Jurnal Multidisipliner Kapalamada
KAPALAMADA JURNAL MULTIDISIPLINER is a quarterly journal that is published in Maret, Juni, September, and Desember. KAPALAMADA JURNAL MULTIDISIPLINER seeks Review articles, Case reports and original contributions from all areas of: Social Science and Humanities; Life Sciences; Health Science; Physical, Chemical Science and Engineering. The Journal invites original Research Papers, Review articles, Technical or Case reports and Short communications that are not published or not being considered for publication. This journal utilizes the LOCKSS system to create a distributed archiving system among participating libraries and permits those libraries to create permanent archives of the journal for purposes of preservation and restoration. Jurnal Multidisipliner Kapalamada seeks Review articles, Case reports and original contributions from all areas of: Social Science and Humanities: Arts and Humanities, Business Management, Hotel Management, Management, Tourism, Accounting, Decision Science, Education, Economics, Law, Finance, Psychology, Political Science, Physical Education, English Literature, Social Work and History. Life Sciences: Agricultural, Biological Sciences, Biotechnology, Biochemistry, Genetics, Molecular Biology, Environmental Science, Ecology, Arachnology, Biodiversity and Conservation, Entomology, Limnology, Ichthyology, Malacology, Immunology and Microbiology, Neuroscience, Marine Biology. Health Science: Medicine and Dentistry, Nursing and Health Professions, Pharmacology and Toxicology, Pharmaceutical Science, Veterinary Science, Veterinary Medicine. Physical, Chemical Science and Engineering: Chemical Engineering, Chemistry, Computer Science, Earth and Planetary Science, Energy, Mathematics, Physics and Astronomy, Engineering, Material Science, Statistics. The Journal invites original Research Papers, Review articles, Technical or Case reports and Short communications that are not published or not being considered for publication.
Articles
302 Documents
ASCOGENLY: ANANAS COMOSUS ENZYME FOR DETERGEN ENVIRONMENTALY FRIENDLY
Tathya Dhiany Rahmania;
Yuniar Dwi Setyaning
Jurnal Multidisipliner Kapalamada Vol. 5 No. 01 (2026): JURNAL MULTIDISIPLINER KAPALAMADA
Publisher : Pusat Studi Ekonomi, Publikasi Ilmiah dan Pengembangan SDM
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DOI: 10.62668/kapalamada.v5i01.2253
Water is one of the most important resources for living organisms; therefore, its quality must be maintained. Indonesia is a maritime country where about 70% of its territory consists of sea and 30% land. The Surabaya City Environmental Service (DLH) reported that around 80% of pollutants entering the Tambak Wedi River originate from household waste. One major cause is surfactant substances from detergents that reduce water surface tension and harm aquatic life. To address this issue, we developed an innovation called Ascogenly, an eco-enzyme made from pineapple peels (Ananas comosus). This project aims to reduce organic waste while minimizing the use of environmentally harmful detergents. Ascogenly is produced by mixing eco-enzyme and baking soda in a 1:10 ratio. Experimental testing showed that fish exposed to commercial detergent X died during observation, whereas fish in the Ascogenly solution survived. These results indicate that Ascogenly is safer for aquatic ecosystems and does not disrupt oxygen circulation. Therefore, Ascogenly has potential as an environmentally friendly detergent alternative.
KLASIFIKASI KUALITAS TANAH MENGGUNAKAN METODE GRADIENT BOOSTING (STUDI KASUS: BUDIDAYA KACANG TANAH)
Diah Kamalia;
Meidya Koeshardianto;
Wahyudi Setiawan
Jurnal Multidisipliner Kapalamada Vol. 5 No. 01 (2026): JURNAL MULTIDISIPLINER KAPALAMADA
Publisher : Pusat Studi Ekonomi, Publikasi Ilmiah dan Pengembangan SDM
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DOI: 10.62668/kapalamada.v5i01.2297
This study aims to determine soil quality in peanut cultivation to support precise decision-making for farmers. Peanuts were selected due to their economic and nutritional importance in Madura, as well as their strong dependence on soil conditions. The research method used is the Gradient Boosting Classifier, utilizing four parameters: soil pH, soil moisture, air temperature, and air humidity. This method builds models iteratively by reducing errors from previous models by following the gradient movement towards the negative. The collected data are then processed through a classification approach to accurately determine soil suitability for peanut cultivation. The results indicate that the method can identify relationships among soil variables, making it a useful tool for predicting soil suitability for cultivation. The system is developed to enhance decision-making by enabling real-time soil condition monitoring with precision, improving soil management effectiveness, and optimizing sustainable and efficient cultivation practices for farmers in Buluh, Socah, Bangkalan.