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All Journal CommIT (Communication & Information Technology) Jurnal Ekonomi & Studi Pembangunan Industri Inovatif : Jurnal Teknik Industri Pangripta Jurnal Ilmiah Kajian Perencanaan Pembangunan
Rahma Fitriani
Jurusan Matematika, Fakultas Matematika Dan Ilmu Pengetahuan Alam Universitas Brawijaya Malang
Humanities Computer Science & IT Economics, Econometrics & Finance Industrial & Manufacturing Engineering Social Sciences

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Spatially Filtered Ridge Regression Modeling to Find Out the Rice Production Factors in East Java, Indonesia Vita Dewi Islami; Rahma Fitriani; Henny Pramoedyo
CommIT (Communication and Information Technology) Journal Vol. 14 No. 2 (2020): CommIT Journal
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21512/commit.v14i2.6665

Abstract

The research aims to model rice production in East Java using the Spatially Filtered Ridge Regression (SFRR) method and ensure that all violations of assumptions are resolved by knowing the direct and indirect effect of predictor variables. The data are secondary data sourced from the publication of Badan Pusat Statistik containing provincial food crop agriculture statistics in East Java and the 2018 publication of Dinas Pertanian Jawa Timur (literally translated as Agriculture Department of East Java). The data analysis process is done by RStudio and ArcMap 10.3 software. In the research, the observation unit is 38 regencies or cities in East Java. The analysis results show that SFRR with queen contiguity weighting can overcome spatial autocorrelation and multicollinearity in rice production data in East Java. As for the established model, the variables of rice field area, urea fertilizer, Phonska fertilizer, SP-36 fertilizer, and tractor have a significant effect on rice production. However, ZA fertilizer has no significant effect on rice production. Then, a large comparison of direct and indirect impacts for each predictor variable is also generated. Generally, direct impacts are greater than indirect impacts.
ACCELERATED FAILURE TIME MODEL CURE RATE Liduina Asih Primandari; Henny Pramoedyo; Rahma Fitriani
Industri Inovatif : Jurnal Teknik Industri Vol 3 No 2 (2013): inovatif Vol. 3 No. 2
Publisher : Prodi Teknik Industri S1 Institut Teknologi Nasional Malang

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Abstract

Accelerated Failure Time (AFT) adalah metode yang digunakan untuk mengetahui hubungan antar peubah yangmempengaruhi waktu survival. Metode ini diperluas dengan menggunakan model cure rate. Model cure ratedigunakan apabila data survival terbagi menjadi dua kelompok pasien yaitu susceptible dan immune. Pasiendikatakan susceptible apabila pasien mengalami kejadian yang diamati (kematian) dan dikatakan immune apabilapasien tersebut masih hidup pada akhir penelitian. Model AFT dengan penambahan model cure rate diterapkandalam 3 sebaran yakni sebaran Eksponensial, Weibull dan Log – Logistik kemudian diaplikasikan untukmengetahui hubungan antara usia pasien (Y1) dan waktu menunggu hingga memperoleh donor (Y2) terhadapwaktu survival pasien penerima sumsum tulang belakang (X). Berdasarkan hasil penelitian, diperolehkesimpulan bahwa model AFT parametrik dapat digabungkan dengan model cure rate dengan terlebih dahulumembentuk fungsi survival dari model AFT parametrik. Model AFT parametrik dengan penambahan model curerate hanya dapat digunakan apabila waktu survival terbagi menjadi dua kelompok pasien, yakni susceptible danimmune. Penambahan model cure rate memberikan tambahan informasi, yakni dapat diketahui pula proporsiindividu yang masih hidup (tersensor) dalam kasus ini. Informasi ini dapat berguna untuk mengetahuikeefektifan dari pengobatan yang telah dilakukan.
PENGUKURAN INDEKS KEPUASAN LAYANAN INFRASTRUKTUR (IKLI) KOTA MALANG TAHUN 2022: PENGUKURAN INDEKS KEPUASAN LAYANAN INFRASTRUKTUR (IKLI) KOTA MALANG TAHUN 2022 Eddi Basuki Kurniawan; Rahma Fitriani; Zakaria
PANGRIPTA Vol 6 No 1 (2023): PANGRIPTA
Publisher : Bappeda Kota Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (462.351 KB) | DOI: 10.58411/pangripta.v6i1.187

Abstract

Abstract: Measurement of Malang City Infrastructure Service Satisfaction Index (IKLI) is intended to measure the level of quality and service of infrastructure in Malang City in the 2018-2023 Malang City RPJMD Amendment document, there are target changes to several Regional Performance Indicators based on City Infrastructure Service Satisfaction Index targets Malang in 2022 is 4.35. The measurement of the Malang City Infrastructure Service Satisfaction Index (IKLI) in 2022 is expected to be able to describe the condition of community satisfaction with infrastructure in Malang City. The purpose of this study is to measure the number/achievement of the infrastructure service satisfaction index in 2022. The analysis techniques used are Importance Performance Analysis (IPA), Gap Analysis of Infrastructure Service Satisfaction Index, and Potential Gain Customer Value (PGCV) Analysis. The results of this analysis, namely the 2022 IKLI score of 4.36 are included in the satisfied category which has met the Malang City RPJMD Amendment target for 2018-2023, and there are recommendations for 6 indicators used as indicators of physical availability, physical quality, suitability (appropriateness), utilization (utility), employment (job creation), and contribution to the economy
Fix effect sur to analyze economic growth in developed and developing countries Muhamad Liswansyah Pratama; Rahma Fitriani; Suci Astutik
Jurnal Ekonomi & Studi Pembangunan Vol 24, No 1: April 2023
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jesp.v24i1.17821

Abstract

This study aims to identify the relationship between population density, inflation, and unemployment rates on the human development index, GNP, export-import, and urbanization in the developed and developing countries category using the Fix Effect Seemingly Unrelated Regression (FE SUR) with a dummy variable as the slope component. This research necessitates the development of the Seemingly Unrelated Regression model, specifically the Panel Seemingly Unrelated Regression (Panel SUR) model with a dummy variable as the slope component, due to the dynamic nature of the data and the fact that the same set of predictor variables explains the five response variables. The Panel, the Seemingly Unrelated Regression model with dummy variables, can accommodate research objectives where the SUR model can explain the influence between variables, differences in characteristics between countries can be explained by fixed effect models, and differences in the effect of population density, inflation, and unemployment rates on the human development index, GNP, exports imports and urbanization in the categories of developed and developing countries can be explained by slope dummy variables. The results showed that 98.46% of the diversity of response variables (human development index, GNP, exports, imports, and urbanization) could be explained by predictor variables (population density, inflation, and unemployment rate), while the other 1.54% was explained by other factors not included in the fixed effect SUR model. In addition, the results show that population density has a significant positive relationship with GNP, imports, and exports. However, there is a significant negative relationship between unemployment and GNP. There are large differences in the relationship between the unemployment rate and GNP in developed and developing countries, whereas in developed countries, there is a larger and negative relationship compared to developing countries.
Co-Authors Eddi Basuki Kurniawan Henny Pramoedyo Liduina Asih Primandari Muhamad Liswansyah Pratama Suci Astutik Vita Dewi Islami Zakaria