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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) Jurnal Pengembangan Rekayasa dan Teknologi 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) Fraction: Jurnal Teori dan Terapan Matematika 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 Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Transportation Other

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A Pengelompokan Kabupaten/Kota di Jawa Tengah Berdasarkan Kepadatan Penduduk Menggunakan Metode Hierarchical Clustering Yusrisma Asyfani; Indah Manfaati Nur; Ihsan Fathoni Amri; Novia Yunanita; Febi Anggun Lestari; Zahra Aura Hisani; Febrian Hikmah Nur Rohim
Journal of Data Insights Vol 2 No 1 (2024): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v2i1.158

Abstract

Jawa Tengah merupakan provinsi dengan urutan kelima di Indonesia berdasarkan kepadatan penduduk pada tahun 2020 sebanyak 1.113 jiwa/km2. Pengaruh kepadatan penduduk yang tinggi dapat menyebabkan berbagai masalah diantaranya kemacetan,pengangguran,kesehatan,kriminalitas serta permasalahan serius lainnya. Kepadatan penduduk dipengaruhi oleh angka kelahiran,angka kematian serta laju pertumbuhan, Untuk mengevaluasi kepadatan penduduk di provinsi Jawa Tengah, kita perlu mengklasifikasikan/mengelompokkan kabupaten/kota yang berada didalamnya. Pengelompokan ini bertujuan agar kebijakan yang dibuat oleh pemerintah dapat tepat sasaran. Metode yang dapat digunakan untuk pengelompokkan kabupaten.kota di provinsi Jawa Tengah berdasarkan kepadatan penduduknya yaitu Clustering Hierarchical Ward. Dari hasil analisis pengelompokan tersebut kabupaten/kota di provinsi Jawa Tengah dibagi menjadi empat kelompok berdasarkan kepadatan penduduknya.
Forecasting Honda Car Retail Sales Using the Seasonal Autoregressive Integrated Moving Average Method: Peramalan Penjualan Retail Mobil Honda Menggunakan Metode Seasonal Autoregressive Integrated Moving Average Lea Angelina; Alia Permata; Jesicha Arsusma; Firochul Masichah; M. Al Haris; Ihsan Fathoni Amri
Journal of Data Insights Vol 3 No 1 (2025): Journal of Data Insights
Publisher : Department of Sains Data UNIMUS Universitas Muhammadiyah Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26714/jodi.v3i1.416

Abstract

This article discusses the forecasting of Honda car retail sales using the Seasonal Autoregressive Integrated Moving Average (SARIMA) method. The study aims to forecast Honda car retail sales for the upcoming year. Various SARIMA models have been tested to determine the best model, and the results show that the SARIMA (1,1,0)(1,1,1)¹² model provides the lowest Mean Absolute Percentage Error (MAPE) among all tested models, which is 17,74%. Therefore, this model was chosen for forecasting sales over the next 12 months. The forecast results are expected to assist management in making optimal decisions regarding stock and marketing, as well as significantly enhancing operational efficiency and customer satisfaction in the future.
Pelatihan Pembuatan Dashboard untuk Pemberdayaan Remaja Kanguru di Desa Gayamsari : Pengabdian Ihsan Fathoni Amri; Wikanastri Hersoelistyorini; Muhammad Ivan Ardiansyah; Riska Multiyaningrum
Jurnal Pengabdian Masyarakat dan Riset Pendidikan Vol. 4 No. 4 (2026): Jurnal Pengabdian Masyarakat dan Riset Pendidikan Volume 4 Nomor 4 April - Juni
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 Suspected Factors in Tuberculosis Cases in Semarang City Using a Logistic Regression Model Ihsan Fathoni Amri; Febrian Hikmah Nur Rohim; Muhammad Ivan Ardiansyah; Farid Sam Saputra; Supriyanto; Ariska Fitriyana Ningrum; Arman Mohammad Nakib
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 Siti Mutiah; Yan Nazala Bisoumi; Elsa Nudyawati; Khamidah Arsyad Daud; Rofiah Ainun Nisa; Dwi Sulistiani; Ihsan Fathoni Amri; Ariska Fitriyana Ningrum; Ahmed A. Mostfa
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.
Survival Analysis Using Kaplan-Meier and Cox Regression in Hypertension Patients at Kefamenanu Regional Hospital Muhammad Alvaro Khikman; Riska Multiyaningrum; Revika Inta Nur Kholifah; Lydia Nur Sa'adah; Elfina Latifah Safira; Albertus Dion Sarah; Ihsan Fathoni Amri; M. Al Haris
Eigen Mathematics Journal Vol 8 No 2 (2025): December
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v8i2.270

Abstract

Hypertension is a chronic disease with a steadily increasing global prevalence and is one of the leading causes of serious complications. Indonesia is among the countries with a high prevalence of hypertension, necessitating an understanding of the factors influencing patient treatment duration to enhance the effectiveness of healthcare services. This study aims to analyze differences in the survival rates of hypertensive patients at Kefamenanu Hospital based on gender. The Kaplan-Meier method was used to estimate patient survival rates, while Cox Proportional Hazards regression was used to evaluate the influence of gender on survival time. The Kaplan-Meier analysis results showed that female patients had a higher probability of survival than male patients during hospitalization. However, the Cox Proportional Hazards regression analysis indicated that this difference was not statistically significant. These findings suggest that while there are differences in survival patterns, gender is not the primary determinant of the duration of care for hypertensive patients. The results of this study are expected to provide input for hospitals in designing more effective care strategies that focus on other factors that may influence patient survival time.
Forecasting the Rupiah exchange rate against the US Dollar using the LSTM algorithm Riska Multiyaningrum; Herculianus Rowa Dawi; Raka Nurhaq Mulya Hartanto; M. Al Haris; Ihsan Fathoni Amri
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.
ANALISIS MODEL SARIMA DALAM PERAMALAN PENJUALAN RITEL MOBIL BEKAS BERDASARKAN DATA PENJUALAN BULANAN DI AMERIKA SERIKAT Moch Yahya; Nurmawati Ainun; Nurul Hikmah; Al Aghni Naufalia; Ihsan Fathoni Amri; M. Al Haris
Fraction: Jurnal Teori dan Terapan Matematika Vol. 6 No. 1 (2026): FRACTION: Jurnal Teori dan Aplikasi Matematika
Publisher : Jurusan Matematika, Fakultas Teknik, Universitas Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33019/fraction.v6i1.112

Abstract

Penelitian ini bertujuan untuk meramalkan penjualan ritel mobil bekas di Amerika Serikat dengan menggunakan model Seasonal Autoregressive Integrated Moving Average (SARIMA). Data yang digunakan bersumber dari Federal Reserve Bank of St. Louis (FRED) dengan periode Januari 2019 hingga Desember 2024, memiliki karakteristik musiman dan dianalisis menggunakan bahasa pemrograman R. Model SARIMA dipilih karena mampu menangkap komponen musiman yang tidak dapat dimodelkan secara eksplisit oleh ARIMA. Prosedur dimulai dari analisis stasioneritas hingga pemilihan model terbaik berdasarkan nilai Akaike Information Criterion (AIC) dan uji diagnostik residual. Hasil penelitian menunjukkan bahwa model SARIMA(0,1,2)(1,1,0)¹² adalah model terbaik dengan nilai AIC sebesar 802.87 dan MAPE yang menunjukkan tingkat akurasi sangat baik. Model ini menghasilkan peramalan penjualan selama 12 bulan ke depan dengan pola fluktuatif musiman, di mana penjualan tertinggi diprediksi terjadi pada bulan Maret dan terendah pada bulan Desember.
Meningkatkan Kompetensi Teknologi Informasi Siswa Melalui Pelatihan Tiga Microsoft di SMA 1 Kembang Jepara Ihsan Fathoni Amri; Tiani Wahyu Utami; Febrian Hikmah Nur Rohim; Zahra Aura Hisani; Oktaviana Rahma Dhani; Andri Suherdi
LOSARI: Jurnal Pengabdian Kepada Masyarakat Vol. 6 No. 2 (2024): Desember 2024
Publisher : LOSARI DIGITAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53860/losari.v6i2.238

Abstract

Artikel ini membahas pelaksanaan program pengabdian kepada masyarakat yang bertujuan untuk meningkatkan keterampilan digital siswa kelas 11 di SMA 1 Kembang Jepara. Di era digital saat ini, kemampuan dalam menggunakan aplikasi Microsoft Office seperti Word, Excel, dan PowerPoint menjadi penting untuk keberhasilan akademis dan profesional. Namun, banyak siswa yang belum mendapatkan pelatihan yang memadai dalam penggunaan alat-alat ini, sehingga menghambat kemampuan mereka untuk memenuhi tuntutan dunia teknologi yang terus berkembang. Program ini bertujuan untuk mengatasi kekurangan tersebut dengan memberikan pelatihan intensif Microsoft Office yang disesuaikan dengan kebutuhan siswa. Pelatihan ini tidak hanya meningkatkan keterampilan teknis siswa tetapi juga meningkatkan kepercayaan diri mereka dalam menerapkan keterampilan ini dalam situasi nyata. Hasil survei kepuasan menunjukkan bahwa 45% siswa merasa sangat puas, 30% puas, 20% cukup puas, dan 5% kurang puas dengan pelatihan yang diterima. Hal ini mencerminkan keberhasilan program dalam memenuhi kebutuhan dan harapan mereka. Inisiatif ini menjadi model untuk mengintegrasikan pelatihan keterampilan IT praktis ke dalam kurikulum pendidikan.
Analisis Peramalan Suhu Permukaan Bumi di Kota Semarang Menggunakan Regresi Nonparametrik dengan Estimator Deret Fourier Berdasarkan Penalized Least Square (PLS) Ihsan Fathoni Amri; Tiani Wahyu Utami; Dannu Purwanto; Alwan Fadlurohman; Ariska Fitriyana Ningrum; Saeful Amri
Jurnal Pengembangan Rekayasa dan Teknologi Vol. 10 No. 1 (2026): Mei (2026)
Publisher : Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/jprt.v10i1.14583

Abstract

Perubahan iklim global yang ditandai oleh peningkatan suhu permukaan menjadi isu penting, terutama di wilayah perkotaan dengan tingkat urbanisasi tinggi seperti Kota Semarang. Peningkatan suhu dapat memengaruhi kualitas lingkungan dan kenyamanan masyarakat, sehingga diperlukan pemodelan dan peramalan yang akurat untuk memahami pola perubahannya. Penelitian ini bertujuan membentuk model regresi nonparametrik menggunakan estimator deret Fourier dengan optimasi Penalized Least Square (PLS) serta meramalkan suhu permukaan di Kota Semarang. Parameter optimal ditentukan berdasarkan nilai Generalized Cross Validation (GCV) minimum. Hasil penelitian menunjukkan bahwa model terbaik diperoleh pada koefisien Fourier  dengan lambda optimal 0,00027 dan GCV minimum 0,81182. Model menghasilkan Mean Absolute Percentage Error (MAPE) sebesar 1,203717% dengan akurasi 98,7963%, yang termasuk kategori sangat baik. Hasil ini menunjukkan bahwa pendekatan deret Fourier berbasis PLS efektif dalam memodelkan dan meramalkan suhu permukaan di Kota Semarang.
Co-Authors Abdul Ghufron Abidah, Khansa Ni'mal Adhwaningrum, Arullah Salsabila Ahmed A. Mostfa Ainurrofiah, Safira Al Aghni Naufalia Al Haris, M Albertus Dion Sarah Alia Permata Alwan Fadlurohman Amri, Saeful Andri Suherdi Ardana Setiawan, Deftha Ariska Fitriyana Ningrum Ariska Fitriyana Ningrum Arman Mohammad Nakib Arya, Abimanyu Asrirawan Astuti, Sofi Anggi Ayu Wulandari Azzahrani, Rahma Dewi Bahaudin, Muhammad Choirudin, Mochamad Fahmi Dannu Purwanto Dhani, Oktaviana Rahma Diani, Nandini Lova Dwi Saputri, Atika Dwi Sulistiani Elfina Latifah Safira Elsa Nudyawati Farid Sam Saputra Febi Anggun Lestari Febrian Hikmah Nur Rohim Febrian Hikmah Nur Rohim Febrian Hikmah Nur Rohim Febryana Dilla Setyaningrum Firochul Masichah Haris, M. Al Havinka Angel Salsabilla Heppy Nur Asavia Ginasputri Herculianus Rowa Dawi Inayah Pangestu, Eka Indah Manfaati Nur Irawan, Alfian Chandra Isnaini Maulida Iva Aurellia Khalif Jesicha Arsusma Kaia Raissa Akmalia Kamilah Citra Khumairoh Khamidah Arsyad Daud Khikman, Muhammad Alvaro Kinanta, Ailsha Syafa Laila Qadrini Lea Angelina Lydia Nur Sa'adah Lydia Nur Sa'adah M. Al Haris M. Al Haris Moch Yahya Muhammad Alvaro Khikman Muhammad Fahmuddin Muhammad Ivan Ardiansyah Muhammad Ivan Ardiansyah Muhammad Ivan Ardiansyah Nasyiatul Izzah Novia Yunanita Nufita Nurohmah Nur Arifah, Miftah Nur Mahmudah Nurmawati Ainun Nurul Azka, M. Ilham NURUL HIKMAH Oktaviana Rahma Dhani Pranandira Rilvandri, Quinsy Pratama, Rifin Fadilla Priambodo, Danu Puspitasari, Linda Raka Nurhaq Mulya Hartanto Rakhmawati, Muji Silvi Ramadhan, Wulan Nur Rendi Andika Putra Revika Inta Nur Kholifah Riska Multiyaningrum Riska Multiyaningrum Riska Multiyaningrum Rofiah Ainun Nisa Rohim, Febrian Hikmah Nur Salsabila Dhea Sintya Salwa Salsabila, Galuh Saputri, Atika Dwi Sari, Selvi Ana Windia Sidqi, Isnaeni Miftahul Siti Mutiah siti wulandari Suci Izzati Suherdi, Andri Sulistiya, Indah Supriyanto Syaharani, Nabbila Dyah Tiani Wahyu Utami Velia Arni Widyasari Wahid, Siti Nurasriyanti Wardani, Amelia Kusuma Watur, Annisa Cahyaningrum Wikanastri Hersoelistyorini Wikanastri Hersoelistyorini Wulan Sari Yan Nazala Bisoumi Yolan Triky Yusrisma Asyfani Zahra Aura Hisani Zahra Aura Hisani Zahra Aura Hisani