Search

Land management, especially soil that is not in accordance with the rules, can cause damage / change in soil properties which ultimately impacts on the disruption of biomass production. The lack of existing data on land and or soil damage, especially in Tanjungpinang City, leads to less than optimal supervision and control of land management. Mapping the condition of land damage is absolutely necessary to be able to control land management. The purpose of the research is to assess land degradation in Tanjungpinang City, Riau Islands for biomass production. Land degradation can be modeled by scoring and overlaying four parameters: land use, slope, soil type, and rainfall, resulting in a map of potential land degradation. The results show that the criteria for land degradation in Tanjungpinang City are lightly degraded and moderately degraded. Moderately degraded criteria have the largest area spread across Dompak, Batu Sembilan, Melayu Kota Piring, Bukit Cermin, Tanjungpinang Barat, Tanjungpinang Timur, Kampung Baru, and Tanjung Ayun Sakti urban villages. The main limiting factors that restrict land use in Tanjungpinang City are soil type and slope.

Aspek ketrampilan khusus menjadi salah satu hal penting yang harus ada dalam kurikulum pembelajaran di SMK. Ketrampilan khusus yang harus dimiliki oleh lulusan SMK jurusan Kehutanan adalah ketrampilan pemetaan bidang kehutanan. Pembelajaran ketrampilan pemetaan di SMK Kehutanan perlu mengintegrasikan antara teori dan praktek langsung serta harus sesuai dengan perkembangan ilmu pengetahuan. Akan tetapi, ketrampilan pemetaan dalam bidang kehutanan belum terlalu diajarkan secara rinci di SMK Kehutanan. Hal ini disebabkan masih minimnya pengetahuan pendidik dalam hal praktek pengoperasian software sistem informasi geografis (SIG) khususnya untuk bidang kehutanan. Kondisi inilah yang menjadi latar belakang pelaksanaan kegiatan pengabdian masyarakat yang bertujuan untuk (1) memberi tambahan bekal bagi siswa SMK Bakti Nusa jurusan kehutanan mengenai bentuk pemanfaatan SIG dalam kajian kehutanan utamanya NDVI dan serapan karbon; (2) mengenalkan arti pentingnya vegetasi dalam upaya pengurangan bencana perubahan iklim. Kegiatan pengabdian dilaksanakan dengan bentuk ceramah, diskusi, dan tutorial terkait pemanfaatan SIG untuk pemetaan bidang kehutanan. Peserta kegiatan sangat antusias dalam mengikuti kegiatan dan mengapresiasi pelaksanaan kegiatan yang menarik dan sesuai dengan kebutuhan kompetensi keilmuan dari peserta. Peserta juga meminta dilaksanakan kegiatan lanjutan dengan tema pemanfaatan SIG untuk bidang kajian lingkungan lainnya serta pemanfataan drone untuk pemetaan.

The emergence of a new era of society 5.0 requires every scientific field has high technology development, up-to-date, easily accessible, and internet-based, including geography major. One of the technologies that has developed in the geography major is the use of drone technology for mapping. However, technological developments in the field of geography have not been integrated into geography learning, especially at the secondary education level. This is due to the lack of scientific updates for educators at the secondary education level regarding the development of this technology. This is the background for the implementation of this service activity which aims to introduce and improve the understanding of teachers at the secondary education level in the use of drones for various geographical studies. The service is carried out in the form of socialization related to drone technology, training and drone operation simulations. The activity participants were very enthusiastic in participating in the activities and appreciated the implementation of interesting activities and provided a lot of knowledge for participants. In fact, participants asked for further activities that were more specific to discuss the use of drones in a particular study, from data collection to data processing.

Ada banyak metode screening variabel yang bisa menangani data berdimensi tinggi. Beberapa dari metode tersebut bisa mengurangi dimensi data secara efektif dan menjamin semua variabel aktif tetap muncul dengan probabilitas tinggi. Namun, kebanyakan prosedur screening yang ada saat ini dikembangkan hanya untuk data lengkap berdimensi tinggi dan tidak layak diterapkan pada data survival dengan informasi tersensor. Metode Screening Kolmogorov-Smirnov dapat dimodifikasi untuk mengatasi masalah ini dengan mengganti fungsi distribusi kumulatif dengan fungsi survival yang diestimasi dengan estimator Kaplan-Meier. Metode ini dapat bekerja dengan berbagai tipe kovariat baik itu kontinu, diskrit, maupun kategorikal. Performa dari metode ini diukur berdasarkan studi simulasi. Suatu contoh data riil mengenai ekspresi gen juga digunakan sebagai aplikasi dari metode ini.

Survival data is the length of time until an event occurs. If the survival time is affected by other factor, it can be modeled with a regression model. The regression model for survival data is commonly based on the Cox proportional hazard model. In the Cox proportional hazard model, the covariate effect act multiplicatively on unknown baseline hazard. Alternative to the multiplicative hazard model is the additive hazard model. One of the additive hazard models is the semiparametric additive hazard model that introduced by Lin Ying in 1994. The regression coefficient estimates in this model mimic the scoring equation in the Cox model. Score equation of Cox model is the derivative of the Partial Likelihood and methods to maximize partial likelihood with Newton Raphson iterasi. Subject from this paper is describe the multiplicative and additive hazard model that applied to the duration of the birth process. The data is obtained from two different clinics,there are clinic that applies gentlebirth method while the other one no gentlebirth. From the data processing obtained the factors that affect on the duration of the birth process are baby’s weight, baby’s height and method of birth. Keywords: survival, additive hazard model, cox proportional hazard, partial likelihood, gentlebirth, duration

Penalized spline is a suitable nonparametric approach in estimating mean model in small area. However, application of the approach in informative sampling in a published article is uncommon. We propose a semiparametric mixed-model using penalized spline under informative sampling to estimate mean of small area. The response variable is explained in terms of mean model, informative sample effect, area random effect and unit error. We approach the mean model by penalized spline and utilize a penalized spline function of the inclusion probability to account for the informative sample effect. We determine the best and unbiased estimators for coefficient model and derive the restricted maximum likelihood estimators for the variance components. A simulation study shows a decrease in the average absolute bias produced by the proposed model. A decrease in the root mean square error also occurred except in some quadratic cases. The use of linear and quadratic penalized spline to approach the function of the inclusion probability provides no significant difference distribution of root mean square error, except for few smaller samples.

Background: Starting from 2014, the Indonesian government has implemented Universal Health Coverage (UHC) with the aim to make healthcare services accessible and affordable to all Indonesian citizens. A major reason for childhood cancer treatment failure in low- and middle-income countries, particularly among families with low socioeconomic status (SES), is abandonment of expensive cancer treatment. Our study compared childhood cancer treatment outcomes of the overall, low, and high SES population before and after introduction of UHC at a large Indonesian academic hospital. Methods: Medical records of 1040 patients diagnosed with childhood cancer before (2011-2013, n = 506) and after (2014-2016, n = 534) introduction of UHC were abstracted retrospectively. Data on treatment outcome, SES, and health-insurance status at diagnosis were obtained. Findings: After introduction of UHC, the number of insured patients increased from 38% to 82% (P

The Bayesian networks are a graphical probability model that represents interactions between variables. This model has been widely applied in various fields, including in the case of disaster. In applying field data, we often find a mixture of variable types, which is a combination of continuous variables and discrete variables. For data processing using hybrid and continuous Bayesian networks, all continuous variables must be normally distributed. If normal conditions unsatisfied, we offer a solution, is to discretize continuous variables. Next, we can continue the process with the discrete Bayesian networks. The discretization of a variable can be done in various ways, including equal-width, equal-frequency, and K-means. The combination of BN and k-means is a new contribution in this study called the k-means Bayesian networks (KMBN) model. In this study, we compared the three methods of discretization used a confusion matrix. Based on the earthquake damage data, the K-means clustering method produced the highest level of accuracy. This result indicates that K-means is the best method for discretizing the data that we use in this study.

The investigation of environment impact have important role to development of a city. The application of the artificial intelligence in form of computational models can be used to analyze the data. One of them is rough set theory. The utilization of data clustering method, which is a part of rough set theory, could provide a meaningful contribution on the decision making process. The application of this method could come in term of selecting the attribute of environment impact. This paper examine the application of variable precision rough set model for selecting attribute of environment impact. This mean of minimum error classification based approach is applied to a survey dataset by utilizing variable precision of attributes. This paper demonstrates the utilization of variable precision rough set model to select the most important impact of regional development. Based on the experiment, The availability of public open space, social organization and culture, migration and rate of employment are selected as a dominant attributes. It can be contributed on the policy design process, in term of formulating a proper intervention for enhancing the quality of social environment.

Many troubles in life require decision-making with convoluted processes because they are caused by uncertainty about the process of relationships that appear in the system. This problem leads to the creation of a model called the Bayesian Network. Bayesian Network is a Bayesian supported development supported by computing advancements. The Bayesian network has also been developed in various fields. At this time, information can implement Bayesian Networks in determining the extent of damage to buildings using individual building data. In practice, there is mixed data which is a combination of continuous and discrete variables. Therefore, to simplify the study it is assumed that all variables are discrete in order to solve practical problems in the implementation of theory. Discretization method used is the K-Means clustering because the percentage of validity obtained by this method is greater than the binning method.

Semarang City, as a capital city of a province in Indonesia, has experienced intensive rural or suburban migration to urban robinareas. Consequently, the land surface temperature (LST) is getting warmer in urbanized areas and leading to microscale temperature variation from time to time. The objectives of this study are 1) to investigate the geographical distribution of LST and vegetation covers in Semarang, and 2) to map microscale urban ecological condition with regards to LST based on urban thermal field variance index (UTFVI). Landsat 8 data was utilized to derive LST as well as vegetation covers by means of normalized difference vegetation index (NDVI). Next, UTFVI was classified based LST. This study revealed that relatively low NDVI values which mainly consists of built up areas and grassland are predominantly concentrated in the northern and central parts of Semarang. High NDVI values representing vegetation covers are predominantly located in the southern portion of Semarang. The most ecologically depressed areas are mainly distributed in the central portions of the city toward the northern portions of coastal areas. Prioritized sub-districts to be ecologically restored are Ngaliyan, Semarang Utara and Semarang Barat. Upcoming studies should emphasize on finding suitable measures to restore ecologically stressed areas.

The transmission to be developed in this research a manual transmission type synchromesh which will be combined with the addition of replacement clutch in the form of cone. From the research of electric vehicles that have been carried out still retain the use of manual transmission for changing from conventional vehicles fuels oil by replacing the engine with a motor as a driver. This research was conducted to design synchromesh system on manual transmission which allows gearshift done without reduction of torque in one axis so as to produce gear shifting that does not experience slowing of vehicle to improve motor efficiency in electric vehicle. The mathematical model for the propulsion system is developed using the Matlab / Simulink software package, where the throttle engine angle and the power draw synchronously as a control signal to adjust the synchromesh in shifting then simulate, process and compare to obtain the effectiveness value of the control algorithm . The designs that have been made will be tested to obtain the optimal value of the transmission performance that has been designed. The simulation image of the development of the shift in the development manual transmission uses dynamic models of external and internal linkage, synchronization and drivetrain output.Keywords: transmission , efficiency, synchromesh, simulinkABSTRAKTransmisi yang akan dikembangkan pada penelitian ini adalah transmisi manual jenis synchromesh yang akan dikombinasikan dengan penambahan pengganti kopling berupa cone .Dari penelitian kendaraan listrik yang sudah dilakukan tetap mempertahankan penggunaan transmisi manual karena merubah dari kendaraan konvensional berbahan bakar minyak dengan menggantikan mesin dengan motor sebagai penggerak. Penelitian ini dilakukan untuk mendesain sistem synchromesh pada transmisi manual yang memungkinkan perpindahan gigi dilakukan tanpa pengurangan torsi di salah satu poros sehingga menghasilkan perpindahan gigi yang tidak mengalami perlambatan kendaraan untuk meningkatkan efisiensi motor pada kendaraan listrik. Model matematika untuk sistem propulsi dikembangkan dengan menggunakan paket perangkat lunak Matlab / Simulink , di mana sudut mesin throttle dan kekuatan menarik sinkron sebagai sinyal kontrol untuk mengatur synchromesh pada perilaku pergeseran, kemudian hasinya simulasi, diolah dan dibandingkan untuk mendapatkan nilai efektivitas algoritma control. Rancangan yang telah dibuat akan diuji untuk mendapatkan nilai optimal dari unjuk kerja transmisi yang telah dirancang .Gambaran simulasi pengembangan pergeseran pada transmisi manual pengembangannya menggunakan model dinamis dari eksternal dan internal linkage, sinkronisasi dan output drivetrain.Kata kunci : transmisi, efisiensi, synchromesh, simulink

Biduk-Biduk Karst Region has great potential to absorb and store organic carbon in vegetation and soil as well as to absorb inorganic carbon through the process of dissolution. The area has important economic value in supporting the REDD Program in Berau District. The purpose of this study is (1) to identify the amount of carbon stocks in various ecosystems; and (2) to identify the amount of carbon uptake in various ecosystems in the study area. Carbon stocks are computed based on four carbon sinks, i.e., above ground biomass, underground biomass, litter, and soil organic matter using the standard measurement method of SNI 7724: 2011. Carbon sequestration is calculated based on the input of carbon from the atmosphere to ecosystems through litter fall and karstification process and the output of carbon from the ecosystem to the atmosphere through soil respiration. Litter fall is measured using the litter trap method. Karstification is measured with standard limestone tablet method. Soil respiration is calculated with the closed chamber method. The results show that the ecosystems in the Biduk-Biduk Karst Region have a potential carbon stock of 4,800.92 tons/ha with the largest value in the secondary tropical forest of 732.6 tons/ha and the lowest value in the teak forest plantation of 358.2 tons/ha. Ecosystems in the Biduk-Biduk Karst Region have a potential carbon sequestration of 37.33 tons/ha/year with the largest contribution in the primary tropical forest of 7,63 tons/ha/year.

Increased of the number of visitor at Gelatik Cave is a challenge in terms of cave management. In natural conditions, Caves are vulnerable with environmental changes especially microclimates condition. The change of microclimate inside the cave can destruct cave ornaments.Therefore, it is necessary to calculate the cave carrying capacity with microclimates as the main parameter. This research aims to (1) explore the daily variation of speleoclimate in Gelatik Cave Tourism and (2) analyze the cave tourism capacity in Gelatik Cave. Microclimate parameter that was measured in this research was temperature, relative humidity, and carbon dioxide inside the cave. Measurement of microlimate parameter was carried out automatically for 24 hours during peak season in December 2017 and low season in May 2018. Cave tourism capacity was measured using Lobo method (Lobo, 2015). The results showed that temperature, relative humidity, and carbon dioxide in the Gelatik Cave varry due to tourism activities. The most sensitive parameter is the carbon dioxide concentration inside the cave. The maximum of tourists allowed to visit Gelatik Cave is 76 visitors/ day during holidays and working days. Meanwhile, the maximum time of stay accepted for a particular area inside Gelatik Cave is 17 minutes 10 seconds during weekdays and 12 minutes 53 seconds during the holiday season.

Rough set is a set theory which is have been applied in the many areas. One of them is in data mining. The utilization of feature selection and clustering methods, that are a part of data mining application, could contribute for decision support. This paper investigates the application of rough set theory to select attribute and cluster environment impact. The Maximum Dependency Attribute (MDA) and fuzzy partition based on indiscernible relation are used to select the most important impact and cluster the object using the selected attributes, respectively. The data are collected from the field survey at identifying the environmental impact experienced by several communities in Yogyakarta, Indonesia. The results show that the water quality is the important attribute on physical and chemical aspects. Furthermore, on economic aspect, the highest attributes are immigration and employee absorption. Moreover, the number of cluster recommended is 9 based on the silhouette coefficient which is rising 0.9. This paper can be used to make recommendation to improve the quality of social environment.

Multiple imputation is one of estimation method used to impute missing observations. This method imputes missing observation several times then it is more possible to get the right estimate than just one time imputation. In this research, the method will be applied to estimate missing observations in covariates of recurrent event data. Some multiple imputation methods will be considered including combination of the event indicator, the event times, the logarithm of event times, and the cumulative baseline hazard. To compare these methods, Monte Carlo simulation will be used based on relative bias and Mean Squared Error (MSE). The recurrent events will be modelled using Cox proportional hazard model. Furthermore, real data application will be presented. Abstra k . Metode multiple imputation merupakan salah satu metode untuk mengestimasi observasi yang hilang. Metode ini melakukan imputasi beberapa kali pada observasi yang hilang sehingga kemungkinan untuk memperoleh estimasi yang tepat lebih besar dari pada hanya melakukan imputasi satu kali. Pada penelitian ini metode tersebut akan diaplikasikan pada data kejadian berulang untuk mengestimasi observasi yang hilang pada kovariat. Akan dicoba beberapa metode multiple imputation yang melibatkan pengamatan terhadap kejadian, waktu kejadian, logaritma dari waktu kejadian, dan baseline hazard kumulatif. Kejadian berulang akan dimodelkan dengan model hazard proporsional Cox. Simulasi Monte Carlo akan digunakan untuk membandingkan beberapa metode multiple imputation berdasarkan nilai bias relatif dan Mean Square Error (MSE). Lebih lanjut, aplikasi pada data real akan diberikan.