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All Journal International Journal of Electrical and Computer Engineering Jurnal Teknologi Informasi dan Ilmu Komputer POSITIF RABIT: Jurnal Teknologi dan Sistem Informasi Univrab Jurnal SOLMA JOURNAL OF APPLIED INFORMATICS AND COMPUTING JTAM (Jurnal Teori dan Aplikasi Matematika) METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi Jurnal Sisfokom (Sistem Informasi dan Komputer) METIK JURNAL Vocatech : Vocational Education and Technology Journal JOURNAL OF INFORMATICS AND COMPUTER SCIENCE JINAV: Journal of Information and Visualization Rambideun : Jurnal Pengabdian Kepada Masyarakat International Journal of Engineering, Science and Information Technology Jurnal Tika JURNAL ILMIAH GLOBAL EDUCATION Jurnal Saintekom : Sains, Teknologi, Komputer dan Manajemen Jurnal Minfo Polgan (JMP) Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Teknologi Terapan and Sains 4.0 Jurnal Bangun Abdimas Variasi : Majalah Ilmiah Universitas Almuslim MEUSEURAYA : JURNAL PENGABDIAN MASYARAKAT Journal of Deep Learning, Computer Vision and Digital Image Processing Journal of Advanced Computer Knowledge and Algorithms Journal Serambi Engineering (JSE) Jurnal Elektro dan Teknologi Informasi Bulletin of Engineering Science, Technology and Industry Jurnal Ragam Pengabdian Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN) Proceedings of Malikussaleh International Conference on Multidisciplinary Studies (MICoMS) Buletin Pengabdian
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Journal : journal of applied informatics and computing

Implementation of The Logistic Regression Algorithm to Analyze Poverty Factors in Aceh Province Mursyidah, Mursyidah; Kesuma Dinata, Rozzi; Yunizar, Zara
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9715

Abstract

Aceh Province continues to face a high poverty rate despite its abundant natural resources. This study aims to analyze the factors influencing poverty status in Aceh Province by applying a binary logistic regression algorithm. The research specifically focuses on an inferential analytical approach to reveal significant relationships among socioeconomic variables. Secondary data were obtained from the Aceh Provincial Statistics Agency (Badan Pusat Statistik/BPS) for the period 2019–2023. Inferential analysis was conducted using the entire dataset through the statsmodels library to identify variables that are statistically significant to poverty status. In addition, a classification approach was implemented using scikit-learn, with a data split between training data (2019–2022) and testing data (2023), yielding an accuracy of 0.70, precision of 0.81, recall of 0.70, F1-score of 0.66, and AUC of 0.69. These findings provide empirical evidence that improving access to education and equitable infrastructure development in densely populated areas can serve as effective policy focuses in efforts to alleviate poverty in Aceh Province.
Real-Time Heart Rate Pattern Analysis During Computer-Based Work Activities Muhammad Fatiha Assyfa; Muhammad Fikry; Zara Yunizar
Journal of Applied Informatics and Computing Vol. 10 No. 4 (2026): August 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i4.13148

Abstract

The development of Internet of Things (IoT) technology provides opportunities for real-time health monitoring systems, including stress detection based on users’ physiological conditions. This study aims to develop an IoT-based heart rate monitoring and stress detection system using a Pulse Sensor and ESP8266 microcontroller. The system is designed to read heart rate signals in real-time and transmit the data to a computer through serial USB communication for further processing using the Python programming language. The data processing stages include signal preprocessing, Beats Per Minute (BPM) calculation, sliding window processing, and kurtosis analysis as an indicator of user stress levels. The processed data are visualized through a Streamlit-based monitoring dashboard in the form of time-series graphs, gauge meters, and real-time user condition status. The study involved 20 Informatics Engineering students performing computer-based work activities within a certain duration. The results show that the system is capable of performing real-time heart rate monitoring and stress analysis effectively. The kurtosis values indicate changes in heart rate signal distribution patterns that can be used as indicators of normal and stress conditions. The developed system is expected to provide a simple, affordable, and extensible health monitoring solution.
Prediction of Remaining Productive Life of Oil Palm Plantation Soil Using Support Vector Regression with Permutation-Based Feature Importance Analysis Zara Yunizar Zainal; Nurdin Nurdin; Zharif Athaya Andarfi
Journal of Applied Informatics and Computing Vol. 10 No. 4 (2026): August 2026
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v10i4.13229

Abstract

Oil palm (Elaeis guineensis Jacq.) is a strategically vital crop in Southeast Asia, yet progressive soil degradation driven by prolonged monoculture, pathogen pressure, and intensive land use poses a critical threat to long-term plantation sustainability. Existing soil assessment methods deliver static fertility classifications without quantifying the remaining productive lifespan of a given plot. This study introduces Remaining Productive Life (RPL) as a novel regression target defined as the estimated number of years before plantation soil productivity falls below a critical economic threshold. A Support Vector Regression (SVR) model with Radial Basis Function (RBF) kernel, formulated as K(xi, xj) = exp(−γ‖xi − xj‖²) with γ = 0.0303 (= 1/n_features) and regularization parameter λ = 0.5, was applied to a realistic synthetic multi-year dataset comprising 14,400 observations across 800 plantation plots spanning five soil types (Ultisol, Inceptisol, Alfisol, Peat, Oxisol) and the period 2008–2025. Thirty-three soil physicochemical, biological, management, and economic indicators constituted the input feature set. The SVR model achieved R² = 0.9141, MAE = 0.5122 years, RMSE = 1.1026 years, and MAPE = 11.883% on the independent test set, with 92.0% of predictions yielding an absolute error below one year. Permutation-based feature importance analysis identified Degradation Rate (ΔMAE = 0.2864), Plantation Age (0.2560), and Soil Productivity Index (0.2530) as the three dominant predictors, while Ganoderma Risk Index ranked fourth (0.2138), revealing the pivotal contribution of biological soil health to long-term productivity prediction. These findings establish SVR-based RPL estimation as an effective, interpretable framework for precision plantation management and proactive soil sustainability planning.
Co-Authors ,, Iqbal ,, Maulidasari ,, Zulaifani ., Yulisma Agil, Helvina Aidilof, Hafizh Al-Kautsar Aisah, Sri Purwani Al Kautsar Aidilof, Hafiz Alfisyahrin Amelia, Ulva Andra Munandar Ansharulhaq Aminsyah Arief Fazillah Arif H., Nanda Nan Arnawan Hasibuan Asran Asran Ayu Suningsih Ayunda Putri Bariah, Hairul Bustami Bustami Cindy Rahayu Dahlan Abdullah Devi, Salma Dhyra Gibran Alinda Dr M Rajeswari Elma Fitria Ananda ERNAWITA ERNAWITA Ersa, Nanda Savira Eva Darnila Ezra Sasqia Syahna Fadlisyah Fadlisyah Fadlisyah Fajri, Riyadhul Fajri, Ryadhul Fajriana, Fajriana Fardiansyah, T. Fasdarsyah Fasdarsyah Fathan Maulana Helmi Fatimah Zuhra Fatimah Zuhra Fatimah Zuhra Febi Anriani Fuadi, Wahyu Gilang Wahyu Ramadhan Gilang Hafidh Rafif, Teuku Muhammad Hafizh Al Kautsar Aidilof Hamdhana, Defry Harahap, Ilham Taruna Hasan, Phadlin HENDRA ZULKIFLI Herman Fithra Huan Margana Ritonga Irshad Ahmad Reshi Johan, T. M. Juanda Pratama Kartika Kartika Kurnia Amanda, Destiara Lidya Rosnita M Ishlah Buana Angkasa M. Fauzan M.Cs, Iqbal, Maghfirah Maghfirah Maha, Dedi Torang P Mahara, Sabda Mahendra Febriliansyah Maizuar Maizuar Maryana Maryana Maulana, O.K.Muhammad Majid Maulida Yani Siregar Melizar Meutia Rahmi Misbahul Jannah Muhammad Daud Muhammad Fatiha Assyfa Muhammad Fauzan Muhammad Fikri Muhammad Fikry Muhammad Ikhwani Muhammad Muhammad Muharni Muharni Mukhlis Mukhlis Mukhlis Mulaesyi, Syibbran Munar, Munar Munirul Ula Mursyidah Mursyidah MUTHMAINNAH Muthmainnah Muthmainnah Nanda Nan Arif H Nazwa Aulia NinaUlfauza Nunsina, Nunsina Nur Mauliza Nura Usrina Nurdin Nurdin Nuryawan, Nuryawan OK Muhammad Majid Maulana Majid Putri, Riska Yolanda Ramadhana Juseva Reza Pratama Ridha, Ridha Rifkial Iqwal Rini Meiyanti Rizal S.Si., M.IT, Rizal Rizal Tjut Adek Rizki Suwanda Rizky Almunadiansyah Rizky Putra Fhonna Rizky, Rahmat Rizkya, Dini Dara Rozzi Kesuma Dinata Rusnani Rusnani Rusnani Rusnani Rusniati Rusniati Ruwaida Ruwaida Safwandi Safwandi Said Fadlan Anshari Silvia Nanda Siregar, Winda Ramadhani Sriana, Anis Subhan Hartanto Suci Fitriani, Suci Sujacka Retno Sutri Wandani Syintia, Icut Tarigan, Tasya Amelia Taufiq Taufiq Tejas Shinde Tjut Adek, Rizal Wahyu Fuadi Walad Hidayat Winda Yanti Yesy Afrillia Zahratul Fitri Zalfie Ardian Zharif Athaya Andarfi Zulnazri, Z Zulsuhendra, Edi