DEVELOPMENT OF DESIGN PRINCIPLES AND EVALUATION METHODS OF APPROPRIATE TECHNOLOGY MACHINES FOR AGRICULTURAL PRODUCT PROCESSING
Appropriate Technology (AT) is technology that meets community needs, addresses community problems, is environmentally friendly, and can be easily utilized and maintained by the community. Additionally, it should produce added value from both economic and environmental aspects. The use of AT in c...
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Format: | Dissertations |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/86591 |
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Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Summary: | Appropriate Technology (AT) is technology that meets community needs, addresses
community problems, is environmentally friendly, and can be easily utilized and
maintained by the community. Additionally, it should produce added value from
both economic and environmental aspects. The use of AT in communities is one of
the Indonesian Government's strategies to increase productivity and add value to
products, especially agricultural commodities. However, a problem arises because
currently, not many AT designs consider the characteristics and capabilities of the
users. Therefore, this research proposes a design principles and evaluation
methods for AT machine design. This research focuses on AT agricultural product
processing machines. The model was developed to solve AT design and utilization
problems in society by paying attention to ergonomics and human factors, thereby
increasing effectiveness and productivity.
The first stage of the research involved model development using literature studies,
interviews, and field observations. Field observations and interviews were
conducted with AT users, with eight respondents participating in this stage. The
goal of the field observations was to directly observe the practice of using AT in the
community and to understand the obstacles faced by users related to AT design.
The second stage involved data collection through distributing questionnaires
aimed at identifying AT design factors. The research respondents for this stage
included both AT designers and users, with a total of 221 respondents. Data
processing was conducted using principal component analysis (PCA) and
importance performance analysis (IPA) methods. The third stage involved
evaluating the AT machines through subjective and objective usability tests. These
tests used the system usability scale (SUS) questionnaire and experiments with an
electroencephalograph (EEG) and heart rate monitor (HRM).
As a result of direct observations in the field and interviews, seven general
problems were identified in using AT machines: functional aspects, physical
workload, technical issues, energy consumption, security, maintenance and repair,
ease of use, and tool dimensions. The results of the PCA analysis produced six
principles and 42 design indicators namely safety and error prevention,
functionality and economics, user friendly, low physical effort, user compatibility,
and perceptible information. The results of the IPA analysis indicate several areas
for improvement in AT design. Prioritized improvements for AT machine design
include the importance of having guidelines regarding use and safety, as well as
the need for AT machine design to incorporate and emphasize safety features.
The third stage of research is to evaluate the AT machine. The selection of AT
machines for this evaluation was based on questionnaire interviews with experts.
Factors considered that influence reusability include process stages (set up,
operation, finish) and AT machines with different ergonomic levels (extruder type
noodle printing machines, mini extruder type noodle printing machines, sheeting
slitting type noodle printing machines). The experiment was conducted using a
within-subject design with 22 participants. The EEG parameters evaluated
included delta, theta, alfa, and beta waves, while the HRV parameters evaluated
included root mean square of successive RR interval differences (RMSSD),
standard deviation of the NN interval (SDNN), high frequency (HF), low frequency,
and the LF/HF ratio. In addition to these physiological parameters, the study also
conducted a subjective usability evaluation using the SUS questionnaire. The
results of the usability evaluation are used to determine the AT design evaluation
method and to determine sensitive and accurate physiological parameters in the
evaluation of the AT machine.
The EEG parameters used in this study, delta, theta, and alpha waves, showed
significant differences between AT machines at the operation stage. In contrast,
beta waves showed significant differences at the set-up stage. Delta waves showed
fluctuations in average values , while theta, alpha, and beta waves showed a
decrease in average values from machine 1 to machine 3. The usability of a product
is generally characterized by an increase in theta waves, an increase in alpha
waves, and a decrease in beta waves. HRV parameters, namely SDNN, RMSSD,
LF, HF, and the LF/HF ratio showed variations in the increase and decrease in
average values between each process stage (set-up, operation, and finish) between
machines. However, only the LF/HF ratio parameter statistically showed a
significant difference. The results of the SUS questionnaire showed that,
subjectively, the mini extruder machine had the best usability, followed by the
sheeting slitting machine and the extruder machine. Based on the results of this
study, the evaluation test method on the AT machine based on physiology, namely
with HRV and EEG, can be used in usability assessment with LF/HF ratio and
alpha wave indicators.
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