13, No 1 (2024): Maret Vol 12, No 2 (2023): September Vol 12, No 1 (2023): Maret Vol 11, No 2 (2022): September Vol 11, No 1 (2022): Maret Vol 10, No 2 (2021): September Vol 10, No 1 (2021): Maret Vol 9, No 2 (2020): September Vol 9, No 1 (2020): Maret Vol 8, No 2 (2019): September Vol 8, No 1 (2019): Maret Vol 7, No 2 (2018): September Vol 7, No 1 (2018): Maret Vol 6, No 2 (2017): September Vol 6, No 1 (2017): Maret Vol 5, No 2 (2016): September Vol 5, No 1 (2016): Maret Vol 4, No 2 (2015): September Vol 4, No 1 (2015): Maret Vol 3, No 2 (2014): September Vol 3, No 1 (2014): Maret Vol 2, No 2 (2013): September Vol 2, No 1 (2013): Maret Vol 1, No 2 (2012): September Vol 1, No 1 (2012): Maret More Issue