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All Journal JETT (Jurnal Elektro dan Telekomunikasi Terapan) JITTER (Jurnal Ilmiah Teknologi Informasi Terapan) JURNAL CEMERLANG: Pengabdian pada Masyarakat Jurnal Rekayasa Hijau MIND (Multimedia Artificial Intelligent Networking Database) Journal REKA ELKOMIKA: Jurnal Pengabdian kepada Masyarakat Jurnal Pelayanan Hubungan Masyarakat Alkhidmah: Jurnal Pengabdian dan Kemitraan Masyarakat Scientific Journal of Informatics
Marisa Premitasari, Marisa
Institut Teknologi Nasional Bandung
Agriculture, Biological Sciences & Forestry Humanities 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 Engineering Health Professions Industrial & Manufacturing Engineering Law, Crime, Criminology & Criminal Justice Mechanical Engineering Other

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Sistem Pengelolaan Arsip Pada Kelurahan Sukaluyu Kecamatan Cibeunying Kaler Berbasis Website Yusup Miftahuddin; Marisa Premitasari; Galih Al Hakim; Adam M Afriazi; M Razi Saefunazar; Naufal Nurul Hadi H; Abdurrafi Fawwaz
ALKHIDMAH: Jurnal Pengabdian dan Kemitraan Masyarakat Vol. 1 No. 2 (2023): April : Jurnal Pengabdian dan Kemitraan Masyarakat
Publisher : Sekolah Tinggi Ilmu Syariah Nurul Qarnain Jember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59246/alkhidmah.v1i2.395

Abstract

Kelurahan is administratively located at the lowest level in the government system in Indonesia. The kelurahan has the task of serving the community. Archives have a role as a memory and source of information, one of which in the Sukaluyu sub-district, Cibeunying Kaler sub-district, Bandung city. Based on observations at the Sukaluyu sub-district office, that the condition of archive management in the kelurahan still has deficiencies, namely the filing system is still in physical form, some documents have been damaged and some missing due to the archival system implemented by this kelurahan still manually. With that, a digital archive management system was created is making website for archive management. This community service is one that is carried out by the lecturer staff and students of the ITENAS informatics study program. This system expected to help increase the effectiveness of archival data management, reduce archive loss, and shorten archive search time.
Pemanfaatan Aplikasi Binasehat dalam Peningkatan Kesadaran Kesehatan di Puskesmas Cimaragas Premitasari, Marisa; Lukmansyah, Rifqi; Farisi, Farhan Al; Fadillah, Muhammad Hafidz; Chairy, Qays Arkan
JURNAL CEMERLANG: Pengabdian pada Masyarakat Vol 7 No 1 (2024): JURNAL CEMERLANG: Pengabdian Pada Masyarakat
Publisher : LP4MK STKIP PGRI Lubuklinggau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31540/jpm.v7i1.3380

Abstract

Peningkatan prevalensi Penyakit Tidak Menular (PTM) di Indonesia menimbulkan tantangan besar dalam sistem kesehatan nasional. Puskesmas, sebagai ujung tombak layanan kesehatan primer, memainkan peran penting dalam mengatasi masalah ini melalui pendekatan promotif dan preventif. Aplikasi BinaSehat dikembangkan sebagai solusi teknologi digital untuk mendukung upaya ini. Program ini bertujuan untuk meningkatkan kesadaran kesehatan masyarakat di wilayah Puskesmas Cimaragas melalui fitur pelacakan kalori, panduan olahraga interaktif, dan edukasi kesehatan berbasis digital. Hasil implementasi menunjukkan respons positif dari tenaga kesehatan dan masyarakat. Aplikasi ini tidak hanya mempermudah edukasi kesehatan tetapi juga mendorong perubahan perilaku menuju gaya hidup sehat. Namun, tantangan seperti adaptasi terhadap teknologi digital dan keterbatasan infrastruktur internet tetap menjadi hambatan. Diharapkan aplikasi BinaSehat dapat menjadi model inovasi layanan kesehatan primer yang dapat direplikasi di seluruh Indonesia untuk mendukung transformasi digital sektor kesehatan.
Impact of Feature Engineering on XGBoost Model for Forecasting Cayenne Pepper Prices Pardede, Jasman; Putri Setyaningrum, Anisa; Ilyas Al-Fadhlih, Muhammad; Premitasari, Marisa
Scientific Journal of Informatics Vol. 12 No. 4: November 2025
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v12i4.32157

Abstract

Purpose: Cayenne pepper represents one of Indonesia’s key horticultural commodities, widely utilized in both household culinary practices and the food processing industry. Nevertheless, its market price is subject to considerable volatility, driven by factors such as weather variability, limited supply, production costs, and inefficiencies in distribution systems. This price instability generates uncertainty that adversely impacts farmers, traders, and consumers. Consequently, the development of a reliable price forecasting model is crucial to facilitate price stabilization and enable data-driven decision-making across the supply chain. This study aims to investigate the extent to which feature engineering techniques can enhance the predictive performance of the Extreme Gradient Boosting (XGBoost) algorithm in forecasting cayenne pepper prices. Through the integration of lag features, moving averages, and seasonal indicators, the proposed model is expected to more effectively capture market dynamics and provide a robust analytical tool for relevant stakeholders. Methods: The forecasting model was constructed using the XGBoost algorithm in combination with various feature engineering methods. The dataset consists of daily price records obtained from Bank Indonesia’s PIHPS system and meteorological variables sourced from BMKG, encompassing the period between 2021 and 2024. The engineered features include lag variables identified through Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) analyses, Simple Moving Averages (SMA), seasonal indicators, and holiday-related variables designed to capture recurring patterns and event-driven price fluctuations. To enhance predictive performance, hyperparameter tuning was conducted using a grid search optimization approach. Result: The optimal model demonstrated substantial performance improvements under the following hyperparameter configuration: alpha = 0, gamma = 0.3, lambda = 1, learning_rate = 0.05, max_depth = 3, min_child_weight = 3, n_estimators = 200, and subsample = 0.6. The application of feature engineering markedly enhanced the model’s predictive capability, increasing the R² value by 99.10% while reducing the MAE, RMSE, and MAPE by 72.63%, 71.31%, and 72.04%, respectively. These outcomes signify a notable reduction in forecasting errors and demonstrate the model’s improved accuracy. Novelty: This study integrates multi-level price data with weather and holiday-related features, employing the ACF and the PACF analyses to determine optimal lag values (techniques commonly utilized in statistical modeling). This integration enhances both the accuracy and interpretability of the XGBoost algorithm, thereby providing a practical and effective tool for agricultural price forecasting and market planning.
Co-Authors Abdurrafi Fawwaz Adam M Afriazi Alwamahaib, Zulfa Sulthany Arefa, Zalfa Tsana Chairy, Qays Arkan Chondro seto Nur Suryawan Dhiki Romadinur Dixy Abdul Rochman S Fadillah, Muhammad Hafidz Farisi, Farhan Al Galih Al Hakim Hadiwibowo, Wirawan Hendi Handian Ibrahim, Farrel Adi Ilyas Al-Fadhlih, Muhammad Jasman Pardede KRISTIANA, LISA Lukmansyah, Rifqi M Razi Saefunazar Mochammad Rizal Muhammad Daffa Fathur Rahman Naufal Nurul Hadi H Petrick Juliansz Kakalang Putri Setyaningrum, Anisa Rafid, Rayhan Alea Rakhmat, Galih Ashari Rangga Alfyansyah UUNG UNGKAWA Uung Ungkawa Yusup Miftahuddin