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All Journal Sistemasi: Jurnal Sistem Informasi JUTIM (Jurnal Teknik Informatika Musirawas) Martabe : Jurnal Pengabdian Kepada Masyarakat JSAI (Journal Scientific and Applied Informatics) Building of Informatics, Technology and Science Indonesian Journal of Business Intelligence (IJUBI) Jurnal Abdi Insani JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Bulletin of Information Technology (BIT) The Indonesian Journal of Computer Science Research Journal of Community Services: Sustainability and Empowerment Intechno Journal : Information Technology Journal Edu Komputika Journal Nawadeepa: Jurnal Pengabdian Masyarakat
Wulandari, Irma Rofni
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Redesain UI/UX Sistem Pemesanan Menu Menggunakan Metode Design Thinking Falaq, Zilva Nur Fajrul; Sharazita Dyah Anggita; Wulandari, Irma Rofni; Baita, Anna
JSAI (Journal Scientific and Applied Informatics) Vol 8 No 3 (2025): November
Publisher : Fakultas Teknik Universitas Muhammadiyah Bengkulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36085/jsai.v8i3.9457

Abstract

This study aims to design and develop the user interface (UI) and user experience (UX) of a web-based menu ordering system using the Design Thinking method. The development process includes the stages of empathize, define, ideate, prototype, and testing to ensure that the final solution aligns with user needs. The prototype was further refined into a frontend design emphasizing ease of navigation, clarity of information, and efficiency of the ordering flow. Usability evaluation was conducted using the System Usability Scale (SUS). The assessment results show a SUS score of 70, in the Good category in the adjective rating. This indicates that the system design is acceptable to users and can be further developed into a complete frontend implementation. Overall, the Design Thinking approach proved effective in producing an intuitive, functional, and user-centered interface design.
Peningkatan Ketepatan Makharijul Huruf melalui Media Pembelajaran Digital Berbasis Android di TPA Masjid Diponegoro Hartatik, Hartatik; Supriatin, Supriatin; Widayani, Wiwi; Wulandari, Irma Rofni; Hartanti, Ninik Tri
Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat Vol. 6 No. 1 (2026): Januari 2026 - Jurnal Altifani Penelitian dan Pengabdian kepada Masyarakat
Publisher : Indonesian Scientific Journal

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59395/altifani.v6i1.973

Abstract

Kegiatan pengabdian masyarakat ini dilaksanakan di TPA Masjid Diponegoro, dengan tujuan meningkatkan ketepatan makhrijul urf santri tingkat pemula hingga menengah melalui media pembelajaran digital berbasis Android. Permasalahan utama yang dihadapi adalah ketidaktepatan pelafalan huruf, keterbatasan waktu tatap muka, dan minimnya latihan mandiri di rumah. Solusi yang ditawarkan berupa pengembangan aplikasi FlutterAndroid yang memuat 84 audio huruf hijaiyah dengan tiga harakat, ilustrasi makhraj interaktif, serta gim drag-and-drop dengan umpan balik instan. Metode pelaksanaan mencakup pelatihan guru, implementasi pembelajaran audiovisual di kelas, dan latihan micro-learning harian yang dipantau melalui ceklist orang tua. Hasil menunjukkan peningkatan rerata skor artikulasi sebesar 0,60,8 poin (skala 14) dan ukuran efek tinggi (Cohens d > 1,5). Program ini efektif meningkatkan kemampuan artikulasi, kemandirian belajar, dan standarisasi pengajaran, serta layak direplikasi di TPQ lain.
PENERAPAN METODE GAP PADA SISTEM PENDUKUNG KEPUTUSAN PENENTUAN BIBIT PADI TERBAIK Ricky Ichsan, Muhammad Adithya; Wulandari, Irma Rofni; Astuti, Yuli; Widayani, Wiwi
Indonesian Journal of Business Intelligence (IJUBI) Vol 5 No 2 (2022): Indonesian Journal of Business Intelligence (IJUBI)
Publisher : Universitas Alma Ata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21927/ijubi.v5i2.2715

Abstract

Pemilihan bibit padi merupakan langkah awal dari budidaya tanaman padi. Pemilihan bibit perlu diperhatikan untuk mendapatkan hasil panen yang baik. Petani di Desa Soropadan sering mengalami kesulitan dalam menentukan bibit padi yang akan digunakan. Sistem pendukung keputusan dapat menjadi salah satu solusi untuk permasalahan pemilihan bibit padi. Jenis bibit padi dapat dipilih berdasarkan aspek dan kriteria tertentu. Kriteria yang digunakan yaitu tinggi tanaman, kerontokan, harga bibit, umur tanaman, bentuk tanaman, bentuk gabah, kadar amilosa, dan kerebahan. Metode GAP merupakan salah satu metode pengambilan keputusan dengan mencari gap antar kriteria. Tujuan dari penelitian ini yaitu untuk merancang suatu sistem penunjang keputusan dengan menerapkan metode GAP sehingga dapat membantu memberikan rekomendasi bibit padi unggul. Hasil dari penelitian yaitu Metode GAP berhasil diimplementasikan ke dalam bentuk sistem penunjang keputusan berbasis website dan menampilkan perankingan bibit padi serta memberikan rekomendasi bibit padi terbaik. Blackbox testing digunakan untuk menguji sistem dan mendapatkan hasil sistem berjalan sesuai dengan perancangan.
Optimization of the Linear Regression Algorithm using GridSearchCV for Rice Crop Production Prediction Imel, Imel; M.Kom (SCOPUS ID: 57216417658), Norhikmah; Wulandari, Irma Rofni; Mustofa, Ali; Larasati, Niken; subektiningsih, subektiningsih
SISTEMASI Vol 15, No 1 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i1.5877

Abstract

Rice production in Central Java Province fluctuates annually, affecting food security and agricultural output distribution. Therefore, accurate prediction methods are essential to assist stakeholders in agricultural planning and strategic decision-making. This study applies the Linear Regression algorithm to predict rice production based on historical data from 2014 to 2023 obtained from the official website of the Central Java Provincial Agriculture and Plantation Office. The model is developed using multiple linear regression with variables including planted area, harvested area, and productivity. The novelty of this study lies in the structured application of hyperparameter tuning using GridSearchCV to optimize Linear Regression performance, as well as the integration of a preprocessing pipeline based on data distribution stabilization to improve accuracy and model generalization. The research process includes data collection, preprocessing, modeling, optimization, model evaluation, and deployment as a web-based application using Streamlit Cloud. GridSearchCV optimization results indicate a cross-validation accuracy of 98.26%, confirming the model’s strong predictive capability. Model evaluation shows an R² value of 0.9754, with MAE of 0.0957, MSE of 0.0307, and RMSE of 0.1753, indicating low prediction errors and stable model performance. The optimized model is implemented as a web application via Streamlit Cloud, enabling direct use by end-users. For future research, it is recommended to incorporate additional variables such as rainfall, temperature, and rice variety, or to compare performance with other algorithms such as Random Forest, Support Vector Regression, or Long Short-Term Memory (LSTM) to further enhance prediction accuracy.
Performance Evaluation of Machine Learning Models for Soil Fertility Classification Based on the Indian Soil Fertility Dataset Yoga Pristyanto; Ibrahim Aji Fajar Romadhon; Nugraha, Anggit Ferdita; Nurmasani, Atik; Wulandari, Irma Rofni
Edu Komputika Journal Vol. 12 No. 1 (2025): Edu Komputika Journal
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/edukom.v12i1.10317

Abstract

Rice farming productivity worldwide has been declining due to improper soil management practices, including excessive chemical fertilizer use and irregular irrigation. The main challenge lies in accurately classifying soil fertility levels to support optimal land use and reduce resource waste, especially when dealing with imbalanced datasets. This study aims to compare the performance of single classifiers and ensemble classifiers in classifying soil fertility. The single classifiers used include K-Nearest Neighbor (KNN), Naive Bayes, Decision Tree, Support Vector Machine (SVM), and Artificial Neural Network (ANN), while the ensemble classifiers include Random Forest and XGBoost. The Indian Soil Fertility Dataset, obtained from Kaggle, contains 880 samples with 12 features and 1 output class. The research methodology involved data acquisition, preprocessing, data splitting, standardization, and classification, with performance evaluation conducted using a confusion matrix. The results show that ensemble classifiers, particularly Random Forest and XGBoost, outperform single classifiers in imbalanced datasets, achieving accuracy, precision, recall, and F1-score values exceeding 92%-95% across all split scenarios. The findings conclude that Random Forest and XGBoost can serve as reliable models for assisting farmers and agricultural experts in evaluating soil conditions, minimizing unnecessary fertilizer usage, and improving rice farming productivity globally.
ANIMASI 2 DIMENSI SEBAGAI INFOGRAFIS PENCEGAHAN VIRUS COVID 19 PADA PAUD TERPADU ALLIFA Astuti, Yuli; Wulandari, Irma Rofni; Alim W, Abdiel; Haris A, Vikiyana; Hasanu, Fawwaz; Aries K, Bibit; Utami, Rina Puji
Martabe : Jurnal Pengabdian Kepada Masyarakat Vol 4, No 1 (2021): Martabe : Jurnal Pengabdian Kepada Masyarakat
Publisher : Universitas Muhammadiyah Tapanuli Selatan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31604/jpm.v4i1.215-221

Abstract

Delapan bulan negara ini mengalami kondisi yang tidak biasa karena adanya pandemic virus corona atau sering disebut covid-19. Dunia Pendidikan tetap harus berjalan sebagaimana mestinya biarpun tidak bisa dilaksanakan secaramaksimal, oleh karena itu pihak sekolah harus melakukan proses pembelajarannya menggunakan system online. Untuk pembelajaran online di jenjang Pendidikan usia dini masih butuh pendampingan orang tua secara intensive. Oleh karena itu penyampaian pesan atau materi dilakukan dengan jelas dan semenarik mungkin agar orang tua mudah untuk menyampaikan ke anak. Untuk memberikan pesan pola hidup sehat untuk pencegahan virus covid-19 juga harus menarik dan interaktif agar pesan yang disampaikan mudah diterima untuk anak sehingga pada pengabdian ini dibuatlah video animasi 2 Dimensi infografis tentang pencehagan virus covid-19 dengan jenis file mp4 sehingga bisa dilihat melalui handphone maupun computer. Tahap pembuatannya yaitu menganalisa masalah, menentukan solusi, memilih solusi, kemudian dilanjutkan perancangan dengan storyboard, pembuatan desain karakter, penulisan naskah dan recording kemudian kompositing dan editing dan terakhir adalah pengujian. Pada video ini masih ada kekurangan yaitu durasi video masih cukup pendek sehingga informasi yang disampaikan masih terbatas. 
Co-Authors Ali Mustopa Alim W, Abdiel Amitaba, Asthivia Oktanda Andika, Devandi Kurnia Restu Anggita, Sharazita Dyah Anggun Anindya Sekarningrum Aries K, Bibit Astuti, Yuli Astuti ATIK NURMASANI Baharudin, Muhamad Baita, Anna Darma, Firman Diatullah Guna Devi Wening Astari Devi Wening Astari Fahlevie, Reychandra Tristan Falaq, Zilva Nur Fajrul Ferdiansyah, Pramudhita Ferdiansyah, Ricky Andre Haris A, Vikiyana Hartatik Hasanu, Fawwaz Hidayat, Muhammad Alfi Ibrahim Aji Fajar Romadhon Imel, Imel Indrayani, Rini Kusumaningtyas, Kartikadyota M.Kom (SCOPUS ID: 57216417658), Norhikmah Niken Larasati NINIK TRI HARTANTI Nugraha, Anggit Ferdita Nurerwan, Mizani Achmad Nuri Cahyono Ricky Ichsan, Muhammad Adithya Rifda Faticha Alfa Aziza Rini Indrayani Sangaji, Sangaji Sekarningrum, Anggun Anindya Subektiningsih Subektiningsih Supriatin Supriatin, Supriatin Utami, Rina Puji Wiwi Widayani, Wiwi Yoga Pristyanto Yuli Astuti Zaldiyanto, Dimas