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All Journal Jurnal Statistika Universitas Muhammadiyah Semarang Telematika : Jurnal Informatika dan Teknologi Informasi BAREKENG: Jurnal Ilmu Matematika dan Terapan Jiko (Jurnal Informatika dan komputer) Jurnal Teknologi Terpadu Nusantara Science and Technology Proceedings International Journal of Data Science, Engineering, and Analytics (IJDASEA) Indonesian Community Journal Jurnal Informatika Teknologi dan Sains (Jinteks)
Muhaimin, Amri
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Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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RAINFALL FORECASTING WITH AN INTERMITTENT APPROACH USING HYBRID EXPONENTIAL SMOOTHING NEURAL NETWORK Permata, Regita Putri; Muhaimin, Amri; Hidayati, Sri
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss1pp0457-0466

Abstract

Rainfall forecasting is crucial in agriculture, water resource management, urban planning, and disaster preparation. Traditional approaches fail to capture complicated and intermittent rainfall patterns. The “Hybrid Exponential Smoothing Neural Network” is introduced in this study to handle intermittent rainfall forecasting issues. Exponential Smoothing, an established approach for discovering underlying patterns and seasonal fluctuations in time series data, is combined with Neural Networks, which are good at capturing complex linkages and nonlinearities. Using these two methods, this model hopes to deliver a complete rainfall forecasting solution that accounts for short-term changes and long-term patterns. This research uses residuals from the exponential smoothing model and is modeled using a Neural Network. The residual input is transformed using rolling mean. The results show that the hybrid model is able to capture patterns well, but there are still patterns that experience time lag. Experimental results obtained reveal that the hybrid methodology performs better than the model exponential smoothing, implying that the proposed model hybrid synergy approach can be used as an alternative solution to the rainfall time series forecasting. The results show that the Hybrid method can form patterns better than individual exponential smoothing models or neural networks. The RMSSE values for all areas are 1.0185, 1.55092, 1.0872.
Pemanfaatan Digitalisasi Praktik Baik Guru Bahasa Indonesia Tingkat SMP di Surabaya untuk Meningkatkan Kompetensi Pedagogik Sa'diyah, Ilmatus; Hamid, Abdul; Widiwurjani, Widiwurjani; Muhaimin, Amri
I-Com: Indonesian Community Journal Vol 5 No 3 (2025): I-Com: Indonesian Community Journal (September 2025)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

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Abstract

Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kompetensi pedagogik guru Bahasa Indonesia SMP di Kota Surabaya melalui pemanfaatan digitalisasi praktik baik. Permasalahan yang dihadapi adalah belum optimalnya dokumentasi dan diseminasi praktik baik yang dihasilkan guru dalam forum MGMP, sehingga potensi inovasi pembelajaran belum tersebar secara luas. Adapun tujuan dari kegiatan pengabdian ini yaitu meningkatkan dan mengembangkan kompetensi pedagogik guru melalui digitalisasi praktik baik dari hasil kegiatan belajar mengajar di kelas.  Metode pelaksanaan pada kegiatan pengabdian kepada masyarakat ini dilakukan melalui lima tahapan, yaitu persiapan, pelatihan, penerapan teknologi, pendampingan dan evaluasi, serta keberlanjutan program. Sekitar 50 guru mengikuti kegiatan ini yang mencakup pretest, pelatihan literasi digital, praktik unggah karya pada platform https://guru.thalibulilmi.com/, serta posttest. Hasil kegiatan menunjukkan peningkatan signifikan pada kompetensi pedagogik guru, ditandai dengan nilai posttest yang tinggi serta respon positif dari peserta, di mana lebih dari 85% menyatakan kegiatan ini sesuai kebutuhan. Oleh karena itu, digitalisasi praktik baik cukup efektif sebagai sarana kolaboratif dalam pengembangan profesionalisme antara Guru Bahasa Indonesia Tingkat SMP di Surabaya.
Social Media Analysis and Topic Modeling: Case Study of Stunting in Indonesia Muhaimin, Amri; Fahrudin, Tresna Maulana; Alamiyah, Syifa Syarifah; Arviani, Heidy; Kusuma, Ade; Sari, Allan Ruhui Fatmah; Lisanthoni, Angela
Telematika Vol 20 No 3 (2023): Edisi Oktober 2023
Publisher : Jurusan Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31315/telematika.v20i3.10797

Abstract

Purpose: Stunting is a problem that currently requires special attention in Indonesia. The stunting rate in 2022 will drop to 21.6%, and for the future, the government has set a target of up to 14% in 2024. Rapid technological developments and freedom of expression on the internet produce review text data that can be analyzed for evaluation. This study analyzes the text data of Twitter users' reviews on stunting. The method used is a text-mining approach and topic modeling based on Latent Dirichlet Allocation.Design/methodology/approach: The methodology used in this study is Latent Dirichlet Allocation. The data was collected from twitter with the keyword 'stunting'. After, the data was cleaned and then modeled using the Latent Dirichlet Allocation.Findings/results: The results show that negative sentiment dominates by 60.6%, positive sentiment by 31.5%, and neutral by 7.9%. In addition, this research shows that 'children', 'decrease', 'number', 'prevention', and 'nutrition' are among the words that often appear on stunting.Originality/value/state of the art: This study uses the keyword stunting and analyzes it. Social media analytics show that the people of Indonesia are primarily aware of stunting. Also, the Latent Dirichlet Analysis can be used to create the model.
PERAMALAN MENGGUNAKAN HYBRID SEASONAL ARIMA DAN EXTREME LEARNING MACHINE: STUDI KASUS JUMLAH PRODUKSI BERAS DI PROVINSI JAWA TIMUR Pakpahan, Vera Febrianti; Muhaimin, Amri; Syaifullah, Wahyu
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 7 No 4 (2025): EDISI 26
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v7i4.6673

Abstract

Penelitian ini mengevaluasi performa metode hybrid Seasonal Autoregressive Integrated Moving Average (SARIMA) dan Extreme Learning Machine (ELM) untuk peramalan data deret waktu. Metode SARIMA digunakan untuk menangkap pola musiman dan linier, sedangkan ELM diaplikasikan pada residual prediksi SARIMA untuk mendeteksi pola non-linier yang sulit ditangkap oleh model tradisional. Studi kasus difokuskan pada prediksi produksi beras bulanan di Provinsi Jawa Timur, salah satu lumbung beras nasional dengan fluktuasi produksi yang memengaruhi perencanaan distribusi dan kebijakan pangan. Hasil evaluasi menunjukkan bahwa model hybrid SARIMA–ELM mencapai nilai MAPE sebesar 9,01% dan RMSE sebesar 38.639,93, menunjukkan akurasi prediksi yang baik. Temuan ini menegaskan bahwa kombinasi SARIMA dan ELM dapat menjadi pendekatan yang efektif untuk peramalan deret waktu dengan pola linier dan non-linier, serta memiliki potensi untuk diterapkan pada dataset atau sektor lain yang memiliki karakteristik serupa.
Co-Authors Abdul Hamid Alamiyah, Syifa Syarifah Damaliana, Aviolla Terza Dwi Arman Prasetya Endah Setyowati Fahrudin, Tresna Maulana Hanif Assalmi, Fityan Heidy Arviani Kusuma, Ade Lisanthoni, Angela Maulida H, Kartika Pakpahan, Vera Febrianti Prabowo, Hendri Rahmawati, Adinda Aulia Regita Putri Permata Sa'diyah, Ilmatus Sari, Allan Ruhui Fatma Sari, Allan Ruhui Fatmah Selayanti, Nabilah Sri Hidayati Suhartono Syaifullah Jauharis Saputra, Wahyu Syaifullah, Wahyu Taufik, Ikbar Athallah Trimono Trimono, Trimono Widiwurjani