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All Journal Al-Fiziya: Journal of Materials Science, Geophysics, Instrumentation and Theoretical Physics Jurnal Penelitian Fisika dan Aplikasinya (JPFA) JURNAL FISIKA JFA (Jurnal Fisika dan Aplikasinya) JOURNAL OF NATURAL SCIENCES AND MATHEMATICS RESEARCH JURNAL ILMIAH PENDIDIKAN FISIKA AL BIRUNI Journal of Natural Sciences and Mathematics Research Phenomenon : Jurnal Pendidikan MIPA Jurnal Biodjati JIPF (Jurnal Ilmu Pendidikan Fisika) Al-Kimia Edukasi Islami: Jurnal Pendidikan Islam JURNAL EKSAKTA PENDIDIKAN (JEP) Physics Education Research Journal Journal of Electrical Engineering and Computer (JEECOM) Analisa: Journal of Social Science and Religion Journal of Holistic Medical Technologies
Hadi Kusuma, Hamdan
Universitas Islam Negeri Walisongo Semarang
Religion Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Electrical & Electronics Engineering Energy Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Neuroscience Physics Social Sciences Other

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Designing an Interactive Flip-Mind Module on Temperature and Heat Concepts to Facilitate Critical Thinking-Oriented Learning Intan, Wahyu Noor; Susilawati, Susilawati; Kusuma, Hamdan Hadi
JURNAL EKSAKTA PENDIDIKAN (JEP) Vol 9 No 2 (2025): JEP (Jurnal Eksakta Pendidikan)
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/jep/vol9-iss2/1042

Abstract

Critical thinking skills are essential for students facing the challenges of the Industrial Revolution 4.0 era. This study aimed to develop and analyze the feasibility of the Flip-Mind interactive module, evaluate the improvement of critical thinking skills, and examine students' responses to its use on temperature and heat materials. This study employed a Research and Development (R&D) method, utilizing the 4D model (Define, Design, Develop, and Disseminate), integrating case-based learning and critical thinking components through interactive HTML5-based features to enhance conceptual understanding. This research employed a pretest-posttest control group design with purposive sampling involving grade XI students from a public senior high school. The validation results indicate that the module is in the "very feasible" category. The improvement in critical thinking skills was indicated by an N-Gain value of 62.7% (moderate category), with an average increase in score of 11%. Students' responses to the module’s use were in the "outstanding" category with a percentage of 82%. These findings suggest that the Flip-Mind interactive module is a practical and feasible alternative to innovative teaching materials for improving critical thinking skills in physics learning. Theoretically, this study enriches the framework of digital learning innovation by demonstrating the integration of case-based and critical thinking-oriented approaches. Practically, the Flip-Mind module offers an effective pedagogical model that can be adapted for interactive and student-centered physics instruction.
Comparative Analysis of Nutritional Content of Mudskipper Periophthalmus variabilis and Boleophthalmus boddarti Hidayat, Saifullah; Yusuf, Andi Muhammad; Kusuma, Hamdan Hadi
Jurnal Biodjati Vol 7 No 1 (2022): May
Publisher : UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/biodjati.v7i1.15604

Abstract

Gelodok or mudskipper fish are unique fish that have the ability to live in both aquatic and terrestrial areas. Some Indonesian who live in coastal areas use this fish for consumption. Types of mudskipper that are abundant in Indonesia are from the genera of Boleophtalmus, Periophthalmodon and Periophthalmus, where not all types have been studied for their nutritional content. The aim of this study was to analyze the content of Boleophthalmus boddarti and Periophthalmus variabilis. his study compared the nutritional content of the two types sampled from the Kaliwungu Kendal mangrove ecosystem and the Wedarijaksa Pati mangrove ecosystem. The two types of fish sampled were measured by morphometry which included body length, body width and body weight. Then the fish were analyzed for their nutritional content, namely carbohydrates using the Luff Schroorl test method, protein using the Kjeldahl method, fat using the Soxhlet method, iron using the AAS method, and phosphorus using the spectrophotometer method. The results showed that B. boddarti had a higher protein and iron content than P. variabilis . Meanwhile, P. variabilis had higher carbohydrate, fat and phosphorus content than B. boddarti. The difference was due to different feeding behavior, habitat, and types of food in B.boddarti and P. variabilis.
Classification of normal and cancerous mammogram images based on texture features using the Support Vector Machine (SVM) method Risma Eka Ashari Ashari; Hamdan Hadi Kusuma
Journal of Holistic Medical Technologies (JHMT) Vol. 1 No. 1 (2024): December
Publisher : Konsorsium Pengetahuan Innoscientia (KOPINNOS)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Breast cancer is the leading cause of death in older women, with more than one million women worldwide dying from this disease yearly. Mammography is a specialized radiological examination that uses low-dose X-rays to detect breast abnormalities, even before visible symptoms such as palpable lumps appear. This study aims to develop an effective mammogram image classification model using the SVM (Support Vector Machine) method with texture feature extraction analysis in histograms and GLCM (Gray-Level Co-Occurrence Matrix). The research involved 20 normal and 20 cancer images, starting with mammogram image preprocessing, then texture feature extraction using histograms and GLCM, and ending with data classification using the SVM method. Test results showed that SVM could classify images with an accuracy of 67.5%, a sensitivity of 33.3%, and a specificity of 70%. Therefore, this research could be a foundation for further developments to enhance mammogram image classification accuracy.
Co-Authors Adeni, Adeni Adina Widi Astuti Adityaa, Farhan Al Afda, Mahrunnisa Anasom, Anasom Andi Muhammad Yusuf, Andi Muhammad Anshori Huroeroh Azizah, Nisa Awaliyah Nur Azzahra, Jannatul Firdausa Baehaqi Biaunik Niski Kumila Biaunik Niski Kumila Choeroni Choeroni Destyofrini, Fredina Faqih, Muhammad Izzatul Fariyani, Qisthi Fattah Syukur Fitri Fitri Hardianto, Firman Hidayat, Saifullah Hudawi, Ahmad Ibrahim, Zuhairi Intan, Wahyu Noor Isfaul Maulina Istikomah Jamhari Jamhari Karim, Abdul Kumila, Biaunik Niski Kumila, Biaunik Niski Kustomo Mufakhidin, Ayuf Mujiasih Mujiasih Mulyatun Mulyatun Niam, Muhammad Yusrun Nisa Awaliyah Nur Azizah Nugroho, Deni Ebit Nur Ahmad, Nur Pancorowati, Dhita Azzahra Pertiwi, Salsabiela Prastyo, Irman Said Rahmani, Tara Puri Ducha Risma Eka Ashari Ashari Sari, Fitri Nur Indah Sheilla Rully Anggita Shofani, Maya Sumarti, Heni Supriyono - Susilawati Susilawati Susilawati, Susilawati Tasyakuranti, Alvania Nabila Tika Rahmawati Tri Suryandari, Ervin Tria Nurmar’atin Watson, Lee James Zulkafli Othaman