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EFFECT OF SPINNING PARAMETERS ON PLA/PPC/CURCUMIN MICROFIBER DIAMETER: AN INVESTIGATION VIA RESPONSE SURFACE METHODOLOGY
Get PDFThe initial phase of this study was to investigate the effect of polypropylene carbonate (PPC) additions in polylactic acid (PLA)/curcumin (Cur) blends. It was observed that the presence of curcumin particulates behaved as a reinforcement filler for PPC additions up to 30 wt%. A specific composition was then invested to find the correlation between the fiber diameter and melt-spinning process parameters using central composite design (CCD), a subset of response surface methodology (RSM). Results showed that the spinning temperature had a greater effect than the spinning speed on the diameter of PLA/PPC/curcumin fiber. The response model indicated a good correlation between experimental and predicted values since the ANOVA analysis demonstrated high F-value of model adequacy at 10.34, non-significant lack of fit, precision adequacy of 9.94 and R2 value of 0.80. Therefore, this model can be used in a future study to establish the processing parameters for controlled fiber production.
ABSTRAK: Fasa awal kajian ini adalah bagi mengkaji kesan penambahan karbonat polipropilin ke dalam campuran asid prolaktik (PLA)/kurkumin (Cur). Didapati kehadiran zarah-zarah kurkumin bertindak sebagai pengisi bantuan pada penambahan PPC sehingga 30 wt%. Komposisi tertentu kemudian dikaji bagi mencari kaitan diameter fiber dan parameter proses putaran-cair menggunakan rekaan komposit utama (CCD), dan subset metodologi gerak-balas permukaan (RSM). Keputusan menunjukkan suhu putaran berpengaruh besar berbanding kelajuan putaran pada diameter fiber PLA/PPC/kurkumin. Model yang bertindak balas ini menunjukkan kaitan yang baik antara eksperimen dan nilai yang dijangka kerana analisis ANOVA menunjukkan nilai-F yang tinggi pada 10.34 kecukupan model, tidak-ketara kurang padanan, kecukupan ketepatan pada 9.94 dan nilai R2 sebanyak 0.80. Oleh itu, model ini boleh digunakan pada kajian akan datang bagi menghasilkan parameter proses pengeluaran fiber kawalan
STATISTICAL ANALYSIS OF GROWTH CONDITIONS OF NEWLY ISOLATE BACILLUS SP. PRODUCING L-ASPARAGINASE
Get PDFThe concentrations of nutrient elements together with several physical parameters were screened to find out the significant factors for the production of L-asparaginase from newly isolated strain, Bacillus sp. from Sg Klah, Hot Spring, Perak. Then, the significant factors were optimized for enhancing L-asparaginase production from the bacterium strain. Two statistical designs, Two Level Factorial Design and Face Centered Composite Design (FCCD), Design expert @version 8.0 were employed in screening and optimization of the process variables, respectively. The results for all experiment runs were analyzed by analysis of variance (ANOVA). Peptone (nitrogen source) concentration and temperature were found as significant factors, positively influenced the production of L-asparaginase. The two factors were then optimized to increase the desired enzyme production. The optimum peptone concentration and the temperature were found at 1.4 g/L and 30ºC, respectively. The L-asparaginase production under optimized conditions increased from 0.15±0.023 U/mL to 0.19 ± 0.03 U/mL. The kinetic studies showed that the biomass production dropped after 24 hours while L-asparaginase activity is active and positively increased until the fermentation period ended.
ABSTRAK: Kepekatan unsur-unsur nutrien bersama-sama dengan beberapa parameter fizikal telah diteliti untuk mengetahui faktor-faktor penting untuk pengeluaran L-asparaginase dari spesis baru diasingkan, bacillus sp. dari kolam air panas tempatan. Kemudian, faktor penting dioptimumkan untuk meningkatkan pengeluaran L-asparaginase daripada bakteria tersebut. Two Level Factorial Design dan Face Centered Composite Design (FCCD), Design expert @version 8.0 telah digunakan dalam penyaringan dan pengoptimuman pembolehubah proses dalam kajian ini. Keputusan untuk semua eksperimen dianalisis dengan analisis varians (ANOVA). Kepekatan dan suhu peptone (sumber nitrogen) didapati sebagai faktor penting, secara positif mempengaruhi pengeluaran L-asparaginase. Kedua-dua faktor ini dioptimumkan untuk meningkatkan pengeluaran enzim yang dikehendaki. Kepekatan peptone dan suhu optimum didapati masing-masing pada 1.4 g / L dan 30ºC. Pengeluaran L-asparaginase di bawah keadaan yang dioptimumkan meningkat dari 0.15 ± 0.023 U / mL kepada 0.19 ± 0.03 U/mL. Kajian kinetik menunjukkan bahawa pengeluaran biojisim menurun selepas 24 jam manakala aktiviti L-asparaginase aktif dan meningkat secara positif sehingga tempoh penapaian berakhir.
FVS-TECHNOLOGY: INTELLECTUAL SEARCH TOOLS
Get PDFIt is enough to have 3 basic stages of the modules in the SPD of a diversified corporate network: (F) - the method of submitting the request, i.e. the method of forming the expression of the information needs of the system user (S) - the function of the correspondence of the electronic resource to the request degree of compliance with the request and the found electronic resource; (V) - method of presenting electronic resources. Combining these three stages for models, methods, and software modules of the AML, is referred to as FSV technology (FSV platform, FSV Framework). FSV technology is an instrumental software platform based on a client-server architecture, integration and modification of models, and methods and algorithms of AML in the information environment of corporate networks. The following architecture has been developed for the FSV technology proposed for the search index in data retrieval systems.
ABSTRAK: Tiga peringkat asas modul adalah cukup dalam pelbagai rangkaian korporat SPD iaitu: (F) - kaedah penyerahan permintaan, kaedah membentuk ungkapan keperluan maklumat pengguna sistem (S) - fungsi surat-menyurat sumber elektronik bagi permintaan tahap pematuhan permintaan dan sumber elektronik yang dijumpai; (V) - kaedah penyampaian sumber elektronik. Gabungan tiga peringkat model, kaedah dan modul perisian AML, dipanggil teknologi FSV (platform FSV, rangka FSV). Teknologi FSV adalah platform perisian instrumen berdasarkan seni bina pelanggan-pelayan, integrasi dan pengubah suaian model, kaedah-kaedah dan algoritma AML dalam persekitaran maklumat dalam rangkaian korporat. Seni bina ini telah di bina bagi teknologi FSV yang dicadangkan bagi indeks carian dalam sistem dapatan data
PREDICTING TRUST IN A SOCIAL NETWORK BASED ON STRUCTURAL SIMILARITIES USING A MULTI-LAYERED PERCEPTRON NEURAL NETWORK
Get PDFAlthough research on social networks is progressing rapidly, the positive and negative effects of this area should be evaluated. One of the problems is that social networks are very broad and anyone can have influence on them. This matter can cause the issue of people with different beliefs. Therefore, determining the amount of trust to various resources on social networks, and especially resources for which there is no previous history on the web, is one of the main challenges in this field. In this paper, we present a method for predicting trust in a social network by structural similarities through the neural network. In this method, the web of trust data set is converted to a structural similarity data set based on the similarity of the trustors and trustees first. Then, on the created data set, a part of the data set is considered as the training data and it is trained based on the multilayer perceptron neural network and then the trained neural network is tested based on the test data. In the proposed method, the MSE value is less than 0.01, which has improved more than 0.02 compared to previous methods. Based on the obtained results, the proposed method has provided acceptable accuracy.
ABSTRAK: Walaupun kajian tentang rangkaian sosial adalah sangat pesat, kesan positif dan negatif dalam ruang lingkup ini perlu dinilai. Masalah rangkaian sosial adalah sangat luas dan sesiapa sahaja boleh terpengaruh. Perkara ini akan menyebabkan manusia dengan pelbagai isu kepercayaan. Oleh itu, menentukan nilai kepercayaan melalui pelbagai sumber dalam rangkaian sosial, terutama sumber-sumber yang tidak mempunyai sejarah lepas dalam web, adalah salah satu cabaran dalam bidang ini. Kajian ini membentangkan jangkaan kepercayaan dalam rangkaian sosial melalui persamaan struktur dengan menggunakan rangkaian neural. Kaedah ini ditentukan dengan menukar set data web kepercayaan kepada struktur set data hampir sama berdasarkan kesamaan pemegang dan pemberi amanah. Kemudian, sebilangan set data yang telah dibina ini dipertimbangkan sebagai data latihan dan ia dilatih berdasarkan rangkaian neural perseptron berbagai lapisan dan kemudian rangkaian neural yang terlatih ini diuji berdasarkan data ujian. Dalam kaedah yang dicadangkan ini, nilai MSE adalah kurang daripada 0.01, di mana telah diperbaiki kepada 0.02 lebih daripada kaedah-kaedah sebelum ini. Berdasarkan dapatan kajian, didapati kaedah yang dicadangkan ini menunjukkan ketepatan yang boleh diterima
EDITORIAL
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CHIEF EDITOR
Ahmad Faris Ismail, IIUM, Malaysia
TECHNICAL EDITOR
Sany Izan Ihsan, IIUM, Malaysia
EXECUTIVE EDITOR
AHM Zahirul Alam, IIUM, Malaysia
ASSOCIATE EDITOR
Nor Farahidah Za’bah, IIUM, Malaysia
LANGUAGE EDITOR
Lynn Mason, Malaysia
COPY EDITOR
Hamzah Mohd. Salleh, IIUM, Malaysia
EDITORIAL BOARD MEMBERS
Abdullah Al-Mamun, IIUM, Malaysia
Abdumalik Rakhimov, IIUM, Malaysia
Ali Sophian, IIUM, Malaysia
Erwin Sulaeman, IIUM, Malaysia
Hanafy Omar, Saudi Arabia
Hazleen Anuar, IIUM, Malaysia
Konstantin Khanin, University of Toronto, Canada
Ma'an Al-Khatib, IIUM, Malaysia
Md Zahangir Alam, IIUM, Malaysia
Meftah Hrairi, IIUM, Malaysia
Mohamed B. Trabia, United States
Mohammad S. Alam, Texas A&M University-Kingsville, United States
Mustafizur Rahman, National University Singapore, Singapore
Ossama Abdulkhalik, Michigan Technological University, United States
Othman O Khalifa, IIUM, Malaysia
Razi Nalim, IUPUI, Indianapolis, Indiana, United States
Rosminazuin AB. Rahim, IIUM, Malaysia
Waqar Asrar, IIUM, Malaysia
INTERNATIONAL ADVISORY COMMITTEE
Anwar, United States
Abdul Latif Bin Ahmad, Malaysia
Farzad Ismail, USM, Pulau Pinang, Malaysia
Hanafy Omar, Saudi Arabia
Hany Ammar, United States
Idris Mohammed Bugaje, Nigeria
K.B. Ramachandran, India
Kunzu Abdella, Canada
Luis Le Moyne, ISAT, University of Burgundy, France
M Mujtaba, United Kingdom
Mohamed AI-Rubei, Ireland
Mohamed B Trabia, United States
Syed Kamrul Islam, United States
Tibor Czigany, Budapest University of Technology and Economics, Hungary
Yiu-Wing Mai, The University of Sydney, Australia.
AIMS & SCOPE OF IIUM ENGINEERING JOURNAL
The IIUM Engineering Journal, published biannually (January and July), is a carefully refereed international publication of International Islamic University Malaysia (IIUM). Contributions of high technical merit within the span of engineering disciplines; covering the main areas of engineering: Electrical and Computer Engineering; Mechanical and Manufacturing Engineering; Automation and Mechatronics Engineering; Material and Chemical Engineering; Environmental and Civil Engineering; Biotechnology and Bioengineering; Engineering Mathematics and Physics; and Computer Science and Information Technology are considered for publication in this journal. Contributions from other areas of Engineering and Applied Science are also welcomed. The IIUM Engineering Journal publishes contributions under Regular papers and Invited review papers. It also welcomes contributions that address solutions to the specific challenges of the developing world, and address science and technology issues from an Islamic and multidisciplinary perspective.
REFEREES’ NETWORK
All papers submitted to IIUM Engineering Journal will be subjected to a rigorous reviewing process through a worldwide network of specialized and competent referees. Each accepted paper should have at least two positive referees’ assessments.
SUBMISSION OF A MANUSCRIPT
A manuscript should be submitted online to the IIUM-Engineering Journal website at
http://journals.iium.edu.my/ejournal. Further correspondence on the status of the paper could be done through the journal website.
Whilst every effort is made by the publisher and editorial board to see that no inaccurate or misleading data, opinion or statement appears in this Journal, they wish to make it clear that the data and opinions appearing in the articles and advertisement herein are the responsibility of the contributor or advertiser concerned. Accordingly, the publisher and the editorial committee accept no liability whatsoever for the consequence of any such inaccurate or misleading data, opinion or statement.
IIUM Engineering Journal
ISSN: 1511-788X E-ISSN: 2289-7860
Published by:
IIUM Press,
International Islamic University Malaysia
Jalan Gombak, 53100 Kuala Lumpur, Malaysia
Phone (+603) 6421-5014, Fax: (+603) 6421-6298
PARAMETER EFFECTS OF PH, DOSAGE AND CONTACT TIME ON BORON REMOVAL FROM SYNTHETIC SEA WATER USING MORINGA OLEIFERA SEEDS
No full textBoron is one of the key elements required in flora, fauna, as well as human beings. However, human life and eco-systems could be seriously affected when exposed to excessive levels of boron, especially in seawater and groundwater. In this work Moringa oleifera was selected as a precursor adsorbent owing to its eco-friendliness characteristics and favourable removal efficiency of adsorbates. Besides, M. oleifera does not significantly affect the conductivity of water and pH value after the treatment. The main aim of this work was to investigate the potentiality of M. oleifera in the treatment of boron from contaminated saline water. The effect of adsorption parameters such as pH (7 - 9), adsorbent dose of 4000 – 8000 mg/L of solution and contact time of 60 – 180 min was thoroughly investigated. Face-centred Central Composite Design (FCCCD) was applied to optimize these parameters. Consequently, the highest percentage of removal (65%) was achieved at the pH of 8, 120 min of contact time and 6000 mg/L of adsorbent dosage. The adsorption studies stated that the adsorption fitted well with the Freundlich isotherm. Therefore, the outcome of this work revealed that boron could be significantly treated using a prepared adsorbent from M. oleifera.
ABSTRAK: Boron merupakan salah satu elemen yang diperlukan oleh flora, fauna, juga manusia. Walau bagaimanapun, hidup manusia dan ekosistem pasti terkesan apabila di dedahkan secara berlebihan, terutama pada air di lautan dan daratan. Kajian ini menggunakan Moringa oleifera sebagai penjerap kerana ia mempunyai ciri-ciri mesra dan berkesan membuang bahan terjerap dengan berkesan. Selain itu, M. oleifera tidak langsung memberi kesan kepada konduktiviti air dan nilai pH selepas perawatan. Tujuan utama kajian ini adalah mengkaji potensi M. oleifera dalam larutan rawatan air garam boron yang tercemar. Kesan parameter penjerapan seperti pH (7-9), dos penjerapan 4000 – 8000 mg/L larutan dan masa interaksi 60 – 180 minit di kaji dengan teliti. Kaedah Komposisi Tumpuan Tengah Muka (FCCCD) digunakan bagi mengoptimumkan parameter-parameter ini. Hasilnya, peratus tertinggi penyingkiran adalah sebanyak (65%) pada pH 8, 120 min masa interaksi dan 6000 mg/L dos penjerapan. Kesimpulannya, kajian penjerapan ini menyokong kuat teori isoterma Freundlich. Oleh itu, hasil kajian ini menunjukkan boron dapat dirawat dengan menggunakan larutan penjerapan daripada M. oleifera
DYNAMIC MODELING OF A SINGLE-LINK FLEXIBLE MANIPULATOR ROBOT WITH TRANSLATIONAL AND ROTATIONAL MOTIONS
Get PDFThe flexible manipulator is widely used in space robots, robot arm, and manufacturing industries that produce micro-scale products. This study aims to formulate the equation of motion of a flexible single-link manipulator system that moves translationally and rotationally and to develop computational codes with finite element methods in performing dynamic simulation on the vibration of the flexible manipulator system. The system of the single-link flexible manipulator (SLFM) consists of the aluminum beam as a flexible link, clamp part to hold the link, DC motor to rotate drive shaft, a trajectory to transfer link in translational motion, and servo motor to rotate link. Computational codes in time history response (THR) and Fast Fourier Transform (FFT) processing were developed to identify the dynamic behavior of the link. The finite element-method and Newmark-beta are used in simulating the SLFM. Simulation using the finite element method has displayed dynamic behavior through a graph of FFT on free vibration and THR graph on forced vibration by the excitation force due to the translational and rotational motions of the system. In the simulation of free vibration, the natural frequency of the system is 8.3 [Hz]
THE IMPLEMENTATION OF THE MACHINE LEARNING ALGORITHM FOR THE SENTIMENT ANALYSIS OF INDONESIA’S 2019 PRESIDENTIAL ELECTION
No full textIn 2019, citizens of Indonesia participated in the democratic process of electing a new president, vice president, and various legislative candidates for the country. The 2019 Indonesian presidential election was very tense in terms of the candidates' campaigns in cyberspace, especially on social media sites such as Facebook, Twitter, Instagram, Google+, Tumblr, LinkedIn, etc. The Indonesian people used social media platforms to express their positive, neutral, and also negative opinions on the respective presidential candidates. The campaigning of respective social media users on their choice of candidates for regents, governors, and legislative positions up to presidential candidates was conducted via the Internet and online media. Therefore, the aim of this paper is to conduct sentiment analysis on the candidates in the 2019 Indonesia presidential election based on Twitter datasets. The study used datasets on the opinions expressed by the Indonesian people available on Twitter with the hashtags (#) containing "Jokowi and Prabowo." We conducted data pre-processing using a selection of comments, data cleansing, text parsing, sentence normalization and tokenization based on the given text in the Indonesian language, determination of class attributes, and, finally, we classified the Twitter posts with the hashtags (#) using Naïve Bayes Classifier (NBC) and a Support Vector Machine (SVM) to achieve an optimal and maximum optimization accuracy. The study provides benefits in terms of helping the community to research opinions on Twitter that contain positive, neutral, or negative sentiments. Sentiment Analysis on the candidates in the 2019 Indonesian presidential election on Twitter using non-conventional processes resulted in cost, time, and effort savings. This research proved that the combination of the SVM machine learning algorithm and alphabetic tokenization produced the highest accuracy value of 79.02%. While the lowest accuracy value in this study was obtained with a combination of the NBC machine learning algorithm and N-gram tokenization with an accuracy value of 44.94%.
ABSTRAK: Pada tahun 2019 rakyat Indonesia telah terlibat dalam proses demokrasi memilih presiden baru, wakil presiden, dan berbagai calon legislatif negara. Pemilihan presiden Indonesia 2019 sangat tegang dalam kempen calon di ruang siber, terutama di laman media sosial seperti Facebook, Twitter, Instagram, Google+, Tumblr, LinkedIn, dll. Rakyat Indonesia menggunakan platfom media sosial bagi menyatakan pendapat positif, berkecuali, dan juga negatif terhadap calon presiden masing-masing. Kampen pencalonan menteri, gabenor, dan perundangan hingga pencalonan presiden dilakukan melalui media internet dan atas talian. Oleh itu, kajian ini dilakukan bagi menilai sentimen terhadap calon pemilihan presiden Indonesia 2019 berdasarkan kumpulan data Twitter. Kajian ini menggunakan kumpulan data yang diungkapkan oleh rakyat Indonesia yang terdapat di Twitter dengan hashtag (#) yang mengandungi "Jokowi dan Prabowo." Proses data dibuat menggunakan pilihan komentar, pembersihan data, penguraian teks, normalisasi kalimat, dan tokenisasi teks dalam bahasa Indonesia, penentuan atribut kelas, dan akhirnya, pengklasifikasian catatan Twitter dengan hashtag (#) menggunakan Klasifikasi Naïve Bayes (NBC) dan Mesin Vektor Sokongan (SVM) bagi mencapai ketepatan optimum dan maksimum. Kajian ini memberikan faedah dari segi membantu masyarakat meneliti pendapat di Twitter yang mengandungi sentimen positif, neutral, atau negatif. Analisis Sentimen terhadap calon dalam pemilihan presiden Indonesia 2019 di Twitter menggunakan proses bukan konvensional menghasilkan penjimatan kos, waktu, dan usaha. Penyelidikan ini membuktikan bahawa gabungan algoritma pembelajaran mesin SVM dan tokenisasi abjad menghasilkan nilai ketepatan tertinggi iaitu 79.02%. Manakala nilai ketepatan terendah dalam kajian ini diperoleh dengan kombinasi algoritma pembelajaran mesin NBC dan tokenisasi N-gram dengan nilai ketepatan 44.94%
THE DURABILITY OF HYGRO-IMMERSION AGED CELLULOSE FIBRE REINFORCED POLYMER LAYERED SILICATE NANOCOMPOSITES
Get PDFThis study aims at investigating the effect of water ageing on the durability of cellulose fibre reinforced polymer layered silicate nanocomposite. The material used comprises cellulose fibres from pinewood as reinforcement and high-density polyethene (HDPE) coupled with nanoclay as matrix phase. The prepared material is subjected to tap water ageing for 21 days. The durability is quantified by Barcol hardness for the material and measured at an interval period of 7 days. The obtained results indicate a reduction of hardness by 5.24, 13.17, and 16.60% in 7, 14, and 21 days aged nanocomposites. Besides, the one-way ANOVA test shows that the immersion time for the composite has a significant effect on the durability of the material with an R2 value of 99.96% tested at 95% confidence interval. The concluding remarks are validated using the results obtained for thickness swelling using the Fourier analysis. The work also presents a regression equation with high degree of accuracy, capable of estimating the Barcol hardness value for a given immersion time.
ABSTRAK: Kajian ini bertujuan untuk mengkaji kesan penuaan air terhadap ketahanan nanokomposit silikat berlapis polimer bertetulang serat selulosa. Bahan yang digunakan terdiri daripada serat selulosa dari kayu pina sebagai tetulang dan polietena berketumpatan tinggi (HDPE) ditambah dengan nanoclay sebagai fasa matriks. Bahan yang disediakan mengalami penuaan air paip selama 21 hari. Ketahanan diukur dengan kekerasan bahan Barcol dan diukur pada selang waktu 7 hari. Hasil yang diperoleh menunjukkan penurunan kekerasan sebanyak 4.74, 8.88 dan 18.90% dalam nanokomposit usia 7, 14 dan 21 hari. Selain itu, analisis satu arah ujian varians menunjukkan bahawa masa rendaman komposit mempunyai pengaruh yang signifikan terhadap ketahanan bahan dengan nilai R2 99.96% yang diuji pada selang keyakinan 95%. Ucapan penutup disahkan menggunakan hasil yang diperoleh untuk pembengkakan ketebalan menggunakan analisis Fourier. Karya ini juga menyajikan persamaan regresi dengan tahap ketepatan yang tinggi, yang dapat menganggarkan nilai kekerasan Barcol untuk masa rendaman tertentu
THE EFFECTS OF SUPERCRITICAL CARBON DIOXIDE ON THE DEGRADATION AND ANTIMICROBIAL PROPERTIES OF PLA BIOCOMPOSITE
Get PDFBiopolymer products that is biodegradable presently attracting an attention from researchers and industry. The biodegradable packaging based on polylactic acid (PLA), durian skin fibre (DSF), epoxidized palm oil (EPO) and incorporated with cinnamon essential oil (CEO) as antimicrobial agent have been developed and showed to be a promising field of research. This paper reported the effects of supercritical carbon dioxide on the degradation and antimicrobial properties of PLA biocomposite films produced via solvent casting. The biocomposites underwent supercritical carbon dioxide (SCCO2) treatment at two different conditions under 40 °C temperature and at 100 bar and 200 bar pressure. Water absorption test showed that the untreated PLA biocomposite absorbed most water as compared to treated PLA biocomposite with SCCO2 at 5.1%. This is due to the hydrophilic nature of the fibre that absorbed water molecules. Soil burial test showed that the treated PLA biocomposite possessed the highest value of weight losses after 80 days with 97.8%. Biocomposite with the presence of CEO demonstrated antimicrobial activity against both gram-positive and gram-negative bacteria. This showed that SCCO2 significantly improved the properties of PLA biocomposite films. The supercritical fluid treatment of PLA biocomposite could be an alternative for active packaging industries to ensure that the packaging product meets the requirement by consumers as well as being an eco-friendly product.
ABSTRAK: Produk biopolimer yang biodegradasi pada masa ini menarik perhatian dari penyelidik dan industri. Pembungkusan biodegradasi berasaskan polilaktik asid (PLA), serat kulit durian (DSF), minyak kelapa sawit terepoksi (EPO) dan ditambah dengan minyak pati kayu manis (CEO) sebagai agen antimikrobial telah dibangunkan dan menjadi bidang penyelidikan. Artikel ini melaporkan kesan karbon dioksida superkritikal terhadap sifat-sifat degradasi dan antimikrobik dari filem biokomposit PLA yang dihasilkan melalui pemutus pelarut. Biokomposit telah menjalani rawatan superkritikal karbon dioksida (SCCO2) pada dua keadaan yang berbeza di bawah suhu 40 °C pada 100 bar dan 200 tekanan bar. Ujian penyerapan air menunjukkan bahawa biocomposite PLA yang tidak dirawat menyerap kebanyakan air berbanding komposisi lain dengan 5.1%. Ini disebabkan sifat hidrofilik serat yang menyerap molekul air. Ujian penanaman dalam tanah menunjukkan bahawa biocomposite PLA yang dirawat mempunyai nilai kehilangan berat tertinggi setelah 80 hari dengan 97.8%. Biokomposit dengan kehadiran CEO menunjukkan aktiviti antimikrobial terhadap bakteria gram-positif dan gram-negatif. Ini menunjukkan bahawa SCCO2 meningkatkan sifat-sifat filem biocomposite PLA. Rawatan cecair superkritikal PLA biocomposite boleh menjadi alternatif bagi industri pembungkusan untuk memastikan produk pembungkusan memenuhi keperluan pengguna serta menjadi produk mesra alam