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All Journal International Journal of Electrical and Computer Engineering JURNAL E-DUMATH Science and Technology Indonesia BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Jambura Journal of Mathematics Spatial : Wahana Komunikasi dan Informasi Geografi InPrime: Indonesian Journal Of Pure And Applied Mathematics Journal of Community Service and Empowerment PELS (Procedia of Engineering and Life Science) Jurnal Pengabdian Masyarakat Tapis Berseri Jurnal Dedikasi untuk Negeri Jurnal Mahasiswa Ilmu Komputer Sciencestatistics: Journal of Statistics, Probability, and Its Application SWARNA: Jurnal Pengabdian Kepada Masyarakat Integra: Journal of Integrated Mathematics and Computer Science
Mustofa Usman
Matematika, Universitas Lampung
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Generalized Space Time Autoregressive (GSTAR) Model for Air Temperature Forecasting in the South Sumatera, Riau, and Jambi Provinces Aprianti, Ayu; Faulina, Naflah; Usman, Mustofa
InPrime: Indonesian Journal of Pure and Applied Mathematics Vol 6, No 1 (2024)
Publisher : Department of Mathematics, Faculty of Sciences and Technology, UIN Syarif Hidayatullah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15408/inprime.v6i1.36049

Abstract

Over the past few years, there has been a significant increase in air temperatures in regions such as South Sumatera, Riau, and Jambi, posing threats of drought, water resource crises, and erratic weather patterns. In response, developing air temperature forecasting techniques becomes imperative for effective climate change management. This study proposes implementing the Generalized Space Time Autoregressive (GSTAR) model as a practical approach for forecasting air temperatures in these regions using two weighting methods, i.e., inverse distance and normalized cross-correlation weighting. The GSTAR model, an extension of the Space Time Autoregressive (STAR) model, offers enhanced complexity by incorporating specific time and location factors, thereby increasing forecasting flexibility. The result reveals that GSTAR(1,1) with normalized cross-correlation weighting is the most optimal model, with a Root Mean Square Error (RMSE) value of 3.135, indicating high forecasting accuracy. The selection of this model is grounded in the geographical proximity and similarity of environmental characteristics of the three regions. This research contributes novel insights into the underlying mechanisms of air temperature dynamics in neighboring areas, providing a robust foundation for formulating effective policy and mitigation strategies in addressing climate change challenges.Keywords: Air temperatures, Normalized cross-correlation weighting, GSTAR(1,1), Inverse distance weighting. AbstrakDalam beberapa tahun terakhir, suhu udara mengalami peningkatan signifikan di wilayah-wilayah seperti Sumatera Selatan, Riau, dan Jambi, yang mengancam kekeringan, krisis sumber daya air, dan perubahan pola cuaca yang tidak terduga. Menghadapi situasi tersebut, pengembangan teknik peramalan suhu udara diperlukan untuk mengantisipasi dan mengelola dampak ekstrem dari perubahan iklim. Studi ini mengusulkan implementasi model Generalized Space Time Autoregressive (GSTAR) sebagai pendekatan praktis untuk meramalkan suhu udara di wilayah-wilayah tersebut menggunakan dua metode pembobotan yaitu pembobotan invers jarak dan normali korelasi silang. Model GSTAR, sebagai perluasan dari model Space Time Autoregressive (STAR), menawarkan kompleksitas yang lebih baik dengan menggabungkan faktor-faktor waktu dan lokasi tertentu, sehingga meningkatkan fleksibilitas dalam ramalan. Hasil analisis menunjukkan bahwa GSTAR(1,1) dengan pemberian bobot normalisasi korelasi silang merupakan model yang paling optimal, dengan nilai Root Mean Square Error (RMSE) sebesar 3.135, menandakan tingkat akurasi yang tinggi. Pemilihan model ini didasarkan pada kedekatan geografis dan kesamaan karakteristik lingkungan dari ketiga wilayah tersebut. Penelitian ini memberikan wawasan baru dalam mekanisme dinamika suhu udara di wilayah-wilayah yang berdekatan, serta memberikan dasar yang kuat bagi perumusan kebijakan dan strategi mitigasi yang efektif dalam menghadapi tantangan perubahan iklim.Kata Kunci: Bobot invers jarak, Bobot normalisasi korelasi silang, GSTAR(1,1), Suhu udara. 2020MSC: 62P30
Pembinaan Desa Cinta Statistik Bagi Perangkat Desa Panutan Sebagai Upaya Penyelenggaraan Statistik Desa Berkesinambungan Warsono, Warsono; Usman, Mustofa; Junaidi, Akmal; Herindri Samodera Utami, Bernadhita
SWARNA: Jurnal Pengabdian Kepada Masyarakat Vol. 3 No. 9 (2024): SWARNA: Jurnal Pengabdian Kepada Masyarakat, September 2024
Publisher : LPPM Sekolah Tinggi Ilmu Ekonomi 45 Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/swarna.v3i9.1511

Abstract

Sebagai tindak lanjut MoU (Memorandum of Understanding) antara Universitas Lampung dengan Badan Pusat Statistik Provinsi Lampung, khususnya BPS Kabupaten Pringsewu maka perlu dilakukan pembinaan berkesinambungan yang bertujuan agar perangkat desa di Kabupaten Pringsewu lebih memahami pentingnya data statistik serta berpartisipasi aktif dalam penyelenggaraan statistik desa. Berdasarkan analisis situasi di Desa Panutan, Kecamatan Pagelaran, Kabupaten Pringsewu dimana tampilan monografi di website desa (https://panutan-pringsewu.desa.id/) masih monoton, kurang menarik, dan belum merepresentasikan statistik desa secara lengkap. Oleh karena itu, diperlukan pembinaan diseminasi dan website bagi perangkat desa di Kabupaten Pringsewu sebagai upaya penyelenggaraan statistik desa berkesinambungan. Kegiatan pengabdian ini dilaksanakan pada 26 Juni 2024 menggunakan kombinasi metode ceramah, praktik, dan tanya jawab. Berdasarkan hasil kuisioner, 100% peserta menyatakan tertarik menggunakan perangkat lunak Canva dalam menyajikan infografis profil desa. Dalam hal kemudahan dalam menggunakan aplikasi Canva, sebanyak 62% mampu membuat infografis tanpa kendala dan sebanyak 38% masih mengalami kendala dalam mempraktikkan pembuatan infografis yang disebabkan oleh perangkat dan jaringan sinyal yang tidak mendukung.
Konservasi Anggrek Dan Peningkatan Peringkat Greenmetric Melalui Kegiatan Penanaman Anggrek Di Kampus Widiarti; Usman, Mustofa; Wamiliana; Nurcahyani, Nuning; Master, Jani
Jurnal Pengabdian Masyarakat Tapis Berseri (JPMTB) Vol. 2 No. 1 (2023): Jurnal Pengabdian Masyarakat Tapis Berseri (JPMTB) (Edisi April)
Publisher : Pusat Studi Teknologi Informasi Fakultas Ilmu Komputer Universitas Bandar Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36448/jpmtb.v2i1.39

Abstract

Upaya pelestarian anggrek, khususnya anggrek spesies merupakan salah satu kegiatan konservasi lingkungan hidup. Dalam rangka pelestarian lingkungan, lingkungan kampus sudah dipenuhi berbagai pohon-pohon rindang dan tinggi, yang sangat sesuai untuk habitat anggrek hutan. Adanya tanaman-tanaman ini merupakan salah satu upaya konservasi lingkungan, keindahan, dan pengurangan gas CO2. Untuk menambah keindahannya, pohon-pohon besar yang ada di lingkungan taman kampus dapat ditempel berbagai jenis anggrek yang sesuai dengan habitatnya seperti amabilis, retusa, bulbophyllum, aphyllum, dan dendrobium. Anggrek, selain indah dan cantik, juga akan mengurangi kadar CO2 di udara sehingga penanaman anggrek di lingkungan kampus akan berdampak baik terhadap peringkat greenmetric. Tujuan kegiatan pengabdian ini adalah untuk: (1) melestarikan anggrek spesies khususnya amabilis yang merupakan spesies asli Lampung, (2) mengurangi CO2 dan meningkatkan peringkat greenmetric. Kegiatan ini melibatkan tim dosen, mahasiswa, dan staff untuk membantu merawat tanaman anggrek. Tingkat keberhasilan hidup anggrek untuk beradaptasi di lingkungan kampus sangat baik (lebih dari 95%). Partisipasi dan antusiasme masyarakat dan civitas akademika di lingkungan kampus juga sangat baik. Hal ini ditandai dengan pertumbuhan anggrek yang baik dan masih utuhnya plant anggrek yang ditanam.
Modeling Vector Error Correction with Exogeneous (VECMX) Variable for Analyzing Nonstationary Variable Energy Used and Gross Domestic Product (GDP) Usman, Mustofa; Wamiliana; Russel, Edwin; Kurniasari, Dian; Widiarti; Elfaki, Faiz A.M
Science and Technology Indonesia Vol. 10 No. 1 (2025): January
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2025.10.1.283-293

Abstract

Analysis of energy used, GDP and population has been carried out in many countries and has become a topic of interest for many researchers and governments. This is because energy used is an important factor for society and industry in a country. In this study, the modeling of the relationship between energy used, GDP and population as an exogenous variable for the cases of Indonesia from 1967-2023 will be discussed. The energy used and GDP data are nonstationary with order one, I(1), and there is cointegration between energy used and GDP. Therefore, the model which will be used is the Vector Error Correction Model with Exogenous variable (VECMX) with population as the exogenous variable. From the results of analysis, the best model is VECMX(3,1) with cointegration rank R=1. Based on this model, the pattern of the relationship among the three variables, Granger-causality between energy used and GDP, exogenous impact on energy used and GDP, and forecasting for the next 10 years will be discussed.
Pemetaan Persebaran Penyakit Malaria di Kecamatan Punduh Pidada, Kabupaten Pesawaran, Provinsi Lampung Nugraheni, Irma Lusi; Usman, Mustofa; Sutarto, Sutarto
Jurnal Spatial Wahana Komunikasi dan Informasi Geografi Vol. 23 No. 1 (2023): Spatial : Wahana Komunikasi dan Informasi Geografi
Publisher : Department Geography Education Faculty of Social Science - Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/spatial.231.2

Abstract

Malaria transmission in Pesawaran District has decreased for three consecutive years, namely 2018-2020 where it reached an API rate of 0.67 per 1000 population. In 2020 Punduh Pidada District has 28 positive cases of malaria. Factors that influence the number of cases of malaria transmission include environmental factors such as rainfall, land use, and altitude. The purpose of this study was to determine the distribution of malaria in terms of transmission factors in the form of environmental factors in the form of land use and topography. The method used in this research is qualitative with descriptive analysis. Data analysis techniques in this study are buffering techniques and map analysis. The results of this study indicate that land use and topography have an influence on the number of cases of malaria transmission in Punduh Pidada District. The land uses that had the highest cases were mixed forest (18 cases), plantations (18 cases), settlements (20 cases), and fish ponds (20 cases). Meanwhile, the altitude/topography of less than 200 meters above sea level covers all sample locations of malaria transmission in Punduh Pidada District in 2016-2021.
Enhancing Weather Forecasting in Bandar Lampung: A Hybrid SARIMA-LSTM Approach Kurniasari, Dian; Salsabila, Anindya Dafa; Usman, Mustofa; Warsono, Warsono
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 1 (2025): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i1.27188

Abstract

Indonesia’s tropical climate, marked by rainy and dry seasons, is increasingly affected by extreme weather events driven by climate change. Rising temperatures, shifting rainfall patterns, and sea-level rise have intensified health risks such as malaria, dengue hemorrhagic fever (DHF), and gastrointestinal infections. Accurate weather forecasting is essential for mitigating these challenges and informing risk management strategies. This study develops and evaluates a hybrid SARIMA-LSTM model for weather forecasting in Bandar Lampung, integrating time series analysis with deep learning to enhance predictive accuracy. SARIMA captures seasonal variations, while LSTM models nonlinear relationships, offering a robust approach to forecasting complex weather patterns. The SARIMA (6,1,0)(3,1,0)26 model was selected for its effective seasonal representation and combined with LSTM to leverage its capability in modelling nonlinear dependencies. Hyperparameter optimization using grid search further improved model performance. Two data partitioning approaches were tested: 70%-30% and 80%-20% splits for training and testing, respectively. The SARIMA-LSTM hybrid model demonstrated superior performance with the 80%-20% split, achieving MSE, RMSE, and MAPE values of 0.1174, 0.3426, and 0.0104%, respectively. The model accurately forecasted weather conditions over 21 weeks, aligning closely with observed trends and effectively capturing seasonal patterns. These findings underscore the model’s potential to support public health strategies, including disease outbreak mitigation for malaria and DHF, and enhance disaster preparedness in flood-prone areas.
Penerapan Model Geographically Weighted Logistic Regression dengan Fungsi Pembobot Adaptive Gaussian Kernel pada Data Kemiskinan Nurhasanah, Nunung; Widiarti, Widiarti; Nurvazly, Dina Eka; Usman, Mustofa
Jambura Journal of Mathematics Vol 6, No 2: August 2024
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjom.v6i2.26504

Abstract

Regression analysis is one statistical method used to determine the relationship between a dependent variable and one or more independent variables. Dependent variables that are categorical are analyzed using logistic regression analysis. Geographically Weighted Logistic Regression (GWLR) is a method that is a local version of logistic regression, where location factors are considered. This method assumes that the dependent variable data are distributed binomially. In this study, the GWLR method is used to determine the factors influencing the poverty percentage in West Java Province in 2022 using an adaptive Gaussian kernel weighting function. The variables used are per capita expenditure, average length of schooling, Gross Regional Domestic Product (GRDP) per capita, and population density. The results of this study indicate that the variables of per capita expenditure, Gross Regional Domestic Product (GRDP) per capita, and population density significantly influence the poverty percentage in West Java Province in 2022.
Pelatihan Peningkatan Pemahaman Logika dan Aplikasinya pada Pembuktian dalam Matematika untuk Dosen-Dosen Ilmu Komputer di PTS Bandar Lampung Usman, Mustofa; W, Wamiliana; W, Warsono; Russel, Edwin
Jurnal Pengabdian Masyarakat Tapis Berseri (JPMTB) Vol. 4 No. 1 (2025): Jurnal Pengabdian Masyarakat Tapis Berseri (JPMTB) (Edisi April)
Publisher : Pusat Studi Teknologi Informasi Fakultas Ilmu Komputer Universitas Bandar Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36448/jpmtb.v4i1.134

Abstract

Logic is a very important knowledge in all fields, for example law, mathematics, language, and computer science. In mathematics, logic plays a role in providing ways or methods or steps in proving a theorem. In computer science, logic is very important because it is the mathematical basis of software: logic is used to formalize the semantics of programming languages and program specifications, and to verify the correctness of programs. However, the weakness is that logic is generally not taught in the curriculum in Computer Science and of course this is a gap that must be overcome if we want to build quality alumni. The problem is that lecturers generally do not understand the basic concepts of logic and their applications in mathematical proof methods. To overcome this weakness, a beginner activity was held, namely training in basic logic concepts and their applications in mathematical proof methods. This community service activity was carried out using lecture and discussion methods and exercises attended by computer science lecturers and students.
MEMBANGUN DESAIN EKSPERIMEN, PEMODELAN DAN ANALISIS DENGAN SAS PROGRAM Usman, Mustofa; widiarti, Widiarti; Russel, Edwin; Ragayu, Noti
Jurnal Dedikasi untuk Negeri Vol 1, No 1 (2022)
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat UML

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1017.541 KB) | DOI: 10.36269/jdn.v1i1.877

Abstract

Abstrak Dewasa ini penggunaan statistika dalam analisis data dan penelitian telah secara intensif digunakan, khususnya dikalangan akademisi. Khusus dalam penggunakan perancangan eksperimen pemahaman yang benar tentang pembangunan desain eksperimen dan pemodelan dan analisis datanya yang dirasakan masih kurang dipahami oleh sebagian besar para peneliti. Pengabdian pada masyarakat yang dilakukan ini disampaikan dalam rangka mengatasi kekurangan pemahaman dosen swasta akan pembangunan desain eksperimen dan analisisnya. Metode yang digunakan adalah pemberian kuliah, diskusi dan studi kasus khususnya adalah analisis completely Randomized Desain. Kata kunci: Desain eksperimen, CRD, randomisasi, analisis. Abstract Nowadays, the use of statistics in data analysis and research has been intensively used, especially among academics. Especially in the use of experimental design, a correct understanding of the construction of experimental designs and modeling and data analysis is felt to be still poorly understood by most researchers. This community service is delivered in order to overcome the lack of understanding of private lecturers on the development of experimental designs and their analysis. The method used is giving lectures, discussions and case studies, especially analysis of completely randomized design. Keywords: Experimental design, CRD, randomization, analysis.
IMPLEMENTATION OF FUZZY C-MEANS AND FUZZY POSSIBILISTIC C-MEANS ALGORITHMS ON POVERTY DATA IN INDONESIA Kurniasari, Dian; Kurniawati, Virda; Nuryaman, Aang; Usman, Mustofa; Nisa, Rizki Khoirun
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 3 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss3pp1919-1930

Abstract

Cluster analysis involves the methodical categorization of data based on the degree of similarity within each group to group data with similar characteristics. This study focuses on classifying poverty data across Indonesian provinces. The methodologies employed include the Fuzzy C-Means (FCM) and Fuzzy Probabilistic C-Means (FPCM) algorithms. The FCM algorithm is a clustering approach where membership values determine the presence of each data point in a cluster. On the other hand, the FPCM algorithm builds upon FCM and Possibilistic C (PCM) algorithms by incorporating probabilistic considerations. This research compares the FCM and FPCM algorithms using local poverty data from Indonesia, specifically examining the Partition Entropy (PE) index value. It aims to identify the optimal number of clusters for provincial-level poverty data in Indonesia. The findings indicate that the FPCM algorithm outperforms the FCM algorithm in categorizing poverty in Indonesia, as evidenced by the PE validity index. Furthermore, the study identifies that the ideal number of clusters for the data is 2.
Co-Authors Aang Nuryaman Akmal Junaidi Amanathi, Ani Anjani, Syarli Dita aprianti, ayu Arisman Adnan Budi Susetyo Dian Kurniasari Dian Kurniasari Dina Eka Nurvazly, Dina Eka Elfaki, Faiz A.M Elfaki, Faiz AM Eri Setiawan Faulina, Naflah Favorisen R. Lumbanraja Fitriani Handayani, Vitri Aprilla Herindri Samodera Utami, Bernadhita Hestina P., Shelvira Irfan, Miftahul Irma Lusi Nugraheni Jani Master, Jani Khoirin Nisa Kurniawati, Virda Lestari, Windi Lindrianasari Loves, Luvita Nisa, Rizki Khoirun Nuning Nurcahyani Nunung Nurhasanah Putri, Almira Rizka Putri, Lidya Ayuni Ragayu, Noti Rahman Cahyadi, Rahman Russel, Edwin Salsabila, Anindya Dafa Sari, Dede Ratna Shella, Tiara Pramay Siti Laelatul Chasanah, Siti Laelatul Suciati, Indah Sulandra, Ardelia Maharani Sutarto Sutarto Teguh Panuju, Achmad Yahya Utami, Bernadhita Herindri Samodera W, Wamiliana W, Warsono Wamiliana Wardhani Utami Dewi Warsono Warsono Warsono Warsono Warsono Widiarti Widiarti Widiarti Yoka, Ranara Athalla