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All Journal Pythagoras: Jurnal Matematika dan Pendidikan Matematika Jurnal Matematika Jurnal Ilmu Dasar Jurnal Sains dan Seni ITS Jurnal Gaussian IPTEK Journal of Science CAUCHY: Jurnal Matematika Murni dan Aplikasi Journal of Regional and City Planning Prosiding Seminar Matematika dan Pendidikan Matematik Jurnal Matematika Sains dan Teknologi Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri Jambura Journal of Mathematics Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) Inferensi Berkala Penelitian Hayati Sewagati Journal of Research on Community Engagement
Purhadi Purhadi
Departemen Statistika Institut Teknologi Sepuluh Nopember
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Partitional Clustering of Underdeveloped Area Infrastructure with Unsupervised Learning Approach: A Case Study in the Island of Java, Indonesia Bambang Widjanarko Otok; Agus Suharsono; Purhadi Purhadi; Rahmawati Erma Standsyah; Harun Al Azies
Journal of Regional and City Planning Vol. 33 No. 2 (2022)
Publisher : The Directorate for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/jpwk.2022.33.2.3

Abstract

This study attempted to identify underdeveloped areas in regencies/cities on the island of Java, Indonesia, based on a number of infrastructure indicators. An unsupervised learning approach was used to perform partition clustering with the K-Means, K-Medoids, and CLARA methods. In addition to technically obtaining clustering results and conducting a performance comparison of the three unsupervised learning methods, another objective of this research was to map the clustering results to make it easier to recognize the characteristics of the regions indicated as underdeveloped areas, which should be absolute priorities for infrastructure development. It was found that the best clustering method was the CLARA method, with a connectivity coefficient of 7.4794 and a Dunn’s index value of 0.1042. The partition clustering of regencies/cities on Java Island using the CLARA method based on infrastructure indicators resulted in 99 regencies/cities included in the cluster of areas with underdeveloped infrastructure, while 12 regencies/cities were included in the cluster of areas with developing infrastructure, and 8 regencies/cities were included in the cluster of areas with developed infrastructure.
Pemodelan Faktor – Faktor yang Mempengaruhi Kasus Pneumonia pada Balita di Provinsi Jawa Barat dengan Metode Geographically Weighted Generalized Poisson Regression Vergilia Agam Saputri; Purhadi Purhadi
Inferensi Vol 5, No 2 (2022)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v5i2.12619

Abstract

Acute infection of lung tissue that can be caused by various microorganisms, namely fungi, viruses, and bacteria is called pneumonia. Pneumonia is the leading cause of death in children worldwide. West Java is in the top three of the number of deaths due to pneumonia in children under five in Indonesia and ranks 1st in the number of pneumonia sufferers in children under five. In solving this case, it is necessary to model with spatial effects because it is necessary to pay attention to geographical conditions in West Java, namely the GWGPR method. The highest number of pneumonia cases, as many as 10818 cases, was in Cirebon Regency while the lowest number of cases was in Banjar City as many as 573 cases. The best modeling results from the minimum AICc criteria of 483.98 are using the GWGPR method with exposure that forms two groups of districts/cities based on variables that have a significant effect on cases of pneumonia in children under five in all districts/cities, namely the percentage of vitamin A administration and the percentage of clean-living behavior and healthy.
Pengelolaan Sampah sebagai Kompos di Wisata Gronjong Wariti Berbasis Pemberdayaan Masyarakat dengan Media Bata Terawang Santi Wulan Purnami; Harmin Sulitiyaning Titah; Diah Puspito Wulandari; Yoyok Setyo Hadiwidodo; Bambang Widjanarko Otok; Purhadi Purhadi; Jerry D. T. Purnomo; Achmad Choiruddin; Shofi Andari; Abima Aunur Rochman
Sewagati Vol 7 No 3 (2023)
Publisher : Pusat Publikasi ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (6282.262 KB) | DOI: 10.12962/j26139960.v7i3.501

Abstract

Mejono merupakan sebuah desa yang terletak di Kecamatan Plemahan, Kabupaten Kediri, Provinsi Jawa Timur. Di Desa Mejono terdapat sebuah sungai bernama Gronjong Wariti yang dijadikan tempat wisata dengan wahana yang tersebar di sepanjang sungai. Tingginya aktivitas pengunjung dan banyaknya pohon bambu yang tumbuh disepanjang Sungai Gronjong Wariti menimbulkan peningkatan timbunan sampah yang memberikan dampak buruk bagi kesehatan, lingkungan, ekonomi, serta mengurangi nilai estetika. Dari observasi permasalahan yang ada pada mitra, tim pengabdian masyarakat Institut Teknologi Sepuluh Nopember menawarkan solusi yakni edukasi pemilahan sampah dan mengelola sampah organik menjadi kompos menggunakan media bata terawang. Edukasi pemilahan sampah menjadi sampah organik dan anorganik dilakukan kepada pengelola, warga sekitar dan pengunjung wisata Gronjong Wariti. Tempat pilah sampah diberikan di tempat yang mudah dijangkau di area Wisata. Pembangunan Bata Terawang dengan warna yang menarik ditempatkan di titik yang menghasilkan sampah organik terbanyak tiap harinya. Proses pengomposan media Bata Terawang dimulai dengan pengisian sampah organik, penyemprotan EM4, pengadukan dan pemanenan kompos. Waktu yang dibutuhkan mulai dari tahap pengisian sampah sampai tahap pemanenan diperkirakan memakan waktu 40 hari.
Modeling the Number of Pneumonia in Toddlers in East Java Province in 2021 with Generalized Poisson Regression Fittrofin Amalia Farisa; Syarifah Nisrina Hasna Salby; Annisa Auliya Rahman; Purhadi Purhadi
Inferensi Vol 6, No 2 (2023)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v6i2.15339

Abstract

Pneumonia is one of the highest causes of toddler’s mortality, including Indonesia. In East Java 2021, the discovery of pneumonia is 50%. It is relatively high, especially among children under five. This study aimed to obtain the factors that influence the number of pneumonias in toddlers in East Java by using Generalized Poisson Regression (GPR) model with and without exposure variable. GPR is used when the assumption of Poisson regression is not met due to the overdispersion. Data was obtained from the East Java province health office containing the number of Pneumonia patients in East Java by districts/cities and the factors that allegedly affect them. Based on the analysis, GPR with exposure variable is better than GPR without exposure variable. The possible GPR models with exposure that has the smallest AICc is model that included the percentage of low-birth-weight babies, percentage of coughing/difficulty breathing toddlers given standard management, and percentage of toddlers getting vitamin A. All independent variables included in the model has significance effect to the number of pneumonias in toddlers.
VARIASI VARIABEL PENGARUH FIX DAN RANDOM TERHADAP PRODUKSI GULA DAN TETES I Nyoman Latra; Nur Iriawan; Purhadi Purhadi; Suhartono Suhartono
Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) Vol 4 No 1 (2012): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2012.4.1.2946

Abstract

This paper presents the modeling of the amount of sugar and molasses production in Pabrik Gula Candi Baru Sidoarjo (PGCBS), East Java, by using multivariate mixedlinear models. Estimation of parameters will be done by using maximum likelihood coupled with restricted maximum likelihood methods. The amount of sugar and molasses products which have strong linear correlation, will be set as responses and are supposed to be affected by seven fixed effect variables and four random effect variables. This paper demonstrates that the seven fixed effect variables and only one random effect variable have significant influence on a single response. In the multivariate response modeling, however, all of variables fail to explain the variability of these two responses simultaneously. It is due to the factors matrix has no full rank. As a result, the model response of molasses can be explained by using a model of the amount of sugar obtained.
ESTIMASI PARAMETER PADA MODEL COX MULTIVARIAT DENGAN METODE MAXIMUM PARTIAL LIKELIHOOD ESTIMATION Irfan Wahyudi; Purhadi Purhadi; Sutikno Sutikno; Irhamah Irhamah
Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) Vol 4 No 1 (2012): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2012.4.1.2954

Abstract

Multivariate Cox proportional hazard models have ratio property, that is the ratio of hazard functions for two individuals with covariate vectors z1 and z2 are constant (time independent). In this study we talk about estimation of prameters on multivariate Cox model by using Maximum Partial Likelihood Estimation (MPLE) method. To determine the appropriate estimators that maximize the ln-partial likelihood function, after a score vector and a Hessian matrix are found, numerical iteration methods are applied. In this case, we use a Newton Raphson method. This numerical method is used since the solutions of the equation system of the score vector after setting it equal to zero vector are not closed form. Considering the studies about multivariate Cox model are limited, including the parameter estimation methods, but the methods are urgently needed by some fields of study related such as economics, engineering and medical sciences. For this reasons, the goal of this study is designed to develop parameter estimation methods from univariate to multivariate cases.
Parameter Estimation and Hypothesis Testing of GTW Compound Correlated Bivariate Poisson Regression Model: A Theoretical Development Hargandi, Priyanka Ratulangi; Purhadi, Purhadi; Choiruddin, Achmad
Jambura Journal of Mathematics Vol 7, No 2: August 2025
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjom.v7i2.32712

Abstract

Each observation location and time possesses distinct characteristics, reflecting heterogeneity at every observation point, both spatially and temporally. This condition renders the Compound Correlated Bivariate Poisson Regression (CCBPR) model inadequate for representing data dynamics that exhibit spatial and temporal heterogeneity. To address this limitation, the Geographically and Temporally Weighted Compound Correlated Bivariate Poisson Regression (GTWCCBPR) model is employed, which allows parameter variation across locations and time periods. This model also incorporates the exposure variable as a weighting factor to adjust for differences in risk across observational units. This study aims to estimate the parameters of the GTWCCBPR model using the Maximum Likelihood Estimation (MLE) approach. Due to the complex structure of the model, the log-likelihood function does not yield a closed-form solution. Therefore, parameter estimation is performed using the iterative Berndt-Hall-Hall-Hausman (BHHH) algorithm. Subsequently, hypothesis testing is conducted to evaluate the parameter similarity between the global model (CCBPR) and the spatiotemporal model (GTWCCBPR), as well as to assess the significance of each predictor variable. Simultaneous testing is carried out using the Maximum Likelihood Ratio Test (MLRT), while partial testing is conducted using the Z-test. The scope of this study is limited to theoretical formulation and methodological development, without empirical or simulation-based validation. Future research may extend this work by applying the GTWCCBPR model to practical datasets exhibiting spatio-temporal heterogeneity, particularly in areas such as public health (e.g., maternal and postneonatal mortality), epidemiology, or regional planning.
Parameter Estimation of Mixed Geographically Weighted Bivariate Zero-Inflated Negative Binomial Regression Model Islamiati, Mawadah Putri; Purhadi, Purhadi; Wibawati, Wibawati
Jambura Journal of Mathematics Vol 7, No 2: August 2025
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjom.v7i2.32711

Abstract

The Bivariate Zero-Inflated Negative Binomial (BZINBR) regression model is commonly used to analyze two correlated count response variables characterized by overdispersion and excess zeros. To account for spatial heterogeneity in predictor effects, the BZINBR model has been extended into the Geographically Weighted BZINBR (GWBZINBR) model. However, predictor effects are not always entirely local; certain global effects may persist across regions. This study proposes the Mixed Geographically Weighted BZINBR (MGWBZINBR) model, which integrates both global and local parameter structures for modeling spatially correlated bivariate count data. The theoretical framework of the MGWBZINBR model is developed, including the derivation of the log-likelihood function, parameter estimation procedures, and hypothesis testing. Parameter estimation is conducted using the Maximum Likelihood Estimation (MLE) method via the iterative Berndt–Hall–Hall–Hausman (BHHH) algorithm. Given the complexity of the likelihood equations and the absence of closed-form solutions, numerical optimization is employed to ensure convergence and stability. The MGWBZINBR model offers a flexible and robust framework for analyzing spatial count data with excess zeros and complex dependency structures. It can be applied in various fields, including public health, ecology, and transportation analysis, to understand the influence of both local and global predictors on spatial phenomena. As the focus of this paper is methodological, empirical and simulation-based applications are intentionally excluded.
Pemodelan Zero-Inflated Poisson Inverse Gaussian Regression dan Zero-Inflated Generalized Poisson Regression terhadap Jumlah Kejadian Campak di Kabupaten Pamekasan dan Sumenep Royyanah, Atika Nur; Purhadi, Purhadi
Jurnal Sains dan Seni ITS Vol 13, No 4 (2024)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM), ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j23373520.v13i4.152368

Abstract

Penyakit campak merupakan satu dari penyakit infeksi yang menjadi penyebab kematian bayi di seluruh dunia dan meningkat setiap tahun. Campak diakibatkan oleh virus dan komplikasi penyakit campak antara lain radang selaput otak (meningitis), radang paru–paru, infeksi telinga. Pada ta-hun 2022 di Indonesia terjadi 3.341 kasus campak, sedangkan di Jawa Timur terjadi 443 kasus campak. Umunya campak bisa dicegah dan diatasi dengan pemberian imunisasi dasar lengkap (IDL) yang biasanya diberikan pada anak namun juga bisa diberikan pada orang dewasa. Pada penelitian ini akan dila-kukan pemodelan faktor-faktor yang diduga mempengaruhi jumlah kejadian penyakit campak di Kabupaten Pamekasan dan Sumenep Tahun 2022 menggunakan Zero-Inflated Gene-ralized Poisson Regression (ZIGPR) dan Zero-Inflated Poisson Invers Gaussian Regression (ZIPIGR). Faktor-faktor yang diduga mempengaruhi penyakit campak baik pada model tipe satu dan dua adalah rasio jumlah tenaga kesehatan, kepadatan penduduk, rasio jumlah anak usia <12 bulan yang mendapat imunisasi dasar lengkap, rasio pemberian vitamin A pada anak usia <12 bulan, dan rasio jumlah tenaga medis. Berdasarkan kedua metode, didapatkan model terbaik untuk tipe satu adalah ZIGPR dengan exposure sedangkan model terbaik tipe dua adalah ZIPIGR dengan exposure. Dari hasil penelitian ini diharapkan dapat menjadi bahan pertimbangan bagi peme-rintah agar dapat menurunkan jumlah penderita penyakit cam-pak di Kabupaten Pamekasan dan Kabupaten Sumenep.
Pemodelan Kasus Kusta Jawa Timur Menggunakan Zero-Inflated Generalized Poisson Regression dan Zero-Inflated Negative Binomial Regression Pertiwi, Dhea Mutiara; Purhadi, Purhadi
Jurnal Sains dan Seni ITS Vol 13, No 4 (2024)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM), ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j23373520.v13i4.152756

Abstract

Penyakit kusta atau Morbus Hansen merupakan pe-nyakit yang disebabkan oleh bakteri Mycrobacterium leprae dan menyerang lapisan kulit, sistem saraf perifer, selaput lendir pa-da saluran pernapasan atas, serta mata. Penyakit kusta terdiri dari dua tipe, yaitu kusta kering atau Paucibasillary (PB) dan kusta basah atau Multibacillary (MB). Penelitian ini berfokus pada jumlah kasus kusta tipe MB atau basah pada anak di Jawa Timur. Kusta tipe MB lebih mudah menular dan anak-anak memiliki daya tahan tubuh yang rendah sehingga mudah tertu-lar penyakit kusta. Jawa Timur memiliki jumlah kasus kusta tertinggi di Indonesia. Pemodelan jumlah kasus kusta tipe MB pada anak perlu dilakukan untuk mengetahui faktor apa saja yang berpengaruh terhadap jumlah kusta sehingga jumlah pen-derita kusta bisa diminimalisir. Metode yang dapat digunakan untuk pemodelan jumlah kasus kusta tipe MB pada anak di Jawa Timur tahun 2022 adalah regresi Zero-Inflated Generali-zed Poisson (ZIGP) dan regresi Zero-Inflated Negative Binomia (ZINB). Alasan menggunakan metode ini karena data jumlah kasus kusta tipe MB pada anak berisikan data yang bernilai nol dengan proporsi sebanyak 42,1% dan adanya kasus over disper-si. Hasil penelitian menunjukkan bahwa model terbaik adalah regresi Zero-Inflated Generalized Poisson (ZIGP) berdasarkan nilai AICc yang lebih kecil dibandingkan dengan regresi Zero-Inflated Negative Binomial (ZINB). Faktor-faktor yang berpe-ngaruh signifikan terhadap jumlah kasus kusta tipe MB pada anak di Jawa Timur adalah persentase penduduk miskin, rasio banyaknya puskesmas terhadap jumlah penduduk, persentase KK (Kartu Keluarga) akses rumah sehat dan persentase pela-yanan kesehatan untuk usia pendidikan dasar.
Co-Authors Abima Aunur Rochman Achmad Choiruddin Affanda Abdul Hakim Aminullah Agus Suharsono Alia Lestari Alifa Silfi Mufidah Andriana Yoshinta Herindrawati Angga Dwi Mulyanto Annisa Auliya Rahman Arrafi Dwiargatra Bambang Widjanarko Otok Barep Adji Widhi Pangestu Brianika Irawati Choiruddin, Achmad Cindy Cahyaning Astuti Diah Puspito Wulandari Dina Oktafia Sulistyani Dinar Ariana Viestri Dinarta Dinarta Hanum Hanum Efta Dhartikasari Priyana Eriska Evadianti Ernawati Ernawati Esti Wulandari Fa'rifah, Riska Yanu Fefy Dita Sari Feni Ira Puspita, Feni Ira Fitria Nur Maghfiroh Fitria Nurul Alfariz Fitriarma Putri Santoso Fittrofin Amalia Farisa Gressa Widha Audrina Hani Khaulasari Hargandi, Priyanka Ratulangi Harmin Sulitiyaning Titah Harun Al Azies Hasbi Yasin Herni Anggi Riski Rahayuning Heru Purwanto I Dewa Ayu Ratih Weda Iswara I Nyoman Latra I Nyoman Latra I Nyoman Latra I Nyoman Latra Ika Wuryanti Febrina Wuryanti Irfan Wahyudi Irhamah - Islamiati, Mawadah Putri Ita Noviana Jatikusuma, Andhika Jauhara Rana Budiani Jerry D. T. Purnomo Lucy Dian Puspitasari Luh Eka Suryani Madu Ratna Mahestri, Alea Erdinna Makkulau Makkulau Makkulau Makkulau Makkulau Makkulau Maudi Pramedia Putri Meylita Sari Muhamad Adryanta Muhammad Luthfi muhammad mashuri Mulyaputri, Rifna Fadhilah Nendy Septi Arniva Ni Putu Lisa Ernawatiningsih Nina Fauziah Rachmah Nindya Kemala Astuti Nur Iriawan Nur Lailiyah Nurina Hayu Ratri Nuroini, Husna Mir'atin Pertiwi, Dhea Mutiara Rahmania Azwarini Rahmawati Erma Standsyah Rahmawati Pane Rahmi Amelia Ratih Kumala Puspa Nusantara Retno Anggarini Rida Dwi Lestari Rizwan Arisandi, Rizwan Royyanah, Atika Nur Ruslan Ruslan Ruslan Santi Wulan Purnami Shofi Andari Shofi Andari Siti Azizah Sony S Sony Sunaryo Sri Nurhatika Sri Pingit W Sri Pingit Wulandari Sri Pingit Wulandari Suhartono Suhartono Suprianto Simanjuntak Susanti Linuwih Susanti Linuwih Susanti Linuwih Susanti Linuwih Susanti Linuwih Sutikno Sutikno Sutikno Sutikno Sutikno Sutikno Sutikno Sutikno Sutikno Sutikno Syarifah Nisrina Hasna Salby Syarifah Nisrina Hasna Salby Theresia Widiastuti Urifah Hidayanti Vergilia Agam Saputri Vita Ratnasari Wibawati Wibawati Yoyok Setyo Hadiwidodo Yurike Septi Angelina Monica Zuzun Miranti