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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 of Data Insights Emerging Statistics and Data Science Journal Amalgamasi: Journal of Mathematics and Applications
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 Bank Indonesia Currency Inflow and Outflow Using ARIMA, Time Series Regression (TSR), ARIMAX, and NN Approaches in Lampung Laila Qadrini; Asrirawan Asrirawan; Nur Mahmudah; Muhammad Fahmuddin; Ihsan Fathoni Amri
Jurnal Matematika, Statistika dan Komputasi Vol. 17 No. 2 (2021): JANUARY 2021
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/jmsk.v17i2.11803

Abstract

There are various types of data, one of which is the time-series data. This data type is capable of predicting future data with a similar speed as the forecasting method of analysis.  This method is applied by Bank Indonesia (BI) in determining currency inflows and outflows in society. Moreover, Inflows and outflows of currency are monthly time-series data which are assumed to be influenced by time. In this study, several forecasting methods were used to predict this flow of currency including ARIMA, Time Series Regression (TSR), ARIMAX, and NN. Furthermore, RMSE accuracy was used in selecting the best method for predicting the currency flow. The results showed that the ARIMAX method was the best for forecasting because this method had the smallest RMSE.
Sentiment Analysis of Public Opinion on Handling Stunting in Indonesia using Random Forest Ningrum, Ariska Fitriyana; Ihsan Fathoni Amri; Zahra Aura Hisani
Jurnal Statistika dan Aplikasinya Vol. 8 No. 1 (2024): Jurnal Statistika dan Aplikasinya
Publisher : LPPM Universitas Negeri Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21009/JSA.08103

Abstract

The issue of stunting is important to address, as it has the potential to affect the human resource potential and is related to health levels, and even child mortality. The Indonesian government targets to reduce the stunting rate to 14 percent by 2024 through an accelerated stunting reduction program as an effort to improve the nutritional status of the society and also reduce the prevalence of stunting or stunted children. Understanding public sentiment towards the stunting initiative is crucial for policymakers and stakeholders to design effective interventions and allocate resources efficiently. This study aims to analyze public sentiment related to stunting in Indonesia, which impacts children's growth and development. Through the use of sentiment analysis techniques, this study aims to understand public perceptions and attitudes towards the issue of stunting, evaluating whether the general sentiment is positive, negative or neutral. The results of this analysis are expected to provide useful insights for policymakers and health practitioners in designing and implementing more effective strategies to address the issue of stunting. This study conducted sentiment analysis from crawled Twitter data, showing positive and negative sentiments of the public regarding stunting handling in Indonesia. Furthermore, classification analysis using random forest was conducted and resulted in an accuracy score of 97.5%. The model is good enough but, we suggest trying other algorithms in further research.
Pemodelan ARIMA dan ARIMAX untuk Memprediksi Jumlah Produksi Padi di Kota Magelang Amri, Ihsan Fathoni; Ramadhan, Wulan Nur; Ainurrofiah, Safira; Haris, M. Al
Square : Journal of Mathematics and Mathematics Education Vol 5, No 2 (2023)
Publisher : UIN Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/square.2023.5.2.17059

Abstract

Memprediksi atau meramalkan perilaku observasi biasanya menggunakan pemodelan time series yang dilakukan secara berurutan. Prediksi jumlah produksi padi diharapkan dapat memberikan masukan bagi pemerintah dan dimanfaatkan oleh siapa saja sebagai pengembangan pada sektor pertanian serta sebagai bahan ajar penggunaan metode ARIMA (Autoregressive Integrated Moving Average) dan ARIMAX (Autoregressive Integrated Moving Average with Exogenous Variable). Tujuan dari penelitian ini sebagai perbandingan dalam menemukan model terbaik dari metode ARIMA dan ARIMAX untuk memprediksi jumlah produksi padi pada tahun 2023 di kota Magelang. Data yang digunakan merupakan data produksi padi dan luas lahan tanam sebagai variabel eksogen di Kota Magelang pada bulan Januari 2019 sampai Desember 2022. Berdasarkan hasil analisis, diperoleh model ARIMA terbaik untuk meramalkan jumlah produksi padi di kota Malang adalah ARIMA (0,1,1), sedangnkan model ARIMAX terbaik adalah ARIMAX (0,0,1). Perbandingan kedua model tersebut berdasarkan nilai MAPE, model ARIMAX (0,0,1) menjadi model terbaik untuk meramalkan jumlah produksi padi di Kota Malang karena menghasilkan MAPE terkecil 6,31%. Hasil peramalan menggunakan model ARIMAX (0,0,1) menunjukkan data cenderung mengalami pola trend turun. Hal ini dikarenakan lahan pertanian yang semakin sempit setiap tahunnya sehingga menyebabkan jumlah produksinya semakin menurun.Kata Kunci: Pemodelan, metode ARIMA, metode ARIMAX, Produksi Padi.
Pemodelan ARIMAX untuk Meramalkan Harga Minyak Mentah Dunia Amri, Ihsan Fathoni; Wulandari, Ayu; Abidah, Khansa Ni'mal; Irawan, Alfian Chandra; Haris, M. Al
Square : Journal of Mathematics and Mathematics Education Vol 5, No 1 (2023)
Publisher : UIN Walisongo Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/square.2023.5.1.17074

Abstract

Perdagangan secara umum dikelompokkan menjadi dua yaitu, ekspor dan impor. Salah satu contoh perdagangan tersebut adalah minyak mentah. Diketahui saat ini harga pasar minyak mentah dunia mempengaruhi tingkat perekonomian global. Harga minyak yang terus berubah, tentu saja menjadi sumber kekhawatiran dan perhatian tersendiri, terutama dalam industri minyak. Dalam penelitian ini, akan mengkaji harga minyak mentah menggunakan model ARIMAX (Autoregressive Integrated Moving Average with Exogenous Variables). Model ARIMAX dipilih karena mampu mengintegrasikan variabel eksternal, seperti volume nilai tukar rupiah dan produksi minyak, yang mempengaruhi harga minyak mentah. Tujuan utama penelitian ini adalah untuk mengembangkan model prediktif yang akurat dengan mempertimbangkan pengaruh produksi minyak (Richard et al., 2021)dan nilai tukar rupiah terhadap harga minyak mentah dunia. Berdasarkan hasil analisis model ARIMAX (0,1,2) merupakan model terbaik dalam meramalkan harga minyak mentah dunia karena memiliki nilai AIC dan MAPE terkecil, yaitu AIC sebesar 408,49 dan MAPE 8,88. Berdasarkan hasil tersebut peramalan dengan model model ARIMAX (0,1,2) dapat dikategorikan sangat baik.Kata Kunci: ARIMAX, Perekonomian, Harga minyak mentah dunia, Nilai tukar rupiah, Produksi minyak.
Peramalan Harga Emas Antam Menggunakan Metode Generalized Autoregressive Conditional Heterokedasticity (GARCH) Amri, Ihsan Fathoni; Astuti, Sofi Anggi; Sulistiya, Indah; Suherdi, Andri; Haris, M.Al
UJMC (Unisda Journal of Mathematics and Computer Science) Vol 10 No 1 (2024): Unisda Journal of Mathematics and Computer Science
Publisher : Mathematics Department, Faculty of Mathematics and Sciences Unisda Lamongan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52166/ujmc.v10i1.4679

Abstract

ANTAM gold is a long-term inflation-resistant investment instrument with a low-risk profile. Socio-economic conditions greatly influence gold price fluctuations, so gold price forecasting is very important for investors to understand the dynamic of changes in gold price. This study proposes the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) methods to model the forecasting of gold price fluctuations. The data used is ANTAM’s daily gold price data for the period June 2018 – June 2023. The results show that by using the best ARIMA (0,1,1) GARCH (2,1) model, the gold price forecasting results are in the price range of Rp 947.100.
Sistem Pakar Tertib Administrasi Kependudukan Desa Katonsari Provinsi Jawa Tengah Menggunakan Metode Forward Chaining Systems Fathoni Amri, Ihsan; Wahyu Utami, Tiani; Pranandira Rilvandri, Quinsy; Suherdi, Andri
LOSARI: Jurnal Pengabdian Kepada Masyarakat Vol. 6 No. 1 (2024): Juni 2024
Publisher : LOSARI DIGITAL

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53860/losari.v6i1.199

Abstract

Abstract The community service program implemented in Katonsari Village, Demak Subdistrict, Demak Regency, aims to improve population administration orderliness through the application of an expert system utilizing forward chaining method. The stages of the service activity include collecting primary data through field surveys and in-depth interviews with the community and related agencies to understand the dynamics and challenges in population administration. Based on the analysis of collected needs, an expert system was developed as an information technology solution to support efficiency and accuracy in population data management. This program also emphasizes on the training of system implementation provided to the community and village administrative officers to ensure effective transfer of knowledge and skills. The evaluation of the system's success and effectiveness is conducted by measuring the improvement in population administration quality and user satisfaction of the system. Abstrak Program pengabdian masyarakat yang dilaksanakan di Desa Katonsari, Kecamatan Demak, Kabupaten Demak ini bertujuan untuk meningkatkan tertib administrasi kependudukan dengan penerapan sistem pakar yang memanfaatkan metode forward chaining. Tahapan kegiatan pengabdian meliputi pengumpulan data primer melalui survei lapangan dan wawancara mendalam dengan masyarakat dan instansi terkait untuk memahami dinamika dan tantangan dalam administrasi kependudukan. Berdasarkan hasil analisis kebutuhan yang terkumpul, dikembangkan sistem pakar sebagai solusi teknologi informasi yang dapat mendukung efisiensi dan akurasi dalam pengelolaan data kependudukan. Program ini juga menekankan pada pelatihan implementasi sistem yang diberikan kepada masyarakat dan petugas administrasi desa untuk memastikan transfer pengetahuan dan keterampilan yang efektif. Evaluasi keberhasilan dan efektivitas sistem dilakukan dengan mengukur peningkatan kualitas administrasi kependudukan dan kepuasan pengguna sistem.
Forecasting Hotel Occupancy Rates in Bali Province using the SARIMAX Method with Tourist Data as an Exogenous Variable Ihsan Fathoni Amri; Arya, Abimanyu; Yolan Triky; Kaia Raissa Akmalia; Abdul Ghufron; M. Al Haris
EKSAKTA: Journal of Sciences and Data Analysis VOLUME 5, ISSUE 2, October 2024
Publisher : Fakultas Matematika dan Ilmu Pengetahuan Alam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20885/EKSAKTA.vol5.iss2.art2

Abstract

Tourism is a crucial economic sector in Bali, Indonesia. Sustainable tourism management requires an understanding of the dynamics between tourist numbers and hotel occupancy levels. This study uses the SARIMAX (Seasonal Autoregressive Integrated Moving Average) method to estimate between the two indicators and reveals a positive correlation between the two indicators. The SARIMAX model effectively captures seasonal patterns and external factors, providing accurate forecasts and supporting tourism management in Bali. Monthly data from 2010 to 2023 were analyzed. Accurate estimates can help tourism stakeholders in formulating appropriate management strategies to optimize the tourism sector. Implementing the right strategy can help ensure the preservation of the local environment and culture, as well as long-term economic benefits for Bali. From the data we use the SARIMAX (6,1,0) (1,1,0)12 model with an AIC value of 1920.553 and a MAPE value of 27%.
Estimasi Risiko Pada Saham PT. Gojek Tokopedia Tbk dan Expected Shortfall Menggunakan ARIMA-GARCH Model Amri, Ihsan Fathoni; Puspitasari, Linda; Priambodo, Danu; Azzahrani, Rahma Dewi; Haris, M. Al
Jambura Journal of Probability and Statistics Vol 5, No 2 (2024): Jambura Journal of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjps.v5i2.22552

Abstract

Evaluation of losses is very important when investing in stocks where an approach is needed to take into account risk, the approaches that can be used are Value-at-Risk and Expected Shortfall. The purpose of this research is to estimate the Value-at-Risk and Expected Shortfall of PT. Gojek Tokopedia Tbk uses the time series model methodology. One year daily closing price of PT. Gojek Tokopedia Tbk will be used as a source of research data. During the time series modeling process, the ARIMA model is intended as an average model and the GARCH model for model volatility, both of which are used to predict stock movements. The average value and variance models are then intended to calculate the Value-at-Risk and Expected Shortfall of the stocks used, respectively. The results obtained for the VaR value were 0.088911 and the ES value was 0.122084. This shows that the ES method is superior in considering the risk of stock investment that has been analyzed. 
Meningkatkan Kompetensi Teknologi Informasi Siswa Melalui Pelatihan Tiga Microsoft di SMA 1 Kembang Jepara Fathoni Amri, Ihsan; Wahyu Utami, Tiani; Hikmah Nur Rohim, Febrian; Aura Hisani, Zahra; Rahma Dhani, Oktaviana; Suherdi, Andri
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.
Data Visualization Excellence: Google Data Studio Workshop At Sekolah Indonesia Kuala Lumpur Amri, Saeful; Fadlurohman , Alwan; Ningrum, Ariska Fitriyana; Purwanto, Dannu; Amri , Ihsan Fathoni; Wardani, Amelia Kusuma; Dhani, Oktaviana Rahma
Journal Of Human And Education (JAHE) Vol. 5 No. 1 (2025): Journal of Human And Education (JAHE)
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/jh.v5i1.2178

Abstract

The development of information technology and the entry of the industrial revolution 4.0 era has led to the inseparability of human activities related to the use of technology. In today's rapidly growing information age, data is one of the most valuable assets. The ability to collect, analyze, and interpret data is becoming a very important skill not only in the world of work but also in education. Education is the foundation for preparing future generations for increasingly complex global challenges, and a good understanding of data can provide a significant competitive advantage. In schools, the ability to analyze and interpret data is becoming an invaluable skill for students. Along with the development of technology, data visualization has become an effective method to convey information in a more comprehensible manner. In this context, Google Data Studio offers a powerful and easy-to-use tool for creating interactive dashboards that help in analyzing and presenting data. Indonesian Migrant Workers (TKI) are Indonesian citizens who live and work abroad. TKI provide a large contribution of foreign exchange to the country of Indonesia. However, there are problems in the field of education for children whose parents work as TKI in Malaysia, especially education that is relevant to success in terms of opening their own jobs abroad. This is considered important because to get jobs in government agencies or companies in Malaysia, the children of TKI working in Malaysia must compete with job seekers who are Malaysian citizens. One alternative that can be taken to overcome competition in getting jobs is to create your own jobs. Opening your own jobs is not an easy thing. Knowledge and insight about this are needed which are given early on to the children of TKI in school. By teaching Google Data Studio in the form of data visualization to students, they not only learn how to read and interpret graphs and diagrams, but also how to present their own data in a more interesting and informative way. This ability will be very useful in the future, both in academic and professional environments. By providing insight into Google Data Studio to students in schools, these students have the provisions to be able to read data and have the opportunity to work and get decent jobs. As a Community Service activity with an international scope, this activity takes partners in Malaysia, namely the Indonesian School-Kuala Lumpur - SIKL which is located in Sentul, Kuala Lumpur, Federal Territory of Kuala Lumpur. The Community Service Team of Muhammadiyah University of Semarang is very receptive to criticism and suggestions so that the implementation of Community Service in the future can be even better.
Co-Authors Abdul Ghufron Abidah, Khansa Ni'mal Adhwaningrum, Arullah Salsabila Ainurrofiah, Safira Al Haris, M Al Haris, M. Alwan Fadlurohman Amri, Saeful Angelina, Lea Ariska Fitriyana Ningrum Arsusma, Jesicha Arya, Abimanyu Asrirawan Astuti, Sofi Anggi Aura Hisani, Zahra Ayu Wulandari Azzahrani, Rahma Dewi Dannu Purwanto Dhani, Oktaviana Rahma Diani, Nandini Lova Dwi Saputri, Atika Ginasputri, Heppy Nur Asavia Haris, M. Al Hikmah Nur Rohim, Febrian Irawan, Alfian Chandra Kaia Raissa Akmalia Khikman, Muhammad Alvaro Kholifah , Revika Inta Nur Laila Qadrini M. Al Haris Masichah, Firochul Muhammad Fahmuddin Multiyaningrum, Riska 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 Rohim, Febrian Hikmah Nur Sa'adah , Lydia Nur Safira, Elfina Latifah Salsabilla, Havinka Angel Saputri, Atika Dwi Sarah, Albertus Dion Sintya, Salsabila Dhea Suherdi, Andri Sulistiya, Indah Syaharani, Nabbila Dyah Tiani Wahyu Utami Wahid, Siti Nurasriyanti Wardani, Amelia Kusuma Watur, Annisa Cahyaningrum Widyasari, Velia Arni Wulan Sari Yolan Triky Zahra Aura Hisani