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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi BAREKENG: Jurnal Ilmu Matematika dan Terapan Saintifik : Jurnal Matematika, Sains, dan Pembelajarannya Jurnal Pendidikan Matematika (Jupitek) Jurnal Magister Pendidikan Matematika (JUMADIKA) Science Map Journal Devotion: Journal of Research and Community Service Pakem : Jurnal Pengabdian Kepada Masyarakat Pattimura International Journal of Mathematics (PIJMath) ATOM : Jurnal Riset Mahasiswa BAKTI : Jurnal Pengabdian Kepada Masyarakat
Taufan Talib
Universitas Pattimura
Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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Journal : Pattimura International Journal of Mathematics (PIJMath)

 1 
Modeling Biodegradation of Polyethylene Terephthalate Involving the Growth of Factor Escherichia Coli Bacteria Talib, Taufan
Pattimura International Journal of Mathematics (PIJMath) Vol 1 No 1 (2022): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (604.926 KB) | DOI: 10.30598/pijmathvol1iss1pp07-16

Abstract

A design of a Polyethylene Terephthalate (PET) waste biodegradation system using Escherichia Coli (E-Coli) bacteria in a whole-cell biocatalyst system. E-Coli bacteria will produce LC-Cutinase enzyme on the cell surface so PET can be broken down into Ethylene glycol and Terephthalate acid. With the help of Reductase and Dehydrogenase enzymes, a chemical reaction occurs that converts Ethylene glycol into Malate. Through the chemical reaction process, it is guaranteed that Ethylene glycol does not explain the environment but can be used as an energy source for the growth of E-Coli bacteria. Thus E-Coli can grow faster, so the more bacteria, the more PET that can be broken down quickly.
Ordinal Logistic Regression Analysis of Factors that Affecting the Blood Sugar Levels Diabetes Mellitus Patients Mayawi, Mayawi; Nurhayati, Nurhayati; Talib, Taufan; Bustan, Ariestha W; Laamena, Novita S
Pattimura International Journal of Mathematics (PIJMath) Vol 2 No 1 (2023): Pattimura International Journal of Mathematics (PIJMath)
Publisher : Pattimura University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/pijmathvol2iss1pp33-42

Abstract

Penelitian ini bertujuan untuk menganalisis pengaruh faktor-faktor risiko terhadap kadar gula darah pada penderita diabetes mellitus menggunakan analisis regresi logistik ordinal. Faktor-faktor risiko yang dijadikan variabel bebas adalah usia, jenis kelamin, Indeks Massa Tubuh (IMT), tekanan darah, Tingkat Kolesterol (TC), Low Density Lipoprotein (LDL), High Density Lipoprotein (HDL), Thyrocalcitonin Hormone (TCH) dan Loss Trigliserida(LTG). Data yang digunakan dalam penelitian ini diperoleh dari https://hastie.su.domains/Papers/LARS/diabetes.data. Jumlah sampel yang diambil sebanyak 100 responden yang telah terdiagnosis diabetes mellitus. Hasil penelitian menunjukkan bahwa faktor-faktor risiko seperti usia, Indeks Massa Tubuh (IMT), Tingkat Kolesterol (TC), Low Density Lipoprotein (LDL), High Density Lipoprotein (HDL) dan jenis serum Thyrocalcitonin Hormone (TCH) berpengaruh signifikan terhadap kadar gula darah pada penderita diabetes mellitus. Model logit terbaik untuk regresi logistic ordinal adalah Logit 1 yaitu g(x_1 )= -2.721-0.079 X_1+2.813〖 X〗_3+〖0.100 X〗_5-0.099 X_6-0.119 X_7-0.989 X_8 dan Logit 2 yaitu g(x_2 )= -8.571-0.079 X_1+2.813〖 X〗_3+〖0.100 X〗_5-0.099 X_6-0.119 X_7-0.989 X_8. Disimpulkan bahwa analisis regresi logistik ordinal dapat digunakan untuk mengidentifikasi faktor-faktor yang mempengaruhi kadar gula darah pada penderita diabetes mellitus dan membantu pengembangan strategi pengelolaan dan intervensi yang lebih efektif
Co-Authors Alhamid, Khadijah Azzahra Amelia Amelia Anderson Leonardo Palinussa Attamimi, Zeidun Ayal, Carolina S Binti Rohmawati Boinauw, Zaenab Bustan, Ariestha W Bustan, Ariestha Widyastuty Bustan, Ariestha Widyastuty Carolina Selfisina Ayal Christi Matitaputty Christina Martha Laamena Daniel Pandapotan, Daniel Day, Aprilia Faqihuddin Faqihuddin Huwaa, Novalin C Imam Nurhadi Purwanto Jurniasih, Nia Kairoti, Achmad Arsil Azim Keliangin, Maimuna Koedoeboen, Filda Laamena, Novita S Laamena, Novita Serly Lattan, Kezia Ramona Latupeirissa, Indri Kezia Mahuda, Isnaini Makatita, Fakhran Masry, Indah Lestari Mayawi Mayawi Mayawi, Mayawi Munazat Salmin Narahubun, Albertina Nisa, Fakhrun Nurhayati Nurhayati Nurhayati Nurviana, Nurviana Pakay, Gita Febriani Riezky Purnama Sari, Riezky Purnama Sari Robiwala, Emiliana Rofiroh Rofiroh Rumalean, M Samad Rumbaru, Musri Salamor, Reinhard Salmin, Munazat Samsuri, Diah Faradila Saputra, Lamanisa Rasid Sobri Abusini Solissa, Welmi Tamalene, Hanisa Ucu, Murni Ulya Nabilla, Ulya Nabilla Welmintje Mataheru Wulandari, Megawati Putri Zulkarnaen, M. Naufal Reza