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All Journal EKSAKTA: Journal of Sciences and Data Analysis JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Unisda Journal of Mathematics and Computer Science (UJMC) EIGEN MATHEMATICS JOURNAL Square : Journal of Mathematics and Mathematics Education Jurnal Statistika dan Aplikasinya JAMBURA JOURNAL OF PROBABILITY AND STATISTICS LOSARI: Jurnal Pengabdian Kepada Masyarakat Journal Of Human And Education (JAHE) Journal Focus Action of Research Mathematic (Factor M) Journal of Data Insights Jurnal Pengabdian Masyarakat dan Riset Pendidikan Parameter: Jurnal Matematika, Statistika dan Terapannya Emerging Statistics and Data Science Journal Amalgamasi: Journal of Mathematics and Applications Scientific Journal of Computer Science
Ihsan Fathoni Amri
Universitas Muhammadiyah Semarang
Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Physics Public Health Social Sciences Transportation Other

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Forecasting the Rupiah exchange rate against the US Dollar using the LSTM algorithm Multiyaningrum, Riska; Dawi, Herculianus Rowa; Hartanto, Raka Nurhaq Mulya; Haris, M. Al; Amri, Ihsan Fathoni
Journal Focus Action of Research Mathematic (Factor M) Vol. 8 No. 2 (2025): December 2025
Publisher : Universitas Islam Negeri (UIN) Syekh Wasil Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30762/f_m.v8i2.6530

Abstract

Exchange rates are a vital indicator of an economy's balance. The fluctuations of Indonesia's currency, the rupiah, against the USD influenced trade patterns, investment, and both monetary and fiscal policy. Exchange rate fluctuations affect international trade, investment, inflation, and overall economic stability. The high volatility of the Rupiah against the USD, driven by macroeconomic and monetary factors, has a significant impact on national economic policy, necessitating research that utilizes the latest data and adaptive models. To capture the nonlinear and complicated behavior of exchange rates, an advanced methodology for forecasting is needed. This journal utilizes the Long Short-Term Memory (LSTM) neural network model to forecast the exchange rate of the rupiah towards the dollar from March 1, 2022, up to February 28, 2025, in daily data. The data used in this research are sourced from www.bi.go.id, which provides the official daily exchange rate of USD to IDR. The Long Short-Term Memory method was chosen for modeling long-term dependencies within time series. After normalization, an 80/20 split is performed for training and testing on the dataset. The network runs optimization using three hidden layers with 50 neurons each and a batch size of 32 for 200 epochs. The optimal configuration, achieved through experimental trials, consisted of two hidden layers with 50 neurons, a batch size of 32, and 200 epochs. This is manifest in the fact that LSTM effectively captures movements in exchange rates, with an RMSE of 0.6226 and a MAPE of 0.3031%. This degree of accuracy enables the model to inform economic policy decisions based on data.
Analysis of Suspected Factors in Tuberculosis Cases in Semarang City Using a Logistic Regression Model Amri, Ihsan Fathoni; Rohim, Febrian Hikmah Nur; Ardiansyah, Muhammad Ivan; Saputra, Farid Sam; Supriyanto; Ningrum, Ariska Fitriyana; Nakib, Arman Mohammad
Scientific Journal of Computer Science Vol. 1 No. 1 (2025): June
Publisher : PT. Teknologi Futuristik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64539/sjcs.v1i1.2025.32

Abstract

Tuberculosis (TB) is one of the world's deadliest infectious diseases, with Indonesia being among the countries with the highest TB burden. Semarang City, as an urban area with a dense population, faces significant challenges in controlling TB, particularly among vulnerable populations. This study identifies significant risk factors influencing TB incidence in Semarang City using a binary logistic regression model. Descriptive analysis reveals an imbalance in the data, with the majority of patients categorized as "not indicated for TB." Chi-Square tests show that variables such as shortness of breath, persistent fever for more than one month, diabetes mellitus, and household contact are significantly associated with TB incidence. The logistic regression model demonstrates overall significance (G statistic = 275.13; p-value = 1.23×10−55), with shortness of breath and diabetes mellitus emerging as major risk factors based on odds ratio interpretation. However, the model's performance in detecting the "indicated for TB" category is very low (Precision 36.36%; Recall 2.05%; F1-Score 3.88%), despite an overall accuracy of 87.25%. The poor performance in the "1" category and the Pseudo R2 value of 7% are likely related to data imbalance, where the number of cases in the "1" category is much smaller than in the "0" category, leading to bias toward the majority class. Additionally, the distribution of predictor variables that do not provide sufficient information to distinguish the "1" category from the "0" category further contributes to the model's limited ability to explain data variability overall.
Waiting Time Analysis of Willingness to Pay for Rice Farming Insurance Premiums Using Cox Proportional Hazard Modeling and Weibull Method Mutiah, Siti; Bisoumi, Yan Nazala; Nudyawati, Elsa; Daud, Khamidah Arsyad; Nisa, Rofiah Ainun; Sulistiani, Dwi; Amri, Ihsan Fathoni; Ningrum, Ariska Fitriyana; Mostfa, Ahmed A.
Scientific Journal of Computer Science Vol. 1 No. 1 (2025): June
Publisher : PT. Teknologi Futuristik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.64539/sjcs.v1i1.2025.34

Abstract

Rice is a primary commodity in Indonesia's agricultural sector but is highly vulnerable to climate risks such as floods, droughts, and pest infestations. To mitigate these risks, the government, in collaboration with PT. Asuransi Jasa Indonesia (Jasindo), launched the Rice Farming Insurance Program (AUTP) in 2015. This study aims to analyze the willingness-to-pay time of farmers for AUTP premiums in Jayaraksa Village, Cimaragas Subdistrict, Ciamis Regency, using Weibull regression and Cox Proportional Hazard models. Factors such as education, secondary employment, rice production, and farming costs were examined to understand their influence on farmers' participation. Based on the analysis, the Weibull regression model, with a lower AIC value compared to Cox Proportional Hazard (270.4431 vs. 330.9111), demonstrated better performance in explaining the data. This research contributes to the development of more effective AUTP policies by identifying key factors influencing farmers' participation.
Peramalan Produksi Tanaman Padi Indonesia Tahun 2025 Menggunakan Metode Triple Exponential Smoothing Holt-Winters : Peramalan Produksi Tanaman Padi Indonesia Tahun 2025 Menggunakan Metode Triple Exponential Smoothing Holt-Winters Inayah Pangestu, Eka; Wulandari, Siti; Salwa Salsabila, Galuh; Nur Arifah, Miftah; Ardana Setiawan, Deftha; Fathoni Amri, Ihsan; Bahaudin, Muhammad; M. Al Haris
Emerging Statistics and Data Science Journal Vol. 4 No. 1 (2026): Emerging Statistics and Data Science Journal
Publisher : Statistics Department, Universitas Islam Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/esds.vol4.iss.1.art07

Abstract

Produksi padi memiliki peran penting dalam mendukung ketahanan pangan nasional. Untuk memastikan ketersediaan pangan di tengah peningkatan jumlah penduduk, diperlukan peramalan produksi yang akurat. Penelitian ini bertujuan untuk memodelkan peramalan produksi padi Indonesia tahun 2025 selama periode Januari 2019 hingga Desember 2024 menggunakan Triple Exponential Smoothing Holt-Winters, baik model aditif maupun model multiplikatif. Hasil penelitian menunjukkan bahwa model aditif merupakan model terbaik untuk meramalkan produksi tanaman padi Indonesia tahun 2025. Dengan parameter optimal α=0,3, β=0,4, dan γ=0,1, serta nilai MAPE sebesar 25,72% yang menunjukkan bahwa hasil peramalan cukup akurat.
Pelatihan Pembuatan Dashboard untuk Pemberdayaan Remaja Kanguru di Desa Gayamsari : Pengabdian Amri, Ihsan Fathoni; Hersoelistyorini, Wikanastri; Ardiansyah, Muhammad Ivan; Multiyaningrum, Riska
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 4 (2026): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 4 Tahun 2026
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jerkin.v4i4.5750

Abstract

Artikel ini melaporkan pelaksanaan program pengabdian kepada masyarakat yang bertujuan untuk memberdayakan Remaja Kanguru di Desa Gayamsari melalui pelatihan pembuatan dashboard. Di era transformasi digital, literasi data dan kemampuan visualisasi informasi menjadi keterampilan penting dalam meningkatkan tata kelola dan transparansi organisasi. Hasil identifikasi awal menunjukkan bahwa dokumentasi dan pelaporan kegiatan masih dilakukan secara manual dan belum terintegrasi dalam sistem digital yang terstruktur. Program dilaksanakan dengan metode partisipatif yang meliputi sosialisasi, praktik pengolahan data menggunakan spreadsheet, pembuatan dashboard berbasis Google Data Studio, serta pendampingan pascapelatihan. Kegiatan ini diikuti oleh 15 remaja aktif. Meskipun terdapat kendala koordinasi lokasi akibat perubahan kepengurusan masjid, kegiatan berhasil dilaksanakan di Universitas Muhammadiyah Semarang (UNIMUS) sebagai bentuk strategi adaptif. Hasil kegiatan menunjukkan adanya peningkatan kemampuan peserta dalam mengelola data, menyusun laporan, dan membuat dashboard interaktif. Evaluasi kepuasan menunjukkan 14 peserta menyatakan sangat puas dan 1 peserta menyatakan puas terhadap pelaksanaan kegiatan. Program ini membuktikan bahwa pelatihan literasi digital berbasis dashboard efektif dalam memperkuat transparansi, akuntabilitas, dan profesionalisme organisasi kepemudaan berbasis komunitas.
Analysis of Passenger Flight Distance as an Indicator of Economic Activity Ihsan Fathoni Amri; Suci Izzati; Rendi Andika Putra; Iva Aurellia Khalif; Febryana Dilla Setyaningrum; Isnaini Maulida; M. Al Haris
Parameter: Jurnal Matematika, Statistika dan Terapannya Vol 5 No 1 (2026): Parameter: Jurnal Matematika, Statistika dan Terapannya
Publisher : Jurusan Matematika FMIPA Universitas Pattimura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/parameterv5i1pp111-124

Abstract

Understanding macroeconomic dynamics in the United States requires advanced forecasting techniques capable of capturing both seasonal structures and external shocks. This study investigates the relationship between passenger flight distance and the unemployment rate through the implementation of the Seasonal Autoregressive Integrated Moving Average with Exogenous Variables (SARIMAX) model—an enhancement of the SARIMA framework. While SARIMA accounts for autoregressive, differencing, and moving average components with seasonal integration, SARIMAX further augments this structure by incorporating exogenous predictors, enhancing explanatory and predictive power. Monthly time series data from 2015 to 2024 were utilized, with flight distance as the endogenous variable and the unemployment rate as the exogenous regressor. The modeling procedure involved rigorous stationarity testing via the Augmented Dickey-Fuller (ADF) test, model selection using the Akaike Information Criterion (AIC), and residual diagnostics employing the Box–Ljung and Shapiro–Wilk tests. SARIMAX(0,1,0)(0,1,1)[12] + X emerged as the optimal specification, with all parameters statistically significant and a MAPE of 3.68%, denoting excellent forecast accuracy. Empirical findings reveal a significant and negative association between unemployment and air travel activity, emphasizing the role of labor market dynamics in shaping mobility trends. These results reinforce the utility of SARIMAX as a robust tool in macroeconomic forecasting and evidence-based policy formulation.
Co-Authors Abdul Ghufron Abidah, Khansa Ni'mal Adhwaningrum, Arullah Salsabila Ainurrofiah, Safira Al Haris, M Alwan Fadlurohman Amri, Saeful Angelina, Lea Ardana Setiawan, Deftha Ariska Fitriyana Ningrum Arsusma, Jesicha Arya, Abimanyu Asrirawan Astuti, Sofi Anggi Aura Hisani, Zahra Ayu Wulandari Azzahrani, Rahma Dewi Bahaudin, Muhammad Bisoumi, Yan Nazala Dannu Purwanto Daud, Khamidah Arsyad Dawi, Herculianus Rowa Dhani, Oktaviana Rahma Diani, Nandini Lova Dwi Saputri, Atika Dwi Sulistiani Febryana Dilla Setyaningrum Ginasputri, Heppy Nur Asavia Haris, M. Al Hartanto, Raka Nurhaq Mulya Hikmah Nur Rohim, Febrian Inayah Pangestu, Eka Irawan, Alfian Chandra Isnaini Maulida Iva Aurellia Khalif Kaia Raissa Akmalia Khikman, Muhammad Alvaro Kholifah , Revika Inta Nur Laila Qadrini M. Al Haris Masichah, Firochul Mostfa, Ahmed A. Muhammad Fahmuddin Muhammad Ivan Ardiansyah Multiyaningrum, Riska mutiah, siti Nakib, Arman Mohammad Nisa, Rofiah Ainun Nudyawati, Elsa Nur Arifah, Miftah Nur Mahmudah Nurohmah, Nufita Nurul Azka, M. Ilham Permata, Alia Pranandira Rilvandri, Quinsy Pratama, Rifin Fadilla Priambodo, Danu Puspitasari, Linda Rahma Dhani, Oktaviana Rakhmawati, Muji Silvi Ramadhan, Wulan Nur Rendi Andika Putra Rohim, Febrian Hikmah Nur Sa'adah , Lydia Nur Safira, Elfina Latifah Salsabilla, Havinka Angel Salwa Salsabila, Galuh Saputra, Farid Sam Saputri, Atika Dwi Sarah, Albertus Dion Sintya, Salsabila Dhea siti wulandari Suci Izzati Suherdi, Andri Sulistiya, Indah Supriyanto Syaharani, Nabbila Dyah Tiani Wahyu Utami Wahid, Siti Nurasriyanti Wardani, Amelia Kusuma Watur, Annisa Cahyaningrum Widyasari, Velia Arni Wikanastri Hersoelistyorini Wulan Sari Yolan Triky Zahra Aura Hisani