Claim Missing Document
Check
Articles

Found 3 Documents
Search

The Effect of Comparison of Soybeans and Coconut Water on Bio-Battery Electrical Power Valensia, Valensia; Sadiyyah, Fitriani Halimatus; Hibatulloh, Miussa Rio; Setiadi, Dwi Putra; Nandiyanto, Asep Bayu Dani; Anggraeni, Sri; Kurniawan, Tedi
Indonesian Journal of Multidiciplinary Research Vol 1, No 1 (2021): IJOMR: VOLUME 1, ISSUE 1, 2021
Publisher : Universitas Pendidikan Indonesia (UPI)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1203.091 KB) | DOI: 10.17509/ijomr.v1i1.33668

Abstract

The world is currently facing an energy crisis. This research was conducted to create alternative energy by utilizing abundant biomass in nature. The novelty of this study: (1) Use of soybean biomass with coconut water as an electrolyte paste, (2) Testing of bio-battery resistance to wall clocks, and (3) Comparison of the composition of the two materials. In this study, an electrolyte paste made from soybeans (SBs) and coconut water (CWs) with a ratio of 7/1, 6/2, 5/3, 4/4, 3/5, 2/6, and 1/7. To support the analysis, an electrical voltage test and a battery resistance test for wall clocks were carried out.  The experimental results show that the composition of coconut water increases the value of the electric voltage on the bio-battery. The composition of coconut water serves to activate the ions in the paste. Meanwhile, more soybean content will increase bio-battery life. It was found that the bio-battery with electrolyte paste of soybeans and coconut water can be used as alternative energy. The results of this research are expected to offer renewable alternative energy for world energy security.
Ciherang Stunting Corner: A step to reduce the prevalence of stunting Putra, Rio Mahesa; Sadiyyah, Fitriani Halimatus
Dedicated: Journal of Community Services (Pengabdian kepada Masyarakat) Vol 1, No 2 (2023): Dedicated: Journal of Community Services (Pengabdian kepada Masyarakat), Decembe
Publisher : Universitas Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17509/dedicated.v1i2.62468

Abstract

Stunting is a serious global public health challenge and a major concern in Indonesia. Stunting refers to impaired child growth, primarily caused by nutritional deficiencies during early development. Data from the Ministry of Health of the Republic of Indonesia indicates that the prevalence of stunting in children in 2023 reached 21,6%, highlighting malnutrition in children as an urgent issue. Various approaches have been undertaken to address this problem, including the Ciherang Stunting Corner, which is the focus in the Ciherang Village, West Java. The method used in this study is quantitative, with a survey approach and data collection. This program emphasizes a community-based and holistic approach to stunting prevention. By involving the community in planning and implementing nutritional interventions, the program can provide solutions tailored to local needs while addressing sanitation and environmental aspects. Initial results show increased community awareness of nutrition and participation in child growth monitoring. Furthermore, the Community Service Learning (KKN) approach has helped to raise awareness about nutrition issues and gather crucial data to support stunting prevention efforts. Integrating the Ciherang Stunting Corner model with a significant reduction in stunting rates is a strategic step in addressing this issue in Indonesia, offering hope for a brighter future for the nation's next generation.
PENENTUAN LINTASAN OPTIMAL DISTRIBUSI BARANG MENGGUNAKAN HYPERGRAPH - PARTITIONING DAN ALGORITMA GENETIKA Sadiyyah, Fitriani Halimatus; Yulianti, Kartika; Sispiyati, Ririn
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 16 No 2 (2024): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2024.16.2.13545

Abstract

Efficient distribution of goods is critical in logistics management, which requires the selection of optimal distribution paths to achieve delivery targets with minimal total distance. This research combines Hypergraph-Partitioning and genetic algorithm to determine the optimal distribution path of goods to several customers. The Hypergraph-Partitioning divides the goods to be distributed equally to several vehicles, while the genetic algorithm is applied to determine the best distribution path in each partition. The results showed that the Hypergraph-Partitioning method successfully divided 62 customers into two partitions. The first partition serves 31 customers with a total demand of 865 loaves of bread, while the second partition also serves 31 customers with a total demand of 1,035 loaves of bread. The genetic algorithm was then used to find the shortest path for each partition, resulting in an efficient distribution solution.