Mapping of Education Quality and E-Learning Readiness to Enhance Economic Growth in Indonesia

PRAMANA, Setia,ASTUTI, Erni Tri Korea Distribution Science Association 2022 Asian journal of business environment Vol.12 No.1

Purpose: This study is aimed to map the provinces in Indonesia based on the education and ICT indicators using several unsupervised learning algorithms. Research design, data, and methodology: The education and ICT indicators such as student-teacher ratio, illiteracy rate, net enrolment ratio, internet access, computer ownership, are used. Several approaches to get deeper understanding on provincial strength and weakness based on these indicators are implemented. The approaches are Ensemble K-Mean and Fuzzy C Means clustering. Results: There are at least three clusters observed in Indonesia the education quality, participation, facilities and ICT Access. Cluster with high education quality and ICT access are consist of DKI Jakarta, Yogyakarta, Riau Islands, East Kalimantan and Bali. These provinces show rapid economic growth. Meanwhile the other cluster consisting of six provinces (NTT, West Kalimantan, Central Sulawesi, West Sulawesi, North Maluku, and Papua) are the cluster with lower education quality and ICT development which impact their economic growth. Conclusions: The provinces in Indonesia are clustered into three group based on the education attainment and ICT indicators. Some provinces can directly implement e-learning; however, more provinces need to improve the education quality and facilities as well as the ICT infrastructure before implementing the e-learning.

Mapping of Education Quality and E-Learning Readiness to Enhance Economic Growth in Indonesia

Setia PRAMANA,Erni Tri ASTUTI 한국유통과학회 2022 Asian Journal of Business Environment (AJBE) Vol.12 No.1

Purpose: This study is aimed to map the provinces in Indonesia based on the education and ICT indicators using several unsupervised learning algorithms. Research design, data, and methodology: The education and ICT indicators such as studentteacher ratio, illiteracy rate, net enrolment ratio, internet access, computer ownership, are used. Several approaches to get deeper understanding on provincial strength and weakness based on these indicators are implemented. The approaches are Ensemble KMean and Fuzzy C Means clustering. Results: There are at least three clusters observed in Indonesia the education quality, participation, facilities and ICT Access. Cluster with high education quality and ICT access are consist of DKI Jakarta, Yogyakarta, Riau Islands, East Kalimantan and Bali. These provinces show rapid economic growth. Meanwhile the other cluster consisting of six provinces (NTT, West Kalimantan, Central Sulawesi, West Sulawesi, North Maluku, and Papua) are the cluster with lower education quality and ICT development which impact their economic growth. Conclusions: The provinces in Indonesia are clustered into three group based on the education attainment and ICT indicators. Some provinces can directly implement elearning; however, more provinces need to improve the education quality and facilities as well as the ICT infrastructure before implementing the e-learning

Torrefaction for Improving Quality of Pellets Derived from Calliandra Wood

Johanes Pramana Gentur SUTAPA,Ahmad Harun HIDYATULLAH 한국목재공학회 2023 목재공학 Vol.51 No.5

Densification is a technique used to improve biomass quality in wood pellet manufacturing and torrefaction treatment. In this study, the effects of torrefaction on the quality of Calliandra wood pellets were investigated, and pellets of Calliandra wood (Calliandra calothyrsus) and bark were evaluated. The study was conducted using a completely randomized design with two treatment factors, namely torrefaction temperature (250℃ and 300℃) and torrefaction duration (30, 45, and 60 min). The results showed that the interaction between temperature and torrefaction duration significantly affected the compressive strength, proximate value, and calorific value of the torrefied Calliandra wood pellets. An increase in the temperature and torrefaction duration decreased the compressive strength, moisture content, volatile matter content, and ash content of the torrefied Calliandra wood pellets. Conversely, the calorific value of Calliandra wood pellets increased with increasing temperature and torrefaction duration. The best-quality Calliandra wood pellets were produced at a torrefaction temperature and duration of 300℃ and 60 min, respectively. In terms of important quality parameters, ash content of 0.90% and calorific value of 6,303.80 cal/g were observed, which complied with the quality standards of Indonesian National Standard 8675:2018 and Deutsche Industrie Norm 51731.

Utilization of Sapwood Waste of Fast-Growing Teak in Activated Carbon Production and Its Adsorption Properties

( Johanes Pramana Gentur Sutapa ),( Ganis Lukmandaru ),( Sigit Sunarta ),( Rini Pujiarti ),( Denny Irawati ),( Rizki Arisandi ),( Riska Dwiyanna ),( Robertus Danu Priyambodo ) 한국목재공학회 2024 목재공학 Vol.52 No.2

The sapwood portion of fast-growing teak is mostly ignored due to its inferior quality. One of the possibilities for utilizing sapwood waste is to convert it into activated carbon that has good adsorption capabilities. The raw materials used in this research were sapwood of 14-year-old fast-growing teak sapwood (FTS) waste, which was taken from three trees from community forests in Wonosari, Gunungkidul, Yogyakarta Special Region. FTS waste was taken from the bottom of the tree up to a height of 1.3 m. The activation process is conducted with an activation temperature of 750℃, 850℃, and 950℃. The heating duration consists of three variations: 30 min, 60 min, and 90 min. The quality evaluation parameters of activated carbon include yield, moisture content, volatile matter content, ash content, fixed carbon content, adsorption capacity of benzene, adsorption capacity of methylene blue, and adsorption capacity of iodine. The results showed that the activated carbon produced had the following quality parameters: yield of 75.61%; moisture content of 1.27%; volatile matter content of 9.98%; ash content of 5.43%; fixed carbon content of 84.58%; benzene absorption capacity of 8.58%; methylene blue absorption capacity of 87.73 mg/g; and iodine adsorption capacity of 948.19 mg/g. It can be concluded that activated carbon from FTS waste has good iodine adsorption, which fulfilled the SNI 06-3730-1995 quality standard. Due to the iodine adsorption ability of FTS waste activated carbon, the conversion of FTS waste to activated carbon is categorized as a potential method to increase the value of this material.

B-Corr Model for Bot Group Activity Detection Based on Network Flows Traffic Analysis

( Dandy Pramana Hostiadi ),( Waskitho Wibisono ),( Tohari Ahmad ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.10

Botnet is a type of dangerous malware. Botnet attack with a collection of bots attacking a similar target and activity pattern is called bot group activities. The detection of bot group activities using intrusion detection models can only detect single bot activities but cannot detect bots' behavioral relation on bot group attack. Detection of bot group activities could help network administrators isolate an activity or access a bot group attacks and determine the relations between bots that can measure the correlation. This paper proposed a new model to measure the similarity between bot activities using the intersections-probability concept to define bot group activities called as B-Corr Model. The B-Corr model consisted of several stages, such as extraction feature from bot activity flows, measurement of intersections between bots, and similarity value production. B-Corr model categorizes similar bots with a similar target to specify bot group activities. To achieve a more comprehensive view, the B-Corr model visualizes the similarity values between bots in the form of a similar bot graph. Furthermore, extensive experiments have been conducted using real botnet datasets with high detection accuracy in various scenarios.

Utilization of Sapwood Waste of Fast-Growing Teak in Activated Carbon Production and Its Adsorption Properties

Johanes Pramana Gentur SUTAPA,Ganis Lukmandaru,Sigit SUNARTA,Rini PUJIARTI,Denny Irawati,Rizki ARISANDI,Riska DWIYANNA,Robertus Danu PRIYAMBODO 한국목재공학회 2024 목재공학 Vol.52 No.3

The sapwood portion of fast-growing teak is mostly ignored due to its inferior quality. One of the possibilities for utilizing sapwood waste is to convert it into activated carbon that has good adsorption capabilities. The raw materials used in this research were sapwood of 14-year-old fast-growing teak sapwood (FTS) waste, which was taken from three trees from community forests in Wonosari, Gunungkidul, Yogyakarta Special Region. FTS waste was taken from the bottom of the tree up to a height of 1.3 m. The activation process is conducted with an activation temperature of 750℃, 850℃, and 950℃. The heating duration consists of three variations: 30 min, 60 min, and 90 min. The quality evaluation parameters of activated carbon include yield, moisture content, volatile matter content, ash content, fixed carbon content, adsorption capacity of benzene, adsorption capacity of methylene blue, and adsorption capacity of iodine. The results showed that the activated carbon produced had the following quality parameters: yield of 75.61%; moisture content of 1.27%; volatile matter content of 9.98%; ash content of 5.43%; fixed carbon content of 84.58%; benzene absorption capacity of 8.58%; methylene blue absorption capacity of 87.73 mg/g; and iodine adsorption capacity of 948.19 mg/g. It can be concluded that activated carbon from FTS waste has good iodine adsorption, which fulfilled the SNI 06-3730-1995 quality standard. Due to the iodine adsorption ability of FTS waste activated carbon, the conversion of FTS waste to activated carbon is categorized as a potential method to increase the value of this material.

Air Pollution Changes of Jakarta, Banten, and West Java, Indonesia During the First Month of COVID-19 Pandemic

Setia PRAMANA,Dede Yoga PARAMARTHA,Yustiar ADHINUGROHO,Mieke NURMALASARI 한국유통과학회 2020 Asian Journal of Business Environment (AJBE) Vol.10 No.4

Purpose: This research aims to explore the level of air pollution in Jakarta, the epicenter of COVID-19 Pandemic in Indonesia and its surrounding provinces during the first month of the Pandemic. Research design, data and methodology: This study uses data, which have been obtained real time from API (Application Programming Interfaces) of air quality website. The measurements of Air Quality Index (AQI), temperature, humidity, and other factors from several cities and regencies in Indonesia were obtained eight times a day. The data collected have been analyzed using descriptive statistics and mapped using QGIS. Results: The finding of this study indicates that The Greater Jakarta Area experienced a decrease in pollutant levels, especially in the Bogor area. Nevertheless, some areas, such as the north Jakarta, have exhibited slow reduction. Furthermore, the regions with high COVID-19 confirmed cases have experienced a decline in AQI. Conclusions: The study concludes that the air quality of three provinces, Jakarta, Banten, and West Java, especially in cities located in the Jakarta Metropolitan Area during COVID-19 pandemic and large-scale social restrictions, is getting better. However, in some regions, the reduction of pollutant concentrations requires a longer time, as it was very high before the pandemic.

Mapping Poverty Distribution of Urban Area using VIIRS Nighttime Light Satellite Imageries in D.I Yogyakarta, Indonesia

KHAIRUNNISAH(KHAIRUNNISAH ),Arie Wahyu WIJAYANTO(Arie Wahyu WIJAYANTO ),Setia PRAMANA(Setia PRAMANA ) 한국유통과학회 2023 Asian Journal of Business Environment (AJBE) Vol.13 No.2

Purpose: This study aims to map the spatial distribution of poverty using nighttime light satellite images as a proxy indicator of economic activities and infrastructure distribution in D.I Yogyakarta, Indonesia. Research design, data, and methodology: This study uses official poverty statistics (National Socio-economic Survey (SUSENAS) and Poverty Database 2015) to compare satellite imagery's ability to identify poor urban areas in D.I Yogyakarta. National Socioeconomic Survey (SUSENAS), as poverty statistics at the macro level, uses expenditure to determine the poor in a region. Poverty Database 2015 (BDT 2015), as poverty statistics at the micro-level, uses asset ownership to determine the poor population in an area. Pearson correlation is used to identify the correlation among variables and construct a Support Vector Regression (SVR) model to estimate the poverty level at a granular level of 1 km x 1 km. Results: It is found that macro poverty level and moderate annual nighttime light intensity have a Pearson correlation of 74 percent. It is more significant than micro poverty, with the Pearson correlation being 49 percent in 2015. The SVR prediction model can achieve the root mean squared error (RMSE) of up to 8.48 percent on SUSENAS 2020 poverty data.Conclusion: Nighttime light satellite imagery data has potential benefits as alternative data to support regional poverty mapping, especially in urban areas. Using satellite imagery data is better at predicting regional poverty based on expenditure than asset ownership at the micro-level. Light intensity at night can better describe the use of electricity consumption for economic activities at night, which is captured in spending on electricity financing compared to asset ownership.

The Impact of Development and Government Expenditure for Information and Communication Technology on Indonesian Economic Growth

Neli AGUSTINA,Setia PRAMANA 한국유통과학회 2019 Asian Journal of Business Environment (AJBE) Vol.9 No.4

Purpose - This research is aimed to investigate the impact of the Information and Communication Technology (hereinafter ICT) development index and ICT investment on Indonesian economic growth. Research design, data and methodology - The data used consist of ICT development index, government expenditure on ICT sector, and economic growth from 33 provinces in Indonesia from 2012 to 2015. Based on the Networked Readiness Index published by the World Economic Forum (WEF), Indonesia was ranked 80th among 142 countries in 2012 and had climbed 64th in 2014. This indicates that the businesses in Indonesia have adopted ICTs to increase productivity and expand their activities. Panel data regression analysis is performed to reveal the change of the impact over time in each of the provinces. Result - The ICT development index and government expenditure for ICT have a positive effect on the economic growth of all provinces, although the impact is different in each of the provinces. There is a digital gap between the provinces, especially the large digital gap occurring with DKI Jakarta. The provinces of Eastern Indonesia such as NTT and Papua are still relatively slow in development of ICT. Conclusions - ICT development index and allocation of local government expenditure for ICT have significant effect on economic growth. ICT development index has a bigger role in increasing economic growth.

Integration of somatic mutation, expression and functional data reveals potential driver genes predictive of breast cancer survival

Suo, Chen,Hrydziuszko, Olga,Lee, Donghwan,Pramana, Setia,Saputra, Dhany,Joshi, Himanshu,Calza, Stefano,Pawitan, Yudi Oxford University Press 2015 Bioinformatics Vol.31 No.16

<P><B>Motivation:</B> Genome and transcriptome analyses can be used to explore cancers comprehensively, and it is increasingly common to have multiple omics data measured from each individual. Furthermore, there are rich functional data such as predicted impact of mutations on protein coding and gene/protein networks. However, integration of the complex information across the different omics and functional data is still challenging. Clinical validation, particularly based on patient outcomes such as survival, is important for assessing the relevance of the integrated information and for comparing different procedures.</P><P><B>Results:</B> An analysis pipeline is built for integrating genomic and transcriptomic alterations from whole-exome and RNA sequence data and functional data from protein function prediction and gene interaction networks. The method accumulates evidence for the functional implications of mutated potential driver genes found within and across patients. A driver-gene score (DGscore) is developed to capture the cumulative effect of such genes. To contribute to the score, a gene has to be frequently mutated, with high or moderate mutational impact at protein level, exhibiting an extreme expression and functionally linked to many differentially expressed neighbors in the functional gene network. The pipeline is applied to 60 matched tumor and normal samples of the same patient from The Cancer Genome Atlas breast-cancer project. In clinical validation, patients with high DGscores have worse survival than those with low scores (<I>P</I> = 0.001). Furthermore, the DGscore outperforms the established expression-based signatures MammaPrint and PAM50 in predicting patient survival. In conclusion, integration of mutation, expression and functional data allows identification of clinically relevant potential driver genes in cancer.</P><P><B>Availability and implementation:</B> The documented pipeline including annotated sample scripts can be found in http://fafner.meb.ki.se/biostatwiki/driver-genes/.</P><P><B>Contact:</B> yudi.pawitan@ki.se</P><P><B>Supplementary information:</B> Supplementary data are available at <I>Bioinformatics</I> online.</P>