Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal ASEAN Journal of Chemical Engineering Jurnal Riset Rumpun Matematika dan Ilmu Pengetahuan Alam (JURRIMIPA)
Sahiba Sahila
Unknown Affiliation
Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Mathematics

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
The Effect of Reaction Time and Temperature on the Synthesis of Methyl Ester Sulfonate Surfactant from Palm Oil as a Feedstock using Microwave-Assisted Heating Lailatul Qadariyah; Sahiba Sahila; Mahfud Mahfud
ASEAN Journal of Chemical Engineering Vol 21, No 1 (2021)
Publisher : Department of Chemical Engineering, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ajche.63786

Abstract

Methyl ester sulfonate is an anionic surfactant that can be synthesized from palm oil as a raw material with the addition of sodium bisulfite and calcium oxide catalyst through transesterification and sulfonation process using microwave-assisted heating. The effect of microwave-assisted heating in the transesterification-sulfonation process was investigated in this study. The transesterification process was carried out using a microwave power of 300 watts for 10 minutes with an addition of a KOH catalyst of 1%. The transesterification process gave a result of palm oil methyl ester with a yield of up to 98% and density of 0.8546 gr/ml, and kinematic viscosity of 3.19 cSt. The sulfonation process is carried out using palm oil methyl ester and sodium bisulfite with a mole ratio of 1:3 and calcium oxide catalyst of 1.5% with the microwave power of 300 watts while varying the sulfonation time and temperature. The physicochemical properties of methyl ester sulfonate were analyzed, and the sulfonate group was characterized using FTIR. The optimum condition gave a yield of up to 98.68%, the density of 0.8657 gr/ml, viscosity of 3.75 cSt, pH of 2.12, and surface tension of up to 27.34 dyne/cm at a temperature of 100oC and sulfonation time of 40 minutes.
K-Means Clustering to Classify Indonesian Provinces Based on School Participation and Socio-Economic Indicators Nilam Novita Sari; Khaola Rachma Adzima; Sahiba Sahila; Tiara Husnul Khotimah
JURNAL RISET RUMPUN MATEMATIKA DAN ILMU PENGETAHUAN ALAM Vol. 4 No. 2 (2025): Agustus: Jurnal Riset Rumpun Matematika dan Ilmu Pengetahuan Alam
Publisher : Pusat riset dan Inovasi Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55606/jurrimipa.v4i2.6657

Abstract

Education serves as a fundamental pillar in national development, as it not only enhances individual capacities but also improves overall social welfare. Despite this crucial role, Indonesia continues to face disparities in both access to and quality of education among its regions, as can be seen from variations in school participation indicators and socio-economic backgrounds. To analyze these differences, this study applied the K-Means Clustering method to categorize provinces in Indonesia using six variables: School Participation Rate, Net Enrollment Rate, Gross Enrollment Rate, Poverty Rate, High School Ratio, and Teacher Ratio. To identify the most suitable number of clusters, three validation indices were utilized, namely Dunn Index, C-Index, and Davies-Bouldin Index, with cluster counts tested from three to six. The results indicated that the best clustering solution was five clusters, as reflected in the highest Dunn Index (0.1569), lowest C-Index (0.0321), and lowest Davies-Bouldin Index (0.5062). The robustness of this clustering was further supported by the ratio between within-cluster and between-cluster standard deviation (S(w)/S(b) = 0.33). Each cluster revealed unique characteristics of education and socio-economic conditions, where Cluster 4 displayed the most favorable outcomes with high participation and low poverty levels, whereas Cluster 5 highlighted the weakest performance across all observed indicators.
Co-Authors Adzima, Khaola Rachma Lailatul Qadariyah Mahfud Mahfud Nilam Novita Sari Tiara Husnul Khotimah