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DISTRIBUSI KUAT GESER BATUAN PADA FORMASI MUARAENIM YANG MENGANDUNG BATUBARA DI KECAMATAN MERAPI BARAT, KABUPATEN LAHAT, PROVINSI SUMATERA SELATAN Hamid, Nur; Hendarmawan, Hendarmawan; Muslim, Dicky; Ruchjana, Budi Nurani
Buletin Sumber Daya Geologi Vol 11 No 3 (2016): Buletin Sumber Daya Geologi
Publisher : Pusat Sumber Daya Mineral Batubara dan Panas Bumi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47599/bsdg.v11i3.32

Abstract

Masalah kemantapan lereng sering ditemukan dalam operasi penambangan terutama pada dinding penggalian tambangnya. Kegiatan produksi akan terganggu apabila lereng-lereng yang terbentuk sebagai akibat dari proses penambangan  tidak stabil. Suatu tambang terbuka belum tentu memiliki besar sudut kemiringan lereng yang sama, hal ini diantaranya akibat dari kuat geser batuan (τ) yang merupakan indeks kualitas batuan, semakin kecil kuat geser batuan maka semakin lemah kekuatan batuan dalam menyangga beban dan akan menjadi bidang lemah yang mudah longsor. Dalam penelitian ini digunakan metode pemetaan geologi dan analisis gama ray dari 43 lubang bor. Metode Kriging digunakan untuk mengetahui distribusi kuat geser batuan di daerah penelitian. Hasil analisis metode Kriging memperlihatkan distribusi kuat geser batuan yang mempunyai nilai rendah yaitu 200 ton/m2 mengarah ke selatan semakin menyempit dan secara vertikal distribusinya semakin dalam semakin berkurang.
Penerapan Perangkat Lunak RStudio untuk Penaksiran Parameter Model Spatial Autoregressive Salsabil, Tsuroyya; Kusuma, Dianne Amor; Ruchjana, Budi Nurani
KUBIK Vol 8 No 1 (2023): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v8i1.30037

Abstract

Research and analysis that are not only based on time (temporal) but also on space (spatial) require tools in the form of software to ensure that the data analysis and processing yield good, fast, and accurate results. One of the software tools that can be used for this purpose is RStudio software. The advantages of RStudio include being open-source software (OSS), which can be used freely without cost, and it has many packages and functions that can facilitate data processing. One of the spatial-based analyses is spatial data analysis. The structure within RStudio allows users to call functions related to spatial data analysis, perform computations with sparse matrices (matrices with many zero values), such as spatial weight matrices, estimation of spatial model parameters, and so on. This research examines the application of RStudio software in estimating the parameters of a first-order Spatial Autoregressive (SAR) model using the Maximum Likelihood Estimation (MLE) method on the data of the designation of Intangible Cultural Heritage (ICH) in Indonesia. Based on the results of applying RStudio software, a first-order SAR model with a Queen contiguity weight matrix for the categories of Traditional Customs, Rituals, and Celebrations (TCRC) and Performing Arts (PA) with the minimum Akaike Information Criterion (AIC) value and maximum pseudo- value was obtained for predicting the designation data of ICH in Indonesia. The application of RStudio software to the first-order SAR model for the designation data of ICH in Indonesia speeds up and simplifies calculations, making it suitable as a recommendation for relevant agencies such as the Department of Culture, Tourism, Youth, and Sports (Disbudparpora). 
Penerapan Model Geographically Weighted Regression pada Data Penetapan Warisan Budaya Takbenda di Indonesia Pratomo, Firdaus Ryan; Kusuma, Dianne Amor; Ruchjana, Budi Nurani
KUBIK Vol 9 No 1 (2024): KUBIK: Jurnal Publikasi Ilmiah Matematika
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/kubik.v9i1.33492

Abstract

Intangible Cultural Heritage (WBTb) determination data in Indonesia is a cultural investment that needs to be preserved. One of the efforts to preserve WBTb is to determine the cultural preservation factors that influence the WBTb determination data in Indonesia. These factors include Percentage of Population Watching Performances/Art Exhibitions (PPWP), Percentage of Population Using Regional Languages (PPURL), and Percentage of Households Using Traditional Products (PHUTP). However, the different cultural wealth in each province results in spatial heterogeneity, resulting in differences in the determination of cultural preservation factors in each province. This determination can be done with the Geographically Weighted Regression (GWR) model. This study aims to apply the GWR model with Fix Gaussian Kernel, Fix Bisquare Kernel, and Fix Tricube Kernel weighting to determine cultural preservation factors in WBTb determination data in Indonesia so that it can be known what cultural preservation factors are most influential in each region. The research findings show the existence of spatial heterogeneity only in the category of WBTb designation data for Performing Arts (PA) and Oral Expression Tradition (OET), as well as different GWR models in each province that reflect differences in cultural preservation factors. Evaluation with the coefficient of determination shows that the GWR model with the Fix Gaussian Kernel weighting function is the best model for the PA category. 
Penerapan Model Seasonal Autoregressive Integrated Moving Average (SARIMA) dalam Peramalan Curah Hujan di Kabupaten Bandung Barat nadhira, valda azka; Ruchjana, Budi Nurani; Parmikanti, Kankan
KUBIK Vol 10 No 1 (2025): IN PRESS
Publisher : Jurusan Matematika, Fakultas Sains dan Teknologi, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The expansion of the Kabupaten Bandung, namely Kabupaten Bandung Barat (KBB) is located in hilly and lowland areas. Rainfall in Kabupaten Bandung Barat has an impact on the productivity and performance of key sectors, such as agriculture, plantations and tourism. Low rainfall can lead prolonged dry seasons and result in drought. Conversely, extreme rainfall can also have negative impacts, such as causing soil erosion and potentially affecting the appeal and smooth operation of tourist destinations. Therefore, rainfall forecasting is needed in making appropriate policies, especially regarding the impacts of rainfall changes in KBB. The Seasonal Autoregressive Integrated Moving Average (SARIMA) method is applied in this study to forecast rainfall in KBB. The aims of this research are to estimate the parameters of the SARIMA model using the Maximum Likelihood Estimation (MLE) method and to apply the SARIMA method in forecasting rainfall in KBB, particularly during the December-January-February (DJF) period. The results of the analysis show that the SARIMA model can be applied to forecast rainfall in KBB. The best SARIMA model obtained ARIMA(2,1,0)(0,0,1)3 with a MAPE value 17,80%, which indicates an accurate forecasting criterion. Keywords: SARIMA, MLE, Rainfall.
Spatial Weight Matrix Comparison of SAR-X Model using Casetti Approach Tsanawafa, Almeira; Kusuma, Dianne Amor; Ruchjana, Budi Nurani
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 9, No 1 (2024): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/ca.v9i1.25579

Abstract

The Spatial Autoregressive Exogenous (SAR-X) model with the Casetti approach is used to describe the influence of location and exogenous variables in the description and prediction of spatial observations, namely, people's habits and behavior towards culture in Java Island. The SAR-X model with the Casetti approach is characterized by a spatial weight matrix that describes the coordinates of the region at each location. The spatial weight matrix is determined outside the model. This study examines the spatial weight matrix determined based on rook contiguity, bishop contiguity, queen contiguity, inverse distance and inverse distance squared, and compares the application of the spatial weight matrix to the SAR-X model with the Casetti approach for the description and prediction of people's habits and behavior towards culture in Java Island. The description and prediction results obtained are measured using the Root Mean Square Error (RMSE) value. The results of data processing show that the best spatial weight matrix in the SAR-X model with the Casetti approach to community habits and behavior in Java Island is the inverse distance squared spatial weight matrix, supported by the calculation of the minimum RMSE value and the coefficient of determination above 60%.
Penerapan Model Spatial Autoregressive pada Data Penetapan Warisan Budaya Takbenda di Indonesia Tsuroyya Salsabil; Kusuma, Dianne Amor; Ruchjana, Budi Nurani
Matematika: Jurnal Teori dan Terapan Matematika Vol. 22 No. 2 (2023): Jurnal Matematika
Publisher : UPT Publikasi Universitas Islam Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/matematika.v22i2.2560

Abstract

Warisan Budaya Takbenda (WBTb) dengan sifatnya yang dapat berlalu dan hilang dalam waktu seiring perkembangan zaman membutuhkan perlindungan lebih. Salah satu program pelindungan yang dilakukan oleh pemerintah adalah penetapan WBTb. Kegiatan penetapan ini memiliki keterbatasan dalam menggambarkan pengaruh lokasi dan prediksi data penetapan WBTb di Indonesia. Sedangkan, WBTb di suatu wilayah bisa saja saling memengaruhi dengan WBTb di wilayah lain di sekitarnya. Salah satu dari model yang dapat digunakan adalah Model Spatial Autoregressive (SAR). Oleh karena itu, penelitian ini bertujuan untuk menerapkan Model Spatial Autoregressive (SAR) orde satu untuk menggambarkan pengaruh lokasi dan prediksi data penetapan WBTb di Indonesia. Berdasarkan hasil pemilihan model terbaik dengan indikator nilai AIC dan pseudo-  model yang terpilih untuk prediksi data penetapan WBTb di Indonesia adalah Model SAR orde satu dengan matriks pembobot Queen Contiguity.   The Application of Spatial Autoregressive Model to the Data of Intangible Cultural Heritage Designation in Indonesia Cultural Heritage with intangible characteristics (WBTb), which can fade and disappear over time due to the development of the era, requires greater protection. One of the protective programs carried out by the government is the designation of WBTb. However, the designation process has limitations in depicting the influence of location and predicting the data of WBTb designation in Indonesia. Meanwhile, WBTb in one region may influence the WBTb in neighboring regions. One of the models that can be used is the Spatial Autoregressive Model (SAR). Therefore, this research aims to apply the first-order Spatial Autoregressive Model (SAR) to depict the influence of location and predict the data of WBTb designation in Indonesia. Based on the results of selecting the best model using the indicators of AIC value and pseudo- , the chosen model for predicting the data of WBTb designation in Indonesia is the first-order SAR model with Queen Contiguity weight matrix.
Pemodelan Indeks Pembangunan Manusia di Kalimantan Timur Menggunakan Spasial Durbin Data Panel Kaerudin, Nandira Putri; Gusriani, Nurul; Ruchjana, Budi Nurani
Jurnal Matematika Integratif Vol 20, No 1: April 2024
Publisher : Department of Matematics, Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jmi.v20.n1.55158.101-115

Abstract

Indeks Pembangunan Manusia (IPM) merupakan salah satu indikator yang dapat digunakan untuk mengukur kemajuan suatu negara. Di Indonesia sendiri masih terdapat ketimpangan IPM antar provinsinya. Provinsi Kalimantan Timur merupakan salah satu provinsi yang memiliki rata-rata IPM tinggi di Indonesia, sehingga perlu dilakukan studi mengenai IPM untuk memberikan gambaran bagi provinsi dengan IPM rendah. IPM di suatu wilayah dipengaruhi oleh wilayah sekitarnya, hal ini disebabkan oleh efek spasial. Analisis regresi spasial merupakan metode yang mampu mengakomodasi efek spasial. Spatial Durbin Model (SDM) adalah salah satu pengembangannya. Selain itu, penggunaan data panel pada model menyebabkan variabilitas pada data. Penelitian ini bertujuan untuk memodelkan IPM di Kalimantan Timur menggunakan spasial durbin data panel meliputi lima kategori: Persentase penduduk miskin; Tingkat Partisipasi Angkatan Kerja (TPAK); Persentase penduduk; Angka Partisipasi Murni (APM); Persentase rumah tangga menurut fasilitas toilet sendiri. Berdasarkan hasil uji Hausman dan Chow, terdapat efek tetap pada setiap kabupaten/kota sehingga FEM merupakan jenis data panel yang digunakan. Selain itu, Hasil uji Moran’s I mengindikasikan adanya dependensi spasial positif dalam data IPM. Koefisien determinasi pada model spasial Durbin data panel menunjukkan nilai 99,92417% yang berarti model ini baik digunakan untuk memodelkan IPM di Kalimantan Timur.
Penerapan Analisis Diskriminan untuk Klasifikasi Pengaruh Data Warisan Budaya Takbenda terhadap Banyaknya Wisatawan Domestik Annisafiya, Nadira; Kusuma, Dianne Amor; Ruchjana, Budi Nurani
Jurnal Matematika Integratif Vol 19, No 2: Oktober 2023
Publisher : Department of Matematics, Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jmi.v19.n2.46791.149-161

Abstract

Analisis diskriminan adalah analisis multivariat yang dapat digunakan pada hubungan dependensi dalam kasus dimana variabel prediktor berupa data kuantitatif dan variabel respon berupa data kualitatif. Warisan Budaya Takbenda (WBTb) memiliki hubungan dengan banyaknya wisatawan khususnya wisatawan domestik yang datang ke suatu provinsi, semakin banyak WBTb yang dimiliki suatu provinsi diharapkan semakin banyak wisatawan domestiknya. Penelitian ini bertujuan mengkaji model diskriminan untuk mengklasifikasikan banyaknya wisatawan domestik dengan kategori tinggi dan rendah beserta menentukan pengaruh variabel WBTb dengan lima kategori, yaitu : (1) Adat Istiadat Masyarakat, Ritus, dan Perayaan-Perayaan (AIMRP); (2) Kemahiran dan Kerajinan Tradisional (KKT); (3) Pengetahuan dan Kebiasaan Perilaku Mengenai Alam dan Semesta (PKPMAS); (4) Seni dan Pertunjukan (SP); (5) Tradisi dan Ekspresi Lisan (TEL). Metode yang digunakan adalah analisis diskriminan. Berdasarkan kelima kategori tersebut, AIMRP, PKPMAS, dan TEL merupakan kategori yang paling memengaruhi tinggi-rendahnya wisatawan domestik dengan tingkat akurasi klasifikasi yang diperoleh pada model diskriminan sebesar 96,57%.
Comparison of Spatial Weight Matrices in Spatial Autoregressive Model: Case Study of Intangible Cultural Heritage in Indonesia Sobari, Muhamad; Desiyanti, Armalia; Yanti, Devi; Monika, Putri; Abdullah, Atje Setiawan; Ruchjana, Budi Nurani
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 7, No 1 (2023): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v7i1.10757

Abstract

Intangible Cultural Heritage (ICH) can effectively contribute to Sustainable Development Goals (SDGs) in all economic, social, and environmental dimensions, along with peace and security. Studying ICH in Indonesia cannot be separated from the spatial aspect of how an area's attributes are related to other areas located close to each other. Spatial regression modeling needs to be done by considering the selection of spatial weight matrix. Using the wrong spatial weight matrix will increase the standard error in parameter estimation. Therefore, this study aims to determine: the best spatial weight matrix to accommodate the spatial autocorrelation in analyzing the description of the spread of ICH in Indonesia; and the variables that are thought to influence the number of ICH determination in Indonesia. The spatial regression modeling used in this study is the Spatial Autoregressive (SAR) model and the spatial weight matrices compared in this study are queen contiguity and inverse distance. The best model is the SAR model used the queen contiguity spatial weight matrix because it has minimum values of AIC, BIC, RMSE and MAPE which are 310.397, 319.555, 18.857 and 57.169 respectively. Simultaneously, involved in performing arts, wearing traditional dress, knowing Indonesian folklore and the spatial lag contribute significantly to number of ICH determination in Indonesia. Partially, only knowing Indonesian folklore have a significant effect on number of ICH determination in Indonesia at significance level α=5%. Each additional 1% of population that knowing Indonesian folklore in an area increases number of ICH determination in that area by 0.6719 units . 
Application of GSTARI (1,1,1) Model for Forecasting the Consumer Price Index (CPI) in Three Cities in Central Java Permatasari, Noverlina Putri; Chotimah, Husnul; Permana, Pandu; Tarigan, Wenny Srimeinda; Toharudin, Toni; Ruchjana, Budi Nurani
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 6, No 1 (2022): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v6i1.6114

Abstract

Economic development is affected by several factors, one of which is the inflation rate. One indicator used to measure the inflation rate is Consumer Price Index (CPI). The CPI data is recorded simultaneously at several locations over time, produces space-time data. In Central Java Province, CPI is calculated in six regency/cities, so the CPI is affected by the time and other locations named space-time effect. The forecasting methods involve space and time effect simultaneously is GSTAR. This study used the GSTAR model to forecasting the CPI in 3 cities in Central Java, assuming that autoregressive and space-time parameters differ for each location. This study aims to obtain the best GSTAR model to forecast the CPI in three cities in Central Java by using the IDW and NCC weighting. The results indicated that the best GSTAR model for forecast the CPI in three cities (Surakarta, Semarang, and Tegal) was the GSTARI (1,1,1) model. The GSTARI (1,1,1) model fulfils the assumption of homoscedasticity, white noise, and multivariate normal. The MAPE values obtained using the IDW and NCC weighting are 0.2922% and 0.2914%, respectively. From these results, it can be concluded that the best GSTARI (1,1,1) model to forecast the CPI data in three cities in Central Java is NCC weights, as they have a minimum MAPE value . The results of this research can  be used as consideration for the government in making economic policies at the present and in the future.
Co-Authors Ahdian, Muhammad Rhafi Ahmad Fawaid Ridwan Akmaliah, Syifani Al Fataa W Haq Al Madani, Aulia R. Al Madani, Aulia Rahman Alawiyah, Mutik Almeira Tsanawafa Anggraeni A Ani Pertiwi Annisa Alma Yunia Annisa Nur Falah, Annisa Nur Annisafiya, Nadira Arisya Maulina Bowo Asep Kurnia Permadi Asep Kurnia Permadi Asri Yuniar Asrirawan Atika Tresna Arianto Atje Setiawan Abdullah Auliyazhafira, Shabira A. Ayu Indriani Ayun Sri Rahmani Bambang Suhandi Bambang Suhandi Bowo, Arisya Maulina Chotimah, Husnul Dedi Rosadi Delvi Rutania Prama Desiyanti, Armalia Devi Munandar, Devi Devi Yanti, Devi Diah Chaerani Dian Islamiaty Puteri Dianne Amor Kusuma Dicky Muslim Dwipriyoko, Estiyan Eddy Hermawan Emah Suryamah Emah Suryamah, Emah Endang Rusyaman Endang Soeryana Hasbullah Fadhilah, Dila Nur Fajriatus Sholihah Falah, Annisa N. Gumgum Darmawan Gumgum Darmawan Hamim Tsalis Soblia Hardianto A Hendarmawan Hendarmawan Hendarmawan Hendarmawan, Hendarmawan Hera Khoirunnisa Husein Hernadi Bahti I Gede Nyoman Mindra I Gede Nyoman Mindra Jaya I Gede Nyoman Mindra Jaya Ibrahim, Riza Andrian Iin Irianingsih Kaerudin, Nandira Putri Kankan Parmikanti Kartika Sari Khafsah Joebaedi Khoirunnisa Rohadatul Aisy Muslihin Khoirunnisa Rohadatul Aisy Muslihin Kusuma, Dianne Amor Lucy Fitria Dewi Mahrudinda Mahrudinda Maryanto Rompon Mindra, I Gede Nyoman Monika, Putri Muhamad Sobari Muhammad Herlambang Prakasa Yudha Muthalib A nadhira, valda azka Najwa, Sandrina Nauli, Theresia S. Novi - Saputri Nur Hamid NUR HAMID Nurdeni, Nurdeni Nurul Gusriani, Nurul Permana, Pandu Permatasari, Noverlina Putri Pratiwi, Dhanti Aurilia Pratomo, Firdaus Ryan Puteri, Dian Islamiaty Putri Monika Putri Monika Putri, Fariza A. Putri, Salsabila Eka Resa Septiani Pontoh Rizka Pradita Prasetya Rizki Apriva Hidayana Salsabil, Tsuroyya Salsabila Salsabila Setialaksana, Wirawan - Shailla Rustiana Sobari, Muhamad Soetikno, Christophorus Sri Adi Widodo Sri Indra Maiyanti Suhandi, Bambang Sutawanir Darwis Tarigan, Wenny Srimeinda Tegar Bratasena WKM Tilas Notapiri Toni Toharudin Tsanawafa, Almeira Tsuroyya Salsabil Tubagus Robbi Megantara Viona Prisyella Balqis Vivian Wilhelmina Vivian Wilhelmina WKM, Tegar Bratasena Yunia, Annisa Alma Zahra, Nabila Zulfa Hidayah Satria Putri