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All Journal Media Statistika Journal of Degraded and Mining Lands Management BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Ecces: Economics, Social, and Development Studies JSMARTech : Journal of Smart Bioprospecting and Technology Jurnal Teknik Informatika (JUTIF) SEMINAR NASIONAL PENELITIAN DAN PENGABDIAN KEPADA MASYARAKAT Journal of Statistics and Data Science
Fernandes, Adji Achmad Rinaldo
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Transportation Other

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PERFORMANCE OF NEURAL NETWORK IN PREDICTING MENTAL HEALTH STATUS OF PATIENTS WITH PULMONARY TUBERCULOSIS: A LONGITUDINAL STUDY Rahmanda, Lalu Ramzy; Fernandes, Adji Achmad Rinaldo; Solimun, Solimun; Ramifidiosa, Lucius; Zamelina, Armando Jacquis Federal
MEDIA STATISTIKA Vol 16, No 2 (2023): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.16.2.124-135

Abstract

Comorbidity between pulmonary tuberculosis and mental health status requires effective psychiatric treatment. This study aims to predict anxiety and depression levels in patients with pulmonary tuberculosis and consider future mental health treatment for patients. A sample of 60 pulmonary tuberculosis patients in Malang were involved and evaluated longitudinally every two weeks over 13 periods. In this study, we use the Generalized Neural Network Mixed Model (GNMM) to obtain better results in predicting anxiety and depression levels in patients with pulmonary tuberculosis and compare the results with the Generalized Linear Mixed Model (GLMM). The flexibility of GLMM in modeling longitudinal data, and the power of neural network in performing a prediction makes GNMM a powerful tool for predicting longitudinal data. The result shows that neural network's prediction performance is better than the classical GLMM with a smaller MSPE and fairly accurate prediction. The MSPEs of the three compared models: 1-Layer GNMM, 2-Layer, and GLMM, respectively are 0.0067, 0.0075, 0.0321 for the anxiety levels, and 0.0071, 0.0002, and 0.0775 for the depression levels. Furthermore, future research needs to investigate the data with a larger sample size or high dimensional data with large network architectures to prove the robustness of GNMM.
Educational Workshop Berbasis HOTS: Upaya Meningkatkan Kualitas Guru SMP dan SMA pada Olimpiade Guru Nasional Fernandes, Adji Achmad Rinaldo; Lusia, Dwi Ayu; Nisa, Hilwin; Hidayatulloh, Moh Zhafran; Rizqia, Anggun Fadhila; Nasywa, Alfiyah Hanun; Putri, Nazwa Anindya; Amirullah, Khoirul Insan
Seminar Nasional Penelitian dan Pengabdian Kepada Masyarakat 2025 Prosiding Seminar Nasional Penelitian dan Pengabdian Kepada Masyarakat (SNPPKM 2025)
Publisher : Universitas Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35960/snppkm.v4i1.1411

Abstract

The National Teacher Olympiad (OGN) is a prestigious event that aims to improve teacher competence, especially in the field of mathematics, through mastery of pedagogy, learning innovation, and the application of Higher Order Thinking Skills (HOTS). However, junior and senior high school teachers in Malang Regency still face obstacles in the form of limited access to training, lack of professional community, and low literacy in learning technology. This service program was carried out at PP & SMA Sumber Putih, Malang Regency, with the aim of strengthening teacher competence through strategies to strengthen positive mindsets, increase motivation, and interactive training based on Higher Order Thinking Skills. The implementation method includes educational workshops, motivational sessions, group discussions, preparation of learning modules, and reflection to measure the effectiveness of the program. The results of the activity showed an increase in teachers' mental readiness in facing the National Teachers' Olympiad, strengthening the understanding of Higher Order Thinking Skills in mathematics learning, and improving technological skills in the learning process. In addition, training modules are arranged as outputs that can be used continuously. This program contributes to improving the professionalism of teachers, encouraging participation in OGN, and building an innovative and competitive education ecosystem in Malang Regency.
Screening potential local seed species for hydroseeding of post-coal mining land multilayering revegetation Anshari, Muhammad Fadhil; Fernandes, Adji Achmad Rinaldo; Leksono, Amin Setyo; Arisoesilaningsih, Endang
Journal of Degraded and Mining Lands Management Vol. 11 No. 1 (2023)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2023.111.4969

Abstract

This study aimed to screen some potential local seed grains for hydroseeding and describe their characteristics based on the literature review and a year of hydroseeding application. This study used six species/variants of Poaceae (Coix lacryma-jobi, Eleusine indica, Setaria italica (brown, black, and red), Sorghum timorense, S. bicolor, Themeda arundinaceae), five species of Leguminosae (Adenanthera pavonina, Cajanus cajan, Sesbania grandiflora, S. sesban, Indigofera sp.), a species of Cyperaceae (Cyperus javanicus), Sapindaceae (Sapindus rarak), Rhamnaceae (Ziziphus jujuba), and Moringaceae (Moringa oleifera). A seed germination test was held using soil media placed in 5 pots per species until 15 days after sowing (DAS). Characters were scored, and data were statistically analyzed. A field record of one-year hydroseeding applied on 6 m x 6 m post-coal mining land plot was presented. Some data such as pH H2O, pH KCl, conductivity, and soil organic carbon among hydroseeding areas, unrevegetated areas, and reference sites were observed. Results showed that there were 13 of 17 species could variably germinate. The fastest germination time was recorded for S. timorense, S. bicolor, red S. italica, C. cajan, and S. grandiflora, while the highest germination rate (≥50%) was black S. italica (80%), brown S. italica (58%) and S. bicolor (50%). The annual black and brown S. italica, S. bicolor, and S. timorense were highly recommended to be used in hydroseeding. The perennial C. cajan, Indigofera sp., S. sesban, and T. arundinaceae were also potential to be added into a hydroseeding slurry to improve pioneer vegetation multilayering structure and diversity.
Co-Authors Achmad Efendi Al Jauhar, Hafizh Syihabuddin Amanda, Devi Veda Amin Setyo Leksono Amirullah, Khoirul Insan Anshari, Muhammad Fadhil Arini, Luthfia Hanun Yuli Atiek Iriany Azizah, Laila Nur Bakar, Normizan bin Endang Arisoesilaningsih Eni Sumarminingsih Fimba, Adfi Bio Hamdan, Rosita Hamdan, Rosita Binti Hidayatulloh, Moh Zhafran Junainto, Fachira Haneinanda Junianto, Fachira Haneinanda Lusia, Dwi Ayu Maisaroh, Ulfah Marchamah, Mamlu’atul Nasywa, Alfiyah Hanun Ni Wayan Surya Wardhani Nisa, Hilwin Nurdin, Muhammad Rafi Hasan Nurjannah Nurjannah Nurjannah Pramaningrum, Dea Saraswati Pratama, Yossy Maynaldi Putri, Henida Ratna Ayu Putri, Nazwa Anindya Rahma Fitriani Rahman R, Abd Rahmanda, Lalu Ramzy Ramadhan, Rangga Ramifidiosa, Lucius Ramifidisoa, Lucius Rejeki, Sasi Wilujeng Sri Rizqia, Anggun Fadhila Rohma, Usriatur Sabir Sabir Solimun Solimun, Solimun Suci Astutik Sumara, Rauzan Ullah, Mohammad Ohid Ullah, Muhammad Ohid Yulianto, Shalsa Amalia Zamelina, Armando Jacquis Federal Zuhdi, Muhammad Rizal