Complex land cover classifications and physical properties retrieval of tropical forests using multi-source remote sensing

The work presented in this thesis mainly focuses on two subjects related to the application of remote sensing data: (1) for land cover classification combining optical sensor, texture features generated from spectral information and synthetic aperture radar (SAR) features, and (2) to develop a non-destructive approach for above ground biomass (AGB) and forest attributes estimation employing multi-source remote sensing data (i.e. optical data, SAR backscatter) combined with in-situ data. Information provided by reliable land cover map is useful for management of forest resources to support sustainable forest management, whereas the generation of the non-destructive approach to model forest biophysical properties (e.g. AGB and stem volume) is required to assess the forest resources more efficiently and cost-effective, and coupled with remote sensing data the model can be applied over large forest areas. This work considers study sites over tropical rain forest landscape in Indonesia characterized by different successional stages and complex vegetation structure including tropical peatland forests. The thesis begins with a brief introduction and the state of the art explaining recent trends on monitoring and modeling of forest resources using remote sensing data and approach. The research works on the integration of spectral information and texture features for forest cover mapping is presented subsequently, followed by development of a non-destructive approach for AGB and forest parameters predictions and modeling. Ultimately, this work evaluates the potential of mosaic SAR data for AGB modeling and the fusion of optical and SAR data for peatlands discrimination. The results show that the inclusion of geostatistics texture features improved the classification accuracy of optical Landsat ETM data. Moreover, the fusion of SAR and optical data enhanced the peatlands discrimination over tropical peat swamp forest. For forest stand parameters modeling, neural networks method resulted in lower error estimate than standard multi-linear regression technique, and the combination of non-destructive measurement (i.e. stem number) and remote sensing data improved the model accuracy. The up scaling of stem volume and biomass estimates using Kriging method and bi-temporal ETM image also provide favorable estimate results upon comparison with the land cover map.Die in dieser Dissertation präsentierten Ergebnisse konzentrieren sich hauptsächlich auf zwei Themen mit Bezug zur angewandten Fernerkundung: 1) Der Klassifizierung von Oberflächenbedeckung basierend auf der Verknüpfung von optischen Sensoren, Textureigenschaften erzeugt durch Spektraldaten und Synthetic-Aperture-Radar (SAR) features und 2) die Entwicklung eines nichtdestruktiven Verfahrens zur Bestimmung oberirdischer Biomasse (AGB) und weiterer Waldeigenschaften mittels multi-source Fernerkundungsdaten (optische Daten, SAR Rückstreuung) sowie in-situ Daten. Eine zuverlässige Karte der Landbedeckung dient der Unterstützung von nachhaltigem Waldmanagement, während eine nichtdestruktive Herangehensweise zur Modellierung von biophysikalischen Waldeigenschaften (z.B. AGB und Stammvolumen) für eine effiziente und kostengünstige Beurteilung der Waldressourcen notwendig ist. Durch die Kopplung mit Fernerkundungsdaten kann das Modell auf große Waldflächen übertragen werden. Die vorliegende Arbeit berücksichtigt Untersuchungsgebiete im tropischen Regenwald Indonesiens, welche durch verschiedene Regenerations- und Sukzessionsstadien sowie komplexe Vegetationsstrukturen, inklusive tropischer Torfwälder, gekennzeichnet sind. Am Anfang der Arbeit werden in einer kurzen Einleitung der Stand der Forschung und die neuesten Forschungstrends in der Überwachung und Modellierung von Waldressourcen mithilfe von Fernerkundungsdaten dargestellt. Anschließend werden die Forschungsergebnisse der Kombination von Spektraleigenschaften und Textureigenschaften zur Waldbedeckungskartierung erläutert. Desweiteren folgen Ergebnisse zur Entwicklung eines nichtdestruktiven Ansatzes zur Vorhersage und Modellierung von AGB und Waldeigenschaften, zur Auswertung von Mosaik- SAR Daten für die Modellierung von AGB, sowie zur Fusion optischer mit SAR Daten für die Identifizierung von Torfwäldern. Die Ergebnisse zeigen, dass die Einbeziehung von geostatistischen Textureigenschaften die Genauigkeit der Klassifikation von optischen Landsat ETM Daten gesteigert hat. Desweiteren führte die Fusion von SAR und optischen Daten zu einer Verbesserung der Unterscheidung zwischen Torfwäldern und tropischen Sumpfwäldern. Bei der Modellierung der Waldparameter führte die Neural-Network-Methode zu niedrigeren Fehlerschätzungen als die multiple Regressions. Die Kombination von nichtdestruktiven Messungen (z.B. Stammzahl) und Fernerkundungsdaten führte zu einer Steigerung der Modellgenauigkeit. Die Hochskalierung des Stammvolumens und Schätzungen der Biomasse mithilfe von Kriging und bi-temporalen ETM Daten lieferten positive Schätzergebnisse im Vergleich zur Landbedeckungskarte

MARTIN LUTHER KING, JR.’S STRUGGLE FOR EQUALITY FOR BLACK PEOPLE IN AMERICA

This research is about “Martin Luther King Jr.’s Struggle for Equality for Black People in America”. This library research thesis is based on historical and biographical approach. The purpose of this research is to find out how Martin Luther King Jr. struggled for equality in America especially for the black people. Historical approach is used to view the historical background of the black people in America from the first settlement and first slave trade to the slave abolishment until in the middle of 20th Century. Biographical approach, however, is used in this thesis to view the struggle conducted by Martin Luther King Jr. in order to fight for the civil rights. After analyzing the background of the black people, the writer found out that the reason Martin Luther King Jr. fought for civil rights was because of the law that was not run in practice in America, even though black people are guaranteed by the law. Martin Luther King, Jr. made a significant change to America especially for the black people. Even though issues of racism are still found these days in America, generally the life of the black people in America developed to a good improvement in economy as well as in politics

Analisis Sentimen Terhadap Dampak Inflasi di Indonesia Menggunakan Metode Multinomial Naïve Bayes

Inflasi yang terjadi di seluruh dunia termasuk negara Indonesia mengakibatkan masalah bagi masyarakat maupun negara, terjadinya ketidakstabilan ekonomi negara dan meningkatnya pengangguran dikarenakan banyaknya pengurangan karyawan kerja, selain itu dengan kelangkaan minyak terutama bahan bakar kendaraan salah satu faktor yang mendorong kenaikan inflasi sehingga mengakibatkan harga-harga barang dan sandang mengalami kenaikan yang signifikan, dari persoalan tersebut menimbulkan opini-opini masyarakat pada jejaring sosial khususnya twitter dari timbulnya masalah inflasi. Maka dibuatkan sistem untuk melakukan analisis sentimen dari masalah kondisi Inflasi Indonesia. Proses sistem memerlukan data tweet dengan jumlah 1725 tweet hasil dari proses crawling data twitter menggunakan bantuan library python yaitu tweepy pada masing-masing kata kunci inflasi. Algoritma naïve bayes clasiffier dengan model multinomialnb sebagai metode untuk melakukan klasifikasi. Hasil klasifikasi dari search key inflasi indonesia mengandung beberapa kelas yaitu positif, negatif dan netral. Proses penelitian diuji menggunakan beberapa skenario pembagian data yaitu 90:10, 80:20, 70:30, untuk tingkat akurasi terbaik dihasilkan menggunakan skenario 90% data train dan 10% data test mendapatkan hasil akurasi 75,5%, precision 75%, f1-score 75% dan recall 74%

PENGARUH PENAMBAHAN SUPERPLASTICIZER PADA BETON GEOPOLIMER BERBAHAN DASAR NaOH 14M MOLAR TERHADAP KUAT TEKAN DAN POROSITAS

Abstrak Beton geopolimer adalah beton yang menggunakan abu terbang sebagai bahan utama, beton geopolimer dapat dijadikan alternatif untuk pengganti beton konvensional karena sifatnya yang ramah lingkungan dan tidak menghasilkan gas CO2. Untuk meningkatkan kuat tekan beton geopolimer dilakukan berbagai upaya salah satunya adalah penambahan bahan aditif superplasticizer (SP). Penelitian ini mempelajari pengaruh variasi kadar SP terhadap nilai kuat tekan dan porositas beton geopolimer. Material yang digunakan adalah abu terbang kelas C, aktivator sodium hidroksida (NaOH) 14M dan Sodium Silikat (Na2SiO3) dengan perbandiangan NaOH/ Na2SiO3 sebesar 1,5. SP yang digunakan adalah merek Sika Viscocrete 1003 yang dikategorikan aditif tipe F. Penelitian yang dilakukan meliputi uji XRF pada abu terbang, uji vikat untuk binder beton geopolimer, uji slump untuk beton geopolimer segar, pemeriksaan berat volume, uji tekan dan uji porositas pada beton usia 3, 7, dan 28 hari. Hasil penelitian menunjukkan bahwa untuk varian campuran beton geopolimer dengan penggunaan SP dapat memperlambat setting time awal binder geopolimer dari 39 menit untuk penambahan SP 0.5% hingga 45 menit untuk penambahan SP 2.0%. Uji porositas didapatkan SP dapat menurunkan nilai porositas. Dari uji tekan didapatkan bahwa SP dapat meningkatkan kuat tekan beton geopolimer hingga rata-rata maksimum 12.49 MPa pada usia 28 Hari, semakin banyak penggunaan SP semakin tinggi kuat tekan yang dihasilkan. Kata kunci: Beton geopolimer, Abu terbang, Superplasticizer (SP), Porositas, Kuat tekan Abstract Geopolymer concrete is a concrete that uses fly ash as the main material, geopolymer concrete can be used as an alternative to conventional concrete replacement because it is environmentally friendly and does not produce CO2 gas. To increase the compressive strength of geopolymer concrete made various efforts one of them is the addition of superplasticizer (SP) additive. This study studied the effect of SP variation on the value of compressive strength and porosity of geopolymer concrete. The materials used are C class fly ash, 14M sodium hydroxide (NaOH) and Sodium Silicate (Na2SiO3) activator with NaOH / Na2SiO3 ratio equal 1,5. SP used is the Sika Viscocrete 1003 brand categorized type F additive. The research includes XRF test on fly ash, vikat test for geopolymer concrete binder, slump test for fresh geopolymer concrete, volume weight check, compression test and porosity test on concrete ages 3, 7, and 28 days. The results showed that for the mixed variant of geopolymer concrete with the use of SP can slow the initial time setting of the geopolymer binder from 39 minutes for the addition of SP 0.5% to 45 minutes for the addition of SP 2.0%. The porosity test obtained by SP can decrease the porosity value of geopolymer concrete. From the compression test it was found that SP can increase the compressive strength of geopolymer concrete up to a maximum average of 12.49 MPa at 28 days, more uses SP more high a result of compressive strength. Keywords: Geopolymer concrete, fly ash, superplasticizer, porosity, compressive strengt

Disposition Effect: Does Investor Confidence Matter? Examining Service From Securities Brokerages

Purpose: This study aims to analyze the role of training program to develop novice investors confidence in buying a stock. Novice investors undergo dilemma to buy stock due to limited knowledge which resulting disposition effect. Research regarding disposition effect which associated with training for novice investors is still limited   Theoretical framework: The disposition effect is the tendency when investors sell stocks that have the potential to experience future profits early, otherwise investors tend to hold stocks that have the potential to experience losses for too long so that investors tend to experience losses.      Design/methodology/approach:  The research using quantitative approach and employ purposive sampling method with a total sample of 192 respondents. Respondent criteria are novice investor and have limited knowledge in stock market. Each respondent is required to fill questionnaire to obtain data which consist of strongly disagree and strongly agree. Validity, reliability, and hypothesis testing is examined   Findings:  The results indicate investor training influence investor experience. The result also showed that the training program and investor experience impact investor confidence. The result implies investor need training and experience to reduce disposition effect. The result represents training program, investor experience, and investor confidence affect investor satisfaction   Research, Practical & Social implications: The research is asserted that novice investor with limited experience and knowledge need do practice. Novice investor understanding to buy stock will develop investor confidence.   Originality/value: The result elaborate training for novice to develop investor confidence and experience. The more experienced investor will reduce disposition effect. Previous research is lack of disposition effect elaboration and its implication on investor satisfaction

APPLICATION OF REMOTE SENSING TO ESTIMATE ABOVE GROUND BIOMASS IN TROPICAL FORESTS OF INDONESIA

This work aims to estimate Above Ground biomass (AGB) of a tropical rainforest in East Kalimantan, Indonesia using equation derived from the stand volume prediction and to study the spatial distribution of AGB over aforest area. The potential of remote sensing and field measurement data to predict stand volume and AGB were studied Landsat ElM data were atmospherically corrected using Dark Object Subtraction (DOS) technique, and topographic corrections were conducted using C-correction method Stand volume was estimated using field data and remote sensing data using Levenberg-Marquardt neural networks. Stand volume data was converted into the above ground biomass using available volume - AGB equations. Spatial distribution of the AGB and the error estimate were then interpolated using kriging. Validated with observation data, the stand volume estimate showed integration of field measurement and remote sensing data has better prediction than the solitary uses of those data. The AGB estimate showed good correlations with stand volume, number of stems, and basal area

Pathogenesis, evaluation, and recent management of diabetic foot ulcer

Diabetic foot ulcers (DFUs) are a major health problem as the number of patients continues to increase, are difficult to heal, require enormous management costs, and deteriorate the quality of life of patients, their families and societies. The pathogenesis of DFUs is complex. Most important factors that increase the risk of DFUs are peripheral neuropathy, foot deformities, frequent minor trauma, and peripheral arterial disease. Neuropeptides derangement, hypoxia, hyperglycemia, and infection act as the cause of chronicity of DFUs. Therefore, during the initial evaluation of DFU, patients need to be checked for their metabolic status, presence or absence of peripheral neuropathy, vascular insufficiency, foot deformities, and infection of the ulcer and its underlying bone. Then, DFUs are classified by the severity of vascular insufficiency, the depth of the wound, and the severity of the infection. This classification system helps clinicians to determine whether the patient needs to be hospitalized or amputated and helps to establish DFU management strategies. In the management of DFUs, adequate blood flow to the wound area should be achieved. Glycemic control and standard wound care should be encouraged. Standard wound care includes debridement, offloading, wound moisture balance with suitable dressing, edema control, and infection control. Education about preventive foot care should be taught to the patients and their families. As the pathogenesis and management of DFUs are complex, a multidisciplinary team consists of expert individuals in their respective fields should be involved