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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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Journal : Indonesian Journal of Engineering and Science (IJES)

 1 
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.
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