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Hairani Hairani
Universitas Bumigora, Mataram, Indonesia
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture 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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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.
Sosialisasi Peran Penggunaan Management Learning System sebagai Platform Pembelajaran Daring untuk Mendukung Pembelajaran Mandiri Aprianto, Dedi; Mardedi, Lalu Zazuli Azhar; Sutarman, Sutarman; Hendri, Wira; Hairani, Hairani; Innuddin, Muhammad; Rahmawati, Lela
ADMA : Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol. 5 No. 2 (2025): ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/adma.v5i2.4569

Abstract

keterbatasan kesadaran mahasiswa tentang optimalisasi penggunaan MLS sebagai media yang dapat menunjang belajar mandiri meskipun telah diterapkan sebagai media belajar komplementer, tetapi belum sepenuhnya efektif. Sehingga hal ini mengurangi potensi maksimal dalam mendukung proses belajar mereka. Kegiatan Pengabdian kepada Masyarakat (PkM) ini bertujuan untuk meningkatkan pemahaman dan kesadaran mahasiswa mengenai penggunaan Management Learning System (MLS) dalam mendukung pembelajaran mandiri. Isu yang diangkat adalah rendahnya kesadaran mahasiswa tentang MLS, yang berdampak pada efektivitas pembelajaran daring guna meningkatkan pembelajaran mandiri. Untuk mencapai tujuan tersebut, metode yang digunakan, yaitu sosialisasi; ceramah, diskusi, tanya-jawab, dan demonstrasi langsung. Kegiatan ini terdiri dari tiga tahapan: persiapan, pelaksanaan, dan evaluasi. Hasil kegiatan PkM ini menunjukkan bahwa bahwa (85%) peserta merasa lebih memahami cara menggunakan MLS setelah pelatihan, dan (78%) merasa siap untuk menerapkan MLS dalam pembelajaran mandiri. Selain itu, (90%) peserta menyatakan bahwa kegiatan ini bermanfaat bagi mereka. Kesimpulan kegiatann ini menunjukkan keberhasilan dalam memperkuat pemahaman mahasiswa tentang penggunaan MLS, sekaligus mendukung peningkatan pembelajaran mandiri dalam konteks pembelajaran daring.
A DESAIN SMART ARMY ROBOT SEBAGAI MEDIA PEMANTAU DAN NEGOSIASI BERBASIS ARTIFICIAL INTELLIGENCE: DESAIN SMART ARMY ROBOT SEBAGAI MEDIA PEMANTAU tadianta m., Winardi aries; Widiatmoko, Dekki; Hairani, Hairani
Jurnal Elkasista Vol 5 No 2 (2024): Jurnal Elkasista
Publisher : Pustaka Poltekad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54317/elka.v5i2.521

Abstract

One of the most critical components of hostage rescue efforts is the agreement on hostage release. Officer errors in taking action during the negotiation process can jeopardize the safety of personnel and officers as well as hostage victims. Lack of communication often leads to dangerous conflicts that can hamper hostage taking. To solve this problem, we designed a specialized negotiation robot that is armed to ensure the safety and security of officers in the line of duty, both in war situations and hostage release operations. By having weapons, officers responsible for the safety of victims can perform their duties without compromising their personal security. These military robots enable negotiation and monitoring without threatening lives, providing a more efficient and safe approach. In addition, the robot's ability to operate autonomously with the help of artificial intelligence allows for faster assessment of the situation and a more appropriate response, thereby increasing the chances of a successful rescue mission without adding risk to the humans involved. The robot is also equipped with advanced sensors and machine learning algorithms that can detect changes in the hostage-taker's behavior and body language, providing valuable information to the negotiation team to devise a more effective strategy. Thus, the implementation of this technology not only improves the security and efficiency of military operations, but also paves the way for further innovations in the use of robotics and Artificial Intelligence in various aspects of defense and security.
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 5 No 2 (2024): Jurnal Elkasista
Publisher : Pustaka Poltekad

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54317/elka.v5i2.522

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 bertujuanagar 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.
Improving Classification Performance on Imbalanced Stroke Datasets Using Oversampling Techniques Innuddin, Muhammad; Hairani; Jauhari, M. Thonthowi; Mardedi, Lalu Zazuli Azhar
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 5 (2025): October 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i5.6859

Abstract

Stroke is the second leading cause of death worldwide and a major factor in long-term disability. Although early detection based on machine learning continues to be developed, it still faces challenges in the form of data imbalance, which can reduce classification performance. This study aimed to evaluate the effectiveness of several oversampling techniques, such as SMOTE, Borderline-SMOTE, and SVM-SMOTE, in improving the performance of stroke classification models on imbalanced data. The methods used included the application of three oversampling techniques, namely SMOTE, Borderline-SMOTE, and SVM-SMOTE, to balance the data distribution. Furthermore, Random Forest and XGBoost algorithms were used as classification models to identify stroke cases. The results of this study show that the use of oversampling techniques significantly improves model performance, especially in MCC and AUC metrics, compared to models without oversampling. Borderline-SMOTE provides the best results, with the highest accuracy of 96.45% on Random Forest and 96.41% on XGBoost, as well as MCC and AUC values that are consistently superior to other techniques. Furthermore, this study highlights that the use of Borderline-SMOTE significantly enhances model performance, as evidenced by an increase in MCC of 87.51% and an AUC of 45.40% in Random Forest, along with an increase in MCC of 76.52% and an AUC of 41.81% in XGBoost. These findings confirm that Borderline-SMOTE is an effective approach for dealing with data imbalance and improving the model's ability to detect minority classes in stroke classification.
SMOTE Variants and Random Forest Method: A Comprehensive Approach to Breast Cancer Classification Baiq Candra Herawati; Hairani Hairani; Juvinal Ximenes Guterres
International Journal of Engineering Continuity Vol. 3 No. 1 (2024): ijec
Publisher : Sultan Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58291/ijec.v3i1.147

Abstract

This research focused on using machine learning methods for breast cancer diagnosis, considering that breast cancer is the scariest disease for women because it can cause mortality. Not only that, but there is also an increase in breast cancer death rates in women yearly.  Early prediction is the right solution to increase life expectancy and reduce mortality rates caused by breast cancer. However, breast cancer data has a problem, namely that the data is imbalanced, which harms the performance of the machine learning method itself. In the data, breast cancer had a Benign class (357 instances) more than the Malignant class (212 instances). Therefore, this study aimed to solve the problem of imbalanced data using the Smote variants and Random Forest approaches in breast cancer classification. The results of this study showed that the Smote approach with Random Forest had the best performance compared to Borderline Smote and Random Forest in the case of breast cancer data classification, where Smote with Random Forest produced an accuracy of 97.3%, sensitivity of 96.9%, and specificity of 97.8%. In comparison, Borderline Smote with Random Forest produced an accuracy of 96.4%, sensitivity of 95.6%, and specificity of 96.9%. The results of this study can contribute to predicting breast cancer using the proposed method, because it has been proven to have high accuracy.
Edukasi Seksual & Konseling Remaja untuk Pencegahan Pernikahan Dini di Klinik Bumi Sehat Desa Batu Mekar Kabupaten Lombok Barat Isviyanti, Isviyanti; Triandini, I Gusti Agung Ayu Hari; Hairani, Hairani; Gumangsari, Ni Made Gita; Hidayati, Diana; Kandisa, Amelia; Mayasari, Astri; Gustiya, Sherly Dwi; Astuti, Ni Luh Budi
Jurnal Pengabdian UNDIKMA Vol. 6 No. 1 (2025): February
Publisher : LPPM Universitas Pendidikan Mandalika (UNDIKMA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/jpu.v6i1.13990

Abstract

This community service activity aims to provide sexual education and prevent early marriage to teenagers using a holistic psychological counseling and parenting approach, from a legal, social, and midwifery perspective. The method of implementing this service used counseling and mentoring on sexual and reproductive health education using a question-and-answer design. The targets of this activity were teenagers from Batu Mekar Village, West Lombok Regency who were still of school age using a questionnaire instrument which was then statistically analyzed using the t test. The results of this service showed that teenagers were aware of the impact of early marriage and understood anemia, and sexual reproductive health about the incidence of early marriage and stunting. By implementing this community service program, a youth posyandu/youth class was successfully established at the Bumi Sehat Clinic. This is useful in providing a forum for teenagers to discuss and consult regarding sexual, physical, and mental reproductive health issues as well as positive activities to prevent early marriage.
Sistem Pakar Diagnosa Penyakit THT Menggunakan Inferensi Forward Chaining dan Metode Certainty Factor Dirgantara, Bhintang; Hairani, Hairani
Jurnal Bumigora Information Technology (BITe) Vol. 3 No. 1 (2021)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v3i1.1241

Abstract

Currently, Ear, Nose, and Throat (ENT) has become a disease that is quite common in the world. In Indonesia, people with ENT disease are around 190-230 per 1000 population. The types of diseases studied in this study were Serous Orthitis Media, Nasal Polyps, Acute Pharyngitis, Retrofaryngeal Abscess, and Nafosaryngeal Carcinoma. The purpose of this study was to make an application of an expert system for the diagnosis of ENT diseases using forward chaining inference and certainty factors that can facilitate medical personnel to diagnose types of ENT diseases. The stages of developing an expert system in this study consisted of problem identification for problem domain, knowledge acquisition was used to obtain the MB and MD value of each symptom in ENT disease with the interview method, the design was used to design knowledge representations such as decision tables and inference engine. With the expert system of ENT disease diagnosis, it can make it easier for doctors to make decisions, or the right diagnosis of a symptom that arises in ENT, so that proper treatment is obtained and minimizes the occurrence of misdiagnoses
Peningkatan Kinerja Metode Random Forest Berbasis Smote-Tomek Link Pada Sentimen Analisis Pariwisata Lombok Marzuki, Khairan; Rady Putra, Lalu Ganda; Hairani, Hairani; Mardedi, Lalu Zazuli Azhar; Guterres, Juvinal Ximenes
Jurnal Bumigora Information Technology (BITe) Vol. 5 No. 2 (2023)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/bite.v5i2.3166

Abstract

Background: Tourists visiting Lombok Island can access various sources of tourist information and can share their views and tourist experiences through social media such as positive and negative experiences. Objective: This research aims to analyze the sentiment of Lombok tourism reviews using the Smote-Tomek Link and Random Forest algorithms.Methods: The research was carried out in several stages, namely collecting the Lombok tourism dataset, text preprocessing, text weighting using the Term Frequency-Inverse Document Frequency (TF-IDF) method, data sampling using SMOTE-Tomek Link, text classification using Random Forest, and the final stage was performance testing based on accuracy. Result: The research results obtained using the Smote-Tomek Link and Random Forest methods in sentiment analysis analysis of tourist reviews about Lombok were 94%. Conclusion: The use of the Smote-Tomek Link and Random Forest methods in Lombok tourism sentiment analysis produces very good accuracy.
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 Andini, Nisha 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 Gede Yogi Pratama Gibran Satya Nugraha Gibran Satya Nugraha Gumangsari, Ni Made Gita Guntara, Muhammad Gusti Ayu Diah Gita Kartika Santi, I Gustiya, Sherly Dwi Guterres, Juvinal Ximenes Hadi, M Fawazi Hammad, Rifqi Hartono Wijaya Haryono Haryono Hasbullah Hasbullah Herawati, Baiq Candra Heru Kurnianto Tjahjono Hery Widijanto Hidayati, Diana Huda, Dias Nabila Husnul Madihah, Husnul 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 Juvinal Ximenes Guterres Kandisa, Amelia Kasiyanto Kasiyanto, Kasiyanto Khairan marzuki Khairil Ihsan Khasnur Hidjah Khurniawan Eko Saputro Kurniadin Abd Latif Kurniawan Kurniawan Lalu Ganda Rady Putra Lalu Zazuli Azhar Mardedi Lilik Nurhayati lnnuddin, Muhammad M. Ade Candra M. Rasyid Ridho M.Khaerul Ihsan Maariful Huda, Muhammad Malika, Riwayati Mardedi, Lalu Zazuli Azhar Mardedi, Lalu Zazuli Azhar Mayadi Mayadi Mayadi Mayadi Mayadi, Mayadi Mayasari, Astri Melati Rosanensi 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 Rahman, Mochamad Farhan Caesar Rahmawati, Lela Rahmi, Agustina Ramadhanti Ramadhanti Ramadhanti, Ramadhanti Rifqi Hammad Riosatria, Riosatria Riwayati Malika Rizki Wahyudi 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 Wangiyana, I Gde Adi Suryawan Widiatmoko, Dekki Wira Hendri Wiyanto, Suko Ximenes Guterres, Juvinal Yuri Ariyanto Zilullah Nazir Hadi