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All Journal Jurnal Akuakultur Indonesia Jurnal Ekonomi : Journal of Economic Jurnal Kesehatan Masyarakat Jurnal English Education: Jurnal Tadris Bahasa Inggris Jurnal Ilmu-Ilmu Peternakan (Indonesian Journal of Animal Science) SITEKIN: Jurnal Sains, Teknologi dan Industri Geo-Image Journal Journal of Livestock Science and Production DIDAKTIKA TAUHIDI: JURNAL PENDIDIKAN GURU SEKOLAH DASAR JURNAL PENDIDIKAN TAMBUSAI PROMOTOR Jurnal Sosial Humaniora Jurnal FARMAKU (Farmasi Muhammadiyah Kuningan) JISKa (Jurnal Informatika Sunan Kalijaga) Jurnal 'Aisyiyah Medika Jurnal Ners Jurnal Statistika dan Aplikasinya AKMENIKA Jurnal Pendidikan, Sains, Geologi, dan Geofisika (GeoScienceEd Journal) Jurnal Biosense Jurnal Keperawatan GSH Jurnal Nasional Manajemen Pemasaran dan SDM Journal of Soft Computing Exploration GANESHA: Jurnal Pengabdian Masyarakat Jurnal Media Informatika Journal Peqguruang: Conference Series Journal of Language and Health Journal of Aafiyah Health Research (JAHR) Edusoshum: Jurnal Pendidikan Islam dan Sosial Humaniora JRKN JEER (Journal of Elementary Educational Research) Berita Kedokteran Masyarakat Tsaqofah: Jurnal Penelitian Guru Indonesia Asian Journal of Healthcare Analytics Jurnal Pengabdian Masyarakat Ekonomi, Manajemen dan Akuntansi (JPMEMA) Naradidik: Journal of Education & Pedagogy Journal of Information System Exploration and Research ALENA : Journal of Elementary Education JIM: Jurnal Ilmiah Mahasiswa Pendidikan Sejarah Educandumedia: Jurnal Ilmu Pendidikan dan Kependidikan Jurnal Tumbuhan Obat Indonesia The Indonesian Journal of Computer Science Journal of Fundamental Management (JFM) Jurnal Media Informasi Teknologi
Putri Utami, Putri
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Predicting Olympic Medal Trends for Southeast Asian Countries Using the Facebook Prophet Model Qohar, Bagus Al; Tanga , Yulizchia Malica Pinkan; Utami, Putri; Ningsih, Maylinna Rahayu; Muslim, Much Aziz
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 10 No. 1 (2025): January 2025
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2025.10.1.16-32

Abstract

The Olympics is a world sporting event held every four years and is a meeting place for all athletes worldwide. The Olympics are held alternately in different countries. The Olympics were first held in Athens in 1896 and have now reached the 33rd Olympics, which will be held in Paris in 2024. Much work has been done to develop prediction models emphasizing improving accuracy to predict Olympic outcomes. However, low-performance regression algorithms are the main problems with prediction. By integrating custom seasonality with the Facebook-Prophet prediction model, this study aims to increase the accuracy of Olympic prediction. The proposed new model involves several steps, including preparing the data and initializing and fitting the Facebook-Prophet model with several parameters such as seasonal mode, annual seasonality, and prior scale. The model is tested using the Olympic dataset (1994–2024). The evaluation results show that this prediction model can provide a good value in predicting the total medals earned. On the Olympic Games (1994-2024) dataset, the model has a very low error MAE, MSE, and RMSE and has an R2 score of 0.99, which is close to perfect. This research shows that the model is effective in improving prediction accuracy.
Ekstrak Akar Purwoceng sebagai neuroprotektan Terhadap Model Stroke pada Tikus: Memori Spasial, Jumlah Sel Piramidal, Ekspresi SOD1 dan SOD2 Munawaroh, Fauziyatul; Efiyanti, Christy; Utami, Putri; Dewi, Trisni; Batubara, Irmanida
Jurnal Tumbuhan Obat Indonesia Vol. 17 No. 2 (2024): December 2024
Publisher : Universitas Tidar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31002/jtoi.v17i2.2236

Abstract

Stroke due to cerebral ischemia is one of the leading causes of disability worldwide. Animal models of cerebral ischemia that is often used is Global Cerebral Ischemia (GCI). In GCI, the hippocampus is the most susceptible to neuronal cell death. Complications that occur after ischemia are due to increased oxidative stress. Some compounds in purwoceng are reported to have antioxidant activity which oxidative stress have not been studied in the GCI model stroke. This study aims to examine the effect of purwoceng extract on a stroke model (GCI) as a neuroprotective agent in the prevention of stroke complications that have not been previously studied. 25 rats with a stroke model were given purwoceng root extract with 3 doses (20, 30, and 40mg/kg BW) orally for three days. The mice were then tested for memory with the Morriz Water Maze (MWM) test; then histopathological analysis of pyramidal cells in the hippocampus and the expression of SOD1 and SOD2 genes was analyzed using RT-PCR. The MWM test showed that the memory results at the dose of 20mg/kg BW were better than that of the GCI group (p=0.0384), and the PCR of SOD2 showed improvement at the dose of 20mg/kg BW (p=0.0171). No significant difference in histopathological analysis and SOD1 mRNA expression across group. The administration of purwoceng root extract at a dose of 20 mg/kg BW had the effect of improving memory and SOD2 expression in GCI model rats
Health Status of Spiny Lobster Panulirus homarus with Sub-Mersible Net Cage System in the Different Depths at Kepulauan Seribu, DKI Jakarta Wahjuningrum, Dinamella; Effendi, Irzal; Hadiroseyani, Yani; Budiardi, Tatag; Diatin, Iis; Setiawati, Mia; Puji Hastuti, Yuni; Oman Sudrajat, Agus; Yonvitner; Sri Nuryati; Utami, Putri
Jurnal Akuakultur Indonesia Vol. 21 No. 1 (2022): Jurnal Akuakultur Indonesia
Publisher : Indonesian Society of Scientific Aquaculture (ISSA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.19027/jai.21.1.68-80

Abstract

ABSTRACT Cultivation of Panulirus homarus lobster is now carried out with sub-mersible net cage system at a certain depth in order to obtain optimal temperature, light and water pressure. The purpose of this study was to evaluate the health status of the sand lobster P. homarus which was kept in sub-mersible net cage system measuring 250 cm × 272 cm × 135 cm with a depth of 6 m and 8 m in the waters of Semak Daun Island, Seribu Islands, DKI Jakarta. The average size of lobster seeds used was 93.23 ± 0.99 g/head with a density of 4 lobsters/m2. Lobsters were fed trash fish, molluscs and crustaceans, with a frequency of twice a day at 07.00 WIB 30% and 17.00 WIB 70% of the lobster biomass weight. This study used a completely randomized design with the two depth treatments mentioned above and three replications. Observations of total haemocyte count, differential haemocyte count, phenoloxidase activity, respiratory burst phagocytic activity and histology of lobster hepatopancreas were performed twice every 14 days. Based on the above observations, the depth does not affect the immune response, there is no visible damage to the cells and tissues of the lobster hepatopancreas. Keywords: haemolymph, histology, lobster cultivation, sea, sub-mersible net cage system
Vehicle CO2 Emission Predictive Analytics Using HistGradientBoosting Regression Algorithms Al Qohar, Bagus; Dullah, Ahmad Ubai; Utami, Putri; Unjung, Jumanto
Jurnal Media Informasi Teknologi Vol. 2 No. 1 (2025): Februari 2025
Publisher : Digital Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69616/mit.v2i1.198

Abstract

Vehicle CO2 emissions are a significant contributor to climate change, so research on this subject is needed. Strong prediction models and data analysis techniques are required to obtain accurate results. This research aims to analyze and predict vehicle CO2 emissions using machine learning algorithms. Given its efficiency in handling large datasets, the HistGradientBoosting Regression algorithm was selected for predicting vehicle CO2 emissions. The process commenced with meticulous data preparation, which involved cleaning and feature engineering. Key factors such as engine size, fuel economy, and vehicle weight were analyzed to gain insights into their impact on emissions. The study utilized a dataset comprising vehicle specifications and emissions, training and testing the HistGradientBoosting. The model's performance was evaluated using metrics like Mean Absolute Error (MAE),  Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and the Coefficient of Determination (R²). The findings indicate that this approach effectively identifies significant factors influencing emissions while achieving impressive prediction accuracy. This research offers valuable insights for policymakers and manufacturers aiming to develop low-emission vehicles and promote sustainable transportation initiatives. The paper highlights the capability of machine learning to address environmental challenges.
Pengembangan Sistem Informasi Kesesuaian Lahan Tanaman Pangan Berdasarkan Faktor Cuaca Berbasis Website Utami, Putri; Abdullah, Asrul; Hudjimartsu, Sahid Agustian; Wicaksono, Aditya; Viona, Tiara Aurilia
The Indonesian Journal of Computer Science Vol. 13 No. 1 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i1.3758

Abstract

Evaluasi lahan dapat dilakukan untuk meningkatkan kualitas dan kuantitas komoditas pertanian. Salah satunya dengan persyaratan penggunaan lahan dengan mempertimbangkan karakteristik lahan. Namun, Dinas Pertanian selaku koordinator sulit mendapatkan informasi terkait karakteristik lahan yang sesuai dengan jenis tanaman berdasarkan faktor cuaca. Anomali cuaca menyebabkan turunnya produktitivitas tanaman. Tujuan penelitian ini adalah mengembangkan sistem informasi kesesuaian lahan untuk menentukan jenis tanaman pangan beradasarkan karakteristik lahan serta evaluasi kesesuaian lahan tanaman. Metode dalam penelitian ini adalah Framework for the Application of System Thinking (FAST). Tahapan FAST yaitu scope definition, problem analysis, requirement analysis, decision analysis, design, contruction and testing, dan instalation and delivery. Berdasarkan hasil uji kelayakan aplikasi menghasilkan nilai 87% dengan kriteria baik. Hasil ini menunjukkan bahwa sistem informasi kesesuaian lahan tanaman pangan dapat digunakan dengan baik.
Rasionalitas Ketercapaian Swasembada Daging 2026 Berdasarkan Analisis Tren dan Peramalan Produksi Daging Sapi-Kerbau Berbasis Data Badan Pusat Statistik Syamsi, Afduha Nurus; Kusrianty, Nelly; Sahiman, Kunta Adnan; Ardilla, Yohana Nanita Nansy; Pinandita, Egi Pur; Utami, Putri
Journal of Livestock Science and Production Vol 9, No 1 (2025): Journal of Livestock Science and Production
Publisher : Universitas Tidar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31002/jalspro.v9i1.9186

Abstract

Indonesia masih perlu meningkatkan produksi daging merah dalam negeri minimal 30% dari kondisi saat ini (60%) untuk mencapai Swasembada Daging Sapi-Kerbau pada Tahun 2026. Data produksi dan konsumsi daging per wilayah dan nasional setiap tahunnya, tersedia pada website Badan Pusat Statistik Republik Indonesia (BPS RI). Data tersebut dapat digunakan untuk meramalkan konsumsi dan produksi daging merah hingga Tahun 2026. Artikel bertujuan untuk mengkaji rasionalitas ketercapaian Swasembada Daging Sapi berdasarkan pada data yang tersedia pada website BPS RI (www.bps.go.id). Data konsumsi daging, produksi daging, dan populasi ternak dianalisis dengan analisis tren dan peramalan forcasting sederhana menggunakan Microsoft excel, sedangkan untuk data lainnya disitasi dari berbagai sumber ilmiah dan dijabarkan secara deskriptif. Konsumsi daging merah Tahun 2026 diramalkan mencapai 2,76 Kg/Kapita/Tahun dengan agregat pertumbuhan (2023-2026) sebesar 2,33%/Tahun. Populasi sapi dan kerbau Tahun 2026 diramalkan sebanyak 22.042.784ekor, dengan agregat pertumbuhan (2023-2026) sebesar 1,99%/Tahun. Produksi daging merah Tahun 2026 diramalkan sebanyak 512.087,72ton, dengan agregat pertumbuhan sebesar 0,95%/Tahun. Produksi dibandingkan dengan proyeksi jumlah konsumsi daging merah Tahun 2026 masih akan mengalami devisit hingga 280.627.667,2ton. Kajian menyimpulkan bahwa pencapaian swasembada daging merah (Sapi dan Kerbau) Tahun 2026 belum rasional, ditilik dari data yang dirilis oleh BPS. Pemerintah perlu memastikan data yang sinkron antar lembaga dan juga mengoptimalisasi program peningkatan populasi dan produksi daging melalui integrasi pengembangan balai inseminasi buatan, inseminator, dan peternak, juga mengontrol pemotongan ternak di RPH, distribusi, dan harga daging dipasaran.  
Fostering a Class Positive Environment in Elementary Schools Using Positive Discipline Approach Utami, Putri; Maryanto; Atim Rinawati; Muhyidin; Umi Arifah; Imam Subarkah; Siti Fatimah
Jurnal Pendidikan, Sains, Geologi, dan Geofisika (GeoScienceEd Journal) Vol. 6 No. 2 (2025): May
Publisher : Mataram University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/goescienceed.v6i2.717

Abstract

A conducive learning environment impacts children's development. Schools, as educational institutions, play a crucial role in creating a supportive and child-friendly learning environment. The objective of this study is to analyze the implementation of a positive discipline approach in efforts to establish a conducive learning environment for elementary school students. This research employs a qualitative phenomenological approach. The study was conducted at Jemur Public Elementary School in Kebumen. The subjects of this study include the school principal, teachers, and students. Data collection techniques involve interviews, observations, and documentation studies. Triangulation techniques were used to ensure data validity. Data analysis was carried out using the Miles & Huberman & Saldana model. The results of the study indicate that the positive discipline approach has been implemented effectively at Jemur Public Elementary School in Kebumen. However, collaboration between parents and the school needs to be further enhanced to ensure children can learn comfortably wherever they are. Strong collaboration among schools, families, and the community is recommended based on this research.
Pengaruh Penempatan Kerja terhadap Kinerja Pegawai Pada Kantor Camat Megang Sakti Kabupaten Musi Rawas Utami, Putri; Purnamasari, Endah Dewi; Handayani, Susi
Jurnal Nasional Manajemen Pemasaran dan SDM Vol. 4 No. 1 (2023): Jurnal Nasional Manajemen Pemasaran dan SDM
Publisher : Training & Research Institute - Jeramba Ilmu Sukses

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47747/jnmpsdm.v4i1.1135

Abstract

This study aims to evaluate the effect of job placement on employee performance at the Megang Sakti District Office, Musi Rawas Regency. This study uses a quantitative approach research method with a sample of 37 employees at the Megang Sakti District Office, Musi Rawas Regency. Based on the results of the study, it can be concluded that work placement does not have a significant effect on employee performance, job placement perceived by the employees of the Megang Sakti District Office, Musi Rawas Regency is considered high. The magnitude of the effect of work placement on the performance of the Megang Sakti District Office employees, Musi Rawas Regency is 4.8%. This shows that work placement has a low influence on employee performance. This research is expected to be an additional consideration to improve employee performance
Efektivitas Gerak Lokomotor Melalui Metode Bermain Di Sdn 107399 Bandar Khalipa Suyono, Suyono; Rahmadani, Aulia; Hasanah, Nurul; Utami, Putri
Jurnal Media Informatika Vol. 5 No. 2 (2024): Jurnal Media Informatika
Publisher : Jurnal Media Informatika

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

Abstract

Pendidikan jasmani pada tahap anak usia dini diarahkan untuk merangsang pertumbuhan organik, motorik, intelektual dan perkembangan emosional mempunyai peran berkarakter. Salah satu perkembangan yang harusnya diterapkan pada anak usia dini atau sekolah dasar ialah motorik kasar. Salah satu alternatif pembelajaran pendidikan jasmani ialah dengan menggunakan metode bermain. Metode ini membahas tentang aktivitas jasmani anak yang dilakukan dengan rasa senang serta kaitannya metode bermain sebagai wahana rasa senang serta wahana pencapaian tujuan pembelajaran. Penelitian ini menggunakan metode kualitatif yang dipadukan dengan metode deskriptif. Teknik pengumpulan data yang digunakan yaitu data primer dengan cara wawancara dan observasi. Sedangkan data sekunder diperoleh dari studi kepustakaan. Hasil penelitian ini mengungkapkan bahwa metode bermain dalam pendidikan olahraga sudah pasti diterapkan dalam pembelajaran penjas. Penerapan metode bermain dalam pendidikan jasmani dan olahraga  jika tidak digunakan akan membuat pembelajaran susah dimengerti dikarenakan pembelajaran penjas sendiri lebih banyak menggunakan praktek. Metode bermain ini sangat berpengaruh dalam meningkatkan gerak lokomotor siswa sekolah dasar. Metode bermain yang diterapkankan dapat menambah minat peserta didiknya untuk mengikuti mata pelajaran pendidikan jasmani dan olahraga.
Optimasi Model Algoritma Machine Learning Suppervised menggunakan Algoritma Genetika untuk Prediksi Kebakaran Hutan dan Lahan Utami, Putri; Sucipto; Risli , Andrea; Aurilia Viona, Tiara
The Indonesian Journal of Computer Science Vol. 14 No. 2 (2025): The Indonesian Journal of Computer Science
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v14i2.4395

Abstract

Forest and land fires are a common occurrence in Indonesia, particularly in the provinces of Sumatra and Kalimantan. One strategy for mitigating the impact of forest and land fires is to predict areas that are prone to such incidents. In this study, genetic algorithm (GA) optimization was employed to enhance the efficacy of the random tree and hyper-SVM algorithms, with a view to identifying the most optimal test results. The dataset utilized in this study comprises hotspot data and climate data for Ketapang Regency during the 2021-2022 period. The results of the training and testing demonstrate that the Random Tree +GA algorithm optimization with a PC value of 0.6 and Bolzmann selection parameters yields an accuracy of 99.77%, a recall of 94.88%, a precision of 95%, an RMSE of 0.015, and a Kappa of 0.9. In contrast, the Hyper-SVM +GA optimization, with a PC value of 0.6 and Bolzmann selection parameters, yielded an accuracy of 70.48%, a recall of 52.14%, a precision of 50.58%, an RMSE of 0.493, and a Kappa of 0.026. The results demonstrate that the Random Tree +GA algorithm model optimization exhibits superior performance compared to Hyper-SVM +GA optimization. Consequently, it can be inferred that the Random Tree +GA algorithm represents the most effective classification model for predicting the likelihood of forest and land fires in Ketapang Regency
Co-Authors Aditya Wicaksono Agus Oman Sudrajat Akhiroh, Puji Al Qohar, Bagus Alfindo, Nico Dian Ali Mustadi Ambarwati, Dyah Amelia Putri, Winda Amelia Rika Anah, Sri Ananto Aji, Ananto Andi Asrina Anwar, Muh Apik Budi Santoso Ardilla, Yohana Nanita Nansy Aripa Hasanah , Nur Armawan, Ladyka Viola Asrul Abdullah atim rinawati Aulia Puspita Anugra Yekti Aulia Putri, Devita Aulia, Usna Aurilia Viona, Tiara Bayu , Silvana Budi Hartono Caska - Chotimah, Indira Christina Ismaniati Christy Efiyanti Cicih Ratnasih, Cicih Denny Nurdiansyah Dewi, Trisni Dinamella Wahjuningrum Dullah, Ahmad Ubai Eka Kusumastuti, Anie Eka Yusnaldi Ekawati Ekawati Eko Nugroho Endah Dewi Purnamasari Endang Silaningsih Fadillah Fadillah Fatmah Afrianty Gobel Fatria Harwanto Febrianto, Nanang Hamzah Hasyim Hermanto Hilda Zulkifli Ida Wahyuni Idris, Fairus Prihatin Iis Diatin Imam Subarkah Imas Maesaroh Irmanida Batubara irviana, ira Irzal Effendi Ismail Hasan, Ismail Istiqomah Nur Rahmawati Juhadi Juhadi Jumanto Unjung Jundi, Muhamad Kartini, Alif Yuanita Khairani, Aulia Kurniawan, Egy Kusrianty, Nelly Kusumawati, Tri Indah Lewinsca, Maurend Yayank Marcela, Raya Maryanto Masriana Masriana, Masriana Maulidnawati, Abrina Mia Setiawati Much Aziz Muslim Muhammad Ali, Hendry Muhammad Helmi Muhammad Kaulan Karima Muharramah, Disa Hijratul Muhyidin Muji Burrohman Mujihari, Mujihari Munawaroh, Fauziyatul Mursal Aziz Murti, Wahyu Muslima, Patriotika Nadia Ramli, Nurul Ningsih, Maylinna Rahayu Nita Yunianti Ratnasari Novalinda, Novalinda Novitasari, Prihatini Dini Novitrie, Ayu Nurlinda, SE., MM, R.A Nurlizawati Nurul Hasanah Nurul Isnaini Octaviany, Efi Pertiwi, Dwika Ananda Agustina Pinandita, Egi Pur Prameswari, Ayu Priyo Sugeng Winarto Puji Hastuti, Yuni Puspita Anugra Yekti, Aulia Qohar, Bagus Al Rahmadani, Aulia Rahmaddeni Rahmaddeni Rambe, Riris Nurkholidah Restu Restu Risli , Andrea Risma Handayani Ritonga, Yunizar Rizki Amalia Rizki Wandini, Rora Sahid Agustian Hudjimartsu Sahiman, Kunta Adnan Salbila, Isal Saputra, Yoerdy Agusmal Sibarani, Benly Levi Andreas Sinaga, Leonardo SITI FATIMAH Siti Khodijah Parinduri Sri Nuryati Sucipto Sukmawati Sukmawati Sumiaty Sumiaty Supriadi Supriadi Suprida, Suprida Susi Handayani Suyono Suyono Syah, Habib Asshidiq Syamsi, Afduha Nurus Tanga , Yulizchia Malica Pinkan Tatag Budiardi umi arifah Utami*, Rahayu Dwi Vidya Vitta Adhivinna, Vidya Vitta Viona, Tiara Aurilia Wahjuningsih , Sri Widya Ningsih, Mutiara Wira Wibawa, Herry Y. Hadiroseyani Yonvitner - Yunola, Satra Yusriani, Yusriani