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All Journal J Statistika: Jurnal Ilmiah Teori dan Aplikasi Statistika Al-Ard: Jurnal Teknik Lingkungan Jurnal Pertanahan Journal of Regional Economics Indonesia
Joko Ade Nursiyono
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences

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Determinan Harga Tanah di Indonesia Menggunakan Big Data (Studi Kasus: www.lamudi.co.id) Joko Ade Nursiyono; Dewi, Dyah Makutaning
Jurnal Pertanahan Vol 11 No 2 (2021): Jurnal Pertanahan
Publisher : Pusat Pengembangan dan Standarisasi Kebijakan Agraria, Tata Ruang dan Pertanahan, Kementerian Tata Ruang dan Pertanahan, Badan Pertanahan Nasional

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3668.758 KB) | DOI: 10.53686/jp.v11i2.105

Abstract

ABSTRAKKehidupan masyarakat berkaitan dengan tanah, sehingga membutuhkan lahan untuk tempat tinggal dan beraktivitas. Namun ketersediaan lahan kosong sangat terbatas karena adanya kenaikan jumlah penduduk di Indonesia, sehingga berdampak pula terhadap harga tanah. Tujuan penelitian ini adalah memberikan gambaran kondisi transaksi penjualan tanah dan menganalisis faktor-faktor yang memengaruhi harga tanah di Indonesia. Metode penelitian menggunakan regresi linear berganda yang dipadukan dengan big data. Hasil penelitian menunjukkan faktor-faktor yang signifikan berpengaruh terhadap harga tanah di Indonesia yaitu luas tanah dan posisi tanah (strategis atau tidak strategis). Harga tanah yang semakin mahal dan tidak sebanding dengan pendapatan masyarakat mengakibatkan masyarakat kesulitan untuk membeli rumah karena harga semakin tinggi. Oleh karenanya, diperlukan payung hukum guna mengawasi harga tanah di Indonesia.Kata kunci : harga tanah, big data, regresi linear berganda ABSTRACTCommunity life is related to land, so it requires land for shelter and activity. But the availability of vacant land today is very limited because of the increase of the number of people in Indonesia, so that it also has an impact on land prices. The purpose sof this study are to provide an overview of the condition of land sales transactions and analyze the factors that affect land prices in Indonesia. The research method uses multiple linear regression combined with big data. The results showed the significant factors affect land prices in Indonesia, are land area and land position (strategic or not strategic). The higher land prices are not comparable to the community income, so that people difficult to buy a house. It is necessary to prepare a legal protection in supervising land prices in Indonesia.Keywords : land price, big data, multiple linear regression
Analisis Sentimen Netizen Twitter terhadap Pemberitaan PPN Sembako dan Jasa Pendidikan dengan Pendekatan Social Network Analysis dan Naive Bayes Classifier Joko Ade Nursiyono; Chusnul Chotimah
J STATISTIKA: Jurnal Imiah Teori dan Aplikasi Statistika Vol 14 No 1 (2021): Jurnal Ilmiah Teori dan Aplikasi Statistika
Publisher : Faculty of Science and Technology, Univ. PGRI Adi Buana Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (421.889 KB) | DOI: 10.36456/jstat.vol14.no1.a3868

Abstract

Pandemi covid-19 yang terjadi memberikan dampak di berbagai bidang kehidupan. Salah satu dampaknya penerimaan negara semakin tertekan hebat. Padahal di sisi lain negara dalam proses pemulihan ekonomi nasional (PEN) yang membutuhkan dana sangat besar. Sehingga pemerintah ingin menggenjot pendapatan negara dari pajak pertambahan nilai (PPN). Jika pemungutan PPN dapat dilakukan dengan seoptimal mungkin, maka akan meningkatkan penerimaan negara. Rencana tersebut mengakibatkan maraknya pemberitaan mengenai pengenaan PPN sembako dan jasa pendidikan di Indonesia. Pemberitaan tersebut secara otomatis memicu opini di masyarakat. Salah satu cara untuk melihat opini masyarakat adalah melalui media sosial Twitter. Penelitian ini bertujuan untuk mengkaji lebih dalam tentang network dan sentimen netizen Twitter tentang PPN Sembako dan jasa pendidikan. Hasil Social Network Analisis (SNA) menghasilkan 5 klaster dengan record ke-90 merupakan bottleneck node yaitu aktor utama penyebaran informasi antar klaster. Model Naive Bayes Classifier memberikan hasil Recall Accuracy bahwa untuk Accuracy Classified sebesar 74.865 persen sementara persentase untuk Incorrectly Classified Instance sebesar 25.135 persen. Hasil klasifikasi berdasarkan emosi terbentuk 5 ekspresi fear, sadness, surprise, joy, dan anger dan emosi kata yang paling banyak adalah emosi anger (amarah), artinya mayoritas respon masyarakat terhadap kebijakan pengenaan PPN sembako dan jasa pendidikan diidentifikasikan oleh R Studio sebagai wujud keamarahan.
Determinan Indeks Pembangunan Manusia Jawa Timur Tahun 2020 dengan Pendekatan Geograpichally Weighted Regression Khaerul Agus; Joko Ade Nursiyono; Chusnul Chotimah
Journal of Regional Economics Indonesia Vol 3, No 1 (2022): Februari 2022
Publisher : University Merdeka Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26905/jrei.v3i1.8003

Abstract

HDI is an outcome indicator that measures how much of a development impact is felt by the community. In addition to being a measure of development success, HDI is also used as an important component of Key Performance Indicators (IKU), especially contained in targets 7 and 9. Data mentions that HDI increases every year, especially the East Java region. However, the speed of HDI has not been accompanied by a decreased maternal and infant mortality rate. The study aimed to look at the spatial influence of the percentage of maternal and infant mortality on HDI. The study also included dependency ratio variables and gender empowerment indices to sharpen the analysis. The approaches used are OLS regression and Geographically Weighted Regression (GWR). By looking at the lowest AIC value and the highest R Square, the best GWR model is obtained. A SQUARE GWR value of 0.7226 indicates the model's ability to explain the proportion of HDI diversity is 72.26 percent, while the rest is determined by other variables outside the model.
Determinants of the Amount of Waste in East Java Joko Ade Nursiyono; Chotimah, Chusnul; Fitrianti , Warisna Endah
Al-Ard: Jurnal Teknik Lingkungan Vol. 7 No. 2 (2022): March
Publisher : Department of Environmental engineering, Faculty of Science and Technology, Islamic State University Sunan Ampel Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29080/alard.v7i2.1405

Abstract

Listed as one of the largest waste contributor provinces in Indonesia. The population of East Java in 2020 reached 39 million people, it is the second highest in Indonesia. The increasing number of people accompanied by an increase in income will increase people's consumption in an area and this will cause the increasing amount of waste. If this waste problem is not handled properly, it will have a domino effect as well as degrading the environment. This study wanted to determine the effect of population, real expenditure per capita per year and the number of waste banks on the amount of waste in 2020 in East Java Province. This study uses a comparison of OLS Regression and Robust Regression models. The criteria for selecting the best model use the smallest MAPE, RMSE, and RSE values and the largest R-square value. The results of the partial test and the simultaneous test show that the variables of population, real expenditure per capita per year and the number of waste banks significantly affect the variable amount of waste in East Java with the selected model is the Robust Regression model. The R-square value of the Robust Regression model in this study is 0.8909, meaning that the model's ability to explain the variability of the East Java waste amount data is 89.09 percent, and the rest is explained by other variables not included in the model.
Co-Authors Chusnul Chotimah Chusnul Chotimah Chusnul Chotimah Dewi, Dyah Makutaning Fitrianti , Warisna Endah Khaerul Agus