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This study examines the relationship between the Human Development Index (HDI) and population size with economic growth in North Sumatra Province during 2010-2025 using multiple linear regression based on secondary data. The results indicate that both variables are jointly associated within the model, although they show different directions when observed individually. Population size tends to move in line with economic growth, while HDI shows an opposite tendency. These findings suggest that improvements in human capital have not yet been fully reflected in productive economic activities in the region.

This research aims to: 1) examine the development of the Human Development Index (HDI), Labor Force Participation Rate (LFPR), population size, economic growth, and the poverty gap index in the regencies/cities of Jambi Province from 2020 to 2024; and 2) analyze the influence of the Human Development Index, Labor Force Participation Rate, population size, and economic growth on the poverty gap index in the regencies/cities of Jambi Province. The research method employed is descriptive quantitative. The analytical tool used is Panel Data Regression through the Fixed Effect Model (FEM) approach, processed with EViews 12 software. The results show that the Human Development Index, population size, and economic growth have a significant influence on the poverty gap index in the regencies/cities of Jambi Province during the 2020-2024 period. Conversely, the LFPR does not have a significant effect on the poverty gap index in the region during the same period. These findings imply the importance of strengthening human resource quality through HDI improvement and more inclusive economic growth policies in Jambi Province. Furthermore, the government needs to evaluate the quality of available employment, as the high Labor Force Participation Rate (LFPR) has not yet been able to significantly reduce the depth of poverty.

Penelitian ini bertujuan untuk menganalisis pengaruh knowledge sharing dan pemberdayaan pegawai terhadap kinerja pegawai melalui kepuasan kerja sebagai variabel intervening pegawai di Dinas Pemberdayaan Perempuan, Perlindungan Anak, Pengendalian Penduduk dan Keluarga Berencana Kabupaten Pekalongan. Populasi yang digunakan dalam penelitian ini adalah seluruh pegawai di Dinas Pemberdayaan Perempuan, Perlindungan Anak, Pengendalian Penduduk dan Keluarga Berencana Kabupaten Pekalongan yang berjumlah 105 orang. Jumlah sampel yang digunakan adalah 84 orang yang dipilih dengan Slovin secara proporsional random sampling. Teknik analisis data yang digunakan adalah Structural Equation Modeling-Partial Least Square (SEM-PLS). Hasil penelitian menunjukkan bahwa knowledge sharing dan pemberdayaan pegawai berpengaruh positif dan signifikan terhadap kepuasan kerja dan kinerja pegawai. Kepuasan kerja juga berpengaruh signifikan terhadap kinerja pegawai. Hasil penelitian juga menunjukkan bahwa kepuasan kerja memiliki peran mediasi dalam memediasi knowledge sharing dan pemberdayan pegawai terhadap kinerja pegawai.

Tebing Tinggi City, which has a strategic position in North Sumatra, is experiencing changes in population growth that need to be predicted for development planning purposes. The purpose of this study is to forecast the population of Tebing Tinggi City in 2030 by applying the Double Integral method, and visualize the results in 3D using GeoGebra. The method used is a quantitative approach with a case study, where the population density function is created based on secondary data from the Central Statistics Agency (BPS) of Tebing Tinggi City for the period 2010 to 2024. Data on area and population per sub-district are used to develop a population growth model calculated using the double integral. The forecast results show that the population of Tebing Tinggi City is estimated to reach 26,038 people in 2030, with varying growth rates in each sub-district. 3D visualization through GeoGebra is able to depict the distribution of population density in an interactive geometric form, thus facilitating the understanding of complex mathematical concepts. The conclusion of this study is that double integrals can be applied effectively to predict population size, and GeoGebra serves as a very useful visual aid in presenting the results of multivariable calculus analysis.

This study aims to predict the total population of Deli Serdang Regency for the year 2025 using a multiple linear regression approach. The data used were obtained from the Central Bureau of Statistics (BPS) of Deli Serdang for the years 2015–2024, with total population as the dependent variable and male population and the percentage of male population as the independent variables. The analysis was carried out through a series of basic assumption tests, including normality, multicollinearity, heteroscedasticity, and autocorrelation, all of which indicated that the model met the criteria for a valid regression model. The results of the F-test and t-test showed that both independent variables had a significant influence on the total population. The R² value of 1.000 indicates that the model is capable of explaining 100% of the variation in the population size. Based on the regression model obtained, the projected total population of Deli Serdang in 2025 is estimated to reach 4,075,362 people, an increase of 2,026,882 people from the previous year. These findings are expected to serve as a basis for regional development planning, particularly in the provision of public services and resource management.

Indonesia, with its rapid economic growth, is still haunted by persistent poverty problems. Inflation is like a parasite that sticks to economic growth, has the potential to worsen the poverty gap and hinder its overcoming. The aim of this research is to examine how economic growth and inflation in Indonesia affect the level of poverty in Indonesia. Panel data collected between 1994 and 2023 from 34 provinces in Indonesia is the data source. Multiple linear regression analysis is the technique used. The findings show that the number of poor people in Indonesia is not significantly affected by economic growth or inflation. Only 25.7% of the fluctuation in the number of poor people can be explained by the regression model, based on a coefficient of determination (R-square) of 0.257; the remaining 74.3% can be explained by other factors not taken into account in this study.

Infeksi Saluran Pernapasan Akut (ISPA) merupakan masalah kesehatan utama di Kabupaten Tegal, terutama menyerang anak-anak dan lansia, dengan 25.273 kasus tercatat pada Januari–Juni 2025. Faktor seperti kepadatan penduduk, polusi udara, dan sanitasi buruk mempersulit analisis konvensional dalam mengidentifikasi wilayah berisiko tinggi. Penelitian ini bertujuan mengembangkan Sistem Informasi Geografis (SIG) berbasis web untuk memetakan dan memantau kasus ISPA secara akurat menggunakan pendekatan spasial. Metode Waterfall digunakan dalam pengembangan sistem, meliputi analisis kebutuhan, perancangan, implementasi, pengujian, dan pemeliharaan. Data spasial (koordinat lokasi) dan non-spasial (usia, jenis kelamin, jumlah kasus) dikumpulkan dari Dinas Kesehatan dan dianalisis menggunakan teknik kepadatan titik dan klaster untuk mengidentifikasi pola sebaran. Sistem ini dibangun dengan framework Laravel sebagai backend dan Leaflet.js untuk visualisasi peta interaktif. Hasilnya, SIG ini mampu memvisualisasikan sebaran kasus ISPA per kecamatan, mendukung Dinas Kesehatan dalam mengalokasikan sumber daya medis secara efisien dan mengidentifikasi wilayah prioritas seperti Dukuhwaru dan Tarub. Bagi masyarakat, sistem ini meningkatkan akses informasi digital, mendorong kesadaran pencegahan, dan mendukung edukasi kesehatan. Sistem ini terbukti efektif sebagai alat strategis untuk pengambilan keputusan berbasis data, mempercepat respons terhadap ISPA, dan menjadi fondasi untuk pengembangan SIG dalam memantau penyakit lain di masa depan.

Kemiskinan merupakan salah satu tantangan terbesar yang dihadapi oleh berbagai negara, termasuk Indonesia. Tingginya jumlah penduduk miskin di beberapa wilayah, seperti di Provinsi Jawa Tengah, mencerminkan kompleksitas permasalahan yang dipengaruhi oleh kualitas sumber daya manusia, tingkat kemiskinan, dan pembangunan ekonomi. Provinsi Jawa Tengah, dengan populasi besar, memiliki tingkat kemiskinan yang signifikan, sehingga memerlukan intervensi strategi untuk mengoptimalkan penyaluran program pembangunan. Untuk mendukung pemerintah dalam menentukan prioritas penanganan kemiskinan secara efektif dan efisien, diperlukan sistem pendukung keputusan. Penelitian ini memiliki tujuan untuk merancang sistem pendukung keputusan berbasis TOPSIS yang efisien dan mampu memberikan rekomendasi terbaik berdasarkan beberapa kriteria utama: jumlah penduduk, Tingkat pengangguran, upah minimum, PDRB, dan jumlah penduduk miskin. Hasil analisis menunjukkan bahwa Kota Semarang memiliki tingkat kemiskinan terendah dengan nilai preferensi tertinggi (0,686725), sedangkan Kabupaten Brebes memiliki tingkat kemiskinan tertinggi dengan nilai preferensi terendah (0,154773). Validasi metode TOPSIS yang diterapkan dalam sistem ini mencapai tingkat akurasi sebesar 77,17% yang menunjukkan bahwa hasil pemeringkatan konsisten dengan keselarasan signifikan antara hasil sistem dan kondisi riil. Dengan demikian, sistem pendukung keputusan ini memberikan kontribusi nyata dalam mengklasifikasi wilayah berdasarkan tingkat kemiskinan, sehingga dapat menjadi alat bantu strategi dalam perencanaan program Pembangunan yang lebih tepat sasaran.

This study aims to examine the influence of the number of poor people, average years of schooling, and labor force participation rate on the open unemployment rate (OUR) in Maluku Province from 2017 to 2023. The study uses panel data from 11 districts/cities and applies a regression model using a fixed effect approach. The results show that the average years of schooling have a positive and significant effect on the open unemployment rate. This implies that the longer an individual pursues education, the higher the likelihood of unemployment, as they tend to have higher job expectations and are less willing to accept available jobs. Meanwhile, the labor force participation rate has a negative and significant effect, indicating that a higher number of actively working individuals leads to a lower unemployment rate. The number of poor people does not have a significant effect on unemployment. Overall, the model explains approximately 53.5% of the variation in the open unemployment rate. These findings indicate that education and labor participation are crucial factors in reducing unemployment, but must be supported by the availability of suitable employment opportunities.

This study aims to analyze the effect of population size and open unemployment rate on the Human Development Index (HDI) in Riau Province. The research method used is a descriptive quantitative approach with multiple linear regression analysis. The data used is secondary data based on districts/cities in Riau Province obtained from the Central Statistics Agency (BPS). The analysis results indicate that population size has a positive and significant effect on the HDI, while the open unemployment rate has a negative and significant effect. The F-test also shows that both variables simultaneously have a significant effect on the HDI. The R-squared value of 56.08% indicates that the model adequately explains the variation in the HDI. These findings suggest that improving population quality and reducing unemployment rates are key factors in enhancing human development quality in Riau Province.

This study aims to analyze the influence of population size, Human Development Index (HDI), and Open Unemployment Rate (OUR) on poverty levels in regencies/cities of Special Region of Yogyakarta during 2018-2023 period. The research employed quantitative design with panel data regression analysis approach across five regencies/cities in DIY. Secondary data were obtained from official publications of Statistics Indonesia Yogyakarta Province and analyzed using Fixed Effect Model and Random Effect Model with Stata 17 software. The research findings indicate that HDI has negative and significant effect on poverty level, suggesting that improvement in human resource quality effectively reduces poverty. OUR proved to have positive and significant effect on poverty, confirming that increased unemployment raises poverty levels. Conversely, population size shows no significant influence on poverty in DIY. These findings provide strategic implications for local government to prioritize investment in education and health sectors as well as job creation programs in poverty alleviation efforts. High inter-regional heterogeneity indicates the necessity for policy approaches tailored to specific characteristics of each regency/city in DIY.

This study analyzes the effect of population and Human Development Index (HDI) on poverty in Jambi Province in the period 2018–2024. Using panel data from 11 districts/cities and regression methods with the best approach Random Effect Model (REM), the results show that poverty in Jambi tends to fluctuate. Tanjung Jabung Timur has the highest poverty rate, while Sungai Penuh City has the lowest. This study provides empirical understanding to support the formulation of more targeted poverty alleviation policies at the regional level.

Di era globalisasi, jumlah penduduk Indonesia mengalami pertumbuhan pesat. Akibatnya, muncul tantangan baru dimana terdapat ketidakseimbangan antara jumlah lapangan pekerjaan dengan pencari kerja, yang secara tidak langsung menyebabkan meningkatnya angka pengangguran. Meskipun demikian, banyak mahasiswa yang masih ingin berkarir sebagai pekerja, akibat faktor kenyamanan. Padahal, kewirausahaan dapat menjadi solusi untuk menghindari ancaman pengangguran. Oleh sebab itu, penelitian ini bertujuan untuk menunjukkan pengaruh dari variabel kreativitas, pendidikan kewirausahaan, dan lingkungan keluarga terhadap minat berwirausaha mahassiswa akuntansi. Metode pengumpulan data yang digunakan dalam penelitian ini adalah pendekatan kuantitatif dengan menyebarkan kuesioner menggunakan metode snowball terhadap 64 responden mahasiswa akuntansi di Universitas Atma Jaya Semanggi. Dalam penelitian ini, analisis data dilakukan dengan menggunakan aplikasi smartPLS 4 dengan 3 teknik analisis, yaitu analisis model pengukuran, model struktural, dan kelayakan model. Hasil dari kegiatan penelitian ini menunjukkan bahwa variabel kreativitas dan lingkungan keluarga secara independen memiliki pengaruh positif dan signifikan terhadap variabel minat berwirausaha, sedangkan variabel pendidikan kewirausahaan tidak memiliki pengaruh yang signifikan terhadap variabel minat berwirausaha. Implikasi yang diperoleh dari hasil kegiatan penelitian adalah tingkat kreatifitas mahasiswa dan dukungan lingkungan keluarga memainkan peranan yang penting dalam menumbuhkan minat berwirausaha mahasiswa.

Timbulan sampah di Kabupaten Bone Bolango menunjukkan tren peningkatan yang signifikan dari tahun ke tahun, seiring dengan pertumbuhan jumlah penduduk, ekspansi kawasan permukiman, dan aktivitas ekonomi masyarakat. Berdasarkan data dari Sistem Informasi Pengelolaan Sampah Nasional (SIPSN), terjadi lonjakan volume sampah harian dari 2022 hingga 2024. Namun, peningkatan ini tidak diimbangi dengan kapasitas pengelolaan yang memadai, baik dari sisi infrastruktur, kelembagaan, maupun partisipasi masyarakat. Studi ini bertujuan untuk mengkaji model pengelolaan sampah berkelanjutan di Kabupaten Bone Bolango melalui pendekatan sistem, dengan merujuk pada literatur dan data sekunder. Metode analisis menggunakan pendekatan Causal Loop Diagram (CLD) dan Stock Flow Diagram (SFD) untuk mengidentifikasi hubungan kausal dan dinamika sistem pengelolaan sampah di daerah ini. Hasil kajian menunjukkan bahwa akar permasalahan terletak pada lemahnya sinergi antar-pemangku kepentingan, kurangnya regulasi lokal, serta keterbatasan sarana pengolahan. Solusi strategis yang diusulkan meliputi pembangunan fasilitas TPS3R, penyusunan kebijakan persampahan daerah, pemberdayaan masyarakat melalui edukasi lingkungan dan bank sampah, serta penguatan kemitraan dengan sektor swasta dan lembaga non-pemerintah. Diharapkan, pendekatan integratif ini dapat menjadi dasar bagi pengembangan model pengelolaan sampah yang efektif dan berkelanjutan di Kabupaten Bone Bolango.

One of the socioeconomic problems faced by every region is poverty. Poverty is a social issue that takes place in the long term, so that until now it is still difficult to overcome. The purpose of this study was to determine the effect of Population, Open Unemployment Rate (TPT), and Human Development Index on Poverty Level in North Sumatra Province. This study uses secondary data analysis in the form of time series data which is quantitative in nature, namely data in the form of numbers. The secondary data used in this study are poverty data, population data, open unemployment rate data and human development index data from 2001 to 2021. These data were obtained from the North Sumatra in Figures (SUDA) document from 2001 to 2021. The results of this study prove that population has a significant effect on the poverty rate of North Sumatra Province, the open unemployment rate variable has no significant effect on the poverty rate of North Sumatra Province, the human development index variable has no significant effect on the poverty rate of North Sumatra Province. Simultaneously, population, open unemployment rate (TPT), and human development index have a significant effect on the poverty rate in North Sumatra province.

This study aims to analyze the effect of the unemployment rate and population on economic growth in Ringinpitu Village, Tulungagung Regency. The high unemployment rate and the increase in population each year are factors that can affect economic conditions in the region. This study uses a quantitative method with multiple linear regression analysis, processed using SPSS software. The results of the study indicate that the unemployment rate has a negative and significant effect on economic growth with a regression coefficient value of -0.283 and a significance value of 0.001 (p <0.05). Meanwhile, the population has a positive and significant effect on economic growth with a regression coefficient of 1.018 and a significance value of 0.000 (p <0.05). The simultaneous test (F test) shows that the unemployment rate and population together have a significant effect on economic growth, with an F-count value of 35.125 and a significance of 0.000 (p <0.05). The Adjusted R² value of 0.621 indicates that 62.1% of the variation in economic growth can be explained by the unemployment rate and population, while 37.9% is influenced by other factors outside this research model. Based on these findings, it is recommended that local governments improve job training programs, create more jobs, and optimize population growth control policies to encourage more stable and sustainable economic growth.

Kapal Penunpang KM. Dharma Rucitra 9 milik PT. Dharma Lautan Utama (DLU) di wilayah Semarang mengoperasikan layanan penyeberangan Semarang-Kumai, sedangkan KM. Dharma Kartika 2 melayani layanan penyeberangan Surabaya-Banjarmasin yang disediakan pemerintah untuk masyarakat Indonesia. Terdapat beberapa skema dalam pengangkutan bahan baku antara Ship to Ship, Truck to Ship dan Onshore to Ship Pengadaan bahan baku akan dilakukan melalui skema ship to ship dan Truck to ship di wilayah penumpang, sehingga apabila terjadi kecelakaan akan mengakibatkan kerugian yang tidak sedikit, baik dari segi material maupun manusia. Penelitian ini dilakukan dengan tujuan untuk mengetahui pengaruh pemilihan metode bunker terhadap perhitungan ROB (Quantity Remaining On Board), biaya tumpahan minyak Penelitian ini juga bertujuan menganalisis faktor yang paling dominan pengaruhnya terhadap tumpahan minyak ketika saat melakukan proses bunker. Penelitian ini menggunakan metode kuantitatif dengan menggunakan perhitungan-perhitungan ROB Soundingan – Trim = Hasil sounding, selanjutnya adalah perhitungan untuk menentukan jumlah permintaan minyak untuk bunker.   Kapasitas tangki – ROB (Sisa bahan bakar), untuk analisis biaya kasus tumpahan minyak penulis menggunakan rumus dari (W.wirtz,) yaitu sesuai Persamaan   Ln (TC) = 0,4667 x (t) + 13,894. Berdasarkan hasil penelitian ini peneliti bisa menyimpulkan untuk kedua metode bunker sendiri tidak ada kebocoran pada saat proses bunker sehingga aman untuk pemilihan metode bunker tersebut, tetapi untuk analisis pemilihan metode bunker dapat diambil kesimpulan dari segi keamanan, teknis dan biaya metode bunker dengan menggunakan truk to ship lebih efisien, mendapat 80%, segi keselamatan truck to sehip mendapat 60% segi biaya truk to ship mendapat 60%, berdasarkan analisis perhitungan sisa bahan bakar yang telah peneliti analisis tidak ada over muatan atau kelebihan muatan yang segnifikan, Proses identifikasi risiko tumpahan minyak merupakan risiko ringan atau rendah, namun tetap harus diperhatikan dan dikendalikan untuk mengatasinya apabila terjadi risiko besar, dampak dari tumpahan ini berdampak selama 3 bulan maka kerugian yang di alami nelayan sebesar Rp. 1.240.729,- × 36 = Rp.44.666.244,- perhitungan ini hanya untuk satu nelayan sedangkan untuk penduduk pesisir pelabuhan Tanjung perak surabaya 75% berprofesi sebagai nelayan tentu saja ini menjadi kerugian yang besar bagi nelayan.

One of the biggest problems faced by several countries is the rapid increase in population growth, especially in an archipelagic country like Indonesia. One of the cities in North Sumatra Province that has experienced a significant increase in population is Medan City. This study discusses the population growth each year in Medan City. This study predicts the future population by combining historical data on population, birth rate, death rate, and migration using the Adams-Bashforth-Moulton approach in logistic modeling. This study shows the progress of the approach in predicting the population growth of Medan City. With an area of ​​265.10 thousand km2, and a population reaching 2,474,166 people in 2023. The Adams-Bashforth-Moulton method as a logistic growth model is very effective for decision making in predicting population growth in the city of Medan.

The purpose of this research is to create a JST (artificial neural network) model that can forecast population growth at the Population and Civil Registration Office of West Sumba Regency. population growth at the Population and Civil Registration Office of West Sumba Regency. Regency. Regional development planning must consider the increasing number of population, therefore proper forecasting is essential to encourage sustainable policies and initiatives. sustainable policies and initiatives. Because it can identify complex patterns in past data and produce more accurate forecasts than traditional techniques, an ANN model is used. traditional techniques, the ANN model is used. The data used in this study is the population growth of Southwest Sumba Regency over the past including characteristics such as birth and death rates and population movements. deaths and population movements. The backpropagation algorithm is used to optimize the multilayer perceptron (MLP) architecture for ANN training. Separating the data into training and testing sets and assessing the models model using metrics such as Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE) based on the error. Error (RMSE) based on the prediction error are the steps involved in the training process. involved in the training process. The research findings show that, with a low level of error, the artificial neural network model can estimate the population increase in Southwest Sumba Regency with a reasonable level of accuracy. reasonable level of accuracy. The model is expected to serve as a reference for relevant authorities to better manage population data and as a tool to create more focused and successful population policies.

This research aims to determine and analyze the influence of local revenue, general allocation funds, special allocation funds, profit sharing funds and population on financial performance. The study was conducted at district/city governments in West Java Province in 2014-2023. The sample size was set at 27 districts/cities with observation data from 2014 to 2023. The type of data used is secondary data in the form of panel data. The data analysis technique used is multiple linear regression with the Eviews application. The results of this research show that: 1) local original income, special allocation funds, profit sharing funds, population and regional government financial performance have an increasing trend. Meanwhile, general allocation funds have a downward trend; 2) local original income, general allocation funds, special allocation funds, profit sharing funds and population simultaneously influence the financial performance of regional governments; 3) Original regional income has a positive and significant effect on regional government financial performance. General allocation funds and population have an insignificant negative effect on local government financial performance. Special allocation funds have a negative and significant effect on local government financial performance. Profit sharing funds have an insignificant positive effect on local government financial performance.