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All Journal Dinamik Dimas: Jurnal Pemikiran Agama untuk Pemberdayaan Jurnal Transformatika At-Taqaddum Wahana Akademika: Jurnal Studi Islam dan Sosial Sawwa: Jurnal Studi Gender Isamic Communication Journal InComTech: Jurnal Telekomunikasi dan Komputer JOURNAL OF APPLIED INFORMATICS AND COMPUTING SINTECH (Science and Information Technology) Journal Jurnal Sisfokom (Sistem Informasi dan Komputer) JSiI (Jurnal Sistem Informasi) JURIKOM (Jurnal Riset Komputer) JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) RELIGIA Jurnal Ilmu Dakwah EDUMATIC: Jurnal Pendidikan Informatika Jurnal Sistem Komputer dan Informatika (JSON) Jifosi Aiti: Jurnal Teknologi Informasi Wahana Akademika: Jurnal Studi Islam dan Sosial Jurnal Teknik Informatika (JUTIF) Journal La Multiapp JURNAL ILMIAH GLOBAL EDUCATION Jurnal Algoritma Religia : Jurnal Ilmu-Ilmu Keislaman Jurnal Informatika: Jurnal Pengembangan IT JUTEKOM - Jurnal Teknologi dan Ilmu Komputer
Maya Rini Handayani
Universitas Islam Negeri Walisongo Semarang
Religion Aerospace Engineering Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Mathematics Public Health Social Sciences Other

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Analisis Performa Metode Machine Learning dalam Mengidentifikasi Penyebab Ulasan Rating Satu Aplikasi MyBluebird Azziizah, Almira Farradinda; Mustofa, Hery; Umam, Khothibul; Handayani, Maya Rini
Jurnal Ilmiah Global Education Vol. 6 No. 4 (2025): JURNAL ILMIAH GLOBAL EDUCATION
Publisher : LPPM Institut Pendidikan Nusantara Global

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55681/jige.v6i4.4704

Abstract

This study addresses the increasing prevalence of negative user reviews for the MyBluebird ride-hailing application, focusing on the identification and classification of the main causes of one-star ratings. The research aims to compare the effectiveness of Support Vector Machine, Random Forest, and Naïve Bayes algorithms in classifying user complaints. Employing a quantitative experimental approach, the study utilizes a dataset of 1,399 one-star reviews collected purposively from Google Play Store. Data preprocessing includes cleaning, tokenization, and feature extraction using TF-IDF. The classification models are evaluated using accuracy, precision, recall, and F1-score metrics. Results indicate that Random Forest achieves the highest accuracy (90%), outperforming the other algorithms, with bugs/errors as the most frequent complaint, followed by driver performance, other issues, and price. The study concludes that machine learning-based classification can effectively map user dissatisfaction, though data imbalance remains a limitation. Future research should apply data balancing techniques and expand the dataset for broader generalization. Practical implications suggest that developers can utilize automated classification to improve service quality and address user needs more efficient.
Digital innovation in islamic guidance: Fuzzy mamdani-based stress level detection for muslim adolescents Amal, Muhammad Niltal; Handayani, Maya Rini
Jurnal Ilmu Dakwah Vol. 45 No. 2 (2025)
Publisher : Faculty of Dakwah and Communication, Walisongo State Islamic University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21580/jid.v45.2.28875

Abstract

Purpose - The purpose of this study is to address the urgent need for a reliable and accessible preliminary assessment tool for mental health issues among Indonesian adolescents, a demographic significantly impacted by recent societal changes and showing high rates of psychological distress (e.g., 34.9% experiencing mental problems per I-NAMHS 2022) Method - The methodology employed is the design and development of a web-based expert system utilizing Fuzzy Logic to diagnose stress symptoms. The system is structured with four core components (User Interface, Knowledge Base, Inference Mechanism, Working Memory) and incorporates Fuzzy Tsukamoto/Mamdani/Sugeno principles for mapping firm numerical symptom inputs to linguistic variables through Fuzzification and Defuzzification processes. Result  -  The result (anticipated/achieved) is a functional, dual-role web system (Admin/User) capable of providing objective, preliminary stress categorization, thereby serving as a first step toward early intervention. Implication – The implication of this work is twofold: clinically, it provides an immediate, non-expert-dependent tool for initial screening; ethically and religiously, it supports the collective obligation (fard kifayah) to safeguard youth mental well-being and maintain their fitrah. Originality/Value - The originality of this research lies in the specific integration of Fuzzy Logic reasoning within a web-based expert system tailored explicitly to the Indonesian adolescent context for stress awareness and preliminary diagnosis.*** Tujuan - Tujuan studi ini adalah untuk memenuhi kebutuhan mendesak akan alat penilaian awal yang andal dan mudah diakses untuk masalah kesehatan mental di kalangan remaja Indonesia, kelompok demografis yang sangat terdampak oleh perubahan sosial terkini dan menunjukkan tingkat gangguan psikologis yang tinggi (misalnya, 34,9% mengalami masalah mental menurut I-NAMHS 2022) Metode - Metode yang digunakan adalah desain dan pengembangan sistem pakar berbasis web yang memanfaatkan Logika Fuzzy untuk mendiagnosis gejala stres. Sistem ini terdiri dari empat komponen inti (Antarmuka Pengguna, Basis Pengetahuan, Mekanisme Inferensi, Memori Kerja) dan mengintegrasikan prinsip-prinsip Fuzzy Tsukamoto/Mamdani/Sugeno untuk memetakan masukan numerik gejala yang pasti ke variabel linguistik melalui proses Fuzzifikasi dan Defuzzifikasi. Hasil - Hasil (diperkirakan/tercapai) adalah sistem web fungsional dengan dua peran (Admin/Pengguna) yang mampu memberikan kategorisasi stres awal yang objektif, sehingga berfungsi sebagai langkah awal menuju intervensi dini. Implikasi – Implikasi dari penelitian ini dua arah: secara klinis, menyediakan alat skrining awal yang segera dan tidak bergantung pada ahli; secara etis dan agama, mendukung kewajiban kolektif (fard kifayah) untuk melindungi kesejahteraan mental remaja dan menjaga fitrah mereka. Orisinalitas/Nilai - Keaslian penelitian ini terletak pada integrasi spesifik logika fuzzy dalam sistem pakar berbasis web yang dirancang khusus untuk konteks remaja Indonesia dalam kesadaran stres dan diagnosis awal.
Co-Authors ., Kumarudin ., Kumarudin Amal, Muhammad Niltal Amelia Rahmi Apriliyani, Meli Asep Dadang Abdullah Asep Dadang Abdullah Aufan, Muhammad Haikal Azziizah, Almira Farradinda Chairullah, Dimas Dewi, Fiashintha Dina Wulan Yekti rahayu Dwi Yuni Saraswati Dwi Yuniarti, Wenty Ema Hidayanti Ema Hidayanti Fastabiqul Khusna Febrianto, Bagus Heti Aprilianti Hidayati, Ema Jinan, Muhammad Syifaaul Khoirotulmuadiba Purifyregalia Khoirul Adib Khothibul Umam Khotibul Umam Maizaliyanti, Annisa Malikhatul Ibriza Masuzzahra, Tsaura Rafah Masy Ari Ulinuha Mokhamad Iklil Mustofa Muhadzib Al-Faruq, Muhammad Naufal Muhammad Rafid Pratama Mustofa Hilmi Mustofa, Hery Mustofa, Mokhammad Iklil Musyafak, Najahan Musyafak, Najahan Musyaffaq, Mirza Izzal Nahdhudin, Muhammad Nur Cahyo Hendro Wibowo Nur Cahyo Hendro Wibowo, Nur Cahyo Hendro Nurjanna, Afifah Basmah Nur’aini, Siti Pramesti, Arfiana Diah Prasilda, Dina Rahma putri lathifah, shofi Putri, Indira Alifia Qonita, Nuurun Najmi Rahmadani, Nurul Robby Kurniawan Budhi Safitri, Sindy Eka Sajmira, Danita Divka Salmalina, Divana Taricha Saputra, Adika Kaka Sa’adah, Siti Miftahus Septyorini, Talitha Dwi Siti Hikmah Siti Hikmah, Siti Siti Nur Aini, Siti Nur Siti Nur'aini Sufiya, Ikhwanus Syifa, Achrijal Shohib Arya Tsuroyya, Kamiliya Umam, Khothibulu Vensy Vydia wening wihartati, wening Wenty Dwi Yuniarti Wenty Dwi Yuniarti, Wenty Dwi