Judul: Generalized LASSO in Identifiying Categoric Variables with the same Affection for House Prices in West Java in 2023
Abstrak: Perumahan merupakan sebuah lingkungan tempat tinggal yang terdiri dari sekelompok atau sekumpulan rumah. Rumah sangat berperan penting sebagai tempat berlindung bagi suatu individu dan sarana terbentuknya generasi yang unggul. Dalam menentukan tempat tinggal, manusia cenderung meperhatikan kualitas, kenyamanan, harga, maupun lokasi. Umumnya, besaran harga rumah dipengaruhi oleh banyak faktor, yakni spesifikasi dan lokasi dari rumah tersebut. Faktor ini dapat berupa peubah kategorik maupun numerik. Penelitian ini bertujuan mengidentifikasi kesamaan pengaruh antar kategori pada peubah kategorik yang diduga memengaruhi harga rumah. Peubah kategorik yang digunakan ialah daya listrik, jumlah kamar tidur, jumlah kamar mandi, jumlah tempat kendaraan, dan sertifikasi. Selain itu, terdapat dua peubah numerik yang digunakan yaitu luas bangunan dan luas tanah. Data yang dianalisis sebanyak 300 data harga rumah di Jawa Barat tahun 2023. Provinsi Jawa Barat memiliki jumlah penduduk terbesar pertama mencapai 18% dari total penduduk di Indonesia. Jumlah rumah tangga yang memiliki rumah dengan status kepemilikan milik sendiri mencakup 83% dari total rumah tangga yang ada per tahun 2022. Metode yang digunakan adalah generalized LASSO yang dapat memperhitungkan faktor kedekatan antar kategori. Kategori jumlah kamar tidur enam dan tujuh, jumlah kamar tidur sembilan dan sepuluh, kategori jumlah kamar mandi enam dan delapan, kategori jumlah tempat kendaraan dua dan tiga, jumlah tempat kendaraan enam dan tujuh, serta kategori sertifikasi SHGB dan PPJB memiliki pengaruh yang sama terhadap harga rumah di Jawa Barat tahun 2023., Housing is a residential environment consisting of a group of houses. The house plays an important role as a place to live for an individual and a means of forming a superior generation. In determining a place to live, humans tend to pay attention to quality, comfortable, price, or location. Generally, house prices are affected by many factors, such as the specification and location. This study uses to identify the similarity of influence between categories on categoric variables that are thought to affect house prices. The categorical variables used are electrical power, total number of bedroom, total number of bathroom, total number of vehicle spaces, and certificate. In addition, numerical variables used are building and surface area. The data analyzed were 300 data on house prices in West Java in 2023. West Java Province has the largest total population reaching 18% of the total population in Indonesia. The number of households who owning their own houses reaching 83% of the total households in 2022. The method used is generalized LASSO which can take into account the proximity factor between categories. The number of bedroom of six-seven, the number of bedroom of nine-ten, the number of bathroom of six-eight, the number of vehicle spaces of two-three, the number of vehicle spaces of six-seven, and certificate of SHGB-PPJB have the same effect on house prices in 2023.
Keyword: generalized LASSO, house prices, households, housing, west java

Judul: Analisis Subsidi Perumahan untuk Masyarakat Berpenghasilan Rendah Menggunakan Metode Generalized LASSO di Pulau Jawa
Abstrak: Pada tahun 2021 terdapat 12,7 juta masyarakat berpenghasilan rendah yang tidak memiliki rumah di Indonesia. Sebanyak 49% masyarakat berpenghasilan rendah berada di Pulau Jawa. Hal ini mengakibatkan pemerintah membuat kebijakan berupa subsidi KPR perumahan untuk memudahkan masyarakat untuk memiliki rumah. Eksplorasi data dan penentuan wilayah di Pulau Jawa terkait kondisi permintaan kepemilikan rumah menjadi tujuan utama penelitian ini. Metode yang digunakan antara lain metode statistika deskriptif untuk mengetahui sebaran masyarakat yang menerima subsidi KPR, metode heatmap clustering untuk mengetahui pengelompokkan pendapatan masyarakat penerima rumah subsidi dan metode Generalized LASSO dengan kedekatan wilayah dan K-Nearest Neighbor untuk menggerombolkan wilayah berdasarkan permintaan kepemilikan rumah. Hasil dari penelitian ini diperoleh bahwa mayoritas masyarakat dengan angka penerimaan subsidi KPR tertinggi terdapat pada Kabupaten Bekasi dan Kabupaten Bogor. Selain itu, gerombol pendapatan masyarakat yang paling tinggi menerima rumah subsidi berada pada kisaran pendapatan 3,9 sampai 5,9 juta rupiah. Serta, terbentuk sebanyak tujuh gerombol wilayah di Pulau Jawa berdasarkan hasil terbaik pada K-Nearest Neighbor dengan K = 2 pada kasus penggerombolan permintaan kepemilikan rumah dengan metode Generalized LASSO., In 2021, there were 12.7 million low-income people who did not own a home in Indonesia. As many as 49% of low-income people live in Java. This resulted in the government making a policy in the form of housing mortgage subsidies to make it easier for people to own houses. Data exploration and regional determination in Java related to the condition of demand for home ownership are the main objectives of this study. The methods used include descriptive statistical methods to determine the distribution of people who receive mortgage subsidies, heatmap clustering methods to determine the income grouping of people receiving subsidized houses and the Generalized LASSO method with regional proximity and K-Nearest Neighbor to group areas based on requests for home ownership. The results of this study found that the majority of people with the highest number of mortgage subsidy receipts were in Bekasi Regency and Bogor Regency. In addition, the highest income group of people receiving subsidized houses is in the income range of 3.9 to 5.9 million rupiah. Also, as many as seven regional clusters were formed in Java Island based on the best results on K-Nearest Neighbor with K = 2 in the case of clustering requests for home ownership by the method Generalized LASSO.
Keyword: Generalized LASSO, Low-income community, Subsidized housing

Judul: Adsorpsi–fotodegradasi Biru Metilena oleh Nanokomposit Kaolin/TiO2 yang Diemban dengan ZnO
Abstrak: Synthetic dye waste such as methylene blue pollutes aquatic evironment. Kaolin/TiO2 nanocomposite was made for adsorption–photodegradation process under UV light. The nanocomposite was prepared by paste and ball milling methods. Semiconductor ZnO was used as dopant to ease photodegradation in visible-light range. X-ray diffraction results showed that kaolin/TiO2 and kaolin/TiO2/ZnO nanocomposites were successfully made. However, ZnO doping decreased crystallinity of the nanocomposites. Scanning electron microscopy results showed that the surface morphology of the nanocomposite made by using paste method and that of doped nanocomposite made by using ball milling method were different. ZnO doping increased the adsorption capacity of the nanocomposite. Photodegradation results showed that ZnO doping improved the photocatalytic activity of the nanocomposites under UV and visible irradiation. However, the photocatalytic activity of the nanocomposites was relatively better under UV irradiation than that under the visible irradiation.
Keyword: photodegradation, kaolin/TiO2/ZnO nanocomposites, kaolin, adsorption capacity