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All Journal Indonesian Journal of Engineering and Science (IJES) International Journal of Research in Vocational Studies (IJRVOCAS) Proceeding of International Conference on Science, Education, and Technology
Akbar Teguh Prakoso
Department Of Mechanical Engineering, Faculty Of Engineering, Universitas Sriwijaya, 30662 Indralaya, Sumatera
Aerospace Engineering Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mechanical Engineering Social Sciences Other

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PREDICTION OF PLASTIC-TYPE FOR SORTING SYSTEM USING DECISION TREE MODEL Astuti Astuti; Anthony Costa; Akbar Teguh Prakoso; Irsyadi Yani; Yulia Resti
Indonesian Journal of Engineering and Science Vol. 4 No. 1 (2023): Table of Content
Publisher : Asosiasi Peneliti Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51630/ijes.v4i1.86

Abstract

Plastic is the most widely used inorganic material globally, but its hundred-year disintegration time can harm the environment. Polyethylene Terephthalate (PET/PETE), High-Density Polyethylene (HDPE), and Polypropylene are all commonly used plastics that have the potential to become waste (PP). An essential first step in the recycling process is sorting out plastic waste. A low-cost automated plastic sorting system can be developed by using digital image data in the red, green, and blue (RGB) color space as the dataset and predicting the type using learning datasets. This paper proposes the Decision Tree model to predict the three plastic-type sorting systems based on discretizing predictor variables into two and three categories. The resampling method of k-fold cross-validation with ten folds for less biased. Discretization of the predictor variables into three categories informs that the proposed decision tree model has higher performance compared to the two categories with an accuracy of 81.93 %, a recall-micro of 72.89 %, a recall-macro of 72.30 %, a specificity-micro of 86.45%, and the specificity-macro of 86.51%, respectively. The micro is determined by the number of decisions made for each object. In comparison, the macro is calculated based on the average decision made by each class.
ASSESSMENT MATERIAL SELECTION FOR CHAIN - SUBMERGED SCRAPPER CONVEYOR Gunawan Gunawan; Amir Arifin; Irsyadi Yani; M. A. Ade Saputra; Barlin Oemar; Zulkarnain Ali Leman; Dendy Adanta; Akbar Teguh Prakoso
Indonesian Journal of Engineering and Science Vol. 4 No. 1 (2023): Table of Content
Publisher : Asosiasi Peneliti Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51630/ijes.v4i1.92

Abstract

Chain–submerged scrapper conveyor bottom ash handling in the petrochemical industry has failed several times and was repaired with AISI 420, which can only operate for three months. AISI 420 is recommended in applications requiring moderate corrosion resistance, high hardness, excellent wear resistance, and good edge retention in cutting surfaces. The initial cracks and fractures occur in the pin-link joint hole, which causes chain failure. Some evaluation has been performed for both as-received and failed links. It can be concluded that chain link failure occurs due to fatigue failure with low-stress levels. Microstructure observation, XRD, and hardness properties showed no significant difference in both as-received and failed links. Since the operating conditions of the chain are in a corrosive environment, experiencing dynamic loading and working temperatures between 23 ºC and 60 ºC, the selection of HSL materials such as AISI 4140 should be considered.
Numerical Investigation of the Effect Infill from Different Unit cells Structure on Mechanical Behaviour Imam Akbar; Martin Luther King; Zulkarnain Fatoni; Togar PO Sianipar; Sukarmansyah; Akbar Teguh Prakoso
International Journal of Research in Vocational Studies (IJRVOCAS) Vol. 3 No. 1 (2023): IJRVOCAS - April
Publisher : Yayasan Ghalih Pelopor Pendidikan (Ghalih Foundation)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53893/ijrvocas.v3i1.168

Abstract

This study aims to identify the effect of infill on mechanical behaviour, especially the yield stress and modulus young of polylactide materials with different unit cell structures such as gyroid, diamond, square, and re-entrant but same porosity with value of 60%. Using Computational aided design (CAD) software and analyzed using the finite element method. The results show that the square structure has the highest strength in terms of mechanical behaviour such as yield stress with a value of 27 MPa, while the gyroid is 25.5 MPa, diamond is 25.3 MPa, re-entrant is 23.3 MPa and young modulus square is 2233MPa gyroid is 2199 MPa, diamond is 2195 MPa re- entrant 2182 MPa. In this study, it was also found that the thickness struth of the unit cell and modulus young had a very strong linear correlation with R2 = 0.96 which explains that the higher the thickness value, the higher the modulus young value. The results of this study also show that although lattice structures, especially square ones, have the highest value, TPMS structures, such as gyroids and diamonds, have more stable performance because these structures have an even stress distribution, thereby reducing the risk of failure of the structure. besides that, the researchers concluded that this TPMS can be used as a solution to improve structural performance.
The Effect of Loading Parameters and Dynamic Immersion Time on the Fatigue Life of Magnesium Bone Scaffolds Risky Utama Putra; Nanda Yusril Mahendra; Dicky Pratama Putra; Akbar Teguh Prakoso; Hasan Basri; Hendri Chandra; Amir Putra Md Saad; Ardiyansyah Syahrom
International Conference on Science, Education, and Technology Vol. 9 (2023)
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Bone scaffolding implants are used in orthopedic applications to aid bone growth and regeneration. However, these implants degrade over time and will also be exposed to the burden of physiological activity during use, which can affect their mechanical properties and fatigue life. The aim of this study was to investigate the effect of degradation time and physiological activity load on changes in bone scaffolding implant morphology on fatigue life and determine significant parameters using the ANOVA method. The study was conducted using numerical simulation using finite element method in software Comsol Multiphysics. Bone scaffolding implants are exposed to cyclic fatigue loads and degradation over time as well as loads of different physiological activities. The results showed that degradation time and physiological activity load had a significant effect on changes in bone scaffolding implant morphology and fatigue life. Increased degradation time and physiological activity load lead to decreased implant fatigue life. The results of the analysis using the ANOVA method showed that the degradation time of factors affecting fatigue with a percentage value of 64.56% was significant on morphological changes and the load of physiological activity had an influence of 35.44% on the fatigue life of bone scaffolding implants. This study emphasizes the importance of considering degradation time and physiological activity load in the design and evaluation of bone scaffold implants. Analysis using the ANOVA method can help to determine significant parameters that affect implant performance and improve implant design to extend fatigue life.
Co-Authors Adanta, Dendy Amir Arifin Amir Putra Md Saad Anthony Costa Ardiyansyah Syahrom Astuti Astuti Barlin Oemar Dicky Pratama Putra Gunawan Gunawan Hasan Basri Hendri Chandra Imam Akbar Irsyadi Yani M. A. Ade Saputra Martin Luther King Nanda Yusril Mahendra Risky Utama Putra Sukarmansyah Togar PO Sianipar Yulia Resti Zulkarnain Ali Leman Zulkarnain Fatoni