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GEOSFERA INDONESIA, Journal of Geography
Published by Universitas Jember
Geosfera Indonesia : | ISSN: 2598-9723 (Print)| ISSN: 2614-8528 (Online) is published by Department of Geography Education, University of Jember, Indonesia. We accept mainly research-based articles related to geography. Geosfera Indonesia welcomes contributions in such areas of current analysis in: (1) Geography Education, (2) Geography (Physical Geography and Human Geography), (3) Geographic Information System (GIS), (4) Remote Sensing, (5) Environmental Science, and (6) Disaster Mitigation. Since volume 1, it is published three times a year in April, August, and December. Every issue consisted of 12 articles.
Articles
30
Articles
THE CARRYING CAPACITY ON ECOSYSTEM SERVICES OF LAND USE CHANGE AT BORDER ENTIKONG

Irsan, Robby, Mutaali, Luthfi, Sudrajat, S

GEOSFERA INDONESIA, Journal of Geography Vol 3 No 2 (2018): GEOSFERA INDONESIA
Publisher : Department of Geography Education

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Abstract

Entikong Region is located in Sanggau Regency, West Kalimantan Province, Indonesia, which is directly adjacent to Malaysia. Land use in the Border Area, which is massive and irregular, results in environmental degradation, deculturization, and lack of living standards of the community. High population growth in the border areas leads to excessive use of natural resources, and used land is not appropriately allocated. The land has limited function, and if the demand for the land is greater than the carrying capacity, there will be an imbalance that results in land degradation and its environment. The purpose of this study is to identify the type and extent of land function switch, analyze provider services as part of the Land Support Capacity Ecosystem services, and identify the Accuracy of Image Interpretation. The results showed that the increasing area of massive land use comes from a mixed plantation in 2017 increased by 60.6% of the total area of Entikong District. Degradation occurs in primary forest land use component which is only 18.6% of Entikongs total area in 2017. This indicates that the use of mixed plantation land acquires the protected forest, with many palm, rubber, and pepper. Similarly, the percentage of accuracy test from the interpretation result reaches 83.33% from 42 sample points in accordance with the real conditions. The Value of Clean Water Ecosystem Service Providers in 2011 was 0.36 and was 0.33 in 2017. Then within the period of almost 7 years, it is decreased by 0.03. Thus, the Ecosystem Service Index of clean water providers has a value less than 1, it means the function of the area as a provider of clean water is very small. Similarly, the Provider Ecosystem Services Index for Foodstuffs, the Value of Food Ecosystem Services Index in 2011 was 0.32 and was 0.31 in 2017, then within the nearly 7-year period, it is decreased by 0.01. The ecosystem services index as a food supply provider for the Entikong border area is very low (less than 1) which means the carrying capacity of the environment is not good enough for supplying food needs in Entikong. This indicates that there is a reduction in the availability of environmental services, and if it continues, then Environmental Assets declines sharply and services derived from nature will be lost or will be expensive in the near future. Thus, optimization and revitalization of land use are necessary by applying various policies related to development in the border area in Entikong District. Keywords: Borders, Land Use, Ecosystem Provider Services.   References Admadhani, D. N., Hajil, A. H. S., & Susanawati, L. D. (2013). Analysis of Water Supply and Water Demand for Carrying Capacity Assessment ( Case Study of Malang ). Journal of Natural Resources and Environment. Asdak, C., & Salim, H. (2006). Water Resource Capacity As a Spatial Planning Consideration. Journal of Environmental Engineering P3TL-BPPT. Ernan Rustiadi, Sunsus Saefulhakim, D. R. P. (2011). Planning and Regional Development. Restpent Press. Ghozali. (2013). Referral of Land Use Utilization Through Ecological Footprint in Gresik Regency. Territory and Environment, 1 No.1, 67–78. Hamidy, Z. (2003). Land Cover Change, Composition, and Life Type in Suakaidupan Cikepuh. Faculty of Forestry, IPB. Muta’ali, L. (2015). Regional Analysis Techniques For Regional Planning, Spatial Planning, and Environment (Februari). Yogyakarta: Faculty of Geography UGM. National Standardization Department. (2010). Classification of Land Cover. Purwadhi. (2008). Introduction Remote Sensing Imagery Interpretation. Semarang: LAPAN. Riqqi, A. (2014). Design Concept Techniques Determination of Supporting Capacity and Capacity of the National Environment and Islands / Islands And Provinces. Bali: KLH. Saripin, I. (2003). Identify Land Use Using Landsat TM Imagery. Agricultural Engineering Bulletin. Varika. (2015). Monitoring of Ecosystem Service-Based Ecotourism (Recreation and Ecotourism) Capacity in 2000 and 2015 Using Landsat Image in Badung Regency, Bali. Viska. (2012). Land Use Direction in Batu City Based on Ecological Ecosystem Approach. Pomits Technique, 1 No.1, 1–6.    

LEARNING ACTIVITIES IN HIGHER ORDER THINKING SKILL (HOTS) ORIENTED LEARNING CONTEXT

Nofrion, N, Wijayanto, Bayu

GEOSFERA INDONESIA, Journal of Geography Vol 3 No 2 (2018): GEOSFERA INDONESIA
Publisher : Department of Geography Education

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Abstract

The development of 21st century life requires the higher-level thinking ability developmental for learners. HOTS learning is characterized by; 1) Analysis, Evaluation and Creating, 2) Logical reasoning, 3) Consideration and critical thinking, 4) Problem Solving and Creative Thinking. One effort that can be done by educators to develop higher-level thinking ability for learners is by facilitating learners to do Advanced Learning Activities (ABL) that include: 1) processing/ analyzing, 2) Communicating/ dialogue, 3) discuss/ collaborate, 4) presents/ constructs. ABL is a continuation of Basic Learning Activities which includes; 1) Observing (combination of seeing and hearing), 2) trying/ questioning, 3) searching/ collecting. Therefore, in learning, educators should be more focused on giving learners space to do ABL while still allowing time for ABD as a warm-up activity or initial activity (Schaffolding). The way that can be done as a trigger of Advanced Learning Activities is to present more questions/ tasks/ problems on high cognitive level that is C4, C5, and C6 in every learning. High-level questions/ tasks/ problems will also encourage learners to dialogue and discuss so that collaboration in learning will be created. Keywords: Basic Learning Activity/ABD, Advanced Learning Activities/ ABL, HOTS oriented Learning   References Brookhart, L. Susan. 2010. How to assess Higher Order Thinking Skills in Your Class. ASCD. Alexandria, Virginia USA Hamalik, Oemar. 2001. Learning strategies. Jakarta. Bumi Aksara -------------------- 2010. Learning strategies. Jakarta. BumiAksara Hanafiah, Nanang & Suhana, Cucu. 2010. Learning Strategies. Bandung. Refika Aditama Marzano, R. J., & Kendall, J. S. (2007) .The new taxonomy of educational objectives (2nd ed.). Thousand Oaks, CA: Sage Marzano, R. J & Heflebower, T. 2012.Teaching & Assssing 21st Century Skills (The Classroom Strategies Series). EBook from marzanoresearch.com Nofrion. 2017. Geography Learning Models and Strategies (Designing HOTS and Learning Collaborative Learning). Padang. Sukabina Publisher N, Nofrionet al.2018. Effectiveness of EXO OLO TASK Learning Model Based on Lesson Study in Geography Learning IOP Conf. Ser .: Earth Environ. Sci. 145 012038 Parjito. 2015. Vision of 21st Century Geography Education. Proceedings of the P3GI National Seminar. Poor. ISBN: 978 - 602 - 71506 - 3 – 8 Prayitno.2009 Basic Teaching and Praxis Education. Grasindo. Jakarta Sardiman. 2010. Interaction and Motivation of Learning Teaching. Jakarta. Rajawali Press Silbermen, L. Melvin. 2006. Active Learning: 101 Learning Methods Active Students. Bandung. Nusamedia Law Number 20 of 2003 concerning National Education Systems Woolfolk. 2009. Educational Psychology (Active Learning Edition), Tenth Edition. Yogyakarta. Student Library

AN ASSESSMENT OF SPATIAL VARIATION OF LAND SURFACE CHARACTERISTICS OF MINNA, NIGER STATE NIGERIA FOR SUSTAINABLE URBANIZATION USING GEOSPATIAL TECHNIQUES

Yakubu, Bashir Ishaku, Hassan, Shua’ib Musa, Asiribo, Sallau Osisiemo

GEOSFERA INDONESIA, Journal of Geography Vol 3 No 2 (2018): GEOSFERA INDONESIA
Publisher : Department of Geography Education

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Abstract

Rapid urbanization rates impact significantly on the nature of Land Cover patterns of the environment, which has been evident in the depletion of vegetal reserves and in general modifying the human climatic systems (Henderson, et al., 2017; Kumar, Masago, Mishra, & Fukushi, 2018; Luo and Lau, 2017). This study explores remote sensing classification technique and other auxiliary data to determine LULCC for a period of 50 years (1967-2016). The LULCC types identified were quantitatively evaluated using the change detection approach from results of maximum likelihood classification algorithm in GIS. Accuracy assessment results were evaluated and found to be between 56 to 98 percent of the LULC classification. The change detection analysis revealed change in the LULC types in Minna from 1976 to 2016. Built-up area increases from 74.82ha in 1976 to 116.58ha in 2016. Farmlands increased from 2.23 ha to 46.45ha and bared surface increases from 120.00ha to 161.31ha between 1976 to 2016 resulting to decline in vegetation, water body, and wetlands. The Decade of rapid urbanization was found to coincide with the period of increased Public Private Partnership Agreement (PPPA). Increase in farmlands was due to the adoption of urban agriculture which has influence on food security and the environmental sustainability. The observed increase in built up areas, farmlands and bare surfaces has substantially led to reduction in vegetation and water bodies. The oscillatory nature of water bodies LULCC which was not particularly consistent with the rates of urbanization also suggests that beyond the urbanization process, other factors may influence the LULCC of water bodies in urban settlements. Keywords: Minna, Niger State, Remote Sensing, Land Surface Characteristics   References Akinrinmade, A., Ibrahim, K., & Abdurrahman, A. (2012). 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Lidar: range-resolved optical remote sensing of the atmosphere: Springer Science & Business. Wellmann, T., Haase, D., Knapp, S., Salbach, C., Selsam, P., & Lausch, A. (2018). Urban land use intensity assessment: The potential of spatio-temporal spectral traits with remote sensing. Ecological Indicators, 85, pp. 190-203. Whiteside, T. G., Boggs, G. S., & Maier, S. W. (2011). Comparing object-based and pixel-based classifications for mapping savannas. International Journal of Applied Earth Observation and Geoinformation, 13(6), pp. 884-893. Willhauck, G., Schneider, T., De Kok, R., & Ammer, U. (2000). Comparison of object oriented classification techniques and standard image analysis for the use of change detection between SPOT multispectral satellite images and aerial photos. Proceedings of XIX ISPRS congress. Winker, D. M., Vaughan, M. A., Omar, A., Hu, Y., Powell, K. A., Liu, Z., . . . Young, S. A. (2009). Overview of the CALIPSO mission and CALIOP data processing algorithms. Journal of Atmospheric and Oceanic Technology, 26(11), pp. 2310-2323. Yengoh, G. T., Dent, D., Olsson, L., Tengberg, A. E., & Tucker III, C. J. (2015). Use of the Normalized Difference Vegetation Index (NDVI) to Assess Land Degradation at Multiple Scales: Current Status, Future Trends, and Practical Considerations: Springer. Yu, Q., Gong, P., Clinton, N., Biging, G., Kelly, M., & Schirokauer, D. (2006). Object-based detailed vegetation classification with airborne high spatial resolution remote sensing imagery. Photogrammetric Engineering & Remote Sensing, 72(7), pp. 799-811. Zhou, D., Zhao, S., Zhang, L., & Liu, S. (2016). Remotely sensed assessment of urbanization effects on vegetation phenology in Chinas 32 major cities. Remote Sensing of Environment, 176, pp. 272-281. Zhu, Z., Fu, Y., Woodcock, C. E., Olofsson, P., Vogelmann, J. E., Holden, C., . . . Yu, Y. (2016). Including land cover change in analysis of greenness trends using all available Landsat 5, 7, and 8 images: A case study from Guangzhou, China (2000–2014). Remote Sensing of Environment, 185, pp. 243-257.            

GEOGRAPHY LITERACY OF OBSERVATION INTRODUCTION LANDSCAPE REPRESENTATION PLACE FOR STUDENT EXPERIENCE

Ikhsan, Fahrudi Ahwan, Kurnianto, Fahmi Arif, Nurdin, Elan Artono, Apriyanto, Bejo

Geosfera Indonesia Vol 3 No 2 (2018): GEOSFERA INDONESIA
Publisher : Department of Geography Education

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Abstract

This study aims to describe the understanding of geography literacy and student experience with landscape recognition observations using an ethnometodology perspective. The subject of this study was the chairman of each landscape recognition practice group student geography education program from University of Jember. The results of this study that geography literacy has a dimension of relevance to geographic skills in representing contextual phenomena and places from landscape recognition observation activities. The results of both observational studies provide research experience, motivation, critical and scientific thinking skills for students represented in the mapping of the area. Keywords: Geography Literacy, Student Experience, Ethnometodology References Bogdan, R. And Biklen, S.K.(1998). Qualitative Research for Education: An introduction to theories and methods. Boston: Allyn and Bacon, Inc. Boogart II, Thomas A. (2001). The Powwer of Place: From Semiotics to Ethnogeography, Middle States Geograher, 2001, 34: 38-47. Boyle, A., Maguire, S., Martin, A., Milsom, C., Nash, R., Rawlinson, S., Turner, A., Wurthmann, S. & Conchie, S.(2007). Fieldwork is Good: The Student Perception and the Affective Domain, Journaal of Geography in Higher Education, 31(2), 299-317. Chappell, Adrian.(2007). Using Teaching Observations and Reflective Practice to Challenge Conventions and Conceptions of Teaching in Geography, Journal of Geography in Higher Education, 32(2), 257-268. Comber, Barbara.(2017). Literacy Geography and Pedagogy: Imagining Translocal Research Alliances for Educational Justice, Journal Literacy Research: Theory, Method, and Practice, Sagepub, University of South Australia, 66, 53-72. Cotton, Debby R.E., Stokes, Alison, & Cotton, Peter A.(2010).Using Observational Methods to Research the Student Experience, Journal of Geography in Higher Education, 34(3), 463-473. Denzin, Norman K. And Lincoln Yvonna S. (2008). Strategies of Qualitative Inquiry. California: Sage Publications, Inc. Fatchan, Achmad. (2015). Methodology Research Qualitative of Ethnography and Ethnometodology Approaches for Social Sciences. Yogyakarta: Ombak. Guertin, L., Stubbs, C., Millet, C., Lee, T., & Bodek, M.(2012). Enchancing Geographic and Digital Literacy with a Student Generated Course Portfolio in Google Earth, Journal of College Science Teaching, 42(2), 32-37. Hunter, Nancee.(2016). Assesing Sense of Place and Geo-literacy Indicatorc as Learning Outcomes of an International Teacher Professional Development Program, Dissertation, Porland State University. Johnston, B. And Webber, S. (2003). Information Literacy in Higher Education: a review and case study, Studies in Higher Education, 28 (3), 335-352. Levinson, S.C.(2003). Space in Language and Cognition: Explorations in Cognitive Disversity. New York: Cambridge University Press. Lloyd, Annemaree.(2006). Information Literacy Landscapes: an emerging picture, Journal of Documentation, 62 (5), 570-583. Miles, Matthew B, Huberman, A. Michael, and Saldana, Johnny.(2015). Qualitative Data Analysis A Methods Sourcebook. Thousand Oaks, CA: Sage Publications. Minca, Claudio.(2013). The Cultural Geographies of Landscape, Hungarian Geographical Bulletin 62(1), 47-62. National Research Council.(2005). Learning to Think Spatially. GIS as a Support System in the K12 Curriculum. Washington DC: National Research Council and National Academies Press. Ottati, Daniela F.(2015). Geographical Literacy, Attitudes, adn Experiences of Freshman Students: A Qualitative Study at Florida International University, Dissertation. Miami: Florida International University. Patton, M.Q.(2002). Qualitative Research and Evaluation Methods (3rd ed.). Thousand Oasks CA: Sage Publications. Stokes, A. & Boyle, A.P.(2009). The Undergraduate Geoscience Fieldwork Experience: Influencing Factors and Implications for Learning, in: S.J. Whitmeyer, D.W. Mogk & E.J. Pyle (Eds) Field Geology Education-Historical Perspectives and Modern Approach, 461, Geological Society of America, 313-321. Turner, S., & Leydon, J.(2012). Improving Geography Literacy among First Year Undergraduate Students: Testing the Effectivess of Online Quizzes, Journal of Geography, 111(2), 54-66.

THE SPATIAL STUDY OF HEALTH CONDITION OF SOCIETY TOWARDS INCOME GRADE IN PRAMBANAN, KLATEN REGENCY

Fatonah, Ayu, Setiyani, Fitria Febri, Winardany, Hafiz, Samidu, S, Murdiansyah, Bagas Anindra, Aini, Fitri Nur

GEOSFERA INDONESIA, Journal of Geography Vol 3 No 2 (2018): GEOSFERA INDONESIA
Publisher : Department of Geography Education

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Abstract

Health is the most important aspect of the human being life. A good health will affect other aspects, one of which will affect the economic aspect of the income earned by individuals. The purpose of this research is to know the correlation between health condition and income of society in Prambanan Sub-district. This research uses quantitative descriptive research, with the research variables such as health data and income data. The sample in this study amounted to 2,235 respondents from 16 Villages in Prambanan Sub-district, Klaten. The Data Collection Method used in this research are interview, observation and questionnaire with the data analysis technique is quantitative descriptive analysis which is non statistical analysis with frequency table. The results show that there is not a significant correlation between health and income. Pereng Village has an average of "High" income with the population  average monthly income > Rp. 1.500.000,00 of 52.04% but has health condition in the "Medium" level. Randusari Village has health condition in "Medium" level whereas Randusari Village has average "Low" income with population with average income per month < Rp. 500.000,00 for 44,44%. Keywords: Health Conditions, Income   References Alviana, Hendika. 2017. The Development of the Economic Potential of the Local Areas to Reduce the Gap in Growth between Subdistrict in Sukoharjo Regency years 2010-2015. [Article Scientific Publications]. Surakarta: Muhammadiyah University Of Surakarta Atmawikarta, Arum. (2009). "A health Investment For economic development". BAPPENAS: Director of Community Health and Nutrition BPS Klaten Regency. (2016). Human development Index Klaten 2016. Klaten Regency and Klaten: BPS/BPS-Statistics of Klaten Regency. BPS Klaten Regency. (2016). Sub Prambanan in Number 2016. Klaten Regency and Klaten: BPS/BPS-Statistics of Klaten Regency. Fadhilah, Achmad. Spatial Analysis of the Level of Insecurity Dengue Feverfor Priority Handling System Using geographical InfromasiPrambanan Sub-district Klaten Regency. Analysis of the Spatial Level, 295-305. Hartono, Budiantoro. (2008). Analysis of the Imbalance of Economic Development in the Province of Central Java. [Thesis]. Semarang: University of Diponegoro Klaten Regency. (2015). Community Health Profile Klaten 2015. Head Of Department: Klaten Regency. Ismail M. (2013).The Influence of Family Income Level, Education Level of the Mother and the Mothers Employment Status for Nutritional Status in the District of Darul Makmur, Nagan Raya Regency [Thesis]. University Of Teuku Umar. Mutaali, Lutfi. 2015. The Regional Analysis Techniques for Planning regions, Spatial, and Environment. Yogyakarta: Faculty Of Geography Gadjah Mada University, Publisher. Putra, Andi NepiErtanta. (2012). Economic Growth Imbalances between Klaten Regency in Central Java province Year 1999 – 2009 [Thesis]. Yogyakarta: Atma Jaya University of Yogyakarta Sudarlan. (2015). Economic Growth, Inequality,and Poverty in Indonesia. Journal Exists, Vol 11 (1), 3036-3213 Susilo, Abdi. (2017). Analysis of Economic Growth and Inequality of Income Distribution between the Central Java Regency [Thesis]. Surakarta: Muhammadiyah University Of Surakarta. Syamsurijal. (2008). The Influence of the Level of Health of the Revenue capita Growth Rate Against in South Sumatra. Journal of Economics and Development Policy, Vo1 6 (1), 1-9. Wisana, I Dewa Gede Karma. (January 2001). Health as an Investment. Journal of Economics and the Development of Indonesia, vol. 1 (1), 42-51. Yuhendri. (2013). Influence the Quality of Education, Health,and Investment towards Growth of West Sumatra[Article Publication]. Padang: State University of Padang Yuliartika, Febriyana Niken., Larasati, Dheya Amalia., Sehan, Septia Mahadeka Putri., Okctaviana, Angel., Alfredo, Septian Briantama., (2017). Study of the Level of Knowledge of Early Warning Systems Individual and Household in the Face of Devastating Earthquake in Wonogiri. Presented at the National Seminar on Geography UMS 2017, Surakarta, Central Java, May 22, 2017  

INVESTIGATED THE IMPLEMENTATION OF MAP LITERACY LEARNING MODEL

Segara, Nuansa Bayu, Maryani, Enok, Supriatna, Nana, Ruhimat, Mamat

GEOSFERA INDONESIA, Journal of Geography Vol 3 No 2 (2018): GEOSFERA INDONESIA
Publisher : Department of Geography Education

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Abstract

This article presents the results of the first implementation of map literacy learning model in middle school classes - this is the preliminary test. The implementation of this learning model will gain optimal results when it is conducted by following all the component of the model such as the syntax, theoretical framework, social system, teachers roles, and support system. After the model implementation has been completed, the results showed that there was significantly different in students spatial thinking skills before and after the treatment. However, the implementation also revealed that the model has some technical issues and thus to be improved. In a social system revision, the teacher has to be flexibly provide scaffolding every time he/she sees that the students need it. Teachers book is significantly important to help a teacher lead the learning process. After improvement of the model has been completed, then it is ready to be implemented in the main field testing stage. Keywords: map literacy, social studies learning, spatial thinking   References Abbasnasab, S., Rashid, M., & Saad, M. (2012). Knowledge with Professional Practice A Sociocultural Perspective on Assessment for Learning : The Case of a Malaysian Primary School ESL Context, 66, 343–353. http://doi.org/10.1016/j.sbspro.2012.11.277 Adeyemi, S. B., & Cishe, E. N. (2015). Effects of Cooperative and Individualistic Learning Strategies on Students’ Map Reading and Interpretation. International Journal of Arts & Sciences, 8(7), 383–395. Bednarz, S. W., Acheson, G., & Bednarz, R. S. (2006). Maps and Map Learning in Social Studies. Social Education, 70(7), 398–404. http://doi.org/10.4324/9780203841273 Brophy, J., & Alleman, J. (2009). Meaningful social studies for elementary students. Teachers and Teaching, 15(3), 357–376. http://doi.org/10.1080/13540600903056700 Cohen, L., Manion, L., Morrison, K., & Wyse, D. (2010). A Guide To Teaching Practice (5th ed.). London and New York: Rotledge. Churcher, K. M. A., Downs, E., & Tewksbury, D. (2014). “ Friending ” Vygotsky : A Social Constructivist P edagogy of Knowledge Building Through Classroom Social Media Use, 14(1), 33–50. Durmuş, Y. T. (2016). Effective Learning Environment Characteristics as a requirement of Constructivist Curricula: Teachers’ Needs and School Principals’ Views. International Journal of Instruction, 9(2), 183–198. http://doi.org/10.12973/iji.2016.9213a Fani, T., & Ghaemi, F. (2011). Implications of Vygotsky ’ s Zone of Proximal Development ( ZPD ) in Teacher Education : ZPTD and Self-scaffolding. Procedia - Social and Behavioral Sciences, 29(Iceepsy), 1549–1554. http://doi.org/10.1016/j.sbspro.2011.11.396 Gauvain, M. (1993). The Development of Spatial Thinking in Everyday Activity. Developmental Review, 13, 92–121. Hribar, G. C. (2015). Using Map-Based Investigations with Elementary Students. In ESRI Education GIS Conference (pp. 1–26). Huynh, N. T., & Sharpe, B. (2013). An Assessment Instrument to Measure Geospatial Thinking Expertise An Assessment Instrument to Measure Geospatial Thinking Expertise. Journal of Geography, 112(October 2014), 3–41. http://doi.org/10.1080/00221341.2012.682227 Ishikawa, T. (2012). Geospatial Thinking and Spatial Ability: An Empirical Examination of Knowledge and Reasoning in Geographical Science. The Professional Geographer, (July 2015), 121018062625002. http://doi.org/10.1080/00330124.2012.724350 Jessie A. (1951). Maps and Slow-Learners. Journal of Geography, 50:4, 145-149, DOI: 10.1080/00221345108982661 Jo, I., Bednarz, S., & Metoyer, S. (2010). Selecting and Designing Questions to Facilitate Spatial Thinking. The Geography Teacher, 7(2), 49–55. http://doi.org/10.1080/19338341.2010.510779 Joyce, B.R., Weil, M., & Calhoun, E. (2014). Models of Teaching (8th Ed). New Jersey: Pearson Education. Key, L.V., Bradley, J.A., & Bradley, K.A. (2010).Stimulating Instruction in Social Studies. The Social Studies, 101:3, 117-120, DOI: 10.1080/00377990903283932 Leinhardt, G., Stainton, C., & Bausmith, J. M. (1998). Constructing Maps Collaboratively. Journal of Geography, 97(1), 19–30. http://doi.org/10.1080/00221349808978821 Logan, J. R. (2012). Making a Place for Space: Spatial Thinking in Social Science. Annual Review of Sociology, 38(1), 507–524. http://doi.org/10.1146/annurev-soc-071811-145531 Logan, J. R., Zhang, W., & Xu, H. (2010). Applying spatial thinking in social science research. GeoJournal, 75(1), 15–27. http://doi.org/10.1007/s10708-010-9343-0 National Reseach Council. (2006). Learning to Think spatially. Washington, D.C.: The National Academic Press. Retrieved from www.nap.edu NCSS. (2016). A Vision of Powerful Teaching and Learning in the Social Studies, 80(3), 180–182. Saekhow, J. (2015). Steps of Cooperative Learning on Social Networking by Integrating Instructional Design based on Constructivist Approach. Procedia - Social and Behavioral Sciences, 197(February), 1740–1744. http://doi.org/10.1016/j.sbspro.2015.07.230 Uttal, D. H. (2000). Maps and spatial thinking: a two-way street. Developmental Science, 3(3), 283–286. http://doi.org/10.1111/1467-7687.00121 Verma, K. (2014). Geospatial Thinking of Undergraduate Students in Public Universities in The United States. Texas State University. Wiegand, P. (2006). Learning and Teaching with Maps. London and New York: Routledge Taylor & Francis Group. Retrieved from http://cataleg.udg.edu/record=b1373859~S10*cat          

LEVEL OF LANDSLIDE SUSCEPTIBILITY IN CIBAL DISTRICT OF MANGGARAI EAST NUSA TENGGARA

Bate, Dominikus Victorius, Karyanto, Puguh, Rindarjono, Moh. Gamal

GEOSFERA INDONESIA, Journal of Geography Vol 3 No 2 (2018): GEOSFERA INDONESIA
Publisher : Department of Geography Education

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Abstract

This research aims to determine the degree of susceptibility of landslides in Cibal Districts. The method used in this research is descriptive survey method. The population in this research is all of the land in Cibal Districts. data collection technique is done by using observation technique and documentation study. Data analysis technique in this research uses crosstab technique. The results of this study can be seen that the level of susceptibility of landslides in Cibal based on crosstab results, there are three categories of vulnerability of landslide , they are low, medium and high. Low landslide susceptibility rate of 6.979,65 hectares or 64.09% is found in Nine sub-districts / village. The moderate landslide susceptibility rate has an area of 3,634.67 hectares or 33.38%, in seven villages. While the high landslide susceptibility rate is found only in one village with an area of 275.65 hectares or 2.35% of the total area of Cibal districts. Keywords: Susceptibility, Landslide, Cibal District   References Aditya, Triyas & Marjuki, Bramantyo, (2009) Preparation of DIY Province Risk Map. Yogyakarta: Provincial Government of DIY & PPMU SCDRRRegional Disaster Mitigation Agency (BPBD) of Manggarai Regency in 2017 Nurjanah. 2012. Disaster Management. Bandung: Alfabeta Regulation of National Agency for Disaster Management 04 of 2008 on guidelines for the preparation of disaster management Ministry of Public Works Regulation No. 22 of 2007 Mutaali. 2012. Environmental Support Capacity for Regional Development Planning. Yogyakarta: Faculty of Geography Gadjah Mada Univercity. Gems, S. 2016. Risk Management And Landslide Mitigation. UGM: YogyakartaSugiyono. 2016. Quantitative Research Methods, Qualitative, And R & D. Bandung: AlfabetaSupretno, J. (1996). Statistics, Theory and Applications. Jakarta: Erlangga Suripin.2002. Preservation of Land and Water Resources.Yogyakarta.   

ANALYSIS OF RAINY DAYS AND RAINFALL TO LANDSLIDE OCCURRENCE USING LOGISTIC REGRESSION IN PONOROGO EAST JAVA

Muriyatmoko, Dihin, Phuspa, Sisca Mayang

GEOSFERA INDONESIA, Journal of Geography Vol 3 No 2 (2018): GEOSFERA INDONESIA
Publisher : Department of Geography Education

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Abstract

Referred to data of Badan Nasional Penanggulangan Bencana (BNPB) and Kementerian Kesehatan Republik Indonesia (Kemenkes RI), almost landslide occurrence in Ponorogo always starts with high-intensity rain. This research aimed to determine simultaneously correlation and partial assessment impact of rainy days every month and monthly rainfall toward landslide occurrence in Ponorogo using logistic regression. The data collection was conducted through Badan Pusat Statistik (BPS) in the book of Ponorogo Regency in Figure on 2012 to 2016. The existing data shows that in sixty months have been twenty-six times landslides occurrence in Ponorogo districts.  The data statistically analyzed in simultaneous proves that contribution of rainy days and rainfall to landslide were included adequate correlation (Nagelkerke R Square = 25.4 % and Cox & Snell R Square = 36.9 %) and in partial test proves that rainy days have significant impact (sig. = 0.024) and rainfall does not significant impact (sig. = 0.291) (α = 0.05) to landslide occurrence in Ponorogo regency.  The rainy days per month were abled applied to predict for possible landslide elsewhere. Keywords: rainy days, rainfall, landslide, Ponorogo, logistic regression   References Aditian, A., Kubota, T., & Shinohara, Y. (2018). Geomorphology Comparison of GIS-based landslide susceptibility models using frequency ratio , logistic regression , and arti fi cial neural network in a tertiary region of Ambon , Indonesia. Geomorphology Journal, 318, 101–111. https://doi.org/10.1016/j.geomorph.2018.06.006 Agresti, A. (1996). An Introduction to Categorical Data Analysis. Wiley. https://doi.org/10.1002/0470114754 Amri, M. R., Yulianti, G., Yunus, R., Wiguna, S., Adi, A. W., Ichwana, A. N., … Septian, R. T. (2016). Risiko Bencana Indonesia. Jakarta: Badan Nasional Penanggulangan Bencana. Badan Nasional Penanggulangan Bencana. (2018). Data Pantauan Bencana. Retrieved June 21, 2018, from http://geospasial.bnpb.go.id/pantauanbencana/data/index.php Badan Perencanaan Pembangunan Daerah Ponorogo. (2013). Pembangunan Ponorogo Dalam Angka 2013. Ponorogo. Retrieved from https://ponorogokab.bps.go.id/publication/ Badan Perencanaan Pembangunan Daerah Ponorogo. (2014). Pembangunan Ponorogo Dalam Angka 2014. Ponorogo. Retrieved from https://ponorogokab.bps.go.id/publication Badan Pusat Statistik Kabupaten Ponorogo. (2015a). Ponorogo Dalam angka 2015. Ponorogo. Retrieved from https://ponorogokab.bps.go.id/publication Badan Pusat Statistik Kabupaten Ponorogo. (2015b). Ponorogo Dalam angka 2017. Ponorogo. Retrieved from https://ponorogokab.bps.go.id/publication Badan Pusat Statistik Kabupaten Ponorogo. (2016). Ponorogo Dalam angka 2016. Ponorogo. Retrieved from https://ponorogokab.bps.go.id/publication Chuang, Y. C., & Shiu, Y. S. (2018). Relationship between landslides and mountain development—Integrating geospatial statistics and a new long-term database. Science of the Total Environment Journal, 622–623, 1265–1276. https://doi.org/10.1016/j.scitotenv.2017.12.039 Chuang, Y., & Shiu, Y. (2018). Science of the Total Environment Relationship between landslides and mountain development — Integrating geospatial statistics and a new long-term database. Science of the Total Environment Journal, 622–623, 1265–1276. https://doi.org/10.1016/j.scitotenv.2017.12.039 Departemen Pekerjaan Umum. Pedoman Penataan Ruang Kawasan Rawan Bencana Longsor, Pub. L. No. 22 /PRT/M/2007, 148 (2007). Indonesia: Menteri Pekerjaan Umum Republik Indonesia. Retrieved from landspatial.bappenas.go.id/komponen/peraturan/the_file/permen22_2007.pdf%0A Hosmer, D. W., & Lemeshow, S. (2005). Multiple Logistic Regression. In Applied Logistic Regression (pp. 31–46). Hoboken, NJ, USA: John Wiley & Sons, Inc. https://doi.org/10.1002/0471722146.ch2 Kementerian Kesehatan Republik Indonesia. (2018). Pusat Krisis Kesehatan Kementerian Kesehatan Republik Indonesia. Retrieved June 11, 2018, from http://pusatkrisis.kemkes.go.id/ Lin, G., Chang, M., Huang, Y., & Ho, J. (2017). Assessment of susceptibility to rainfall-induced landslides using improved self-organizing linear output map , support vector machine , and logistic regression. Engineering Geology Journal, 224(May), 62–74. https://doi.org/10.1016/j.enggeo.2017.05.009 Logar, J., Turk, G., Marsden, P., & Ambrožič, T. (2017). Prediction of rainfall induced landslide movements by artificial neural networks. Journal of Natural Hazards and Earth System Sciences Discussions, (July), 1–18. https://doi.org/10.5194/nhess-2017-253 Paimin, Sukresno, & Pramono, I. B. (2009). Teknik Mitigasi Banjir dan Tanah Longsor. (A. N. Ginting, Ed.). Balikpapan: Tropenbos International Indonesia Programme. Retrieved from www.tropenbos.org Pourghasemi, H. R., & Rahmati, O. (2018). Prediction of the landslide susceptibility: Which algorithm, which precision? Catena Journal, 162(November), 177–192. https://doi.org/10.1016/j.catena.2017.11.022 Reed, P., & Wu, Y. (2013). Journal of Fluency Disorders Logistic regression for risk factor modelling in stuttering research ଝ. Journal of Fluency Disorders, 38(2), 88–101. https://doi.org/10.1016/j.jfludis.2012.09.003 Ubechu, B. O., & Okeke, O. . (2017). Landslide: Causes, Effects and Control. International Journal of Current Multidisciplinary Studies, 3(03), 647–663. Yuniarta, H., Saido, A. P., & Purwana, Y. M. (2015). Kerawanan Bencana Tanah Longsor Kabupaten Ponorogo. Jurnal Matriks Teknik Sipil, 3(1), 194–201.              

DOMESTIC ENERGY UTILIZATION AND POTENTIALS OF ALTERNATIVE SOURCES OF ENERGY IN MUBI METROPOLIS

Gadiga, Bulus Luka, Jigumtu, Kevin Ferdinand, Tammi, Hajjatu

GEOSFERA INDONESIA, Journal of Geography Vol 3 No 2 (2018): GEOSFERA INDONESIA
Publisher : Department of Geography Education

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Abstract

The Study investigates domestic energy utilization and potentials of alternative sources of energy in Mubi metropolis of Adamawa State.  To achieve the objectives of this study, data were collected using questionnaire. A total of 108 sets of questionnaire were retrieved and analyse using descriptive statistics. Some of the data collected from respondents include; types of energy used for various purposes, factors that influence such use and preferences for the different types of energy. Other information which cannot be collected using questionnaire were obtained from published and unpublished materials. The findings show that households rely more on fuel-wood. Economic factors were found to influence the choice of energy used in homes. Solar energy and wind energy have high potentials as alternative energy source that will help in mitigating climatic change. The study concludes that households in Mubi metropolis tend to climb the energy ladder from low grade energy types to modern energy when income increases and such energy are made available. The study recommends that households be sensitized on the health and environmental effects of traditional energy. Households should be encouraged to use modern and alternative sources of energy in order to mitigate climate change. Such energies should also be made affordable and available since majority of the respondents were willing to switch when made affordable. Keywords: Domestic energy, alternative energy, climate change, firewood.   References CBN (2009). Statistical Bulletin, Central Bank of Nigeria: Volume 20, December 2009 Climate Change Network Nigeria (CCNN, 2003) Monitoring Nigerian climate change. www.ccnnigeria.org accessed on February, 2018 DECC, (2013) The UK low carbon transition plan: national strategy for climate and energy. Presented to Parliament pursuant to Sections 12 and 14 of the Climate Change Act 2008, TSO ETB (2011) Engineering Tool Box. http://www.engineeringtoolbox.com. Accessed May 2017 Federal Ministry of Environment (2014). Nigeria’s Second National Communication Under TheUnited Nations Framework Convention on Climate Change. Abuja, Nigeria. Halava,  Satu (2013) Carbon Footprint of Thermowood. unpublished project, Satakunnan             University of Applied Sciences. Accessed on 13th August, 2018 from             https://www.theseus.fi/bitstream/handle/10024/63624/Halava_Satu.pdf;sequence=1 Kaltimber (2017) How much CO2 is stored in 1 kg of wood? http://www.kaltimber.com/blog/2017/6/19/how-much-co2-is-stored-in-1-kg-of-wood accessed on 11th August, 2018. Mshelia, A. D (2015). Seasonal Variations of Household Solid Waste Generation in Mubi, Nigeria. International Journal of Innovative Education and Research. Vol. 3, No. 5 Momodu I. M., (2013). Domestic Energy Needs and Natural Resources Conservation: The Case of Fuelwood Consumption in Nigeria. Mediterranean Journal of Social Sciences, Vol 4 No 8. 27-33 NEC, (2006) National Emission Ceilings for Certain Atmospheric Pollutants. Ministry of Housing, Spatial Planning and the Environment, The Hague, Netherlands New, M.,  Bruce Hewitson, David B. Stephenson, Alois Tsiga, Andries Kruger â€¦.Robert Lajoie  (2006): Evidence of trends in daily climate extremes over southern and West Africa, J. Geophys. Res., 111, D14102, doi: 10.1029/2005JD006289. Nigeria Energy Commission, (2006) Report of survey of energy utilization in the informal sector: A case study of the FCT, Federal Ministry of Power Technical Report. September, 2006. Obueh, J. (2008), “The Ecological Cost of increasing Dependence on Biomass fuels as Household Energy in Rural Nigeria”: Lessons from Boiling Point No. 44, GTZ/ITDG. Laurent Cousineau copyright 2011-2017, climate change guide. Osueke C. O and C. A. K. Ezugwu (2011) Study of Nigeria Energy Resources and Its Consumption. International Journal of Scientific & Engineering Research, Vol. 2, (12) Oyeneye O.O., (2004) Socio-economic influence on policies of Power Deregulation, Proc 20th National Conference of the Nigeria Society of Engineering (Electrical Division), October 6th to 7th, 2004, Pp.1-15   Palmer J, Cooper I. (2014) United Kingdom energy housing fact file 2013; 2014. Union of Concerned Scientists (UCS), (2015) Science for a healthy planet and safer world. 2016–2020 Strategic Plan World Bank, (2005).‘‘Household Energy Use in Developing Countries’’ (series No.5). Washington D.C., U.S.A: retrieved on August 16, 2012 from ESMAP Report.http://www.Worldbank.org./esmap/. Accessed on July 10th, 2012.          

THE LAND USE PRIORITY RANKING WITH THE APPROACH OF ANALYTIC HIERARCHY PROCESS (AHP) ON THE BOUNDARY OF ENTIKONG

Irsan, Robby, Mutaali, Luthfi, Sudrajat, S

GEOSFERA INDONESIA, Journal of Geography Vol 3 No 2 (2018): GEOSFERA INDONESIA
Publisher : Department of Geography Education

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Abstract

Entikong is a sub-districts located in the borderline, northern end of Sanggau Regency directly adjacent to Sarawak, Malaysia. The growth of Entikong as a center of growth does not provide a downward trickle effect, but it creates an excessive resources exploitation effect to the surrounding area (backwash effect). The land use within an area should be adjusted to its function. For that reason, this research will determine the priority and rank of land use by using the Analytic Hierarchy Process (AHP). The ranking is based on four aspects of criteria; social, economic, institutional, and environmental. The hierarchy model is sorted into alternatives, criteria, and sub-criteria. The criteria and subcriteria are compared, as well as the value of consistency. After data processing and analyzing with Expert Choice software version 11, the researcher found that the main priority of land use in Entikong is for plantation, which is 29,7%. Keywords: AHP, Land Use, Expert Choice   References Adimihardja, A. (2006). Strategi mempertahankan multifungsi pertanian di indonesia. Jurnal Litbang Pertanian. Bourgeois, R., Penunia, E., Bisht, S., & Boruk, D. (2017). Foresight for all: Co-elaborative scenario building and empowerment. Technological Forecasting and Social Change. https://doi.org/10.1016/j.techfore.2017.04.018 Ernan Rustiadi, Sunsus Saefulhakim, D. R. P. (2011). Perencanaan dan Pengembangan Wilayah. Restpent Press. Fandelli, C. (2014). Bisnis Konservasi Pendekatan Baru Dalam Pengelolaan Sumberdaya Alam dan Lingkungan Hidup (2nd ed.). Yogyakarta: Gadjah Mada University Press. Retrieved from http://ugmpress.ugm.ac.id/id/product/sains-teknologi/bisnis-konservasi-pendekatan-baru-dalam-pengelolaan-sumberdaya-alam-dan-lingkungan-hidup Giyarsih, S. R. (2010). POLA SPASIAL TRANSFORMASI WILAYAH DI KORIDOR YOGYAKARTA-SURAKARTA Spatial Pattern of Regional Transformation In Yogyakarta-Surakarta Corridor. Forum Geografi. Hidayat, W., Rustiadi, E., & Kartodihardjo, H. (2015). Dampak Pertambangan Terhadap Perubahan Penggunaan Lahan dan Kesesuaian Peruntukan Ruang (Studi Kasus Kabupaten Luwu Timur, Provinsi Sulawesi Selatan). Jurnal Perencanaan Wilayah Dan Kota. https://doi.org/10.5614/jpwk.2015.26.2.5 IPCC. (2000). Land Use, Land-Use Change, and Forestry. Forestry. https://doi.org/DOI: 10.2277/0521800838 Ishartono & Raharjo, S. T. (2015). Sustainable Development Goals (SDGs) Dan Pengentasan Kemiskinan. Social Work Jurnal. https://doi.org/ttps://doi.org/10.24198/share.v6i2.13198 Prawira, N. G. A., & Ariastita, P. G. (2014). Rumusan Insentif dan Disinsentif Pengendalian Konversi Lahan Pertanian di Kabupaten Gianyar. Jurnal Teknik Pomits. Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences. https://doi.org/10.1504/IJSSCI.2008.017590