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"Penelitian ini bertujuan untuk mengindentifikasi prediksi financial distress untuk perusahaan yang tercatat di Indonesia. Variabel yang digunakan adalah rasio akuntansi dan faktor pasar. Rasio akuntansi yang digunakan berupa profitabilitas, likuiditas, dan leverage, serta dua faktor pasar yang penting yaitu SIZE dan PER. Sampel yang digunakan sebanyak 241 perusahaan yang tercatat di Bursa Efek Indonesia dari tahun 2008 sampai 2017 dan metode regresi logistik digunakan untuk memprediksi financial distress. Perusahaan yang mengalami distress didefinisikan sebagai perusahaan yang telah melaporkan nilai ekuitas negatif selama tiga tahun berturut-turut. Temuan empiris dari penelitian ini menunjukkan bahwa variabel accounting yang terdiri dari profitabilitas, likuiditas, leverage, dan arus kas berpengaruuh signifikan. Kemudian, SIZE dan PER yang merupakan variabel market juga dinilai memiliki pengaruh yang signifikan dalam memprediksi kemungkinan financial distress.

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This research aims to identify the predictors of financial distress for the Indonesian listed firms. Variables used are the accounting and market variables. Financial ratios representing profitability, liquidity, and leverage, as well as two important market factors which are firm’s size (SIZE) and price earnings ratio (PER) . The sample consist of 241 firms listed in Indonesia Stock Exchange stretching from 2008 to 2017 and logit regression is applied to predict financial distress. A distressed firm is defined as a firm that has reported a negative value of equity for three consecutive years. Empirical findings from this study show that accounting variable consisting of profitability, liquidity, leverage, and cash flow ratios are significant. Also, SIZE and PER as market variable is significant in predicting financial distress.

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"Biodiesel sebagai bahan bakar nabatimemiliki potensi besar terhadap kelangsungan bahan bakar alternatif di masa mendatang. Biodiesel yang dapat dihasilkan melalui sumber daya terbarukan seperti minyak nabati, ataupun lemak hewan tersebut digunakan dalam studi ini. Tujuan utama dari penelitian yang dilakukan adalah untuk menghasilkan biodiesel dari beberapa jenis sumber minyak nabati dan lemak hewan untuk memiliki profil metil ester yang beragam dalam melihat adanya potensi korelasi antara profil metil ester dengan kualitas produksi biodiesel yang dihasilkan. Produksi biodiesel dilakukan dengan tujuh jenis minyak/lemak yang berbeda. Minyak nabati yang digunakan yakni minyak bunga matahari, minyak kacang tanah, minyak kenari, minyak rapeseed, minyak kelapa terhidrogenasi dan minyak kopra terhidrogenasi serta lemak daging sapi. Setelah produksi biodiesel dilakukan, kualitas biodiesel tersebut pun kemudian diuji sesuai peraturan dan spesifikasi standar EN 14214. Berdasarkan hasil penelitian yang telah dilakukan, diketahui bahwa terdapat hubungan yang kuat antara komposisi metil ester dengan beberapa parameter penting biodiesel seperti viskositas, densitas, titik nyala api, titik penyumbatan cold filter plugging point , nilai kalor lebih tinggi, bilangan iodium dan bilangan saponifikasi. Hasil penelitian menunjukkan bahwa tingkat ketidakjenuhan yang tinggi pada biodiesel akan meningkatkan nilai densitas dan nilai kalor lebih tinggi. Di sisi lain, ikatan rangkap yang terdapat pada biodiesel akan menurunkan stabilitas oksidasi dan mengurangi nilai viskositas biodiesel. Selain itu, tingginya jumlah bilangan saponifikasi akan meningkatkan nilai densitas biodiesel, tetapi untuk parameter titik nyala api, hasil penelitian menunjukkan adanya korelasi yang lemah antara titik nyala api dengan bilangan iodium dan bilangan saponifikasi.

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Biodiesel as an alternative diesel fuel holds promise for the future of alternative fuels. Biodiesel that derived from renewable resources such as vegetable oil was used in this experimental study. The main objective of this study to produce biodiesel from different initial feedstock and to study the composition and the quality of biodiesel profile synthesized. Biodiesels were produced from seven different types of vegetable oil sunflower, peanut, walnut, beef tallow, rapeseed, hydrogenated coconut and hydrogenated copra oil . Then, biodiesel quality was tested according to the EU 14214. The results have related methyl ester profile to several specifications such as viscosity, density, flash point, cold filter plugging point, higher heating value, iodine value and oxidative stability. The results show that high degree of unsaturation will increase the higher heating value and density. On the other hand, large number of double bonds will lower the oxidation stability and reduce viscosity. Moreover, high amount of saponification value will increase the number of density. However, the result shows a weak correlation between flash point in function of iodine value and saponification value."

"Concrete is a composite building material. Due to its increasing demand in the construction industry, its basic ingredients such as cement, fine aggregate and coarse aggregate have become extremely costly. Studies have been carried out to find better and more economical alternatives to these conventional building materials. One such alternative is fly ash, which can be used to partially replace cement. The main disadvantage of conventional concrete is its brittle failure, which can be avoided by using steel fibers. This study identifies the behavior of concrete with regard to impact resistance and its mechanical properties by adding hooked-end steel fibers at levels of 0, 0.75, 1.15 and 1.55% and partially replacing 40% of the cement with 40% fly ash. In addition to the control concrete, there has been four mixes with respective addition of steel fibers. The behavior of normal and fly ash concrete with steel fibers was compared. The combination of fly ash and steel fibers provided a homogeneous and very rich mix, with a delay in the setting time of the concrete. Of all the mixes, the one containing 40% fly ash and 1.55% steel fibers proved to be the best, with a maximum increase in strength of 17% in compression, 25% in split tension, 30% in flexure and 95% in impact energy at 56 days. A multiple linear regression model was also formulated using SPSS (Statistical Package for Social Sciences) software, through which corresponding equations were developed to predict the strength and energy at 28 and 56 days. The equations were also used to predict the strength of the mixes from other researchers’ experimental work. The predicted results corresponded well with the experimental results and the percentage difference was found to be less than 5%."

" The study attempted to identify important ejects ofdemographic characteristics on infant and child mortality. The datafor the study was collected in 2004 under the project of the UNFPAentitled "Strengthening the Department of Population Science andHuman Resource Development" of Rajshahi University,Bangladesh. Application of logistic regression model suggests thatdemographic factors are associated with the chance of cliildsurvival. Breastfeeding and immunization practice of children hashighly significant effects on infant and child mortality among all theincluded demographic variables. The results show that the risk ofinfant and child mortality was higher for children whose mothernever breastfed than for children who were breastfed. The analysisresults also show that the children who got full immunizations hadlower risks of infant and child mortality than those who were notimmunized at all. Similarly, risk of infant and child mortalitygradually declined as both mother ?s age at marriage and mother 'sage at birth increased"

"Many previous researches conveyed the superiority of Steepest Ascent (SA) method to find the optimal area in Response Surface Methodology (RSM) by shifting the experiment factor level. By using this method, Design of Experiment (DoE) is enabled to shift the factor level gradually in the right track, so that the global optimum can be reached. However, the response variable that is commonly optimized by using RSM cannot fulfill the classical statistics assumption of surface regression model. Taguchi’s orthogonal array, as alternative of RSM, gives loose statistics assumptions in performing the analysis. However, Taguchi’s orthogonal array has not yet been supported to shift the factor level to an optimum direction. Adopting the procedures of RSM in finding the optimal level combination using SA, integrating SA method in the Taguchi experiment is proposed in this paper. This procedure is applied into a simulated response surface. Then, the performance of this procedure is evaluated based on its direction to reach the optimum solution. The simulation data representing the real case is generated for two factors. Then, the proposed procedure is applied. The result of this simulation study shows that the integrated SA method in the Taguchi experiment successfully found the factor level combination that yields optimum response even though it is not as close as possible as the RSM results."

"Penelitian ini bertujuan untuk menganalisis dan menguji pengaruh dari pengeluaran pemerintah di bidang kesehatan yang dilihat dari Anggaran Pendapatan dan Belanja Daerah (APBD), serta faktor kontrol lainnya seperti PDRB, tingkat pendidikan yang diukur dengan rata-rata lama sekolah, fasilitas persentase fasilitas sanitasi, fasilitas akses air minum, dokter, dan perbedaan antara Pulau Jawa dengan selain Pulau Jawa terhadap kualitas kesehatan masyarakat di 508 kabupaten atau kota di Indonesia pada tahun 2018 dengan perluasan time frame pada variabel independen sehingga data yang digunakan untuk variabel independent merupakan rata-rata tahun 2014 – 2018. Penelitian ini menggunakan metode Beta Regression Model. Hasil penelitian ini menunjukkan bahwa pengeluaran pemerintah daerah di bidang kesehatan dapat memperbaiki tingkat kualitas kesehatan di daerah. Hal ini berarti anggaran pemerintah pada bidang kesehatan efektif dalam memperbaiki kualitas kesehatan masyarakat di daerah.

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This study aims to analyze and examine the effect of Public Expenditure in the Health Sector as seen from the Regional Government Budget (APBD), as well as other control factors such as GRDP, education level as measured by mean years of schooling, the percentage of sanitation facilities, access to drinking water facilities, doctors, and the difference between Java and non-Java on the Public Health Development Index in 508 districts or cities in Indonesia in 2018 using the Beta Regression Model. The results of this study indicate that local government spending in the health sector can improve the level of health quality in the regions. This means that the government budget in the health sector is effective in improving the quality of public health in the regions."

"Traffic flow on roads is a database that forms the basis of traffic planning and decision-making. Traffic flow data can provide road usage information for road resource allocation, maintenance scheduling, and road infrastructure planning, which can help traffic management and control reduce congestion and ensure safety.The main objective of this research is to develop reproducible code using the R programming language, which is a statistical programming language with data processing, visualisation, and geospatial capabilities that are well suited for interactive use; also, scripts that allow others to reproduce the research and make further improvements based on the research (Lovelace et al., 2022). The GWPR method is used for modelling because it has more accurate and representative results (Yu, 2022), where modelling is applied in 2018 with normal traffic conditions and in 2020 with COVID-19 pandemic conditions where there are many restrictions on travel.The results of the analysis show that the traffic volume variable for each vehicle tends to have a high correlation among variables, which results in modelling having a high standard error value. However, the mode split variable can improve the traffic estimation modelling results.

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Arus lalu lintas di jalan raya merupakan basis data yang menjadi dasar perencanaan lalu lintas dan pengambilan keputusan. Data arus lalu lintas dapat memberikan informasi penggunaan jalan untuk alokasi sumber daya jalan, penjadwalan pemeliharaan, dan perencanaan infrastruktur jalan, yang dapat membantu manajemen dan pengendalian lalu lintas untuk mengurangi kemacetan dan memastikan keselamatan.

Tujuan utama dari penelitian ini adalah untuk mengembangkan kode yang dapat direproduksi menggunakan bahasa pemrograman R, yaitu bahasa pemrograman statistik dengan kemampuan pemrosesan data, visualisasi, dan geospasial yang sangat sesuai untuk penggunaan interaktif; juga, skrip yang memungkinkan orang lain mereproduksi penelitian ini dan melakukan perbaikan lebih lanjut berdasarkan penelitian tersebut (Lovelace dkk., 2022). Metode GWPR digunakan untuk pemodelan karena memiliki hasil yang lebih akurat dan representatif (Yu, 2022), di mana pemodelan diterapkan pada tahun 2018 dengan kondisi lalu lintas normal dan pada tahun 2020 dengan kondisi pandemi COVID-19 di mana terdapat banyak pembatasan perjalanan.

Hasil analisis menunjukkan bahwa variabel volume lalu lintas untuk setiap jenis kendaraan cenderung memiliki korelasi antar variabel yang tinggi, yang mengakibatkan pemodelan memiliki nilai standard error yang tinggi. Namun, variabel moda split dapat memberikan hasil pemodelan estimasi lalu lintas."

"Dalam beberapa dekade terakhir, isu lingkungan terkait pemanasan global menjadi pusat perhatian. Pemanasan global menyebabkan terjadinya perubahan iklim karena adanya peningkatan gas rumah kaca yang terjadi akibat penumpukan karbon yang terakumulasi di atmosfer. Peran vegetasi sebagai penyerap karbon menjadi salah satu bagian penting untuk mengurangi gas rumah kaca di atmosfer dalam rangka mengatasi pemanasan global. Penelitian ini bertujuan untuk memetakan dan menganalisis persebaran spasial stok karbon di wilayah Bali Bagian Selatan serta menganalisis hubungan tutupan lahan dengan kerapatan vegetasi terhadap stok karbonnya. Estimasi stok karbon dilakukan dengan membuat model regresi antara nilai stok karbon aktual dengan nilai piksel hasil transformasi indeks vegetasi NDVI pada citra yang diperoleh dari pengolahan citra satelit Sentinel 2-A. Model regresi terbaik akan digunakan untuk mengestimasi persebaran stok karbon di Bali Bagian Selatan. Hubungan nilai stok karbon terhadap tutupan lahan dilakukan menggunakan analisis overlay untuk melihat hubungan kedua variabel tersebut. Hasil penelitian ini menunjukkan bahwa sebagian besar wilayah Bali Bagian Selatan persebaran stok karbon di Bali Bagian Selatan tahun 2015 dan 2021 memiliki stok karbon yang cenderung meningkat. Hubungan tutupan lahan dan stok karbon menunjukkan bahwa perubahan tutupan lahan berdampak pada perubahan nilai stok karbon di Bali Bagian Selatan.

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Global warming causes climate change due to an increase in greenhouse gases that occur because of the accumulation of carbon that accumulates in the atmosphere. The role of vegetation as a carbon sink is an essential part of reducing greenhouse gases in the atmosphere to overcome global warming. This study aims to map and analyze the spatial distribution of carbon stocks in Southern Bali and analyze the relationship between land cover and vegetation density on carbon stocks. Carbon stock estimation is performed by creating a regression model between the actual carbon stock value and the pixel value resulting from the transformation of the vegetation index (NDVI) obtained from processing Sentinel 2-A satellite imagery. The best regression model will be used to estimate the distribution of carbon stocks in Southern Bali. The relationship between the change of carbon stock value and land cover change was carried out using overlay analysis to see the relationship between the two variables. The results showed that the distribution of carbon stocks in Southern Bali tends to increase. Land cover change has an impact to the change of carbon stock value in Southern Bali."

"Model regresi logistik spasial membangun persamaan dengan jenis variabel dependen adalah biner serta mempertimbangkan dependensi spasial pada data. Proses estimasi parameter pada model ini memerlukan algoritma EM. Namun, bentuk ekspektasi dari complete log-likelihood pada E-step tidak tersedia dalam closed-form. Dalam menangani permasalahan ini, metode terbaru yang sedang diteliti oleh Cecille Hardouin memanfaatkan pendekatan deterministik dikenal dengan metode variasional. Metode variasional merupakan metode aproksimasi distribusi yang memanfaatkan suatu batas bawah fungsi distribusi yang akan diaproksimasi lalu mengoptimalkan batas bawah ini. Metode variasional untuk estimasi parameter model regresi logistik spasial bekerja dengan mencari suatu batas bawah dari complete log-likelihood lalu memaksimumkan fungsi ini terhadap parameter model. Dalam studi literatur, didapatkan bahwa metode variasional memiliki akurasi lebih baik daripada algoritma EM dengan aproksimasi Laplace ketika dependensi spasial pada data relatif besar.

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The spatial logistic regression model builds equations in which the dependent variable is binary and considers the spatial dependency on the data. Estimation procedure of the parameters in this model require EM algorithm. However, the expected form of the complete log-likelihood on the E-step is not available in closed-form. In order to deal with this problem, a recent method being researched by Cecille Hardouin utilizes a deterministic approach known as the variational method. The variational method is a distribution approximation method that utilizes a lower bound of the distribution function to be approximated and then optimizes this lower bound. The variational method for estimating the parameters of the spatial logistic regression model works by finding a lower limit of the complete log-likelihood and then maximizing this function to the model parameters. In the literature study, it was found that the variational method has better accuracy than the EM algorithm with Laplace's approximation when the spatial dependence on the data is relatively large."

"Terdapat perdebatan literature mengenai dampak inklusi keuangan ke ketimpangan pendapatan, utamanya di Indonesia. Beberapa penelitian menyatakan bahwa inklusi keuangan berpengaruh negatif terhadap ketimpangan pendapatan. Artinya, semakin tinggi inklusi keuangan, maka ketimpangan pendapatan akan menutun. Sementara itu, beberapa penelitian lainnya menemukan hasil yang berbeda. Dampak inklusi keuangan ke ketimpangan pendapatan dapat berbeda-beda tergantung pada berbagai faktor, sehingga terdapat hasil penelitian yang berbeda-beda. Penelitian-penelitian terdahulu lebih banyak berfokus pada dampak inklusi keuangan ke ketimpangan pendapatan dan tidak banyak membahas mengenai transmisi dibaliknya serta mengapa dampak inklusi keuangan ke ketimpangan pendapatan dapat berbeda-beda. Penelitian ini bertujuan untuk mengestimasi dampak inklusi keuangan ke ketimpangan pendapatan kondisional terhadap intensitas keuangan mikro yang direpresentasikan oleh struktur keuangan. Data yang digunakan pada penelitian ini adalah data tahunan 33 provinsi di Indonesia dari tahun 2010 hingga 2020. Regresi panel data digunakan sebagai metode analisis. Hasil penelitian menunjukkan bahwa inklusi keuangan dan interaksi antara inklusi keuangan dan struktur keuangan tidak berdampak signifikan terhadap ketimpangan pendapatan. Akan tetapi, analisis pada sub-sample menunjukkan bahwa pada provinsi dengan nilai IPM tinggi, inklusi keuangan berdampak negatif signifikan terhadap ketimpangan pendapatan, sedangkan interaksi antara inklusi keuangan dan struktur keuangan menguatkan dampak negatif inklusi keuangan ke ketimpangan pendapatan.

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There are currently debates surrounding empirical studies regarding the effect of financial inclusion on income inequality in Indonesia. Several researchers argue that financial inclusion have negative effect on income inequality. It means that the higher the financial inclusion, the lesser income inequality will be. Meanwhile, several others find different results. The effect of financial inclusion on income inequality might be conditional to several other factors and therefore there are mixed results from empirical studies. These studies also mainly focused on assessing the effect of financial inclusion on income inequality but fails to answer as to why the relationship between these two variables behave in certain way. This study aims to investigate the effect of financial inclusion on income inequality conditional to microfinance intensity that is represented by financial structure. The data used in this study are the Indonesia’s 33 provinces yearly data from 2010 to 2020. Panel Data Regression is used as the statistical tool. The result showed that financial inclusion and the interaction between financial inclusion and financial structure does not significantly affect income inequality. However, the result of sub-sample analysis showed that for provinces with high HDI, financial inclusion affects income inequality in negative sign, while the interaction between financial inclusion and income inequality strengthen the effect of financial inclusion on income inequality. "