Using Literature in the Social Studies Classroom and Cross Curricular Teaching at the High School Level

Educators in the current era acknowledge that high school level students are more sophisticated in their approaches to learning, and as such, this “multi-tasking” generation both requires different methods and desires practical application of the lessons taught. This thesis project asserts that as the American educational system ages it is important that new concepts be examined for potential inclusion of cross-curricular teaching. The research explores the benefits of collaboration between high school curriculums – history and language arts specifically. In the examination of current attitudes and feelings surrounding the practice of cross-curricular collaboration, this project suggests that trends affirm the advantages of this method of teaching history at the high school level. The idea that literature can help students practice reading for analysis, examine elements of language, style and more recently, history, is viewed as a means to strengthen critical thinking skills. Additionally, a brief look at the history behind the use of supplemental materials in the social studies classroom is also considered. Potential benefits to this type of learning practice include increasing imagination, providing differentiation and potential alternatives to textbooks. Concerns for the lack of inclusion considered are time constraints because of standardized test preparation, lack of resources, and lack of knowledge. The concluding sections catalog suggested means to incorporate and collaborate between the language arts and history staff and curriculum

Perubahan Kerapatan Vegetasi dan Penutup Lahan Terhadap Urban Heat Island (UHI) di Kota Bekasi

The replacement of vegetation by roads, buildings, and other structures leads to increased absorption and reflection of solar heat, resulting in elevated surface temperatures in urban areas. This leads to the formation of more hotspots, triggering changes in weather and climate, which are key indicators of the Urban Heat Island (UHI) phenomenon. UHI refers to the phenomenon where urban areas experience higher temperatures compared to their surrounding areas. The primary factor influencing UHI is the conversion of vegetated land cover into developed areas due to urban growth. This causes an increase in surface temperatures due to a reduction in vegetation density and an increase in building density. Changes in land cover within the study area can be identified using unsupervised classification analysis, followed by the analysis of the Normalized Difference Vegetation Index (NDVI) to assess the vegetation index's impact on Land Surface Temperature (LST) and determine the surface temperature of Bekasi city. Accordingly, the objective of this research is to analyze the Urban Heat Island in Bekasi city using a quantitative approach that utilizes Landsat satellite imagery. The results indicate that the temperature in Bekasi city ranges from 25 to 31 degrees Celsius.  Keywords: Landsat-8, Land Surface Temperature, Land Use, NDVI, USGS   Abstrak Pergantian vegetasi oleh jalan, bangunan, dan struktur lainnya menyebabkan peningkatan penyerapan dan pantulan panas matahari, yang mengakibatkan kenaikan suhu permukaan di kota. Akibatnya, terbentuk lebih banyak titik panas yang memicu perubahan cuaca dan iklim, yang menjadi pemicu terjadinya Urban Heat Island (UHI). UHI adalah fenomena di mana wilayah perkotaan mengalami suhu yang lebih tinggi dibandingkan dengan wilayah sekitarnya. Faktor utama yang mempengaruhi terjadinya UHI adalah konversi lahan vegetasi menjadi area perkotaan akibat pembangunan kota. Hal ini menyebabkan peningkatan suhu permukaan karena berkurangnya kerapatan vegetasi dan peningkatan kerapatan bangunan. Perubahan tutupan lahan di dalam area penelitian dapat diidentifikasi melalui analisis klasifikasi tak terbimbing, diikuti oleh analisis Indeks Vegetasi Perbedaan Ternormalisasi (NDVI) untuk mengetahui pengaruh indeks vegetasi terhadap Suhu Permukaan Tanah (LST) dan menentukan suhu permukaan kota Bekasi. Dengan demikian, tujuan penelitian adalah untuk menganalisis Urban Heat Island di kota Bekasi dengan pendekatan kuantitatif yang menggunakan citra satelit Landsat. Hasil penelitian menunjukkan bahwa suhu kota Bekasi berkisar antara 25 hingga 31 derajat Celsius. Kata kunci: Landsat-8, Land Surface Temperatur, NDVI, Tata Guna Lahan, USG

Penggunaan Matlab dan Python dalam Klasterisasi Data

Abstract   Organizations need to dig through the data clustering process, both past data and data from the internet. Sometimes the data has to be re-clustered to match the actual conditions. Therefore, it is necessary to prepare clustering support equipment. In this study the K-Means method was chosen for comparing two technical computational languages, i.e. Matlab and Python which are currently in great demand by researchers and can be used by organizations for a clustering process. This study showed both Matlab and Python have enough libraries (libraries) and toolboxes to help users in data clastering as well as graphics presentation. The test results show that the two programming languages are capable of carrying out the clustering process with two clusters; cluster 1 with a center point at coordinates (1.24, 1.34) and cluster 2 with a center point at coordinates (3.1, 3.07) and are presented by a cluster distribution plot.   Keywords: Clusterization, K-Means, Matlab, Python.   Abstrak   Organisasi perlu menggali data lewat proses klasterisasi data, baik data lampau maupun data dari internet. Terkadang data harus dilakukan klasterisasi ulang untuk mencocokan dengan kondisi yang sebenarnya. Oleh karena itu perlu dipersiapkan peralatan pendukung klasterisasi. Dalam penelitian ini metode K-Means dipilih untuk membandingkan dua bahasa komputasi teknis yaitu Matlab dan Python yang sekarang ini banyak diminati para peneliti yang dan dapat digunakan oleh organisasi yang membutuhkan proses klasterisasi. Hasil dari penelitian ini menunjukan baik Matlab maupun Python memiliki cukup pustaka (library) dan toolbox dalam membantu pengguna mengklasterisasi data, mempresentasikan grafik. Hasil pengujian menunjukan kedua Bahasa pemrograman mampu menjalankan proses klasterisasi berupa klaster 1 yang memiliki titik pusat yang berada pada koordinat (1.24, 1.34) dan klaster 2 dengan titik pusat yang berada pada koordinat (3.1, 3.07) disertai dengan plot sebaran klasternya.   Kata kunci: Klasterisasi, K-Means, Matlab, Python

Prediksi Kelas Jamak dengan Deep Learning Berbasis Graphics Processing Units

For the first time, machine learning did the classical classification process using two classes (bi-class) such as class -1 and class +1, 0 and 1, or the form of categories such as true and false. Famous methods used are Artificial Neural Networks (ANN) and Support Vector Machine (SVM). The current development was a problem with more than two classes, known as multi-class classes. For SVM sometimes the plural classes are overcome by doing a gradual process like a decision tree (DT) method. Meanwhile, ANN has experienced rapid development and is currently being developed with a large number of layers with the new activation functions, i.e. the rectified linear units (ReLu), and the probabilistic-based activation, i.e. softmax, including its optimizer methods (adam, sgd, and others). Then the term changed to Deep Learning (DL). This study aimed to compare two well-known methods (DL and SVM) in classifying multiple classes. The number of DL layers was six with the neuron composition are 128, 64, 32, 8, 4, and 3, while SVM uses a radial kernel base function with gamma and c respectively 0.7 and 5. Besides, this study intends to compare the use of the Graphics Processing Unit (GPU) available on Google Interactive Notebook (Google Colab), an online Python language programming application. The results showed that DL accuracy outperformed SVM but required large computational resources, with the accuracy for DL and SVM are 99% and 98%, respectively. However, the use of the GPU can overcome these problems and is proven to increase the speed of the process as much as 47 times. Keywords: Artificial Neural Networks, Graphics Processing Unit, Google Interactive Notebook, Rectified Linear units, Support Vector Machine. Abstrak Di awal perkembangannya mesin pembelajaran melakukan proses klasikfikasi menggunakan dua kelas (bi-class) misalnya kelas -1 dan kelas +1, 0 dan 1, atau bentuk kategori seperti benar dan salah. Metode terkenal yang digunakan adalah Jaringan Syaraf Tiruan (JST) dan Support Vector Machine (SVM). Perkembangan selanjutnya adalah problem dengan kelas yang lebih dari dua kelas, dikenal dengan istilah kelas jamak (multi-class). Untuk SVM terkadang kelas jamak diatasi dengan melakukan proses berjenjang mirip pohon keputusan (decision tree). Sementara itu JST telah mengalami perkembangan yang pesat dan saat ini sudah dikembangkan dengan jumlah layer yang banyak disertai dengan fungsi-fungsi aktivasi terkini seperti rectified linear unit (ReLu), dan softmax yang berbasis probabilistik, termasuk juga metode-metode optimizernya (adam, sgd, dan lain-lain). Kemudian istilahnya berubah menjadi Deep Learning (DL). Penelitian ini mencoba membandingkan dua metode terkenal (DL dan SVM) dalam melakukan klasifikasi kelas jamak. Jumlah layer DL sebanyak enam dengan masing-masing neuron sebesar 128, 64, 32, 8, 4, dan 3, sementara SVM menggunakan kernel radial basis function dengan gamma dan c berturut-turut 0.7 dan 5. Selain itu penelitian ini bermaksud membandingkan penggunaan Graphics Processing Unit (GPU) yang tersedia di Google Interactive Notebook (Google Colab), sebuah aplikasi online pemrograman bahasa Python. Hasil penelitian menunjukan akurasi DL unggul tipis dibanding SVM namun memerlukan sumber daya komputasi yang besar masing-masing dengan akurasi 99% dan 98%. Namun penggunaan GPU mampu mengatasi permasalahan tersebut dan terbukti meningkatkan kecepatan proses sebanyak 47 kali. Kata kunci: Jaringan Syaraf Tiruan, Graphics Processing Unit, Google Interactive Notebook, Rectified Linear units, Support Vector Machine

Efektifitas Pembatasan Sosial Berskala Besar (PSBB) di Kota Bekasi Dalam Mengatasi COVID-19 dengan Model Susceptible-Infected-Recovered (SIR)

To overcome the COVID-19 outbreak, the government did not carry out the lockdown policy (regional quarantine policy) but implemented the Large-Scale Social Restrictions (PSBB) policy. Starting from the capital city of Jakarta, this policy was followed by other regions. Bekasi City as a buffer zone of Jakarta immediately implemented the PSBB policy since this area is close to Jakarta and is feared to be affected by the Jakarta region which is a red zone with almost half of Indonesian COVID-19 cases are in the Jakarta area. Many people do not agree with the PSBB, but in order to keep the economic growth as well as to overcome the outbreak, the government does not adopt a regional quarantine policy. To determine the effectiveness of PSBB in the city of Bekasi, this study tried to use the Susceptible-Infected-Recovered (SIR) model to measure the spread rate of COVID-19. The results showed a decrease in the number of infected cases with beta and gamma were 0.071 and 0.05, respectively, and the epidemic was predicted to end in June 2020. Keywords: coronavirus, epidemic, pandemic, regional quarantine policy, Bekasi City   Abstrak Dalam mengatasi wabah COVID-19, pemerintah tidak melakukan karantina wilayah (lock down) tetapi menggunakan kebijakan Pembatasan Sosial Berskala Besar (PSBB). Dimulai dari ibukota Jakarta, kebijakan ini diikuti oleh wilayah lainnya. Kota Bekasi sebagai wilayah penyangga Jakarta segera menerapkan kebijakan PSBB mengingat wilayah ini berdekatan dengan Jakarta dan dikhawatirkan terpengaruh dengan kota Jakarta yang merupakan zona merah dengan hampir separuh kasus COVID-19 ada di wilayah Jakarta. Banyak pihak yang mendukung dan juga kurang setuju dengan PSBB, namun agar perekonomian tetap berjalan dan wabah dapat diatasi, pemerintah tidak mengambil kebijakan karantina wilayah. Untuk mengetahui efektifitas PSBB di kota Bekasi, penelitian ini mencoba menggunakan model Susceptible-Infected-Recoverd (SIR) untuk mengukur laju penyebaran COVID-19. Hasilnya menunjukan adanya laju penurunan kasus terinfeksi dengan beta dan gamma beruturut-turut sebesar 0,071 dan 0,05 dan diprediksi akan berakhir di bulan Juni 2020. Kata kunci: virus corona, epidemik, pandemik, karantina wilayah, Bekasi Cit

SIRIP PENDINGIN (FIN) TAMBAHAN UNTUK MENINGKATKAN STABILITAS AERODINAMIKA DAN EFEKTIVITAS PERPINDAHAN PANAS PADA SEPEDA MOTOR

There are two problems when motorbike running at high speed: the aerodynamic effect and over heating of the engine. As a two wheels vehicle, motorbike must keep the tyre at the road to avoidfrom accident. When it runs at high speed, the aeorodynamic factor must be counted. If there is a different from upper and lower air speed of a plat, there must be a force to it. It is very dangerous if the force is lift force because it make the traction of tyre down, so in this research I propose additional design for this purpose. Not only for stabilisation of vehicle, this propose design also has a function as a fin for heat exchanger from engine to air. Analysis by Computational Fluid Dynamics (CFD) to my propose design was adequate for aerodynamic and heat transfer analysi

OPTIMIZING GAS STATION LOCATION USING GENETIC ALGORITHMS

Gas station location is not only based on financial but also environment aspects because it will give negative impact if there are some accidents such as fire, tank leakage, etc. Helping customer in supplying fuels should not sacrifice other needs such as health, food, education, living circumstance, and so on. Therefore we propose the system that can help someone deciding and analyzing the location of gas station, especially when doing proper analysis. By using genetic algorithms our system can find optimum location of gas station after considering other important location that must be far away from it. The distance from important place was counted by normal euclidean after converting road and the river at map into nonlinear equation using interpolation. Population was generated from converting road on the map into equation. The important places that must be far away from gas station are collected and with that equation then give an objective function. Testing result showed the system could find optimum gas stations location at Bekasi regency. Keywords : GAS STATION, GENETIC, ALGORITHM

Aplikasi Pendaftaran Online Berdasarkan Sistem Zonasi Berbasis Sistem Informasi Geografis (Studi Kasus SMK TI Tunas Harapan Bekasi)

The Bekasi City Government uses a zoning system for the registration of prospective new students, especially those applying for junior and senior high schools. For this policy, prospective students are not free to register at the desired school because they must be based on the distance from home to school. This also often triggers academic-based discrimination that often arises in the community. The purpose of this research is to make an application design in one of the schools in Bekasi regarding the design of an online registration application based on the Geographic Information System (GIS). With the application design that is following the data and facts obtained from the analysis of this system, it will be able to provide the final decision of accepting new students at the SMK TI Tunas Harapan school, as a case study. Therefore, the information system can be managed in the future and provide solutions to various problems. Keywords: Android, Website, Application, GIS, Zoning   Abstrak Pemerintah Kota Bekasi menggunakan sistem zonasi untuk pendaftaran calon peserta didik baru khususnya diberlakukan untuk tingkat SMP dan SMA juga yang sederajat. Atas kebijakan itu, calon peserta didik tidak leluasa untuk mendaftar ke sekolah yang diinginkan karna harus berdasarkan jarak dari rumah ke sekolah. Hal ini juga sering memicu diskrimasi berbasis akademis yang kerap muncul di masyarakat. Tujuan dari penelitian ini membuat aplikasi merancang suatu rancangan aplikasi di salah satu sekolah di Kota Bekasi mengenai perancangan aplikasi pendaftaran online berdasarkan sistem zonasi berbasis Sistem Informasi Geografis (SIG) studi kasus SMK TI Tunas Harapan. Dengan adanya rancangan aplikasi yang sesuai dengan data dan fakta yang didapatkan dari analasis sistem ini, akan mampu memberikan informasi beserta keputusan akhir dalam proses penerimaan peserta didik baru di sekolah SMK TI Tunas Harapan sehingga kedepannya sistem informasi tersebut dapat dikelola dan memberikan solusi atas berbagai macam permasalahan yang terjadi. Kata kunci: Android, Website, Aplikasi, SIG, Zonasi

Prediksi, Optimalisasi Penggunaan Lahan, dan Nilai Tanah di Kota Bekasi

Abstract   Urban planning management plays an important role in sustainable development because cities are the main source of environmental degradation. Limited land with high land prices makes it difficult to organize the city. There have been many studies discussing urban planning, but most of them focus on one side, such as only prediction, optimization, or other aspects related to environment conservation. This study intends to discuss aspects of prediction, optimization and their relationship to land values in the city of Bekasi. Prediction results show the addition of buildings, especially in the city center. To optimize land use, especially in relation to high land prices in the city center, it is necessary to build vertical settlements.   Keywords: Land Change Modeler, Geographic Information Systems, Clustering, Driving Factors   Abstrak   Manajemen tata kota memegang peranan penting dalam pembangunan berkelanjutan karena kota merupakan sumber utama permasalahan lingkungan. Keterbatasan lahan dengan harga tanah yang tinggi menyebabkan sulitnya penataan kota. Riset yang membahas perencanaan kota sudah banyak dilakukan, hanya saja kebanyakan focus kepada satu sisi, misalnya prediksi, optimalisasi, atau pun aspek-aspek lain yang terkait konservasi alam. Penelitian ini bermaksud membahas aspek-aspek prediksi, optimalisasi dan keterkaitannya dengan nilai tanah di kota Bekasi. Hasil prediksi menunjukan penambahan bangunan khususnya di pusat kota. Untuk mengoptimalkan penggunaan lahan, khususnya berkaitan dengan harga tanah yang tinggi di pusat kota, perlu dibangun pemukiman vertikal.   Kata kunci: Land Change Modeler, Sistem Informasi Geografis, Klasterisasi, Faktor Pendorong Perubahan Laha

Web Scraping Situs Berita Menggunakan Bahasa Pemograman Python

Currently the rapid development of technology provides innovation, one of which is the technique of obtaining information from portal websites, termed web scrapers. This application provides data needs in the form of information where the process of retrieving information from sites will later be taken to observe behavior and perceptions to get the right segmentation. Most data collection is currently still done manually, as a result, this method has several system limitations, namely the length of the data collection process so that it slows down the performance of market segment analysis. The risk is not getting the right market segmentation. To solve this problem, a web scraping news site is needed. In this study, web scraping news sites were created using the python programming language and the flask library to display web scraping. In addition, the Selenium library is used to simplify application creation, facilitate interaction with the web and provide facilities to control a web browser. This program can retrieve data based on keywords, where the results are in the form of the title, posting date, summary, then collect the data that has been taken into a csv file extension automatically.  Keywords: Internet, News, Python, Scraping, Website   Abstrak Saat ini perkembangan pesat teknologi memberikan inovasi, salah satunya adalah teknik memperoleh informasi dari situs web portal, yaitu web scraper. Aplikasi ini menyediakan kebutuhan data berupa informasi dimana proses pengambilan informasi dari situs-situs nantinya diambil untuk diamati perilaku dan persepsi untuk mendapatkan segmentasi yang tepat. Kebanyakan pengambilan data saat ini masih dilakukan secara manual, akibatnya cara ini memiliki beberapa keterbatasan sistem yaitu lamanya proses pengumpulkan data sehingga memperlambat kinerja analisa segmen pasar. Resikonya adalah tidak mendapatkannya segementasi pasar yang tepat. Untuk mengatasi masalah tersebut diperlukan web scraping situs berita. Pada penelitian ini, web scraping situs berita dibuat dengan menggunakan bahasa pemrograman python dan library flask untuk tampilan web scraping. Selain itu, library selenium digunakan untuk mempermudah pembuatan aplikasi, mempermudah interaksi dengan web dan menyediakan fasilitas untuk mengontrol suatu peramban web. Program ini dapat mengambil data berdasarkan kata kunci, dimana hasilnya berupa judul, tanggal postingnya, rangkuman, lalu mengumpulkan data yang telah di ambil ke file berekstensi csv secara otomatis. Kata kunci: Berita, Internet, Python, Scraping, WebsiteCurrently, the rapid development of technology provides innovation, one of which is the technique of obtaining information from portal websites, termed web scrapers. This application provides data needs in the form of information where the process of retrieving information from sites will later be taken to observe behavior and perceptions to get the right market segmentation. Most data collection is currently still done manually, as a result, this method has several system limitations, namely the length of the data collection process so that it slows down the performance of market segment analysis. The risk is not getting the right market segmentation. To solve this problem, a web scraping news site is needed. In this study, web scraping news sites were created using the python programming language and the flask library to display web scraping. In addition, the Selenium library is used to simplify application creation, facilitate interaction with the Web and provide facilities to control a web browser. This program can retrieve data based on keywords, where the results are in the form of the title, posting date, summary, then collect the data that has been taken into a csv file extension automatically.  Keywords: Internet, News, Python, Scraping, Website   Abstrak Saat ini, perkembangan pesat teknologi memberikan inovasi, salah satunya adalah teknik memperoleh informasi dari situs web portal, yaitu web scraper. Aplikasi ini menyediakan kebutuhan data berupa informasi dimana proses pengambilan informasi dari situs-situs nantinya diambil untuk diamati perilaku dan persepsi untuk mendapatkan segmentasi pasar yang tepat. Kebanyakan pengambilan data saat ini masih dilakukan secara manual, akibatnya cara ini memiliki beberapa keterbatasan system yaitu lamanya proses pengumpulkan data sehingga memperlambat kinerja analisa segmen pasar. Resikonya adalah tidak mendapatkannya segementasi pasar yang tepat. Untuk mengatasi masalah tersebut diperlukan web scraping situs berita. Pada penelitian ini, web scraping situs berita dibuat dengan menggunakan bahasa pemrograman python dan library flask untuk tampilan web scraping. Selain itu, library Selenium digunakan untuk mempermudah pembuatan aplikasi, mempermudah interaksi dengan Web dan menyediakan fasilitas untuk mengontrol suatu peramban web. Program ini dapat mengambil data berdasarkan kata kunci, dimana hasilnya berupa judul, tanggal postingnya, rangkuman, lalu mengumpulkan data yang telah di ambil ke file berekstensi csv secara otomatis. Kata kunci: Berita, Internet, Python, Scraping, Websit