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Contact Name
I Made Wicaksana Ekaputra
Contact Email
made@usd.ac.id
Phone
+62274883037
Journal Mail Official
editorial.ijasst@usd.ac.id
Editorial Address
Kampus III Universitas Sanata Dharma, Paingan, Maguwoharjo, Depok, Yogyakarta
Location
Kab. sleman,
Daerah istimewa yogyakarta
INDONESIA
International Journal of Applied Sciences and Smart Technologies
ISSN : 26558564     EISSN : 26859432     DOI : http://dx.doi.org/10.24071/ijasst
International Journal of Applied Sciences and Smart Technologies (IJASST) is published by Faculty of Science and Technology, Sanata Dharma University Yogyakarta-Central Java-Indonesia. IJASST is an open-access peer reviewed journal that mediates the dissemination of academicians, researchers, and practitioners in engineering, science, technology, and basic sciences which relate to technology including applied mathematics, physics, and chemistry. IJASST accepts submission from all over the world, especially from Indonesia.
Arjuna Subject : Umum - Umum
Articles 51 Documents
Indian Traffic Signboard Recognition and Driver Alert System Using Machine Learning Yadav, Shubham; Patwa, Anuj; Rane, Saiprasad; Narvekar, Chhaya
International Journal of Applied Sciences and Smart Technologies Volume 01, Issue 01, June 2019
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (877.436 KB) | DOI: 10.24071/ijasst.v1i1.1843

Abstract

Sign board recognition and driver alert system which has a number of important application areas that include advance driver assistance systems, road surveying and autonomous vehicles. This system uses image processing technique to isolate relevant data which is captured from the real time streaming video. The proposed method is broadly divided in five part data collection, data processing, data classification, training and testing. System uses variety of image processing techniques to enhance the image quality and to remove non-informational pixel, and detecting edges. Feature extracter are used to find the features of image. Machine learning algorithm Support Vector Machine(SVM) is used to classify the images based on their features. If features of sign that are captured from the video matches with the trained traffic signs then it will generate the voice signal to alert the driver. In India there are different traffic sign board and they are classified into three categories: Regulatory sign, Cautionary sign, informational sign. These Indian signs have four different shapes and eight different colors. The proposed system is trained for ten different types of sign . In each category more than a thousand sample images are used to train the network.                           
Development Study of Deep Learning Facial Age Estimation Adi, Puspaningtyas Sanjoyo
International Journal of Applied Sciences and Smart Technologies Volume 01, Issue 01, June 2019
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (801.238 KB) | DOI: 10.24071/ijasst.v1i1.1899

Abstract

Human age estimation is one of the most challenging problem because it can be used in many applications relating to age such as age-specific movies, age-specific computer applications or website, etc. This paper will contribute to give brief information about development of age estimation researches using deep learning. We explore three recent journal papers that give significant contribution in age estimation using deep learning. From these papers, they selected classification methods and there is gradual improvement in result and also in selected loss function. The best result gives MAE (mean average error) 2.8 years and VGG-16 is the most selected CNN architecture.
Saving the Moving Position on the Continuous Passive Motion Machine for Rehabilitation of Shoulder Joints Noviyanto, Antonius Hendro
International Journal of Applied Sciences and Smart Technologies Volume 01, Issue 02, December 2019
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (648.323 KB) | DOI: 10.24071/ijasst.v1i2.1921

Abstract

This paper presents the results of the motion therapy device Continuous Passive Motion (CPM) Machine which is applied to the shoulder joint with storage movement. The process of joint rehabilitation is carried out by continuous passive movements. This movement is intended not to overload the work of the muscles and there is no stiffness in the joints after surgery or stroke patients or patients who have carried out immobilization for quite a long time. The CPM Machine developed can move flexion and horizontal abduction. The position storage in this tool is carried out in a range of movements in flexion and horizontal abduction. So that with the storage of movement can be done movement / therapy exercises in patients with joint stiffness passively and continuously.
Implementation of k-Medoids Clustering Algorithm to Cluster Crime Patterns in Yogyakarta Atmaja, Eduardus Hardika Sandy
International Journal of Applied Sciences and Smart Technologies Volume 01, Issue 01, June 2019
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (880.674 KB) | DOI: 10.24071/ijasst.v1i1.1859

Abstract

The increase in crime from day to day needs to be a concern for the police, as the party responsible for security in the community. Crime prevention effort must be done seriously with all knowledge that they have. To increase police performance of crime prevention effort, it is necessary to analyze crime data so that relevant information can be obtained.This study tried to analyze crime data to obtain relevant information using clustering in data mining.Clustering is a data mining method that can be used to extract valuable information by grouping data into groups that have similar characters.The data used in this study were crime patterns which were then grouped using K-medoids clustering algorithm.The obtained results in this study were three crime groups, namely high crime levelwith 4 members, medium crimelevel with 6 members and low crime level with 8 members.It is expected that this information can be used as material for consideration in crime prevention effort
Factors Influencing the Difficulty Level of the Subject: Machine Learning Technique Approaches Suparwito, Hari
International Journal of Applied Sciences and Smart Technologies Volume 01, Issue 01, June 2019
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (978.99 KB) | DOI: 10.24071/ijasst.v1i1.1869

Abstract

The difficulty level of a subject is needed either to understand the student acceptance of the subject and the highest level of student achievement in it. Some factors are considered, what kind of instructions, the readiness of the instructor and students in teaching and learning, evaluation and monitoring systems, and student expectations. Many factors are involved, and educators should know this. It is better if they can discern which are the prime factors and which the secondary factors. The purpose of the study is to find out the determinant factors in establishing the difficulty level of the subject from the students?, teachers? and infrastructure point of view using three machine learning techniques. The MSE and the variable importance measurement were used to predict between some factors such as Attendance, Instructors, and other factors as independent variables and the difficulty level of the subject as a dependent variable. The study result showed that Gradient Boosting Machine obtained the MSE value result 1.14 and 1.30 for training and validation dataset. The model generated five variable importance as an independent factor, i.e. Attendance, Instructor, The course can give a new perspective to students, The quizzes, assignments, projects and exams contributed to helping the learning, and The Instructor was committed to the course and was understandable. The Gradient Boosting Machine is superior to other methods with the lowest MSE and MAE values results. Two methods, Gradient Boosting Machine and Deep Learning, have produced the same five main factors that influenced the difficulty of the subject. It means these factors are significant and should get intention by the stakeholders
Microcontroller Based Simple Water Flow Rate Control System to Increase the Efficiency of Solar Energy Water Distillation Parikesit, Elang; Kusbandono, Wibowo; Sambada, FA. Rusdi
International Journal of Applied Sciences and Smart Technologies Volume 01, Issue 02, December 2019
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1210.838 KB) | DOI: 10.24071/ijasst.v1i2.1923

Abstract

The current problem of solar energy water distillation is in its low efficiency. Low efficiency is caused by inefficient water evaporation processes. Increasing the efficiency of water evaporation is done by controlling the rate of water entering into the absorber. The commonly used mechanical control system still has weaknesses such as the instability of the water entering the absorber. This causes less effective evaporation of water so that the resulting distillation efficiency is not optimal. The water rate input system for distillation in this study is based on a simple microcontroller. The microcontroller-based input water rate control system allows the rate of input water with a small but continuous flow rate so that the water evaporation process can be more effective. This study aims to improve the efficiency of solar energy water distillation by increasing the efficiency of the water evaporation process through controlling the flow rate of water inlet. The research was carried out by the experimental method. The parameters varied were: the rate of input water which was 0.3 l / hour, 0.5 l / hour and 1.2 l / hour. Parameters measured in this study were: (1) temperature of absorber, (2) temperature of the cover glass , (3) temperature of cooling water, (4) input water temperature, (5) ambient air temperature, (6) distilled water results, (7) solar energy coming in and (8) time of recording data. The results showed that the production of distillation water using microcontroller-based water rate control was a maximum of 523% compared to the model without water rate control at a water flow rate of 0.3 liters / hour, with distillation efficiency of 66%. From the results of this study it can also be concluded that microcontroller based water flow rate controller is more stable than mechanical water flow controller, especially in small flow
Influences of Annealing on the Electrical Properties of Ba0,5Sr0,5TiO3 Rositawati, Dwi Nugraheni
International Journal of Applied Sciences and Smart Technologies Volume 01, Issue 01, June 2019
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (952.369 KB) | DOI: 10.24071/ijasst.v1i1.1864

Abstract

The research aims to investigate influences of annealing on the electrical properties of Ba0,5Sr0,5TiO3. Ba0,5Sr0,5TiO3 material which was annealed at 900°C for 1, 2 and 4 hours has better mechanical properties. It needs investigation for its electrical contribution, namely the correlation between grain and grain boundaries to values of resistance and capacitance. The changing of electrical properties was controlled by grain, grain boundary and the area between the sample and contact. The electrical properties of Ba0,5Sr0,5TiO3 were investigated by impedance spectroscopy in the room temperature. This method is able to separate the electrical and dielectric properties of the grain, grain boundary and the area between contact with the sample. ZsimpWin software was used to find out the equivalent electrical circuit, the resistance and capacitance value. It was observed that with the increase in annealing time the small grains resistance, the grain boundaries resistance, and the large grain capacitance value also increases. The resistance values of small grains and large grains were smaller than the grain boundaries resistance. The value of capacitance-resistance of the small grains and large grains were obtained values that tend to be smaller.
Measuring privacy leakage in term of Shannon entropy Aditya, Ricky; Skoric, Boris
International Journal of Applied Sciences and Smart Technologies Volume 01, Issue 02, December 2019
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (723.568 KB) | DOI: 10.24071/ijasst.v1i2.1882

Abstract

Differential privacy is a privacy scheme in which a database is modified such that each user?s personal data are protected without affecting significantly the characteristics of the whole data. Example of such mechanism is Randomized Aggregatable Privacy-Preserving Ordinal Response (RAPPOR). Later it is found that the interpretations of privacy, accuracy and utility parameters in differential privacy are not totally clear. Therefore in this article an alternative definition of privacy aspect are proposed, where they are measured in term of Shannon entropy. Here Shannon entropy can be interpreted as number of binary questions an aggregator needs to ask in order to learn information from a modified database. Then privacy leakage of a differentially private mechanism is defined as mutual information between original distribution of an attribute in a database and its modified version. Furthermore, some simulations using the MATLAB software for special cases in RAPPOR are also presented to show that this alternative definition does make sense.
Morphological Map Analysis in Design Cashew Sheller (Kacip) As a Creative Proccess to Produce Design Concept Wahyujati, Bertha Bintari
International Journal of Applied Sciences and Smart Technologies Volume 01, Issue 02, December 2019
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (884.251 KB) | DOI: 10.24071/ijasst.v1i2.1916

Abstract

The design of cashew nut or cashew nut sheller uses appropriate or low technology with consideration of low cost for tool material. This pengkacip tool will be used at Ngudi Koyo, Imogiri, Bantul, Yogyakarta. Cashew shell peeler or cippling device as a result of the design is a modification of the existing cashew shell peeler. Some parts of the existing tool are applied to several modified parts, namely the lever mechanism, picking knife, or lever knife. This paper will discuss the method of selecting a suppressor, lever and picking system on a tool using the morphological map analysis method. Morphological maps will produce alternative designs for cashew nut peeler. The selection of alternative designs will be carried out by analyzing the results of testing in a technical mechanism, material strength, and alternative design quality values. Testing of alternative technical systems mechanisms is done by comparing the mechanical systems of existing tools. The size of the tool uses the anthropometric measurements of the female operator's body, because the operators in the Ngudi Koyo UKM are all women. The tool size adjustment will provide work comfort and increase efficiency. Quality testing in addition to using standard anthropometric standards, will be tested for quality of ease of care, ease of transferring, clean, neat, simple and safe  tool.Key words: Effective technology , low technology tool, security, Design Alternative Testing
The Improvement of Watershed Algorithm Accuracy for Image Segmentation Handwritten Numbered Musical Notation Pinaryanto, Kartono
International Journal of Applied Sciences and Smart Technologies Volume 01, Issue 01, June 2019
Publisher : Universitas Sanata Dharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (671.218 KB) | DOI: 10.24071/ijasst.v1i1.1875

Abstract

In the Implementation of image processing to translate the image of the numbered musical notation into a numerical character requires some initial process that must be passed like image segmentation process. The advantage of successful segmentation process is that it can reduce the failure rate in the object recognition process. Segmentation process determines the success of object recognition process, it takes segmentation algorithm that can perform accurate object separation. The combination segmentation process developed in this research used projection profile algorithm, watershed and non object  filtering. Profile projection algorithm is used to crop the image of the musical horizontally and vertically. The watershed algorithm is used to segment the numerical object of numerical notation generated from the projection profile process. Non object filtering is a continuation of the watershed algorithm that includes the non-object reduction process and the process of combining objects so that the original object segment will be generated. The based on the results of the research, the accuracy of the segment on watershed segmentation is 99.74% higher than watershed segmentation without combination of 94.82%.