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Journal : Empiricism Journal

Identifikasi Karakter Biodisel Minyak Jelantah Menggunakan Instrumen Gas Cromatografi Mass Spectroscopy (GC-MS) Gargazi, Gargazi; Hendrawani, Hendrawani; Hulyadi, Hulyadi
Empiricism Journal Vol. 3 No. 2: December 2022
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/ej.v3i2.1083

Abstract

Tujuan penelitian ini adalah mengidentifikasi dan karakterisasi biodiesel dari miyak jelantah. Penelitian ini merupakan penelitian deskriftif kualitatif. Variabel yang diamati dalam penelitian ini antara lain senyawa kimia dan struktur molekul penyusun biodiesel dari minyak jelantah. Penentuan senyawa-seyawa kimia serta struktur molekul penyusun biodiesel dari minyak jelantah diukur menggunakan instrument GC-MS. Hasil pengukuran selanjutnya dijadikan dasar dalam mengidentifikasi krakter biodiesel. Komponen tertinggi berupa senyawa asam lemak. Asam lemak berupa asam oktadekanoat  dengan % area 45,10, selanjutnya metil ester heksadekanoat dengan % area 35,99%.  Komponen ketiga dengan jumlah tertinggi berupa senyawa metil ester oktadekanoat dengan % area 9,42.  Komponen keempat berupa metil ester tetradekanoat dengan % area 3,43. Metil ester C16 masih rendah yaitu sebesar 35,99%. Karakter biodiesel dari minyak jelahtah masih banyak mengandung asam lemak bebas golongan oktadekanoat dan konsenterasi C16 yang menjadi dasar kemudahan biodiesel untuk terbakar masih rendah. Identification of Characteristics of Used Cooking Oil Biodiesel Using Gas Chromatography Mass Spectroscopy (GC-MS) Instruments Abstract The purpose of this study is to identify and characterize biodiesel from used cooking noodles. This research is a qualitative descriptive research. The variables observed in this study include chemical compounds and the molecular structure of biodiesel constituents from used cooking oil. The determination of chemical compounds and the molecular structure of biodiesel constituents of used cooking oil was measured using the GC-MS instrument. The results of the next measurement are used as a basis in identifying biodiesel krakters. The highest component is in the form of fatty acid compounds. Fatty acids are octadecanoic acid with a % area of 45.10, then methyl hexadecanoic ester with a % area of 35.99%. The third component with the highest amount is the octachonate methyl ester compound with a % area of 9.42. The fourth component is methyl ester tetradecanoate with % area 3.43. Methyl ester C16 is still low at 35.99%. The character of biodiesel from used cooking oil still contains a lot of free fatty acids of the octadecanoic group and C16 concentration, which is the basis for the ease of biodiesel to burn is still low.
Analysis of the Role of Algorithms in the Analysis of Organic Molecular Structures: A Study of Formal Charges and Their Reactivity Muhali, Muhali; Hulyadi, Hulyadi; Gargazi, Gargazi; Azmi, Irham; Bayani, Faizul
Empiricism Journal Vol. 6 No. 4: December 2025
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/q58j9193

Abstract

This study aims to identify students' competency in understanding the formal charge and reactivity of organic molecules through algorithm-based learning and mathematical formulations. A quasi-experimental pretest–posttest design was used with Chemistry Education students who had taken the topic of chemical bonding and Lewis structures. Essay and multiple-choice tests were used to measure the accuracy of Lewis structures, formal charge calculations, charge symbol interpretation, and reactivity predictions. The pretest results showed an average student score of 32.4, while the posttest score increased to 74.1, with an N-gain of 0.62 (moderate–high category). Students showed significant improvement in identifying reactivity centers (electrophilic/nucleophilic) and linking charge distribution to structural stability. The application of algorithms also strengthened their ability to visualize electronic structures, particularly in the context of sp3and sp3 hybridization. Computational chemistry simulations helped students develop stronger symbolic and predictive representations of chemical reactions. This study concludes that the integration of algorithms and symbolic approaches in learning effectively improves students' conceptual and computational literacy in organic chemistry.