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INDONESIA
Indonesian Journal of Mathematics and Natural Sciences
Published by Universitas Negeri Semarang
ISSN : -     EISSN : 27747832     DOI : https://doi.org/10.15294/jm
Core Subject : Education,
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Final decision of articles acceptance will be made by Editors according to reviewers comments. Publication of accepted articles including the sequence of published articles will be made by Editor in Chief by considering sequence of accepted date and geographical distribution of authors as well as thematic issue.
Arjuna Subject : Ilmu Sosial - Ilmu Sosial (Lain-Lain)
Articles 15 Documents
 1   2 
Studi Komputasi Modifikasi 3-Pyropheophorbide α Menggunakan atom Pusat Mg dan Pemanfaatannya sebagai Sensitizer pada Dye Sensitized Solar Cell (DSSC) Mawadha Sasya, Nadasyifa; Sudarlin, Sudarlin
Indonesian Journal of Mathematics and Natural Sciences Vol. 47 No. 2 (2024): Volume 47 Nomor 2 Tahun 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/n1qmvc42

Abstract

Sifat fotoelektrik 3-pyropheophorbide α yang ditambahkan atom pusat Mg sebagai sensitizer pada DSSC telah diteliti menggunakan metode komputasi. Hasil modifikasi dibandingkan dengan klorofil dan 3PPhe-α tanpa atom Mg. Semua molekul dioptimasi pada keadaan dasar menggunakan metode DFT/B3LYP dan pada keadaan tereksitasi menggunakan metode TD-DFT/B3LYP dengan basis set 6-311G** untuk semua atom kecuali atom Mg menggunakan basis set LANL2DZ. Parameter yang digunakan adalah energi HOMO-LUMO, serapan UV-Vis, konstanta kopling (|VRP|), spontanitas elektron (ΔGinject), lifetime elektron (τ), efisiensi sinar masuk (LHE)dan analisis FEDAM. Hasil penelitian menunjukkan nilai terbaik untuk serapan UV-Vis, energi HOMO, |VRP|, dan lifetime elektron (τ) adalah klorofil dengan nilai berturut-turut sebesar 559 nm, -5,122 eV, 0,511, dan 1,000 ns, sedangkan untuk parameter LHE yang terbaik adalah 3PPhe-á dengan nilai sebesar 0,873. Sementara itu, nilai terbaik untuk parameter energi LUMO dan ΔGinject adalah 3PPhe-α+Mg dengan nilai sebesar -2,360 eV dan -3,723. Analisis kualitatif FEDAM menunjukkan kemampuan 3PPhe-α+Mg lebih baik sebagai akseptor maupun donor elektron dibandingkan dengan dua molekul lainnya.
Perbandingan Metode Tree Based Classification untuk Masalah Klasifikasi Data Body Mass Index Alifah, Rifdah Nur; Najib, Mohamad Khoirun; Nurdiati, Sri; Sari, Annisa Permata; Herlambang, Karen; Noval; Ginting, Dini Tri Putri Br; Sya’adah, Syifa Noer
Indonesian Journal of Mathematics and Natural Sciences Vol. 47 No. 1 (2024): Volume 47 Nomor 1 Tahun 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/m2k97436

Abstract

Body mass index (BMI) atau indeks massa tubuh merupakan salah satu indikator yang dapat mengawasi dan menjelaskan status gizi seseorang. Penelitian ini bertujuan untuk mengklasifikasikan BMI berdasarkan gender, tinggi badan, dan berat badan dengan menggunakan metode Tree Based Classification yang terdiri atas model Decision Tree Classifier, Random Forest Classifier, Gradient Boosting Classifier, dan XGBoost menggunakan bahasa pemrograman python. Model Tree Based classification tersebut akan mengklasifikasikan BMI kedalam 6 kelas indeks. Hasil penelitian menunjukkan model klasifikasi XGBoost memiliki akurasi terbaik setelah dilakukan tuning hyperparameter dengan nilai akurasi data test 83.7%. Performa model terbaik sebelum tuning hyperparameter dihasilkan model Random Forest dengan nilai F1-score (macro) untuk data test sebesar 88%. Sementara itu, performa model terbaik setelah tuning hyperparameter dihasilkan model XGBoost dengan nilai F1-score (macro) untuk data test dan data train masing-masing sebesar 79% dan 85%. Berdasarkan model XGBoost, variabel prediktor yang paling berkontribusi terhadap BMI adalah berat badan dengan nilai permutation importance 68.1%.
Simulasi Waveguide SiO2 dan TiO2 untuk Mengurangi Loss daya dengan Python Utomo, Galih Ridho Utomo; Fianti, Fianti; Nurbaiti, Upik
Indonesian Journal of Mathematics and Natural Sciences Vol. 48 No. 1 (2025): Volume 48 Nomor 1 Tahun 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/c701rg52

Abstract

Simulasi adalah sebuah pemodelan secara sederhana yang dirancang untuk mengetahui dan memahami suatu permasalahan yang akan diselesaikan. Sebelum melakukan kegiatan riset, seorang peneliti terlebih dahulu membuat hipotesis eksperiment. Dalam membuat hipotesis eksperiment diperlukan pendekatan secara numerik, atau komputasi. Dua pendekatan ini bertujuan untuk memberi gambaran atau simulasi experiment yaitu dapat memodelkan suatu permasalahan. Salah satu experiment yang sedang banyak dikembangkan oleh peneliti yaitu experiment waveguide. Riset waveguide adalah salah satu riset yang banyak dikembang pada sensor yang memerlukan karakteristik material, dan indeks bias yang tepat guna menciptakan sensor yang mempunyai tingkat akurasi yang tinggi, sensitifitas yang sensitif, dan nilai loss yang kecil. Salah satu material yang sering digunakan pada riset waveguide adalah material SiO2 dan TiO2. Oleh karena itu pada riset ini dicari perbandingan loss daya pada material SiO2 dan TiO2, selain itu Parameter yang menyebabkan tinggi loss daya pada Waveguide dan cara mengatasi tinggi loss daya pada waveguide. Riset ini dilakukan dengan tahap yaitu tahap analisis permasalahan dan tahap pemprogaman komputer. Dengan tahapan yang dilakukan maka riset ini menghasilkan. Waveguide loss use material SiO2: 1.11% Waveguide loss use material TiO2: 2.90% New value of alpha: 0.05; Waveguide loss use material SiO2: 1.16% Waveguide loss use material TiO2: 4.35%; Waveguide loss use material SiO2: 2.22% Waveguide loss use material TiO2: 5.80% New value of alpha: 0.15; New value of alpha: 0.10; Waveguide loss use material SiO2: 2.78% Waveguide loss use material TiO2: 7.25% New value of alpha: 0.20; Waveguide loss use material SiO2: 3.33% Waveguide loss use material TiO2: 8.70% New value of alpha: 0.25; Waveguide loss use material SiO2: 3.89% Waveguide loss use material TiO2: 10.15% New value of alpha: 0.30. Pada data yang didapat kami melakukan variasi pada sudut alpha yaitu sebanyak six variasi dengan setiap variasi berselisih five dimulai dari 0.10 hingga 0.30. Hasil tersebut menunjukan bahwa Perbandingan loss material SiO2 dan TiO2 bernilai sama dan parameter yang mempengaruhinya yaitu sudut alpha datang nya gelombang cahaya, hal ini kita dapat atasi untuk mengurangi daya loss dengan cara mengecilkan sudut alpha dibandingkan sudut kritis nya sehingga gelombang cahaya yang terpantul-pantul pada waveguide tidak keluar pada jalur nya dan mengakibatkan Loss daya.
Penerapan Model Deep-CNN Untuk Meningkatan Akurasi Klasifikasi Bahasa Isyarat Alfabet Menggunakan Algoritma Convolutional Neural Network Al-Hafizh, Fadhl; Alamsyah, Alamsyah
Indonesian Journal of Mathematics and Natural Sciences Vol. 47 No. 1 (2024): Volume 47 Nomor 1 Tahun 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/4x9r3p15

Abstract

Technological developments in the era of artificial intelligence have led to the development of computer systems capable of identifying sign language. Sign language is the primary means of communication for deaf and hard of hearing people used by millions of people around the world. This research aims to improve accuracy in alphabetic sign language recognition by using the Deep-CNN model. The method in this research starts from the selection of sign language datasets based on previous research.  The dataset used in this study comes from Kaggle regarding American Sign Language which contains each training and test class representing a label (0-25) This dataset contains 27,455 training data and 7,172 test data. This research uses the Python programming language in performing data splitting, scaling, data augmentation, training, and evaluating. The architectural model built in this research is the Deep CNN architecture which is implemented to carry out the process of improving the accuracy of sign language recognition classification. The test results show an increase in the accuracy of alphabetic sign language classification compared to previous research. The increase in accuracy in the value of the Deep CNN model built managed to reach an accuracy rate of 99.72%. The model that has been built is the best model among previous research models.
Penerapan Algoritma Convolutional Neural Network Arsitektur ResNet50V2 Untuk Mengidentifikasi Penyakit Pneumonia Izzulhaq, Muhammad Agil; Alamsyah, Alamsyah
Indonesian Journal of Mathematics and Natural Sciences Vol. 47 No. 1 (2024): Volume 47 Nomor 1 Tahun 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/p532ny06

Abstract

Pneumonia is a disease that infects the respiratory tract, disrupting the normal function of the human body. Viruses and bacteria are known as common causes of pneumonia. Identification of Pneumonia can use Convolutional Neural Network (CNN). CNN is an effective artificial neural network architecture for image analysis, inspired by how the human brain processes visual information. CNNs are capable of understanding the hierarchical features in images, from lines and angles to complex shapes and objects. This research aims to use ResNet50V2, a popular CNN architecture, to classify X-ray images as either normal or indicative of pneumonia, with the goal of creating an accurate and efficient diagnostic tool. The research method involves using X-ray image datasets for training, validation, and testing, using the ResNet50V2 CNN architecture. The test results show that ResNet50V2 achieves a pneumonia classification accuracy of 93.26%. This study innovatively explores alternative CNN architectures for pneumonia classification, focusing on ResNet50V2.
Analisis Pengendalian Mutu dan Kadar Logam Timbal pada Gula Kristal Putih di Pasaran Menggunakan ICP-OES Febriana, Nina Kurnia; Wijayati , Nanik
Indonesian Journal of Mathematics and Natural Sciences Vol. 47 No. 1 (2024): Volume 47 Nomor 1 Tahun 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/83kk3662

Abstract

Quality testing and determining levels of lead metal contamination have been carried out in samples of white crystal sugar sold on the market using the ICP-OES method. This test was carried out to evaluate the quality of white crystal sugar on the market and to determine the effectiveness of the ICP-OES method for analyzing lead metal contamination in white crystal sugar samples. The results of testing the quality (quality) of white crystal sugar, namely 8 samples of white crystal sugar meet the provisions of ICUMSA SNI 3140.3: 2020, 15 samples (all samples) meet the provisions of the maximum SO2 content of SNI 3140.3: 2020, 13 samples meet the provisions for drying shrinkage (moisture content) SNI 3140.3: 2020 and 6 samples met the white crystal sugar polarization provisions of SNI 3140.3: 2020. Meanwhile for the 5 samples that were analyzed for lead metal contamination levels, all samples showed results that the lead metal content did not exceed the maximum limit of SNI 3140.3: 2020 and for the linearity test it showed the linear coefficient (R2) value is 0.9999; LoD results of 0.002155 ppm; LoQ results of 0.007183 ppm; The accuracy results are shown by the %Recovery value of 95.21% and the precision results are shown by the %RSD value of 1.95%.
Analisis Pengaruh Massa Sampel, Volume Pelarut, dan Waktu Sonikasi pada Ekstraksi Bawang Merah (Allium ascalonicum L.) terhadap Kandungan Quercetin Chalif, Charisma; Alauhdin , Mohammad
Indonesian Journal of Mathematics and Natural Sciences Vol. 47 No. 1 (2024): Volume 47 Nomor 1 Tahun 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/cmwcz185

Abstract

Shallots (Allium ascalonicum L.) are plants that grow in tropical areas and are commonly consumed by Indonesian people. This plant can be used as  medicine because it contains quercetin which has antioxidant activity. The aim of this research was to determine the effect of sample mass to solvent volume ratio as well as sonication time on the extract yield and quercetin content in shallot extraction. This research used an ultrasonic wave-assisted extraction method with ethanol as solvent. The extraction process was carried out at varying ratios of sample mass (g) to solvent volume (mL) of 1:5, 1:10, 1:15 and 1:20 and extraction times of 15, 25 and 35 minutes. The shallot extract obtained was determined its yield and the quercetin content. Quercetin compound level was determined by HPLC. The highest yield was obtained at a ratio of 1:20 with a sonication time of 25 minutes of 73.23% and the highest content of quercetin compound was obtained at a ratio of 1:5 with a sonication time of 35 minutes of 0.342 mg QE/g. The results of the ANOVA analysis showed that the sample mass ratio to solvent volume parameter had a significant effect on the extract yield, while the sonication time factor had no significant effect on the extract yield. Meanwhile, the ratio of sample mass to volume or sonication time did not have an effect on the levels of quercetin compounds obtained
Study In Silico of the Activity of Bioactive Compounds from Cinnamomum (Cinnamomum verum) Bark as Anti-inflammatory Islami, Prima Gita; R. Susanti
Indonesian Journal of Mathematics and Natural Sciences Vol. 48 No. 1 (2025): Volume 48 Nomor 1 Tahun 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/jdcd5m11

Abstract

Cinnamon bark (Cinnamomum verum) contains various bioactive compounds that can be used in drug development, one of which is anti-inflammatory. Inflammation is the body's defense  response to the occurrence of an injury from objects unknown to the body, such as bacterial  infections, trauma, autoimmune, viruses and toxins. The purpose of this study was to determine the content of bioactive compounds in cinnamon bark. This research method was carried out using the Dr. Duke's Phytochemical database. Duke's Phytochemical database to collect  bioactive compounds in cinnamon bark, PubChem to download the ligand structure of bioactive compounds, PASS Online for screening the anti-inflammatory activity value of bioactive  compounds, SEA and Swiss Target Prediction are used to determine the target protein, STRING is used to analyze the interaction between target proteins, Cytoscape is used to predict tissue  topology, Pyrex is used for molecular docking, and Biovia Discovery Studio is used to visualize  docking results. There are 16 cinnamon bark compounds that have a Pa value > 0.5. Based on the docking results, compounds that have a Pa value> 0.5. Based on docking results, beta caryopyhllene, caryopyhllene, fatty acid, and isocaryopyhllene compounds have PPARA activator mechanism with binding affinity of -7.4 kcal/mol, -7.9 kcal/mol, -7.8 kcal/mol, and -5.6  kcal/mol. Caffeic acid compounds have an MMP-9 activator mechanism with a binding affinity of -5.7 kcal/mol. Visualization of docking results shows that isocaryopyhllene and caffeic acid compounds have similar interactions and amino acid residues with control drugs so that they can be used as anti-inflammatory agents. 
Perancangan Antarmuka Pengguna Interaktif untuk Aplikasi UTBKing dengan Pengembangan Model Florentina Yuni Arini; Gerard Sean Dwayne; Aisyah Nathania Araminta; Inoru Nian Alfita; Ahmad Zidhan Ilmana; Nathania Adristina
Indonesian Journal of Mathematics and Natural Sciences Vol. 47 No. 2 (2024): Volume 47 Nomor 2 Tahun 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/04t8sj08

Abstract

Higher education is crucial for personal development, yet its accessibility often poses a challenge, especially for economically disadvantaged students. Apps like UTBKing aim to provide easily accessible learning resources, aiding students in preparing for college entrance. The development process involves three main stages: data collection, system development, and system design. The discussion will delve into the detailed flow of the UTBKing app, its UI/UX design, and implemented interactive features. Continuous efforts are required to develop and enhance the quality of learning applications in order to provide optimal benefits for students in facing future academic challenges.
Studi in Silico Senyawa Metabolit Sekunder Daun Kenikir (Cosmos Caudatus Kunth.) Sebagai Antikanker Ovarium terhadap ESR-1 Gabriel, Kevin; Hidayat, Nafisa Nurfatia; Khaerani, Fitri Azlia; Gaharani , Prodio Efa
Indonesian Journal of Mathematics and Natural Sciences Vol. 47 No. 2 (2024): Volume 47 Nomor 2 Tahun 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/s43fsj13

Abstract

Ovarian cancer is one of the diseases with a high mortality rate through estrogen receptor alpha (ESR1) as one of the causes of ovarian cancer. Current therapies for ovarian cancer can cause side effects and are expensive. Therefore, alternative therapies with fewer side effects and more affordable costs are needed.  One of the herbs that is rich in flavonoid and phenolic acid content which has anticancer activity with its mechanism as a trigger for apoptosis in ovarian cancer cells is Kenikir leaf (Cosmos caudatus). The study was conducted through pharmacophore screening and molecular docking methods in silico with ESR-1 receptor (PDB code:1SJ0). In addition, absorption, distribution, and toxicity predictions were also carried out through the PreADMET page and the Lipinski Rule of Five suitability test. The results of this study concluded that luteolin is the most potential compound as an ESR-1 receptor inhibitor with a pharmacophore fit-score value of 51.36, binding energy of -8.43 kcal/mol, inhibition constant of 66.366x10-2 µM, and hydrogen bonds as ligand-receptor interactions.

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