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Erifive Pranatal
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Journal of Applied Sciences, Management and Engineering Technology (JASMET)
Published by Institut Teknologi Adhi Tama Surabaya
ISSN : -     EISSN : 27212165     DOI : https://doi.org/10.31284/j.jasmet.2020.v1i1.704
Core Subject : Science, Engineering,
Civil Engineering, Building, Construction & Architecture Decision Sciences, Operations Research & Management Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology
Journal of Applied Sciences, Management and Engineering Technology (JASMET) is an international peer-reviewed journal that was launched by LPPM ITATS. It is dedicated to provide a high-level platform in all aspect of science, management and engineering technology Scope of the journal: Engineering, Science and Management
Arjuna Subject : Teknik (semua kategori) - Teknik Sipil dan Struktur
Articles 5 Documents
 1 
Search results for , issue "Vol 3, No 1 (2022)" : 5 Documents clear
Risk Analysis Using Multi-Attribute Failure Mode Analysis Approach in Mybeb Social Payment Application Bob Maulana Adam; Zeplin Jiwa Husada Tarigan
Journal of Applied Sciences, Management and Engineering Technology Vol 3, No 1 (2022)
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.jasmet.2022.v3i1.2378

Abstract

MyBeb is a social payment application owned by one of the FinTech companies in the Sidoarjo area, East Java Province. Mybeb itself is an application that provides social media features as well as payments. In running the product, several obstacles and operational risks arise that have not been handled properly, and not a few users have not been properly educated in the use of this application. This study aims to identify risk priorities and corrective actions that must be taken using the MAFMA method. The method is to detect failure points that have great potential to be overcome. Then get the results and benefits of the analysis method that will affect the company using the methods. From the methods, the risk with the highest value was at the risk of the P10 value, which was 0.482. At the same time, the lowest risk is at P1 risk with a risk level value of 0.251. Then for managerial implications for the proposed improvement to the method with the highest risk level at P10 risk, a page for a list of friends using referral links from users is given to those who have done uploading profile photos.
The effect of NaOH concentration and stem size in the making of Oxalic Acid from Banana Stem Didik Purwanto; A Rasmito; Sihabuddin Sihabuddin
Journal of Applied Sciences, Management and Engineering Technology Vol 3, No 1 (2022)
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.jasmet.2022.v3i1.2381

Abstract

The main purpose of this research is to determine the effect of NaOH concentration and size of banana stem pieces on the concentration of oxalic acid produced. The experiment procedure is add 20 grams of banana stems that have been dried into 200 ml NaOH then heated and stirred at temperature of 100°C for 1 hour. Then the molten mixture was added with hot 500 ml of water, then cooled and filtered. Filtrate was taken and added to 100 ml CaCl2. Solution is filtered and the sediment is taken. Sediment is inserted into the Erlenmeyer and 200 ml dilute H2SO4 added and then filtered. 10 g active carbon is added into filtrate of the solution, then filtered. Taking 10 ml of the filtrate above to be titrated. From the research has been done, it can be concluded that the greater the concentration of NaOH, the greater the amount of oxalic acid obtained. The longer the size of the banana midrib, the greater the amount of oxalic acid obtained. And, the maximum amount of oxalic acid obtained is 2.99 g that reach at a concentration of 50% NaOH with a length of the banana leaf 2.5 cm.
Fractional Gradient Based Optimization for Nonlinear Separable Data Dian Puspita Hapsari; Muhammad Fahrur Rozi
Journal of Applied Sciences, Management and Engineering Technology Vol 3, No 1 (2022)
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.jasmet.2022.v3i1.2881

Abstract

The Support Vector Machine or SVM classifier is one of the machine learning algorithms whose job is to predict data. Traditional classifier has limitations in the process of training large-scale data, tends to be slow. This study aims to increase the efficiency of the SVM classifier using a fractional gradient descent optimization algorithm, so that the speed of the data training process can be increased when using large-scale data. There are ten numerical data sets used in the simulation that are used to test the performance of the SVM classifier that has been optimized using the Caputo type fractional gradient descent algorithm. In this paper, we use the Caputo derivative formula to calculate the fractional-order gradient descent from the error function with respect to weights and obtain a deterministic convergence to increase the speed of the Caputo type fractional-order derivative convergence. The test results show that the optimized SVM classifier achieves a faster convergence time with iterations and a small error value. For further research, the optimized SVM linear classifier with fractional gradient descent is implemented on the problem of unbalanced class data.
Petrology and Geochemical Comparation of Pumice and Scoria Rocks of Slamet Volcano, Central Java Yogi Adi Prasetya; Atsushi Toramaru
Journal of Applied Sciences, Management and Engineering Technology Vol 3, No 1 (2022)
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.jasmet.2022.v3i1.2954

Abstract

Slamet Volcano is one of Indonesia Quaternary Stratovolcanoes in Central Java Province. Slamet volcano is divided into two parts, Old Slamet in the western part and Young Slamet. The author examined a comparation data of pyroclastic rock of Slamet Volcano, the pyroclastic rocks are pumice from Old Slamet, the scoria fall, and scoria cones are from Young Slamet. They have different geochemical and petrology features, pumice rock has higher SiO2 from 60 to 64 wt.%, scoria fall has SiO2 49.81 to 50.56 wt. %, and scoria cone has SiO2 49.26 wt. %. Petrographic observation showed that pumice is vesicular and contains of phenocryst pyroxene, plagioclase and biotite, scoria fall, and scoria cones have similar petrographic characteristic they have phenocryst of plagioclase, olivine, and pyroxene with hyalopilitic texture. The contrast of major element combined with petrographic features suggest that pyroclastic rock in Slamet Volcano formed by different magma and the magma has differentiation process of Slamet magma is generally caused by magma mixing.
SLOPE STABILITY ANALYSIS IN ANDESITE STONE MINING ROLAS NUSANTARA TAMBANG Ltd. IN PASURUAN REGENCY Yudho Dwi Galih Cahyono; Ratih Hardini Kusuma Putri; Aprilia Dwi Astuti
Journal of Applied Sciences, Management and Engineering Technology Vol 3, No 1 (2022)
Publisher : Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.jasmet.2022.v3i1.2974

Abstract

In mining activities Rolas Nusantara Tambang Ltd. needs to do a slope stability analysis because at that location there has never been a study on the condition of the slopes. In addition, there are several problems that can cause unstable slopes such as slope geometry that is too upright, the presence of discontinuity fields and mining locations that are close to several active volcanoes in East Java, namely Mount Semeru and Mount Bromo so that the potential for earthquakes and vibrations is high and can be affect the stability of the slopes at that location. This study aims to analyze slope stability using the Janbu method in calculating the factor of safety and the Monte Carlo method for the probability of landslides. From the results of the study, the actual slope safety factor (FK) was 1.703 and the probability of landslide (PK) was 0.000% with a slope height of 12 meters and a slope of 850. Then recommendations were given for the overall slope with an overall height of 36 meters and an overall slope of 570, the factor value was obtained. safety (FK) of 2.170 and probability of landslide (PK) of 0.000%. From these results it can be concluded that the slope conditions are in the safe category. 

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