bluuebunny/crossref_metadata_2025 huggingface dataset:
Ant Colony Optimization Based Subset Feature Selection in Speech Processing: Constructing Graphs with Degree Sequences
Authors: Rajoo R. Rajesvary , Abdul Salam Rosalina
Published: November 2018

Feature selection or the process of selecting the most discriminating feature subset is an essential practice in speech processing that significantly affects the performance of classification. However, the volume of features that presents in speech processing makes the feature selection perplexing. Moreover, finding the optimal feature subset is a NP-hard problem (2n). Thus, a good searching strategy is required to avoid evaluating large number of combinations in the whole feature subsets. As a result, in recent years, many heuristic based search algorithms are developed to address this NP-hard problem. One of the several meta heuristic algorithms that is applied in many application domains to solve feature selection problem is Ant Colony Optimization (ACO) based algorithms.  ACO based algorithms are nature-inspired from the foraging behavior of actual ants. The success of an ACO based feature selection algorithm depends on the choice of the construction graph with respect to runtime behavior. While most ACO based feature selection algorithms use fully connected graphs, this paper proposes ACO based algorithm that uses graphs with prescribed degree sequences. In this method, the degree of the graph representing the search space will be predicted and the construction graph that satisfies the predicted degree will be generated. This research direction on graph representation for ACO algorithms may offer possibilities to reduce computation complexity from O(n2) to O(nm) in which m is the number of edges. This paper outlines some popular optimization based feature selection algorithms in the field of speech processing applications and overviewed ACO algorithm and its main variants. In addition to that, ACO based feature selection is explained and its application in various speech processing tasks is reviewed. Finally, a degree based graph construction for ACO algorithms is proposed.
Automatic Detection of Shadda in Modern Standard Arabic Continuous Speech
Authors: Al-Sabri Ammar , Adam Afzan , Rosdi Fadhilah
Published: November 2018

The presence of diacritics Shadda in Arabic continuous speech may lead to the reduction of the accuracy of automatic Word Boundary Detection (WBD), which caused one word will be wrongly detected as two words. Therefore, this will affect the accuracy of Automatic Speech Recognition (ASR), if it is based on WBD. Shadda is one of the essential characteristics of the Arabic language which represents a consonant doubling.  In this paper, a proposed method of automatic detection of Shadda in Modern Standard Arabic (MSA) continuous speech was introduced to improve the accuracy of WBD in MSA continuous speech. The prosodic features namely Short Time Energy (STE), Fundamental Frequency and Intensity were investigated for its ability as Shadda pattern detection in continuous MSA speech. We have analyzed the proposed features by implementing a separated algorithm for each feature to detect Shadda pattern automatically. In addition, a new proposed method which is a combination of STE and Intensity were introduced. The dataset in this work is a collection of 1-hour TV broadcast news from Aljazeera Arabic TV channel for 2018 - broadcasters. We found that the Shadda pattern is very similar to unvoiced regions of speech, and this represents a big challenge for the improvement of WDB using Shadda. Results showed that the detection of Shadda using Short Time Energy and Intensity outperforms the Fundamental frequency with 55% of accuracy. Intensity achieved 71.5% in accuracy. In addition, a combination between Intensity & STE features was performed and achieved good results with 67.15% in accuracy. The number of false positive too has been reduced compared to Intensity alone.
Mobile User Perception Factors for Express Bus Safety Journey Management System: A Survey Analysis
Authors: Hassan Rosilah , Salek Samreen , Hasan Mohammad Khatim , Lam Meng Chun , Wan Hussain Wan Mohd Hirwani
Published: November 2018

Public transportation represents a higher danger of safety and security as there happen to be more travellers in a single vehicle. In Malaysia, bus accident is the highest that occurred to death. Internet of Things (IoT) has expanded the utilization of 4IR for investigation and research. A 4IR mobile technology app for express bus safety and security system in Malaysia for bus user is suggested and required. It is important to identify the main factors that can be collected via the mobile app before the app is developed. Passenger perception on the used and relevancy of using information technology (IT) tools to increase their safety perception is also required. This information will give the developer an insight on the app usability. In this paper, observation from passengers regarded safety and security factors are gathered and investigated by utilizing the IT and non-IT related issue. From the survey, majority respondent agree with all seven IT related issues (at least 70%) and all eight non-IT related issues (at least 80%). This is important to understand the mobile user perceptions and provides safety to the passengers. From these factors, we proposed a conceptual framework for express bus safety journey management system to be developed in the future. Future speculation by enhancing existing express transport arrangement with varies variable information, for example, waiting time, unwavering quality and travel time. This information can positively affect the nature of express transport administrations. Gathered information is stored in the cloud. The express bus management can collect the information from the cloud to enhance safety and security of bus express.
Usability of ReSt Module Using Four-Step Approach Based on Case Study Example and Infographic for SPSS Novice Users
Authors: Ishak Azura , Din Rosseni , Mohamed Hazura
Published: November 2018

The application of analysis data software packages, such as SPSS, appears challenging for those who lack experience in quantitative researches particularly amongst novice users. Prior studies have proven that SPSS novice users face some difficulties in analyzing data correctly for their research purposes. The existing modules that serve as references are insufficiently interesting to promote SPSS learning and does not support on students’ cognitive ability.  Hence, a module using four-step approach based on learning via case study example and infographic called ‘ReSt’ module was developed as an effort to assist novice users in learning quantitative data analysis methods using the SPSS. With that, the research design employed in this study was the survey method in order to determine the ReSt module usability level perception. A total of 78 novice users who comprised of undergraduate and postgraduate students participated in this research throughout a two-day SPSS basic course in order to evaluate their perception regarding the usability level of the module.  A usability questionnaire categorized four primary domains, which are usefulness, ease of use, ease of learning, and satisfaction was applied to evaluate the ReSt module usability level perception.  The outcomes revealed that the usability level of the proposed module had been high among the novice users, for the contexts of usefulness, ease of use, ease of learning, and satisfaction. Therefore, the use of the ReSt module for SPSS novice users is indeed relevant and appropriate, thus fulfill the usability amongst novice users to function as a reference in data analysis learning using the SPSS, especially amongst core quantitative researchers.
Test Case Minimization Applying Firefly Algorithm
Authors: Hashim Nor Laily , Dawood Yasir Salman
Published: November 2018

The objective of this study is to propose a test case minimization method performed on UML statechart to produce test cases that are optimal while considering higher coverage criteria. Current test case generation techniques consume a large amount of time and cost with less testing coverage, while generating large number or test cases, what results in difficulties in detecting the faults and errors in the tested systems. Many approaches on test case minimization use genetic algorithms, model checking, or graph search algorithms to reduce the number of generated test cases, also the using of UML diagrams to test the system requirements and design before implementing it in the coding phase. However, these studies lack concentration in achieving higher coverage criteria and minimization in the generated test cases in the same time. The proposed test case minimization method has the following steps: provide weight to the paths, calculate path coverage for each path, transform an immediate graph into an adjacency matrix, which later is used to apply firefly algorithm and generate optimal test cases. A review on of the previous similar research in this domain has been presented and analysed to identify the issues and gaps in this domain. The steps use to perform the test case minimization have been presented together with some example and formula used. Findings from this study shows that this test case minimization has successful covered more types of test coverage which are all state, all transition, all transition pairs and all-one-loop paths. At the same time, it is capable of minimizing the number of test cases.
Leveraging Multimodal Interaction and Adaptive Interfaces for Location-based Augmented Reality Islamic Tourism Application
Authors: Zainal Abidin Rimaniza , Arshad Haslina , Ahmad Shukri Saidatul Aâ€™isyah , Ling Mah Fui
Published: November 2018

A Location-based Augmented Reality (LBAR) application leveraging multimodal interaction and adaptive interface based on Islamic tourism information was proposed to enhance user experience while travelling. LBAR has the potential to improve tourist experience and help tourists to access relevant information, thus improving their knowledge regarding touristic destination while increasing levels of their entertainment throughout the process. In LBAR application, Point of Interest (POI) displayed are exposed to the “occlusion problem” where the AR contents are visually redundant and overlapping with one another causing the users to loose valuable information. Previous research have suggested the design of AR POI which help user to see the augmented POI clearly. The user can click on the desired POI but it still displays a large amount of POI. From our best study, there is limitation of research studying on how to minimize the amount of displayed POI based on user’s current needs. Therefore, in this paper we suggest to use an adaptive user interface and multimodal interaction to solve this problem. We discussed the process of analysing and designing the user interfaces of previous studies. The proposed mobile solution was presented by explaining the application contents, the combination of adaptive multimodal inputs, system’s flow chart and multimodal task definition. Then the user evaluation was conducted to measure the level of satisfaction in terms of the usability of the application. A total of 24 Islamic tourists have participated in this study. The findings revealed that the average SUS score of 75.83 of respondents agree in terms of satisfaction of the LBAR application to be utilized while traveling. Finally, we conclude this paper by providing the suggestion of future works.
Evaluation of Malaysian Universities Websites based on Quality in Use Evaluation Model
Authors: Nwasra Nedal , Basir Nurlida , Marhusin Mohd Fadzli
Published: November 2018

Quality-in-Use (QinU) is one of the important quality factors in measuring website quality. Most existing studies on measuring website quality only focuses on evaluating quality from the user point of view but not on the similarities and the differences between the users and decision-makers perspective. Different stakeholders have different preference in term of quality aspects that are important. Therefore, the objective of this study is to analyse the quality aspects of the websites from different stakeholders’ perspectives and rank the websites based on the results. In this study, we develop a Quality-in-Use Evaluation Model (QinUEM) to identify the quality aspects' priorities. Two quantitative approaches were used for this purpose. The first was a Multi Criteria Decision Making (MCDM) approach using the Fuzzy Analytic Hierarchy Process (FAHP) method to determine the priority and the weight of each quality aspect from the users’ viewpoint. Then the statistical analysis was used to determine the priority of the same quality aspect from the developers’ perspective. To evaluate the model, we conducted a survey. The respondents of the survey were the students (users) and developers (decision-makers) from six Malaysian universities with 486 numbers of questionnaires been distributed. Based on the results, it shows users (students) prefer Functional Quality rather than Content and Appearance Qualities while the decision makers (developers) favour on Content rather than Appearance and Functional Qualities. These results shows different viewpoint and priority in quality aspects needed for users and decision-makers. Based on the results we then used the QinUEM to rank the universities websites according to the defined QinU.
Question Classification Based on Bloom’s Taxonomy Using Enhanced TF-IDF
Authors: Mohammed Manal , Omar Nazlia
Published: November 2018

Bloom’s Taxonomy has been used widely in the educational environment to measure, evaluate and write high-quality exams. Therefore, many researchers have worked on the automation for classification of exam questions based on Bloom’s Taxonomy. The aim of this study is to make an enhancement for one of the most popular statistical feature, which is TF-IDF, to improve the performance of exam question classification in accordance to Bloom’s Taxonomy cognitive domain. Verbs play an important role in determining the level of a question in Bloom’s Taxonomy. Thus, the improved method assigns the impact factor for the words by taking the advantage of the part-of-speech tagger. The higher impact factor assigns to the verbs, then to the noun and adjective, after that, the lower impact factor assigns to the other part-of-speech. The dataset that has been used in this study is consist of 600 questions, divided evenly into each Bloom level. The questions first pass into the preprocessing phase in which they are prepared to be suitable for applying the proposed enhanced feature. For classification purpose, three machine learning classifiers are used Support Vector Machine, Naí¯ve Bayes, and K-Nearest Neighbour. The enhanced feature shows satisfactory result by outperforming the classical feature TF-IDF via all classifiers in terms of weighted recall, precision, and F1-measure. On the other hand, Support Vector Machine has superior performance over other classifiers Naí¯ve Bayes, and K-Nearest Neighbour by achieving an average of 86%, 85%, and 81.6% weighted F1-measure respectively. However, these results are promising and encouraging for further investigations.
Multi-Classifier Jawi Handwritten Sub-Word Recognition
Authors: Hasan Anton Heryanto , Omar Khairuddin , Nasrudin Muhammad Faidzul
Published: November 2018

The problems and challenges in Jawi handwritten recognition are inherited from Arabic script which consists of cursive natures, large variety of writing styles due to its morphologically rich, ligature, overlapping characters, dialects and the low quality of the manuscripts images. The word segmentation is difficult because the existence of sub words due to the presence of space within words when contain disconnect characters. The performance of previous Jawi handwritten recognition still consider sub-par. There are three main problem of previous approach. First, the recognizer consist of multiple independent components where the improvement of performance in one component not shared across the systems. Secondly, the features extraction using features engineering approach only works on specific subsets of training data and is less capable to handle broader variants of testing data. Finally, the classifier used implicit segmentation where target class is sub-word with limited lexicon. This paper propose use of Deep Learning approach to address the first problem where training is conducted end-to-end from input to class output which enable the improvement of each component to improve overall performance. Secondly, Convolutional Network is use as learning features optimizes the data representation through end-to-end training of the parameters from raw input data to target class. Finally, A multi-classifier implicitly segments the sub-word into sequences of characters are proposed. The classifiers consists of one sub-word length classifier and seven character classifiers. This approach is lexicon-free to address absent of lexicon data. Experiments conducted on a Jawi handwritten standard dataset showed an accuracy of up to 92.20% and suggest that the approach used is superior to state-of-the-art methods of Jawi handwriting recognition.
Isolation and Identification of Bacteria-producing Cellulose from Tropical Fruit for Halal Capsule Application
Authors: A. Awang Nursyahidatul , Amid Azura , Mahamad Maifiah Mohamad H. , Jimat Dzun N.
Published: November 2018

Bacterial cellulose (BC) is pure cellulose synthesized by various species of bacteria. Raising demands on bacterial cellulose is due to its pure and simpler structure. It has plenty of applications in various industries such as food, medical and cosmetics, rendering it a choice in halal industry application as a substitute for non-halal gelatine. However, challenges arise during the BC production such as high production cost and low volumetric yield. In this study, BC is studied to overcome the barriers to BC production. Isolation and identification of cellulose producing bacteria were carried out on eight different tropical fruit sources using Hestrin-Schramm media in static culture condition. Morphological and molecular identification by microscopic observation, gram staining, and 16S rRNA analysis were conducted to identify the characteristics and strain of the new isolates. Next, the selected colonies were challenged to grow in agitating condition using modified HS media. The effects of carbon concentration and agitation speed on the production of cellulose were investigated using on central composite design (CCD). Three new cellulose producing bacteria were successfully isolated and identified to be similar to Enterobacter sp. SJZ-5, Bacterium sp NLAE-zl-H356, and Bulkhoderia sp. RD_DACAR_02 through morphological and molecular analysis. The most potent strain which is similar to Enterobacter sp. SJZ-5 (named as Enterobacter sp.M003) has been chosen for BC optimization study for high BC production using modified HS media. Optimization of bacterial cellulose production using response surface methodology (RSM) with 13 runs indicated that the optimal production parameters were 17.5 g/L for carbon concentration at 277 rpm for agitation speed gave 1.7g/L cellulose. It is expected that the newly isolated bacteria will be able to provide an alternative to gelatine for halal capsule production, thus minimizing and replacing non-halal gelatine usage.
Agarwood Leaf Essential Oil Characterization and Effects on MCF-7 Breast Cancer Cells
Authors: Zainurin Nur A. A. , Hashim Yumi Z. H Y. , Azmin Nor F. Mohamed , Abbas Phirdaous
Published: November 2018

Breast cancer continues to remain as the leading cause of cancer mortality among women worldwide. Agents for prevention and cure for breast cancer are contiuously being researched. Ä°n particular, agarwood essential oil from resin infiltrated heartwood has been reported to have substantial evidences of medicinal benefits. Nevertheless, there is very limited report on agarwood leaf essential oil (ALEO). Hence, this present study was conducted to evaluate the physicochemical properties, chemical constituents and anticancer activity of ALEO. ALEO was observed to be of pale-yellow colour with sweet smell. Other physicochemical properties include refractive index of 1.44, specific gravity of 0.886, saponification value of 131.88 mg KOH/g, acid value of 2.80 mg KOH/g and iodine value of 105.07 gI2/100g. The profiling of chemical constituents using gas chromatography-mass spectrometry (GCMS) revealed 19 compounds. Hexadecanoic acid was the major compound (64.41%). The biomarkers of agarwood; azulene (0.619%) and guaiol (0.2997%) were also detected. ALEO was tested for anticancer activity against MCF-7 cancer cells using WST-8 assay. ALEO showed the IC50 value of 31% (v/v) against MCF-7 cells after 36 hours of treatment. In conclusion, this study provides information on ALEO physicochemical properties and chemical constituents that can be used as benchmark for quality assurance as well as proof that ALEO holds a potential as anticancer agent.
Online Impulse Buying: The Role of Self-Construction and Online Shop Aesthetics
Authors: Himawari Rahayu Crystal , Prayoga Tommy , Fajrianti Sheila Putri , Abraham Juneman
Published: November 2018

Online impulse buying could harm someone financially and psychologically. Previous studies have identified variables that predict impulse buying, but not many of them have examined the human’s self. This study aimed at investigating the roles of insecure self, engulfed self, and perceived aesthetic of online shop in predicting the online impulse buying. The participants were 285 private sector employees (156 males and 129 females; Mean of age of 27.1 years old; Standard deviation of age of 5.9 years) in the Greater Jakarta, Indonesia. Data analysis using multiple linear regression analysis showed that the positive prediction hypotheses were supported by empirical data. An additional descriptive analysis applying the Terror Management Theory showed that participants with higher mortality salience tend to have more online buying experience, and they are inclined to purchase more luxurious items such as jewelry and expensive watch than participants with lower mortality salience. This study contributes in developing the interdisciplinary field of psychological science and information technology by integrating the self and the virtual medium of shopping variables as well as by recommending a behavioral engineering to control online impulse buying.
Effectiveness of Bamboo Biochar Combined with Compost and NPK Fertilizer to Improved Soil Quality and Corn Yield
Authors: Situmeang Yohanes Parlindungan , Adnyana I Made , Netera Subadiyasa I Nengah , Merit I Nyoman
Published: November 2018

Biochar is a carbon-rich material produced from incomplete combustion of agricultural biomass through pyrolysis process. Bamboo biochar can increase soil carbon content, improve soil fertility and restore the degraded soil. Previously we found that bamboo-biochar was effective to improve maize yield with an optimum dosage 10.52 t ha-1 biochar. Here, we examined the effectiveness of bamboo-biochar combined with compost and NPK fertilizer to improved soil quality and crop yield. In this experiment, we used a randomized block design (RBD) with two factors, three replications. The first factor was biochar dosage (four levels), namely without biochar,  biochar dosage 5.26 t ha-1, biochar dosage 10.52 t ha-1, biochar dosage 15.78 t ha-1. The second factor is the type of fertilizer with four types, namely: without fertilizer, compost, NPK, and compost+NPK. The results showed that biochar dosage 10.52 t ha-1 combined with compost+NPK could increase P and K availability, increase total soil microbes, and improved soil quality to be very good with soil quality rating value 18. The biochar dosage 10.52 t ha-1 combined with compost+NPK gave the dry weight seed-corn highest of 12.84 tons per hectare that increased 38.61% when compared with without biochar and with compost+NPK. The highest yield 12.84 tons of the dry weight of seed-corn per hectare provides the highest effectiveness-agronomic value 119.69% and feasibility of corn crop farming in drylands value 1.27.
Comparison of Repair Costs for Small and Mid-Sizes Farm Machinery in Malaysian Oil Palm Plantation
Authors: Samsudin Siti Nabilah , El Pebrian Darius , Wan Ajeng Jok
Published: November 2018

Farm machinery has been tremendously used to perform laborious tasks and speed-up the in-field operations in Malaysian oil palm plantation. In line with significant increase in farm machinery usage in Malaysian oil palm plantation, hence, repair costs of farm machinery should be well-managed. Failure to do so may result the plantations profits will be affected.  This study aims to analyze and compare the current data of repair costs for small and mid-sizes farm machinery that are commonly used in Malaysian oil palm plantation.  Besides, this study also aims to update and adapt the values of repair factors for cumulative repair and maintenance (Crm) costs model of farm machinery in Malaysian oil palm plantation. The relevant data were collected through a survey that was carried out at several oil palm plantations in Melaka and Negeri Sembilan states of Malaysia.  The findings indicated the common sizes of farm machinery used Malaysian oil palm plantation were in range of small-size (28HP) to mid-size (75HP). It was found that annual average repair costs of mid-size farm machinery was 60.08% higher than the small-size one. Meanwhile, mean ages of mid-size farm machinery was also 80.7 % longer than the small-size one. The values of repairs factors 1 (RF1) and repairs factor 2 (RF2) for cumulative repair and maintenance costs model (Crm) of farm machinery in Malaysian oil palm plantation were 1.4061 and 1.6588, respectively.  Conclusively, the findings of study can give a valuable contribution to the oil palm plantations management in developing their strategic planning concerning to the allocation of overall costs of farm machinery.
Passengersâ€™ Perceptions on Effectiveness of Public Facilities in Hasanuddin International Airport Terminal Based on Ordered Logit Model
Authors: Ramli Muhammad Isran , Patandungan Rinto , Adisasmita S. Adji
Published: November 2018

The present study attempts to grasp the effectiveness of the public facilities such as waiting rooms, lounge, and cafe in Hasanuddin International Airport terminal, in Makassar City, Indonesia regarding the preferences of the airport passengers. This study collected the passenger's preferences data through an interview survey approach which using a questionnaire sheet instrument. The inquiry involves individual characteristics and travel attributes of passengers. The study used an ordered logit model in analyzing the passenger's preferences. The analysis results show that there are some significant variables which influence the traveler's preferences in the assessment of the effectiveness of the public facilities in the airport. The relevant variables involve airlines, trip frequency, the time interval between arrival time and boarding time, and the place of waiting for boarding time. The passenger's preferences analyzing described that the public facilities at Hasanuddin International Airport are sufficient enough.
Monitoring and Empirical Modelling for Organic Soil Subsidence Estimation in Sumatra
Authors: Nurhamidah Nurhamidah , Rusman Bujang , Istijono Bambang , Hakam Abdul , Junaidi Ahmad
Published: November 2018

A large area of peat swamp forests has disappeared due to either legally or illegally logging, drainage, agricultural conversion, fire, deforestation or large-scale developments for residential centers and industries. In Indonesia, less than 3% of the remaining forest is protected; the rest is available for logging and conversion to other land uses. Over 93% of the remaining swamp forests in Sumatera had been profoundly degraded. Change the land use to agriculture dramatically changes the characteristics of the peat substrate. Once drained, peat is highly flammable, and the fires can burn for month challenging to extinguish. The peat forest change to agriculture practices and other land use supposed to create short or long-term consequences. One of the consequences is surface degradation due to the oxidation process. A set of field measurements has been conducted using Hobo loggers. The measurement aimed at collecting data about the groundwater level and the soil temperature. The data was gathered within one and half year. The measurements were carried out on two conditions: during dry and wet periods. The difference of the model to other approaches into the measurement of land subsidence rate, this model adapts to the characteristics of the soil, the different temperature and the groundwater level over time as three additional factors that strongly affect to the rate of subsidence. The rate of subsidence in Sumatera varies from 2 until 13 cm per year due to the oxidation processes.
Evaluation of Household Pyrolitic Stove Performance: Effect of Bottom Air Apertures
Authors: Pradana Yano Surya , Hartono Muhamad , Prasetya Agus
Published: November 2018

Nowadays, the global energy crisis has been encouraging the development of renewable energy. Biomass has emerged as one of the most attractive renewable energy sources in Indonesia. Compared with fossil fuels, biomass is available in abundant quantity, renewable, and non-toxic. Pyrolitic, a method to process biomass, was performed in a household cook stove (also known as a pyrolitic stove). The pyrolitic stove will be developed as an option for substituting traditional cook stove improve the thermal efficiency. In this study, the pyrolitic of twigs of Indonesian teak in the pyrolitic stove was investigated. The influence of bottom air apertures on the household pyrolitic stove performance was studied. It was found that the decreasing number of bottom air apertures resulted in a longer leg-phase of temperature change, higher char yield, lower ash yield, and energy recovery. However, the temperature change was only slightly affected by one-third open outer air apertures condition. According to the condition performed in this study, 60 bottom air apertures in the stove provided an optimum energy recovery for cooking.
Quality Function Deployment (QFD) on Product Design Development: Group Riding Safety Equipment
Authors: Yassaruddin Ahmad Rizal , Andi Purnomo Muhammad Ridwan , Ramadhani Rizqi , Asbani Afif , Dewanti Putri Bella Azis , Dharmawan Arman Adhi
Published: November 2018

Motorcycle communities have various of activities, common one is group’s touring or taking a long journey for several purposes such charity as well for community’s gathering. Some condition found in this kind of situation, groups touring creates situations which makes whole pack member have to be focus on their groups riding. In group’s touring, it’s very common for them to using body gestures in order to communicate in a pack. They create some signals by using their body parts which commonly by hand or feet, to deliver their messages such: accelerate; turning; notifying obstacles; break; etc. This contradiction found very risky and dangerous, improper driving position as well with losing focus on driving will endanger the touring group and its surrounding. Considering the existed contradiction, researchers are trying to formulate the solution. GONDEZ "Going on Road Safely" The Touring Safety Riding Equipment with Integrated Control System. The innovation uses to alternate the contradictive condition, the device help the rider in delivering the messages without creating improper dangerous driving gestures. The research methodology adopted from KAIZEN philosophy, followed by QFD as the methods in order to identify and designing the product.
Wearable Technology in Education to Enhance Technical MOOCs
Authors: Ahmad Fesol Siti Feirusz , Salam Sazilah , Bakar Norasiken
Published: November 2018

The low completion rate issue in MOOCs has become one of the main highlights by researchers. It is reported that only 10 to 15 percent of the students were able to complete the MOOCs. This low completion rate is due to the students are less engaged with the MOOCs content causing them to become demotivated to complete the whole MOOCs. Engaging students in MOOCs environment, especially for non-technical subjects, suited very well. However, for technical MOOCs, it involves significant challenges because technical MOOCs must be able to offer the students with practice-oriented learning outcome in-order for the MOOCs to be effective and engaging. Due to the above issue, this paper discussed an improvised MOOCs model for teaching technical subjects with the intervention in the use of wearable technology. A discussion on the e-content and e-activity of the technical MOOC learning design was presented. This study implemented the proposed technical MOOC model through the MOOC development. The students’ perception of the technical MOOC was then evaluated, and all the results were explained in the discussion part. Results of the correlation test revealed that all of the technical MOOC variables correlated substantially and held a positive relationship with students’ perception variable with r=.3 to 1.0, p < .0005. In addition, this result also suggests that the learning materials produced by wearable technology do contribute towards the positive effect of students’ perception when learning technical MOOC.
The Curing Method Influence on Mechanical Behavior of Reactive Powder Concrete
Authors: Bali Ika , Kurnia Wilson
Published: November 2018

The curing method becomes important to be considered in applying the Reactive Powder Concrete (RPC) in the field. Currently, the application of RPC in the field can be simulated with the method of steam curing at 90oC that resulted in compressive strength of 102 MPa. This study used some methods of curing included the method of steam curing at 90oC in order to investigate mechanical behavior of RPC such as compressive, flexural, and splitting tensile strengths. The objective of this research is to obtain the method of in-situ curing which reasonable good in results of the mechanical behavior of RPC. There were 4 types of curing method in this study, namely the steam curing method of 90oC for 8 hours in laboratory (C1), the water curing in laboratory (C2), the in-situ steam curing with flowed steam of 3 hours per day for 7 days (C3), and the in-situ wet curing (C4). This study showed that the compressive, flexural, and splitting tensile strengths of the RPC with in-situ curing method of type C3 compared with the RPC with curing method type C1 have the different of 10.6%, 19.0%, and 13.3%, respectively. The in-situ curing method of type C3 is better than the in-situ curing method of type C4 in term of the strengths.
Effect of Edible Coating on Quality of Chips from Potato Variety Granola
Authors: Wibowo Condro , Wicaksono Rumpoko , Erminawati Erminawati
Published: November 2018

In recent years, Indonesia requires a large quantity of potatoes to meet demands. The required tuber is processing potato for producing French fries and potato chips. In order to provide sufficient supply throughout the year, import is conducted. It occurs due to the widely variety cultivated in Indonesia is Granola that reach about 90% of total area. Due to its inherent characteristic, the tuber is appropriate for table potato and not for processing one. Therefore, an alternative treatment is required for using variety Granola for processing purpose. An alternative is processed Granola tuber into flour and used it as raw material for processed food. This research aims to evaluate the properties' of potato chips that resulted from various combinations of other flours and application of edible coating. Tuber variety Granola was obtained from the potato farmers in Dieng, one of a central potato producer in Indonesia. Tuber was powdered and used as raw material for chips combined with other flours include: wheat, rice and maize flour. In addition, edible coating was introduced before frying of potato slices. Starch based edible coating was applied in this research. Quality of potato chips observed were: content of moisture, ash and fat, and sensory properties including colour, crispiness, flavor and overall acceptance. The result shows that through mixing with other flour, potato flour from variety Granola can be utilized as raw material for potato chips. Application of edible coating significantly improves the quality of chips by minimizing oil absorption during frying. Chips produced in the present research are accepted by the panellist; nonetheless, any effort is still required in order chips' quality meets the criteria of Indonesian National Standard (SNI).
The Utilization of Ceramic Membrane for Treating of Water from Sekanak River Palembang to Produce Clean Water
Authors: Sisnayati - , Said Muhammad , Nasir Subriyer , Priadi Dwi Putro
Published: November 2018

The aims of this research is to produce clean water from Sekanak River by using the ceramic membrane. Also, this study is to analyze the performance of ceramic membranes in terms of its ability to reduce the pollutants contained in water from Sekanak River. The ceramic membrane was tube-shaped, made from clay (87.5 %w), iron powder (2.5 %w) and activated carbon of oil palm empty bunch (10 %w). The operation condition of membrane separation was of 15 minutes, 30 minutes, 45 minutes, 60 minutes, 75 minutes, 90 minutes and the applied  pressure  was of 1.0 bar, 1.5 bar and 2.0 bar. The reduction pollutants (Fe, Mn, Zn, NH3-N, NO2-, PO4-3,H2S, BOD5, and TSS) concentration increased with increasing the pressure and the operating time of membrane separation. After treating by the ceramic membrane, the  average rejection of Fe, Mn, Zn, NH3-N, NO2-, PO4-3, H2S, BOD5, and TSS  are 81.22%, 95.00%,  99.00%, 85.19%, 78.85%, 73.95%, 97.78%, 87.55%, and 75.46% respectively. The pollutant concentrations in the effluent were met the Environmental Quality Standards (BML).
Time Series Predictive Analysis based on Hybridization of Meta-heuristic Algorithms
Authors: Mustaffa Zuriani , Sulaiman Mohd Herwan , Rohidin Dede , Ernawan Ferda , Kasim Shahreen
Published: November 2018

This paper presents a comparative study which involved five hybrid meta-heuristic methods to predict the weather five days in advance. The identified meta-heuristic methods namely Moth-flame Optimization (MFO), Cuckoo Search algorithm (CSA), Artificial Bee Colony (ABC), Firefly Algorithm (FA) and Differential Evolution (DE) are individually hybridized with a well-known machine learning technique namely Least Squares Support Vector Machines (LS-SVM). For experimental purposes, a total of 6 independent inputs are considered which were collected based on daily weather data. The efficiency of the MFO-LSSVM, CS-LSSVM, ABC-LSSVM, FA-LSSVM, and DE-LSSVM was quantitatively analyzed based on Theil’s U and Root Mean Square Percentage Error. Overall, the experimental results demonstrate a good rival among the identified methods. However, the superiority goes to FA-LSSVM which was able to record lower error rates in prediction. The proposed prediction model could benefit many parties in continuity planning daily activities.
Microstructure Analysis of Hydroxyapatite Coating on Stainless Steel 316L Using Investment Casting Technique for Implant Application
Authors: Nuswantoro Nuzul Ficky , Gunawarman Gunawarman , Saputra Masagus Rifqie , Nanda Is Prima , Idris Mohammad Hasbullah , Arafat Andril
Published: November 2018

Osteoporosis and traffic accident are major factor that causes bone fracture in Indonesia. One of solution for the bones fracture treatment is by using fixation implant that has similar characteristics with the human bones. Stainless Steel (SS) 316L is one of biomaterial that has been used as an implant material due to its corrosion resistance, good biocompatibility, and excellent mechanical properties. However, the bioactivity properties of the material is needed to improve by coating it with hydroxyapatite (HA). In this research, HA was coated to the surface of 316L SS by using investment casting technique. A slurry of HA was poured into casting cavity surface prior to metal casting process, and then followed by sintering at temperatures of 850oC, 900oC, and 950oC. Characterization of HA coating layer on specimen surface was conducted by Optical Microscope, Scanning Electron Microscope (SEM), and Energy Dispersive X-Ray (EDX). Hardness of  the samples was measured by Vickers Hardness Tester. Result of the experiment shows that the invvestment casting is successfully to coat the HA on the SS 316L surface. Pouring method produces HA layer with thickness (spongy and porous surface) in the range of 60 µm - 110 µm. The increasing of sintering temperature increases the hardness number of the surfaces, and affect the purity of HA, but it is not related to coating thickness. Optimum sintering temperature is obtained at 900oC which produces the best calcium and phosphate ratio. The investment casting method is found as a simple and non-expensive technique that can be used to coat HA powder to SS 316L that produces good properties and optimum crystallinity of HA that suitable for orthopedic implant application.
Designing of Straw Chopper Machine for Compost Production
Authors: Sugandi Wahyu , Zaida - , Yusuf Asep , Thoriq Ahmad , Kramadibrata Ade
Published: November 2018

Amount of straw wastes in Ciparay, Bandung, West Java Indonesia reaches 10-12 tons.ha-1 but its has not been well managed, after harvested, the remaining unused straw is abandoned on the ground and is eventually burned. In the long run, this straw burning will be very disadvantageous to farmers, especially in terms of the environmental impacts on rice paddy including decreasing soil fertility, killing soil biota, damaging soil physical properties and wasting energy. One of alternatives to utilize rice straw able to provide added value is utilizing its waste as a material to make compost on the condition that the straw is already chopped into a size of 5-10 cm according to SNI standards. Therefore, a study on rice straw chopping technology based on the composting requirements is required. The aim of this study is to design a prototype of rice straw chopper with capacity 100 kg.hr-1. The method used in this research is engineering design with observation of the reasearch, design criteria, functional and structural design, figure design, technical analysis, prototyping of rice straw chopper, machine functional and performance test. The measurement results of rice straw characteristics show that the average length, diameter, bulk density and moisture content of rice straw are 708 mm, 4 mm, 160.6 kg.m-3 and 34.6% wet basis. This straw chopper design were produces a prototype with a dimension of 1040 mm (length) x 1000 mm (height) x 465 mm (width) with a power source generator using 5.5 HP gasoline motor. The result of functional test of the straw chopper shows that the actual capacity of this straw chopper is 100.32 kg.hr-1.
Adoption of Unified Communications and Collaboration from the Perspective of Diffusion of Innovation and Service Dominant Logic: A Preliminary View
Authors: Alias Emy Salfarina , Mukhtar Muriati , Jenal Ruzzakiah
Published: November 2018

Unified Communications and Collaboration (UC&C) is a platform that has become increasingly popular in recent years and used in organizations. The service could increase flexibility, interoperability, efficiency and productivity in managing business processes. As the number and variety of UC&C tools and services increases, many organizations have developed strategic plans and allocate budget to implement UC&C. However, the adoption of some UC&C tools is still below than expected. As a service that continues to evolve in tandem with new developments in technology, it is thus important to investigate the factors that impact upon the adoption of UC&C tools and services. Via a review of the literature, this paper will posit an initial model for the adoption of UC&C. This initial model is developed by adopting the views of two important theories which are the theory of Diffusion of Innovation (DOI) and service dominant logic (SDL). The DOI theory is chosen since UC&C represents evolvement in the communications technology space, whilst SDL is chosen because of its focus on value co-creation and user centeredness, which is an important factor that will influence adoption. The key factors influencing the adoption of UC&C embodied in the model will provide useful insights for managers in implementing UC&C in their organizations.
A Design for Challenge-Based Learning of Programming
Authors: Latih Rodziah , Abu Bakar Marini , Jailani Norleyza , Mohd Ali Noorazean , Mohd Salleh Syahanim , Mohd. Zin Abdullah
Published: November 2018

Computer Science students are expected to acquire good programming skills. Both students and instructors accept that learning programming for first-year college students is fairly difficult. To assist students to achieve this goal, instructors will have to adopt a suitable design for programming courses. This paper reports on the design of a Computer Programming course based on the integrated course design approach, which was conducted by a research group at Universiti Kebangsaan Malaysia from the Faculty of Information Science and Technology. The course is designed to provide relevant teaching and learning activities, feedback, and assessment that will ultimately support the learning goals of students. The design will provide opportunities for preparation time, meaningful feedback, and a competitive feel to the course. The effectiveness of this approach is then evaluated via an online survey that was administered to first-year undergraduate students. The results obtained from 250 first-year students showed that the students were able to improve their programs with the utilization of PC2, as it allowed them to obtain prompt feedback. The use of PC2 also gives them a competitive atmosphere, which motivates them to perform better. The survey results also indicate that the students used their time to prepare for lab sessions via tutorials and self-learning.
Random Forest Weighting based Feature Selection for C4.5 Algorithm on Wart Treatment Selection Method
Authors: Nugroho Handoyo Widi , Adji Teguh Bharata , Setiawan Noor Akhmad
Published: November 2018

Research in the field of health, especially treatment of wart disease has been widely practiced. One of the research topics related to the treatment of wart disease is in order to provide the most appropriate treatment method recommendations. Treatment methods are widely used by doctors for treatment of patients with wart disease that is the method of cryotherapy and immunotherapy. Previous research has been done on  cryotherapy and immunotherapy datasets which resulted in two different prediction methods, but the accuracy level has not been satisfactory. In this study, two datasets are combined to produce a single prediction method. The method uses C4.5 algorithm combined with  Random Forest Feature Weighting (C4.5+RFFW) used to select the relevant features to improve accuracy. Experimental results show that the proposed method can improve performance with accuracy and informedness are 87.22% and 71.24%, respectively. These results further facilitate physicians in determining treatment methods for patients with a single predictive method and better-predicted performance.