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All Journal Techno.Com: Jurnal Teknologi Informasi Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Jurnal Teknik Elektro Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Sistem dan Informatika InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sistemasi: Jurnal Sistem Informasi Jurnal Teknologi dan Sistem Komputer JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JURNAL MANAJEMEN BISNIS Jurnal Literasiologi Jurnal Tekno Kompak Jurnal Ilmiah Kebidanan Indonesia (Indonesian Midwifery Scientific Journal) Jurnal Abdidas Jurnal SASAK : Desain Visual dan Komunikasi Jurnal Bumigora Information Technology (BITe) Jurnal Pengabdian UNDIKMA Journal of Electrical Engineering and Computer (JEECOM) Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Jurnal Silva Samalas: Journal of Forestry and Plant Science Jurnal Elkasista ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Inovasi, Evaluasi dan Pengembangan Pembelajaran (JIEPP) Jurnal PRIMED:Primary Education Journal atau Jurnal Ke-SD An Journal of Engineering, Technology and Computing (JETCom) Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Insand Comtech : Information Science and Computer Technology Journal Valid Jurnal Pengabdian Journal of Economics and Management Scienties Prosiding Seminar Nasional CORISINDO Media Pendidikan Matematika
Hairani Hairani
Universitas Bumigora, Mataram, Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Combination Forward Chaining and Certainty Factor Methods for Selecting the Best Herbs to Support Independent Health Muhamad Azwar; Sri Winarni Sofya; Riwayati Malika; Hairani Hairani; Juvinal Ximenes Guterres
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 24 No. 2 (2025)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v24i2.4485

Abstract

The use of herbal medicine as an alternative treatment is increasingly popular due to its natural benefits and cultural significance. However, a lack of public knowledge about the effectiveness, appropriate dosages, and processing methods of herbal remedies poses a significant barrier to their proper utilization. This knowledge gap often leads to suboptimal or even unsafe usage of herbal medicines. To address this issue, this study proposes an application-based system combining the Forward Chaining and Certainty Factor methods to provide personalized recommendations for the best herbal remedies supporting self-health management. The research aims to enhance accessibility to reliable information on herbal treatments while ensuring accurate and user-specific recommendations. By utilizing the ForwardChaining and Certainty Factor method, this system identifies suitable herbal plants based on the type of disease, processing techniques, recommended dosages, and duration of treatment. Meanwhile, the Certainty Factor method calculates the level of certainty for each recommendation provided. The study’s results showed a validation rate of 90%, indicating that the combination of these two methods effectively bridges the gap between traditional herbal knowledge and modern health needs. This study concludes that the system offers a practical tool for individuals to select and use herbal treatments safely and effectively, promoting better health outcomes.
IMPLEMENTASI BILSTM UNTUK KELASIFIKASI SENTIMEN PADA KASUS PEMILIHAN UMUM 2024 Qososyi, Sayidina Ahmadal; Hairani, Hairani; Hammad, Rifqi
Insand Comtech : Information Science and Computer Technology Journal Vol 10, No 1 (2025): Insand Comtech
Publisher : Universitas Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53712/jic.v10i1.2623

Abstract

Kemajuan media sosial memudahkan kita untuk mengetahui peristiwa dan informasi di seluruh dunia. Twitter merupakan salah satu media sosial dengan banyak pengguna yang sering digunakan untuk mengekspresikan opini atau sentimen terhadap isu-isu terkini. Penelitian ini bertujuan untuk melakukan klasifikasi sentimen dalam bahasa Indonesia terkait opini masyarakat yang berupa positif, negatif, dan netral terhadap pemilu 2024. Metode yang digunakan adalah Bidirectional Long Short-Term Memory (BiLSTM) untuk klasifikasi sentiment. Data yang digunakan pada penelitian ini berasal dari Twitter sebanyak 3.085 data. Hasil klasifikasi sentimen dengan BiLSTM menunjukkan akurasi terbaik 83% menggunakan embedding FastText, diikuti oleh Word2Vec dan Glove dengan akurasi 82%. Analisis ini membantu memahami opini publik terhadap pemilu 2024 dan memudahkan pemantauan serta evaluasi proses demokrasi di Indonesia.
OPTIMASI CHATBOT DALAM SISTEM PENGADUAN PELAYANAN PUBLIK BERBASIS ANDROID Tholib, Abu; Andi, Moh syaiful; Sukron, Moh; Shudiq, Wali Ja'far; Hairani, Hairani; Guterres, Juvinal Ximenes
Insand Comtech : Information Science and Computer Technology Journal Vol 10, No 1 (2025): Insand Comtech
Publisher : Universitas Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53712/jic.v10i1.2637

Abstract

This study presents the development of an Android-based public service complaint application integrated with chatbot technology to improve service responsiveness. The system aims to facilitate community members in submitting complaints and receiving immediate responses through an interactive interface. A user-friendly mobile application was developed using the Kotlin programming language, and chatbot functionality was implemented via API integration to respond to frequently asked questions. The implementation followed the Waterfall model, encompassing stages of analysis, design, implementation, testing, and maintenance. Results show that the application effectively streamlines the complaint process, increases efficiency in complaint management, and enhances communication between the public and local government. The chatbot proved to be reliable in delivering relevant and timely responses, significantly reducing the time needed for initial interactions. This integration demonstrates the potential of artificial intelligence to support e-government services in rural setting
PEMANFAATAN FREE ENERGY UNTUK PENGISIAN DAYA MENGGUNAKAN GENERATOR MAGNET DALAM OPERASI MILITER DI MEDAN TERPENCIL Eka Setiawan, Rian Putra; Kasiyanto, Kasiyanto; Hairani, Hairani
Jurnal Elkasista Vol 6 No 1 (2025): Jurnal Elkasista
Publisher : Pustaka Poltekad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54317/elka.v6i1.616

Abstract

Penelitian ini bertujuan mambantu tugas pokok TNI-AD menggunakan Generator magnet yang memiliki konsep free energy sebagai solusi untuk penyediaan energi dalam operasi militer, terutama di wilayah terpencil di mana sumber energi konvensional kurang dan sulit dijangkau. Generator magnet yang dirancang untuk dapat beroperasi pada kecepatan rendah dapat mengisi perangkat militer dengan generator magnet yang memiliki konsep free energy. Dengan desain, pengujian, dan analisis generator magnet yang dioptimalkan untuk pengisian daya pada kecepatan rendah. Penelitian ini adalah bertujuan agar generator magnet menghasilkan energy yang dapat digunakan di medan operasi militer terpencil. Hasil pengujian menunjukkan bahwa generator ini mampu menghasilkan energi yang tinggi dengan efisiensi mencapai 82,3% pada kecepatan 200 RPM. Energi yang dihasilkan cukup untuk mengisi daya perangkat militer dan menyediakan cadangan daya yang stabil. Dengan kemampuan ini, generator magnet yang dirancang dapat menjadi sumber daya yang cukup untuk mendukung operasi militer di medan yang sulit dijangkau.
IMPLEMENTASI SISTEM INTERNET OF THINGS (IOT) UNTUK PEMANTAUAN WET BULB GLOBE TEMPERATURE (WBGT) REAL-TIME DENGAN NOTIFIKASI WHATSAPP PADA PEKERJA SAWIT DI LAPANGAN Wahyudi, aris; Wiyanto, Suko; Hairani, Hairani
Jurnal Elkasista Vol 6 No 1 (2025): Jurnal Elkasista
Publisher : Pustaka Poltekad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54317/elka.v6i1.626

Abstract

Suhu tinggi dapat membahayakan kesehatan, terutama bagi orang yang bekerja di luar ruangan. Temperatur Bulb Globe Wet (WBGT) digunakan untuk mengevaluasi potensi panas. Sistem Internet of Things (IoT) yang memantau WBGT secara real-time dapat menggunakan WhatsApp untuk mengirimkan pemberitahuan otomatis. Mikrokontroler menggunakan sensor suhu dan kelembapan untuk memproses data, yang kemudian dikirim ke aplikasi yang terhubung ke API WhatsApp untuk disampaikan kepada manajer atau petugas kesehatan. Dengan mengatur ulang aktivitas pekerja atau memberi waktu istirahat, sistem ini memungkinkan respons cepat terhadap bahaya panas. Dengan menggunakan WhatsApp sebagai alat komunikasi, karyawan dan pihak terkait dapat meningkatkan kewaspadaan terhadap cuaca ekstrem. Diharapkan sistem ini akan membantu memantau kondisi lingkungan dan mencegah gangguan kesehatan akibat suhu ekstrem, menciptakan tempat kerja yang lebih aman.
Classification of Learning Styles of Junior High School Students Using Random Forest & XGBoost Algorithm Christine Eirene; Dian Syafitri; Neny Sulistianingsih; Khasnur Hidjah; Hairani Hairani
Jurnal Bumigora Information Technology (BITe) Vol. 7 No. 1 (2025)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v7i1.4913

Abstract

  Background: Accurately identifying students' learning styles so that educators can adjust their teaching methods accordingly is a challenge in the field of education. However, the application of Machine Learning for learning style classification has not yet been implemented in schools in Mataram City. Objective: This study aims to classify the learning styles of students at Junior high school (SMP) Negeri 2 Mataram using Random Forest and XGBoost algorithms.  Method: Data were collected through questionnaires completed by students in grades 7, 8, and 9. The results of data exploration (EDA) show data imbalance in the collected classes. Result: These results indicate that both algorithms performed well in classifying learning styles, with XGBoost showing slightly better performance. However, the accuracy obtained is not yet optimal, likely due to the limited dataset size. To address data imbalance, the SMOTE technique was applied. Initial evaluation showed that both XGBoost and Random Forest achieved an accuracy of 80%. After Hyperparameter Tuning, the accuracy of XGBoost increased to 84%, while Random Forest reached 82%. Conclusion: This study contributes to the application of Machine Learning in the education sector and highlights the need for further research to enhance model performance.  
STRATEGI GURU DALAM MENERAPKAN PEMBELAJARAN INOVATIF DI KELAS Nurvianti, Nurvianti; Hairani, Hairani; Hanifah, Umi
Jurnal Literasiologi Vol 13 No 2 (2025): Jurnal Literasiologi
Publisher : Yayasan Literasi Kita Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47783/literasiologi.v13i2.895

Abstract

Era digital telah membawa perubahan signifikan dalam dunia pendidikan, menuntut penerapan strategi pembelajaran inovatif untuk meningkatkan kualitas pembelajaran di kelas. Guru memiliki peran penting dalam menciptakan lingkungan belajar yang menarik, interaktif, dan sesuai dengan kebutuhan siswa di abad ke-21. Penelitian ini menggunakan pendekatan kualitatif dengan metode deskriptif untuk menganalisis strategi guru dalam menerapkan pembelajaran inovatif serta tantangan yang dihadapi. Hasil penelitian menunjukkan bahwa pendekatan berbasis teknologi, pembelajaran berbasis proyek, dan model pembelajaran kolaboratif menjadi strategi utama dalam pembelajaran inovatif. Namun, terdapat berbagai tantangan dalam implementasinya, termasuk keterbatasan infrastruktur, kurangnya keterampilan guru dalam memanfaatkan teknologi, dan resistensi terhadap perubahan. Untuk mengatasi tantangan ini, diperlukan pelatihan guru yang berkelanjutan, optimalisasi sumber daya sekolah, serta dukungan dari stakeholder pendidikan. Dengan strategi yang tepat, pembelajaran inovatif dapat meningkatkan keterlibatan siswa, mendorong kreativitas, serta mengembangkan keterampilan berpikir kritis dan kolaboratif
Feature Extraction in Eye Images Using Convolutional Neural Network to Determine Cataract Disease Fitra Rizki Ramdhani; Khasnur Hidjah; Muhammad Zulfikri; Hairani Hairani; Mayadi Mayadi; Ni Gusti ayu Dasriani; Juvinal Ximenes Guterres
International Journal of Engineering and Computer Science Applications (IJECSA) Vol. 4 No. 2 (2025): September 2025
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v4i2.5064

Abstract

The eye is one of the vital human senses and serves as the main organ for vision. One of the visual impairments that requires special attention is blindness, and cataracts are a major cause of it. A cataract is a condition in which the eye’s lens becomes cloudy due to changes in the lens fibers or materials inside the capsule. This cloudiness blocks light from entering the eye and reaching the retina, significantly interfering with vision. Early detection of cataracts is essential to prevent blindness. An efficient image-based classification model is needed for cataract detection. This study aims to test the Convolutional Neural Network (CNN) model for early cataract detection by exploring the use of several optimization algorithms: Adaptive Moment Estimation (Adam), Root Mean Square Propagation (RMSprop), Adaptive Gradient Algorithm (AdaGrad), and Stochastic Gradient Descent (SGD). The research method follows an experimental approach, where eye image datasets are trained using the same CNN architecture but with different parameter configurations. The results show that the Adam optimizer, with a data split of 70% for training, 15% for validation, and 15% for testing over 50 epochs, produced the best results, achieving accuracies of 94%, 93%, and 93%, respectively. Other optimizers performed reasonably well but could not match Adam's stability and accuracy. The implication of this research is that the choice of optimizer and hyperparameter configuration plays a crucial role in improving the performance of image-based cataract detection models.
Optimizing Sentiment Analysis for Lombok Tourism Using SMOTE and Chi-Square with Machine Learning Hairani; Anggrawan, Anthony; Muhammad Ridho Akbar; Khasnur Hidjah; Muhammad Innuddin
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 4 (2025): August 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i4.6623

Abstract

Tourism is a vital economic sector for Lombok Island, which is renowned for its natural beauty and cultural richness as a top destination. The rapid growth of tourism in Lombok requires a deep understanding of tourists' perceptions and sentiments to ensure an optimal service quality. The sentiment analysis of online reviews is valuable for identifying service strengths and weaknesses and addressing tourists' needs more effectively. This not only enhances tourist satisfaction, but also aids in the design of more effective marketing strategies. However, text data analysis from online reviews presents unique challenges such as noise, class imbalance, and numerous features that may affect classification results. Therefore, this study aims to classify tourist sentiment toward Lombok tourism using machine learning methods combined with feature selection and oversampling techniques. This study focuses on optimizing sentiment analysis of tourism-related tweets using a combination of SMOTE oversampling and Chi-Square feature selection on improving classification performance without hyperparameter tuning. The study applies machine learning methods, such as SVM and Naïve Bayes, with feature selection and oversampling using Chi-Square and SMOTE. The dataset used was sentiment data regarding Lombok tourism obtained from Twitter in 2023, consisting of 940 instances divided into three classes: Negative, Neutral, and Positive. The research findings show that the use of SMOTE and Chi-Square can improve the accuracy of the SVM and Naive Bayes methods. Without optimization, the SVM method achieved an accuracy of 73.93% and a Naive Bayes of 67.02%. After optimization with SMOTE and Chi-Square, the accuracy increased for SVM by 90% and Naive Bayes by 84% to classify tourist sentiment towards Lombok tourism. The implications indicate that combining data balancing using SMOTE with feature selection via Chi-Square effectively improves the performance of sentiment classification models for tourist opinions on Lombok's tourism.
Analisis Kinerja BAZNAS Kota Medan Menggunakan Maqashid Syariah Index (MSI) dalam Meningkatkan Transparansi dan Akuntabilitas Keuangan Berbasis Digital Hairani, Hairani; Syahbudi, Muhammad; Nurbaiti, Nurbaiti
Journal of Economics and Management Scienties Volume 7 No. 4, September 2025
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jems.v7i4.178

Abstract

Penelitian ini bertujuan untuk menilai kinerja pengelolaan zakat di BAZNAS Kota Medan berdasarkan Indeks Maqashid Syariah (MSI) selama periode 2020 hingga 2023. BAZNAS Kota Medan merupakan lembaga pemerintah non-struktural yang bertugas mengelola Zakat, Infak, Sedekah, dan Dana Sosial Keagamaan Lainnya (ZIS-DSKL) secara profesional, terukur, dan berbasis digital. Dalam konteks pengelolaan zakat, penerapan Maqashid Syariah menjadi penting untuk memastikan bahwa pengelolaan dana tidak hanya sah secara syar’i, tetapi juga membawa maslahat yang nyata bagi masyarakat. Metode yang digunakan adalah pendekatan kualitatif dengan analisis deskriptif, melalui modifikasi indikator MSI yang disesuaikan dengan konteks lembaga pengelola zakat, menggunakan data sekunder dari laporan keuangan BAZNAS Kota Medan tahun 2020 sampai 2023. Hasil penelitian menunjukkan peningkatan skor MSI dari 0,631 pada tahun 2020 menjadi 1,013 pada tahun 2023, yang mencerminkan perbaikan dalam kelembagaan dan kesesuaian pengelolaan zakat dengan prinsip-prinsip Maqashid syariah. Meskipun demikian, masih terdapat tantangan dalam aspek penelitian, Iqamatu Al-Adl, dan investasi jangka panjang. Penelitian ini menegaskan pentingnya penguatan sistem transparansi digital dan inovasi teknologi untuk meningkatkan efektivitas dan keberlanjutan pengelolaan zakat di masa depan.
Co-Authors Abdillah, Mokhammad Nurkholis Abdurraghib Segaf Suweleh Abdurraghib Segaf Suweleh Abu Tholib Adam, M. Awaludin Afrig Aminuddin Ahmad Ahmad Ahmad Fathoni Ahmad Zuli Amrullah Amelia, Bengi Amin, Farda Milanda Andi Sofyan Anas Andi, Moh syaiful Anggarawan, Anthony Anthony Anggrawan Arfa, Muhammad Ashadi, Diki Astuti, Ni Luh Budi Ayu Dasriani, Ni Gusti Candra, M. Ade Christine Eirene Christopher Michael Lauw Dadang Priyanto Dedi Aprianto Dedy Febry Rachman Dedy Febry Rahman Deny Jollyta Dian Syafitri Didik Dwi Prasetya Diki Ashadi Dirgantara, Bhintang Donny Kurniawan Dyah Susilowati Dyah Susilowaty Edddy, Syaiful Eka Setiawan, Rian Putra Fahry, Fahry Fatimatuzzahra Fatimatuzzahra Fitra Rizki Ramdhani Gibran Satya Nugraha Gibran Satya Nugraha Gumangsari, Ni Made Gita Gustiya, Sherly Dwi Guterres, Juvinal Ximenes Hadi, M Fawazi Hammad, Rifqi Hartono Wijaya Haryono Haryono Hasbullah Hasbullah Heru Kurnianto Tjahjono Hery Widijanto Hidayati, Diana Huda, Dias Nabila I Gusti Agung Ayu Hari Triandini I Nyoman Switrayana Ida Putu Andika Ifnaldi, Ifnaldi Ilham Saifuddin Indah Puji Lestari Indradewa, Rhian Isviyanti, Isviyanti Janhasmadja, Mengas Jauhari, M. Thonthowi Jupriadi, Jupriadi Juvinal Ximenes Guterres Juvinal Ximenes Guterres Juvinal Ximenes Guterres Kandisa, Amelia Kasiyanto Kasiyanto, Kasiyanto Khairan marzuki Khasnur Hidjah Khurniawan Eko Saputro Kurniadin Abd Latif Kurniawan Kurniawan Lalu Ganda Rady Putra Lilik Nurhayati lnnuddin, Muhammad M. Ade Candra M. Rasyid Ridho Maariful Huda, Muhammad Malika, Riwayati Mardedi, Lalu Zazuli Azhar Mardedi, Lalu Zazuli Azhar Mayadi Mayadi Mayadi Mayadi Mayadi, Mayadi Mayasari, Astri Michael Lauw, Christopher Miftahul Madani Muhamad Azwar Muhamad Azwar, Muhamad Muhammad Arfa Muhammad Innuddin Muhammad Maariful Huda Muhammad Ridho Akbar Muhammad Ridho Hansyah muhammad Syahbudi, muhammad Muhammad Zulfikri Muhammad Zulfikri Muhammad Zulkarnaen Haris Mujahid Mujahid Neny Sulistianingsih Noor Akhmad Setiawan Nurhayati, Lilik Nurul Azmi Nurvianti, Nurvianti Nuzululnisa, Bq Nadila Pahrul Irfan Putu Tisna Putra Qososyi, Sayidina Ahmadal Rahmawati, Lela Ramadhanti Ramadhanti Ramadhanti, Ramadhanti Rifqi Hammad Riosatria, Riosatria Riwayati Malika RR. Ella Evrita Hestiandari Saifuddin Zuhri Saifuddin, Ilham Samsul Hadi Santoso, Heroe Shudiq, Wali Ja'far Soepriyanto, Harry Sofiansyah Fadli Sri Winarni Sofya Sri Winarni Sofya Sudi Prayitno Sukron, Moh Sutarman Sutarman Syahrir, Moch. tadianta m., Winardi aries Teguh Bharata Adji Tri Widayatsih, Tri Triwijoyo, Bambang Krismono Triyanna Widiyaningtyas Umi Hanifah Vidiasari, Herlita Vidiasari, Viviana Herlita Wahyuningsih, Rr. Sri Handari Widiatmoko, Dekki Winarni Sofya, Sri Wira Hendri Wiyanto, Suko Ximenes Guterres, Juvinal Yuri Ariyanto Zilullah Nazir Hadi