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All Journal ALCHEMY Jurnal Penelitian Kimia Jurnal Serambi Engineering Jurnal Vokasi WISDOM : Jurnal Pengabdian Kepada Masyarakat Wisdom
Muhammad Muhammad
Universitas Serambi Mekkah
Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Economics, Econometrics & Finance Education Energy Engineering Environmental Science Materials Science & Nanotechnology Social Sciences Other

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Journal : Jurnal Serambi Engineering

 1 
Potensi Pemanfaatan Gas Karbon Dioksida (CO2) sebagai Density Agent untuk Larutan Pemisah Cangkang dan Kernel Sawit Muhammad Muhammad; Marwan Marwan; Muhammad Zaki; Edi Munawar
Jurnal Serambi Engineering Vol 7, No 1 (2022): Januari 2022
Publisher : Fakultas Teknik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jse.v7i1.3883

Abstract

In order to achieve the national target of decarbonization by 2030, Palm oil mills (POM) can contribute to reducing CO2 emissions generated from their production activities. The CO2 emitted from POM is currently discharged into the environment without further treatment. As a result, the amount of CO2 in the atmosphere will rise, increasing global warming. This study proposes an approach of utilizing CO2 as a density agent in separation fluid formulation. The formulated fluid is then used to separate palm shells and kernels in the claybath. The solubility of CO2 in water occurs physically and is dependent on temperature and partial CO2 gas in the air. Monoethanolamine (MEA) was used as an absorbent to ensure the full interaction of CO2 with water. The chemisorption method is selected to dissolution CO2 into aqueous MEA. The mass ratios of MEA were varied by 10, 20, 30, 40, 50 % w/w. The achieved appropriate densities of formulated fluid were 1,11, 1,14, dan 1,17 g/cm3 at mass ratios of MEA:H2O is 30, 40, dan 50% w/w, respectively. All achieved densities fall between palm shells and kernels densities. Furthermore, the formulated fluid can be used as separation fluid in claybath for separating palm shells and kernels. In addition to the proposed idea of utilizing CO2  and, at the same time, reducing CO2 emission from POM.
Klasifikasi Citra Songket Aceh Menggunakan Metode Probabilistic Neural Network Ismi Amalia; Indra Mawardi; Indrawati Indrawati; Muhammad Arhami; Muhammad Muhammad; Guntur Syahputra
Jurnal Serambi Engineering Vol 8, No 3 (2023): Juli 2023
Publisher : Fakultas Teknik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jse.v8i3.6132

Abstract

Tujuan penelitian ini untuk mengklasifikasikan citra Songket Aceh. Data penelitian menggunakan sepuluh motif Songket Aceh dan data diperoleh dari tempat usaha tenun Songket Nyak Mu. Tahapan penelitian ini adalah akuisisi citra, pra-proses, ekstraksi fitur, klasifikasi dan evaluasi. Ekstraksi fitur tekstur citra Songket Aceh menggunakan metode Gray Level Co-occurrence Matrix (GLCM). Fitur-fitur yang digunakan pada penelitian ini adalah entropy, energy, sum of squares: variance, difference entropy dan autocorrelation. Metode Probabilistic Neural Network (PNN) diaplikasikan untuk klasifikasi citra Songket Aceh. Metode Leave-One-Out Cross Validation (LOOCV) digunakan untuk pembagian data latih dan data uji. Hasil klasifikasi citra Songket Aceh dengan metode PNN adalah sebesar 93%.
Modifikasi Serat Kenaf (Hibiscus cannabinus L.) Menggunakan Anhidrida Propionat Eka Marya Mistar; Muhammad Muhammad
Jurnal Serambi Engineering Vol 8, No 4 (2023): Oktober 2023
Publisher : Fakultas Teknik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jse.v8i4.6687

Abstract

Kenaf is a local crop that has great potential as a polymer composite reinforcement. However, the main weakness in strengthening composites using kenaf fiber is its hydrophilic or water-absorbing properties. To improve composite properties, surface modification of kenaf fiber is needed to enhance the structure and chemical properties of kenaf fiber. This study aims to explore the potential of chemical modification of kenaf fiber for use in composites. Chemical modification treatment of kenaf fibers was intended to improve the hydrophobicity that the compatibility between the fiber and matrix bonds are enhanced. In this study, chemical modification of kenaf fiber was performed using propionic anhydride. The modification process was done through a three-variation of retention time; 100, 200, 300 minutes at 100 C. This research also compared the kenaf fiber properties with and without the modification process, including the analysis of the weight percent gain and surface morphological structure. The results showed that the optimal weight gain and morphological structure was at a retention time of 200 minutes.
Klasifikasi Citra Songket Aceh Menggunakan Metode Probabilistic Neural Network Ismi Amalia; Indra Mawardi; Indrawati Indrawati; Muhammad Arhami; Muhammad Muhammad; Guntur Syahputra
Jurnal Serambi Engineering Vol 8, No 3 (2023): Juli 2023
Publisher : Fakultas Teknik

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jse.v8i3.6132

Abstract

Tujuan penelitian ini untuk mengklasifikasikan citra Songket Aceh. Data penelitian menggunakan sepuluh motif Songket Aceh dan data diperoleh dari tempat usaha tenun Songket Nyak Mu. Tahapan penelitian ini adalah akuisisi citra, pra-proses, ekstraksi fitur, klasifikasi dan evaluasi. Ekstraksi fitur tekstur citra Songket Aceh menggunakan metode Gray Level Co-occurrence Matrix (GLCM). Fitur-fitur yang digunakan pada penelitian ini adalah entropy, energy, sum of squares: variance, difference entropy dan autocorrelation. Metode Probabilistic Neural Network (PNN) diaplikasikan untuk klasifikasi citra Songket Aceh. Metode Leave-One-Out Cross Validation (LOOCV) digunakan untuk pembagian data latih dan data uji. Hasil klasifikasi citra Songket Aceh dengan metode PNN adalah sebesar 93%.
Co-Authors aljufri aljufri, aljufri Amalia, Ismi Arhami, Muhammad Edi Munawar Eka Marya Mistar Eka Marya Mistar Faisal Faisal Guntur Syahputra Haiyum, Muhd Hanif Hanif Ida Hasmita Indra Mawardi Indrawati Marwan Marwan Muhammad Zaki Nadia Putri Mauliza Nurdin Nurdin