Interconnectedness of Math, Biology and Islamic Education: Designing Teaching Materials for High School


The interconnectedness of a science is characterized by shared bodies of knowledge and shared vocabulary. Other disciplines, such as education and basic science, should be able to complement science and Islamic studies. Many aspects of the Qur’an and Hadith have been scientifically validated. Islamic studies can also be used to examine the concept of learning in schools and higher education. The interconnectedness of mathematics, biology, and Islamic studies derived from the Qur’an and Hadith, as well as based on the secondary school curriculum, was examined and illustrated in this qualitative study using a content analysis approach. In addition, an integration study was presented, which was part of a material instruction and sample test. The study’s findings revealed that mathematics and Islamic education materials, as well as inheritance distribution and the concept of arithmetic operations of whole numbers and fractions, are all interconnected. Gene classification is concerned with problem-solving of binomial odds distributions (statistics) in mathematics, as well as both mathematics and biology materials. At the same time, the human creation, the environment and nature are related materials in Islamic education and biology. The interconnectedness of the three areas of study can thus be seen in classification concepts. In biology and Islamic studies, this concept can be learned in depth through the material classification of lawful and forbidden animals to eat. This classification is discussed in set materials in mathematics. As a result, the discussion of set materials can be traced back to a real-life example in Islamic education and biology. Furthermore, when teaching the concept of permissible and prohibited foods based on the Qur’an and Hadith, mathematics and biology concepts can be used.

Keywords: mathematics, biology, Islamic studies, teaching materials, inheritance, classification, human creation, the environment and nature

[1] Hidayatullo, “Relasi ilmu pengetahuan dan agama,” in Paper presented at: International Seminar on Generating Knowledge Through Research; 2016, Malaysia.

[2] Maksudin, “Transformasi pendidikan agama dan sains dikotomi ke pendidikan nondikotomi,” Jurnal Pendidikan Islam, vol. 4, no. 2, pp. 277–298, 2015.

[3] R. N. Muthmainah, Analisis konten dan nilai-nilai religius dalam komik kecil-kecil punya karya (KkPK) serta pemanfaatannya sebagai media pembelajaran menulis cerita di sekolah dasar. Bandung: Universitas pendidikan Indonesia, 2015.

[4] A. Al-Ad’zam and A. Yazid, Maqasid fi al-Mirats. Kairo: Azhar, 2018.

[5] J. A. Nasution, Akuntansi al-Mawarits. Brunei Darussalam: UNISSA, 2004.

[6] K. Sitriani, L. Arapu, and L. Ndia, “Analisis kemampuan numerik siswa SMP negeri di kota kendari ditinjau dari Perbedaan gender,” Jurnal Pendidikan Matematika, vol. 10, no. 2, pp. 161–171, 2019.

[7] N. Sobarningsih, R. Juariah, A. R. Nurdiansyah, K. Purwanti, and R., “Pengembangan soal matematika Bernuansa Islami,” Jurnal Analisa, vol. 5, no. 2, pp. 109–123, 2019.

[8] N. A. Campbell, J. B. Reece, and U. LA, Biologi jilid, 2nd ed. Jakarta: Erlangga, 2008.

[9] M. Havis, F. Lufri, E. A, and Z.M., “Model pembelajaran interaktif pada biologi perkembangan hewan: Analisis kebutuhan perkembangan,” Ta’dib, vol. 15, no. 1, pp. 1–13, 2012.

[10] Y. Suryaningsih, “Penerapan pembelajaran biologi berbasis al-qur’an sebagai metode untuk pembentukan karakter siswa,” Jurnal Bio Educatio, vol. 3, no. 1, pp. 22–33, 2018.

[11] J. Khan, J. S. Wei, and R. M, “Classification and diagnostic prediction of cancers using gene Expression profiling and artificial neural networks,” Nat Med, vol. 7;673-679, 2001.

[12] A. Ambica, S. Gandi, and A. Kothalanka, “An efficient expert system for diabetes by naive Bayesian classifier,” International Journal of Engineering Trends and Technology, vol. 4, pp. 4634–4639, 2013.

[13] R. Diaz-Uriarte and S. A. Andres, “Gene seletion and classification of microrray data using random forst,” BMC Bioinformatics, vol. 7, no. 3, pp. 21–30, 2006.

[14] Werdhana, Klasifikasi gen yang terkait sindrom alzheimer menggunakan metode naive bayes classifier, binary logstic regression dan logistic regression ensemble. Surabaya: Institut Teknologi Sepuluh Nopember, 2017.

[15] H.-M. A. Luis, B.-H. Edmundo, M.-C. Roberto, and G. A. Jose, Selection and clissification of gene expression data using a MF-GA-TS-SV approach. Cham: Intelligent Computing in, 2014.

[16] B. Chandra and M. Gupta, “An efficient statistical feature selection approach for classification of gene expression data,” Journal of Biomedical Informatics, vol. 44, pp. 529–535, 2011.

[17] H. Chen, Y. Zhang, and I. Gutman, “A kernel-based clustering method for gene selection with gene expression data,” Journal of Biomedical Informatics, vol. 62, pp. 12–20, 2016.

[18] Sutarno, “Rekayasa genetika dan perkembnagan bioteknologi di bidang peternakan,” in Paper presented at: Seminar Nasional XIII Pendidikan Biologi; 2016, Semarang, Indonesia.

[19] F. Mas’oed, Struktur aljabar. Jakarta: Akademia Permata, 2013.

[20] A. R. As’ari, M. Tohir, E. Valentino, Z. Imron, and I. Taufiq, “Matematika,” Kemanterian Pendidikan dan kebudayaan, 2017