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All Journal Microbiology Indonesia TARBIYA : Journal Education in Muslim Society Narra J Makara Journal of Science
ASTUTIATI NURHASANAH
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Biochemistry, Genetics & Molecular Biology Education Health Professions Immunology & microbiology Medicine & Pharmacology Public Health

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The Effect of Growth Medium pH towards Trypsin-Like Activity Produced by Lactic Acid Bacteria DYAH WULANSARI; BUDIASIH WAHYUNTARI; TRISMILAH TRISMILAH; ASTUTIATI NURHASANAH
Microbiology Indonesia Vol. 6 No. 2 (2012): June 2012
Publisher : Indonesian Society for microbiology

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (911.59 KB) | DOI: 10.5454/mi.6.2.1

Abstract

In cases of pancreatic disease, trypsin deficiency often occurs due to reduced expression of trypsin in the pancreas. Patients with pancreatic problem can be treated with a supplement containing digestive enzymes, including trypsin. However, most of the enzymes currently used for the treatment are derived from porcine and bovine sources. On the other hand, lactic acid bacteria are also known to show trypsin-like activity. In the previous work, our group screened 11 lactic acid bacteria isolates, which had previously been proven to show serine protease activity, for trypsin-like activity. The strains were initially grown in MRS (de Mann, Rogosa and Sharpe) medium before being transferred directly to the production medium to produce trypsin. During the previous study, the initial pH of the production medium was set at 6 (the same as the MRS medium pH), which is the optimum pH for the cell growth of lactic acid bacteria. However, most trypsin has an optimum pH of around 8. In this study, we altered the production medium pH to 8 and we harvested the lactic acid bacteria from MRS medium by centrifugation prior to their inoculation to the production medium. Observation of the culture growth and enzyme activity indicated that the new strategy improved the enzyme activity expressed by some strains.
Optimization of Trypsin-like Protease Production by Lactobacillus plantarum FNCC 0270 using Response Surface Methodology Trismilah,; Nurhasanah, Astutiati; Sumaryono, Wahono; Malik, Amarila; Sadikin, Mohamad
Makara Journal of Science Vol. 19, No. 2
Publisher : UI Scholars Hub

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Abstract

The purpose of this study was to get optimum medium composition and agitation to trypsin-like protease production by Lactobacillus plantarum FNCC 0270. The medium composition and agitation for enzyme production was optimized using Central Composite Design and Response Surface Method with Design Expert software version 7.1.5 Fermentation was carried out in erlenmeyer flasks at initial pH 8, 37 °C, using an incubator shaker at 87.5 rpm. The best results showed an enzyme activity of 1.0 mU/mL, a protein level of 0.557 mg/mL, and desirability value of 0.740. Numerical optimization was performed to approach the ideal state of the fermentation or the desirability value of 1. The medium composition containing of 3.64% baker's yeast, 1.21% glucose, and 0.13% skim milk was used for the fermentation. The enzyme activity of 1.51 mU/mL and protein level of 0.205 mg/mL can be achieved. After numerical optimization, the fermentation process was verified in erlenmeyer flasks with incubator shaking at 77 rpm, initial pH 8, 37 °C, and 15 h fermentation. The verification results showed that the enzyme activity of 1.273 ± 0.227 mU/mL and protein level of 0.248 ± 0.012 mg/mL.
Medium Optimization for Penicillin Acylase (PAc) Production by Recombinant B. megaterium MS941 Containing pac Gene from B. thuringiensis BGSC BD1 Using Response Surface Methodology FENTRI PARAMITHA PUTRI; ASTUTIATI NURHASANAH; NIKNIK NURHAYATI; IS HELIANTI; KHASWAR SYAMSU
Microbiology Indonesia Vol. 9 No. 2 (2015): June 2015
Publisher : Indonesian Society for microbiology

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1794.751 KB) | DOI: 10.5454/mi.9.2.3

Abstract

Penicillin G acylase (PAc) hydrolyses of the amide bond of benzylpenicillin (Pen-G) releasing PAA and 6-APA, key intermediate in the production of various semisynthetic penicillins. In this study, we optimised the production medium of PAc by RSM using two variables (xylose as inducer and CaCl2 as divalent cations) to obtain the optimum PAc specific activity from Bacillus megaterium btpacBD1. For this purpose, combinations of five different xylose concentrations (0.13 – 0.87 %) and five different CaCl2 concentrations (0.64 – 4.36 mM) were analysed, in a total of 22 experiments. CCD used for the analysis showed that in shake flask cultivations, xylose and CaCl2 showed significant effects on PAc volumetric activity and the quadratic model was in good agreement with the experimental results (R2= 0.86 (p-value < 0.0001)). The maximum specific activity (130.669 ± 50.241 units mg protein-1) was reached when xylose and CaCl2 concentrations were 0.49% and 2.4 mM, respectively, and medium pH was around 7. Under such conditions, the activity of PAc and protein concentration achieved were 1.318 ± 0.406 units mL-1 and  0.0101 ± 0.01 mg mL-1. The shake flask validation experiments demonstrated that with such medium composition the volumetric activity, protein concentration and specific activity achieved were 1.294 ± 0.171 units mL-1, 0.0102 ± 0.0003 mg mL-1 and 125.91 ± 13.309 units mg-1, respectively. When the optimum medium composition was applied in 10 L bioreactor, the optimum volumetric activity (2.0687 ± 0.0820 units mL-1) and protein concentration (0.0078 ± 0.0008 mg mL-1) were achieved 48 h after the start of the cultivation. However, the optimum PAc specific acivity (1260.52  ± 27.5711 units mg protein-1) was achieved 18 h after the start of the cultivation.
Computational drug repurposing for tuberculosis by inhibiting Ag85 complex proteins Iskandar, Israini W.; Nurhasanah, Astutiati; Hatta, Mohammad; Hamid, Firdaus; Handayani, Irda; Chaera, Ummi; Yusriyyah, Andi A.; Jamaluddin, Balqis D.; Zaenab, St; Hidayah, Najdah; Karimah, Nihayatul; Permana, Andi D.; Massi, Muhammad N.
Narra J Vol. 5 No. 1 (2025): April 2025
Publisher : Narra Sains Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52225/narra.v5i1.1130

Abstract

Tuberculosis (TB) remains a significant and deadly infection among pulmonary diseases caused by Mycobacterium tuberculosis, a highly adaptive bacterium. The ability of M. tuberculosis to evade certain drugs has been linked to its unique structure, particularly in the cell envelope, where the Ag85 complex proteins play an essential role in this part.  The aim of this study was to utilize a drug repurposing strategy targeting the Ag85 complex proteins. This study utilized a computational approach with 120 selected drugs experimentally identified to inhibit Tuberculosis. A virtual screening molecular docking with Autodock Vina was used to filter the compounds and identify the strong binders to the Ag85 Complex. Molecular dynamics simulations employed the Gromacs Packages to evaluate the stability of each complex, including root mean square deviation (RMSD), root mean square fluctuation (RMSF), and radius of gyration (RoG). Additionally, absorption, distribution, metabolism, excretion, and toxicity (ADMET) assessments were conducted to gather more information about the drug-likeness of each hit compound. Three compounds, selamectin, imatinib, and eltrombopag were selected as potential drugs repurposed to inhibit the activity of the Ag85 complex enzyme, with binding affinities ranging between -10.560 kcal/mol and -11.422 kcal/mol. The MD simulation within 100 ns (3 replicas) showed that the average RMSD of each Ag85A complex was 0.15 nm–0.16 nm, RMSF was 0.09 nm–0.10 nm, and RoG was 1.80 nm–1.81 nm. For Ag85B, the average RMSD was 1.79 nm–1.80 nm, RMSF was 0.08 nm–0.09 nm, and RoG was 1.79 nm – 1.80 nm. Then, for Ag85C, the mean RMSD was 0.16 nm–0.18 nm, RMSF was 0.09, and RoG was 1.77 nm. The study highlights that these promising results demonstrate the potential of some repurposed drugs in combating the Ag85 complex.
Evaluating ChatGPT’s Accuracy Across Cognitive Levels in Academic Assessments Nurhasanah, Astutiati; Suralaga, Fadhilah; Rosyidah, Ida; Nihayah, Zahrotun; Sari, Riri Fitri; Solihat, Ade; Ernada, Nabila
TARBIYA: Journal of Education in Muslim Society TARBIYA: JOURNAL OF EDUCATION IN MUSLIM SOCIETY | VOL. 11 NO. 2 2024
Publisher : Faculty of Educational Sciences, Syarif Hidayatullah State Islamic University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/tjems.v11i2.44701

Abstract

AbstractThis study evaluates the accuracy of ChatGPT’s free version in answering academic questions based on Bloom’s Taxonomy cognitive levels (C1–C6) and disciplines (physics, social sciences, and religious studies) at two universities in Jakarta. A mixed-method approach was used, combining statistical and content analyses. Thirty-five lecturers from UIN Jakarta and the University of Indonesia submitted exam questions in Bahasa Indonesia to ChatGPT, and the responses were scored on a 0–100 accuracy scale. Results show that ChatGPT performs well on multiple-choice questions (C1–C3) in physics but struggles with higher-order tasks (C5–C6) requiring synthesis, evaluation, and creativity. In social sciences, accuracy was consistent, particularly in theoretical questions, though ChatGPT faced challenges with data-driven analysis and practical application. Religious studies exhibited high accuracy across all cognitive levels due to the structured and doctrinal nature of the material.Statistical analysis revealed significant differences in accuracy between lower and higher cognitive levels in physics (p = 0.005) and religious studies (p = 0.011), but no significant difference in social sciences (p = 0.137). ANOVA (p = 0.464) showed no significant differences across disciplines. This study highlights ChatGPT’s effectiveness in answering lower to intermediate-level questions (C1–C4) but identifies limitations with higher-level tasks (C5–C6). These findings encourage educators to design questions that assess deeper cognitive skills while utilizing AI’s strengths in supporting learning and knowledge acquisition.AbstrakStudi ini mengevaluasi akurasi versi gratis ChatGPT dalam menjawab pertanyaan akademik berdasarkan tingkat kognitif Taksonomi Bloom (C1–C6) dan disiplin ilmu (fisika, ilmu sosial, dan studi keagamaan) di dua universitas di Jakarta. Pendekatan mixed-method digunakan, menggabungkan analisis statistik dan konten. Sebanyak 35 dosen dari UIN Jakarta dan Universitas Indonesia mengajukan soal ujian dalam Bahasa Indonesia ke ChatGPT, dan jawaban yang dihasilkan dinilai pada skala akurasi 0–100. Hasil penelitian menunjukkan bahwa ChatGPT unggul pada soal pilihan ganda (C1–C3) di bidang fisika, tetapi kesulitan pada tugas tingkat tinggi (C5–C6) yang membutuhkan sintesis, evaluasi, dan kreativitas. Pada ilmu sosial, akurasi cenderung konsisten, terutama pada soal teoretis, meskipun ChatGPT menghadapi tantangan dalam analisis berbasis data dan penerapan praktis. Pada studi agama, ChatGPT menunjukkan akurasi tinggi di semua tingkat kognitif karena struktur materi dan interpretasi doktrin yang jelas. Analisis statistik menunjukkan perbedaan signifikan pada akurasi antara tingkat kognitif rendah dan tinggi di fisika (p = 0,005) dan studi agama (p = 0,011), tetapi tidak pada ilmu sosial (p = 0,137). Hasil ANOVA (p = 0,464) menunjukkan tidak ada perbedaan signifikan antar disiplin ilmu secara keseluruhan. Studi ini menyoroti efektivitas ChatGPT dalam menjawab soal tingkat rendah hingga menengah (C1–C4) tetapi mengidentifikasi keterbatasan pada tugas tingkat tinggi (C5–C6). Temuan ini mendorong pendidik untuk merancang soal yang mengukur keterampilan kognitif mendalam sambil memanfaatkan kekuatan AI dalam mendukung pembelajaran dan akuisisi pengetahuan.How to Cite: Nurhasanah, A., Suralaga, F., Rosyidah, I., Nihayah, Z., Sari, R. F., Solihat, A., & Ernada, N. (2024). Evaluating ChatGPT’s Accuracy Across Cognitive Levels in Academic Assessments. TARBIYA: Journal of Education in Muslim Society, 11(2), 211-224. https://doi.org/10.15408/tjems.v11i2.44701
Evaluating ChatGPT’s Accuracy Across Cognitive Levels in Academic Assessments Nurhasanah, Astutiati; Suralaga, Fadhilah; Rosyidah, Ida; Nihayah, Zahrotun; Sari, Riri Fitri; Solihat, Ade; Ernada, Nabila
TARBIYA: Journal of Education in Muslim Society TARBIYA: JOURNAL OF EDUCATION IN MUSLIM SOCIETY | VOL. 11 NO. 2 2024
Publisher : Faculty of Education and Teacher Training, UIN (State Islamic University) Syarif Hidayatul

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/tjems.v11i2.44701

Abstract

AbstractThis study evaluates the accuracy of ChatGPT’s free version in answering academic questions based on Bloom’s Taxonomy cognitive levels (C1–C6) and disciplines (physics, social sciences, and religious studies) at two universities in Jakarta. A mixed-method approach was used, combining statistical and content analyses. Thirty-five lecturers from UIN Jakarta and the University of Indonesia submitted exam questions in Bahasa Indonesia to ChatGPT, and the responses were scored on a 0–100 accuracy scale. Results show that ChatGPT performs well on multiple-choice questions (C1–C3) in physics but struggles with higher-order tasks (C5–C6) requiring synthesis, evaluation, and creativity. In social sciences, accuracy was consistent, particularly in theoretical questions, though ChatGPT faced challenges with data-driven analysis and practical application. Religious studies exhibited high accuracy across all cognitive levels due to the structured and doctrinal nature of the material.Statistical analysis revealed significant differences in accuracy between lower and higher cognitive levels in physics (p = 0.005) and religious studies (p = 0.011), but no significant difference in social sciences (p = 0.137). ANOVA (p = 0.464) showed no significant differences across disciplines. This study highlights ChatGPT’s effectiveness in answering lower to intermediate-level questions (C1–C4) but identifies limitations with higher-level tasks (C5–C6). These findings encourage educators to design questions that assess deeper cognitive skills while utilizing AI’s strengths in supporting learning and knowledge acquisition.AbstrakStudi ini mengevaluasi akurasi versi gratis ChatGPT dalam menjawab pertanyaan akademik berdasarkan tingkat kognitif Taksonomi Bloom (C1–C6) dan disiplin ilmu (fisika, ilmu sosial, dan studi keagamaan) di dua universitas di Jakarta. Pendekatan mixed-method digunakan, menggabungkan analisis statistik dan konten. Sebanyak 35 dosen dari UIN Jakarta dan Universitas Indonesia mengajukan soal ujian dalam Bahasa Indonesia ke ChatGPT, dan jawaban yang dihasilkan dinilai pada skala akurasi 0–100. Hasil penelitian menunjukkan bahwa ChatGPT unggul pada soal pilihan ganda (C1–C3) di bidang fisika, tetapi kesulitan pada tugas tingkat tinggi (C5–C6) yang membutuhkan sintesis, evaluasi, dan kreativitas. Pada ilmu sosial, akurasi cenderung konsisten, terutama pada soal teoretis, meskipun ChatGPT menghadapi tantangan dalam analisis berbasis data dan penerapan praktis. Pada studi agama, ChatGPT menunjukkan akurasi tinggi di semua tingkat kognitif karena struktur materi dan interpretasi doktrin yang jelas. Analisis statistik menunjukkan perbedaan signifikan pada akurasi antara tingkat kognitif rendah dan tinggi di fisika (p = 0,005) dan studi agama (p = 0,011), tetapi tidak pada ilmu sosial (p = 0,137). Hasil ANOVA (p = 0,464) menunjukkan tidak ada perbedaan signifikan antar disiplin ilmu secara keseluruhan. Studi ini menyoroti efektivitas ChatGPT dalam menjawab soal tingkat rendah hingga menengah (C1–C4) tetapi mengidentifikasi keterbatasan pada tugas tingkat tinggi (C5–C6). Temuan ini mendorong pendidik untuk merancang soal yang mengukur keterampilan kognitif mendalam sambil memanfaatkan kekuatan AI dalam mendukung pembelajaran dan akuisisi pengetahuan.How to Cite: Nurhasanah, A., Suralaga, F., Rosyidah, I., Nihayah, Z., Sari, R. F., Solihat, A., & Ernada, N. (2024). Evaluating ChatGPT’s Accuracy Across Cognitive Levels in Academic Assessments. TARBIYA: Journal of Education in Muslim Society, 11(2), 211-224. https://doi.org/10.15408/tjems.v11i2.44701
Co-Authors Amarila Malik Budiasih Wahyuntari Chaera, Ummi DYAH WULANSARI Ernada, Nabila FENTRI PARAMITHA PUTRI Hamid, Firdaus Handayani, Irda Hatta, Mohammad Hidayah, Najdah IS HELIANTI Iskandar, Israini W. Jamaluddin, Balqis D. Karimah, Nihayatul Khaswar Syamsu Massi, Muhammad N. Mohamad Sadikin NIKNIK NURHAYATI Permana, Andi D. ROSYIDAH, IDA Sari, Riri Fitri Solihat, Ade Suralaga, Fadhilah Trismilah Trismilah Trismilah, Wahono Sumaryono Yusriyyah, Andi A. Zaenab, St Zahrotun Nihayah