https://ejournal.unsrat.ac.id/v3/index.php/jmuo/issue/feed 2024-09-10T04:37:47+08:00 Verna Albert Suoth vernasuoth@unsrat.ac.id Open Journal Systems <p> </p> <table class="data" width="100%" bgcolor="#f0f0f0"> <tbody> <tr valign="top"> <td width="20%">ournal title</td> <td width="80%"><strong>Jurnal MIPA</strong></td> </tr> <tr valign="top"> <td width="20%">Initials</td> <td width="80%"><strong>JM</strong></td> </tr> <tr valign="top"> <td width="20%">Email</td> <td width="80%"><a title="Email Jurnal" href="https://mail.google.com/mail/u/0/?ogbl#inbox/FMfcgzGqPpXKsfdSkXrhGtpWJFxRnGCS?compose=new"><strong>mipa.unsrat.online@gmail.com</strong></a></td> </tr> <tr valign="top"> <td width="20%">Frequency</td> <td width="80%">twice a year on <strong>February and August</strong></td> </tr> <tr valign="top"> <td width="20%">DOI</td> <td width="80%"><strong>https://doi.org/10.35799</strong></td> </tr> <tr valign="top"> <td width="20%">Online ISSN</td> <td width="80%"><strong><strong title="e-issn gulawenah"><strong><a href="http://u.lipi.go.id/1347251749" target="_blank" rel="noopener">2302-3899</a>(online)</strong></strong></strong></td> </tr> <tr valign="top"> <td width="20%">Managing Editor</td> <td width="80%"><strong>Nio Song Ai, <a tabindex="-1" href="http://www.scopus.com/inward/authorDetails.url?authorID=57200108003&amp;partnerID=MN8TOARS" target="_blank" rel="me nofollow noopener noreferrer">Scopus Author ID: 57200206117</a></strong></td> </tr> <tr valign="top"> <td width="20%">Editor-in-chief</td> <td width="80%"><strong>Verna Albert Suoth, <a tabindex="-1" href="http://www.scopus.com/inward/authorDetails.url?authorID=57200108003&amp;partnerID=MN8TOARS" target="_blank" rel="me nofollow noopener noreferrer">Scopus Author ID: 57200108003</a></strong></td> </tr> <tr valign="top"> <td width="20%">Publisher</td> <td width="80%"><strong><strong><strong><a href="https://www.unsrat.ac.id/" target="_blank" rel="noopener">Unversitas Sam Ratulangi Manado</a></strong></strong></strong></td> </tr> <tr valign="top"> <td width="20%">Accreditation</td> <td width="80%"><strong>Peringkat 5 SINTA Certificate</strong></td> </tr> </tbody> </table> <p><em><strong>JURNAL MIPA</strong></em> is a peer-reviewed journal dedicated to the promotion and dissemination of scholarly research on</p> https://ejournal.unsrat.ac.id/v3/index.php/jmuo/article/view/56937 2024-07-26T15:40:33+08:00 Verna Albert Suoth vernasuoth@unsrat.ac.id As'ari as.ari2222@unsrat.ac.id Yusmadi H.M Said 17101104010@student.unsrat.ac.id Hesky Stevi Kolibu heskykolibu@unsrat.ac.id

<p>Panas bumi merupakan salah satu sumber daya alam yang memiliki potensi besar untuk dimanfaatkan sebagai sumber energi terbarukan. Adanya sumber panas bumi bawah permukaan tanah tergambar dari munculnya manifestasi panas bumi. Penelitian ini dilakukan untuk memetakan sebaran temperatur permukaan tanah dan mengetahui pola gradien temperatur di sekitar manifestasi panas bumi Desa Tempang Dua, Kabupaten Minahasa, Sulawesi Utara. Penelitian ini menggunakan metode observasi lapangan dengan mengukur temperatur air sumur, mata air panas dangkal, dan tanah beruap menggunakan termometer yang dilakukan pada siang hingga sore hari. Hasil penelitian di dapatkan sebaran suhu air dengan temperatur 28^oC-90^oC dengan elevasi berkisar 724-760 m dan kedalaman permukaan air sumur 0-23 meter. Pola sebaran suhu yang diperoleh menunjukkan kecenderungan di area yang lebih tinggi pada peta kontur memiliki suhu air paling tinggi.</p> <p>Geothermal is one of the natural resources that has great potential to be utilized as a renewable energy source. The existence of subsurface geothermal sources is illustrated by the emergence of geothermal manifestations. This study was conducted to map the distribution of land surface temperature and determine the temperature gradient pattern around the geothermal manifestation of Tempang Dua Village, Minahasa Regency, North Sulawesi. This study used a field observation method by measuring the temperature of well water, shallow hot springs, and steamy soil using a thermometer conducted in the afternoon to evening. The results of the study obtained the distribution of water temperature with a temperature of 28^o C-90^oC with an elevation ranging from 724-760 masl and a depth of the well water surface of 0-23 meters. The temperature distribution pattern obtained shows a tendency in the higher areas on the contour map to have the highest water temperature.</p>

2024-10-31T00:00:00+08:00 Copyright (c) 2024 Verna Albert Suoth, As'ari, Yusmadi H.M Said, Hesky Stevi Kolibu https://ejournal.unsrat.ac.id/v3/index.php/jmuo/article/view/57778 2024-09-05T00:40:45+08:00 Afrioni Roma Rio afrioni.roma.rio@gmail.com Berton Maruli Siahaan bertonsiahaan@unsrat.ac.id Ernawatil Gani ernawatilgani@gmail.com

<p>Penelitian ini mengkaji potensi energi matahari di Sulawesi Utara dengan menganalisis parameter lingkungan seperti suhu, kelembaban relatif, jumlah awan, dan radiasi matahari selama periode 2018 hingga 2022. Metode <em>machine learning</em> K-Means digunakan untuk mengelompokkan data secara optimal, dengan penentuan jumlah klaster terbaik melalui metode siku. Penggunaan <em>machine learning</em> ini penting untuk menangani data yang besar dan kompleks, serta mengidentifikasi pola tersembunyi yang membantu pemetaan potensi energi matahari. Hasil analisis menunjukkan bahwa Klaster 2, yang terdiri dari wilayah dengan suhu tinggi dan radiasi matahari yang optimal, memiliki potensi terbesar untuk instalasi tenaga surya skala besar, didukung oleh infrastruktur tenaga surya yang sudah ada di wilayah pada klaster tersebut. Penelitian ini menghasilkan peta energi surya hingga tingkat desa, yang dapat digunakan untuk pengembangan energi surya di Sulawesi Utara</p> <p>This study examines the solar energy potential in North Sulawesi by analyzing environmental parameters such as temperature, relative humidity, cloud cover, and solar irradiance over the period of 2018 to 2022. The machine learning K-means method was used to optimally cluster the data, with the best number of clusters determined through the elbow method. The use of machine learning is important for handling large and complex datasets, as well as identifying hidden patterns that aid in mapping solar energy potential. The analysis results show that Cluster 2, which consists of areas with high temperatures and optimal solar irradiance, has the greatest potential for large-scale solar power installations, supported by existing solar infrastructure in the region. This study produces a detailed solar energy map down to the village level, which can be used for the development of solar energy in North Sulawesi</p> <p> </p>

2024-09-10T00:00:00+08:00 Copyright (c) 2024 Afrioni Roma Rio, Berton Maruli Siahaan, Ernawatil Gani