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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 SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan 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 Jurnal Ilmiah Pendidikan Dasar (JIPDAS) Journal of Engineering, Technology and Computing (JETCom) Jurnal: International Journal of Engineering and Computer Science Applications (IJECSA) Journal of Management, Economic and Accounting (JMEA) Insand Comtech : Information Science and Computer Technology Journal International Journal of Engineering Continuity 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 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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Pelatihan Implementasi Machine Learning pada Bidang Pendidikan Hairani Hairani
ADMA : Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol 2 No 2 (2022)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/adma.v2i2.3046

Abstract

Machine learning is a machine that can learn like humans. Machine learning (ML) technology was developed so that machines can learn by themselves without direction from the user. Machine learning consists of various disciplines such as statistics, mathematics and data mining so that machines can learn by analyzing data patterns without the need to be explicitly reprogrammed. Making machine learning applications is not easy because you have to have good understanding of methods and programming skills. Therefore, this service uses a solution to improve the abilities of the participants, namely a training approach by presenting material and demonstrating the use of machine learning in midwifery education. The activity was carried out on April 21 2021 online via the Zoom Meeting application with student participants. Based on the results of the material presentation session and hands-on practice using the Python programming language at Google Colab, it showed that the participants looked enthusiastic in following the material. Not only that, the participants know various machine learning methods and can apply them in completing a case study and building web applications with Flask tools.
SOSIALISASI INTERNET SEHAT, CERDAS, KREATIF DAN PRODUKTIF PADA MASYARAKAT KALIJAGA BARU Hairani Hairani; Muhammad Innuddin; Dedy Febry Rachman; Ahmad Fathoni; Samsul Hadi
Valid Jurnal Pengabdian Vol. 1 No. 3 (2023)
Publisher : Lembaga Pengembangan, Penelitian dan Pengabdian Kepada Masyarakat Sekolah Tinggi Ilmu Ekonomi AMM

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Metode penelitian ini adalah metode deskriptif kualitatif. Teknik yang digunakan dalam pengumpulan data adalah teknik observasi, teknik wawancara, dan dokumentasi. Hasil penelitian ini menemukan dua masalah, antara lain belum memahami cara menggunakan dan memanfaatkan teknologi internet dengan baik dan benar. Kesimpulan dari penelitian ini adalah penggunaan dan pemanfaatan teknologi secara tepat, menimbulkan dampak positif dan mengurangi dampak negatif. Dengan mengetahui cara memanfaatkan teknologi internet secara baik dan benar akan mampu menjadikan masyarakat cerdas, kreatif, dan produktif. Tujuan cerdas, kreatif, dan produktif adalah agar masyarakat dapat mengembangkan dan menerapkan apa yang telah diperoleh dalam teknologi internet, yang diterapkan dalam kehidupan sehari-hari.
Combination of Smote and Random Forest Methods for Lung Cancer Classification Christopher Michael Lauw; Hairani Hairani; Ilham Saifuddin; Juvinal Ximenes Guterres; Muhammad Maariful Huda; Mayadi Mayadi
International Journal of Engineering and Computer Science Applications (IJECSA) Vol 2 No 2 (2023): September 2023
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v2i2.3333

Abstract

Lung cancer is a network of cells that grow abnormally in the lungs. Lung cancer has four severity levels, namely stages 1 to 4. If lung cancer is not treated quickly, it is at risk of causing death. This research aimed to combine Synthetic Minority Over-sampling (Smote) and Random Forest methods for lung cancer classification. The method used was a combination of Smote and Random Forest. Smote was used to balance the data, while Random Forest was used to classify lung cancer data. The results showed that the combination of Smote and Random Forest methods obtained an accuracy of 94.1%, sensitivity of 94.5, and specificity of 93.7%. Meanwhile, without Smote, the accuracy is 89.1%, sensitivity is 55%, and specificity is 94.5%. The use of Smote can improve the performance of the Random Forest classification method based on accuracy and sensitivity. There was an increase of 5% in accuracy and a 39% increase in sensitivity.
Sentiment Analysis and Topic Modeling of Kitabisa Applications using Support Vector Machine (SVM) and Smote-Tomek Links Methods I Nyoman Switrayana; Diki Ashadi; Hairani Hairani; Afrig Aminuddin
International Journal of Engineering and Computer Science Applications (IJECSA) Vol 2 No 2 (2023): September 2023
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v2i2.3406

Abstract

Kitabisa is an Indonesian application that functions to raise funds online. Users can easily support various types of campaigns and donate funds to various social causes through the app. User reviews of the application are very diverse, and it is not sure whether user reviews of the application tend to be positive, neutral, or negative. This research aimed to analyze the sentiment of the Kitabisa application by modeling topics using Latent Dirichlet Allocation (LDA) and classifying user reviews using a Support Vector Machine (SVM). The scrapped dataset showed imbalanced dataset problems, so the SMOTE-Tomek Links oversampling technique was proposed. The results of this study show that using LDA produces five topics often discussed in 750 reviews. Then, the performance of SVM without using SMOTE-Tomek Links was 72% accuracy, 76% precision, 72% recall, and 64% f1 score. Meanwhile, using SMOTE-Tomek Links could significantly improve the performance, namely 98% accuracy, 98% precision, 98% recall, and 98% f1 score. Based on this research, the application of SVM achieved high performance for user sentiment classification, especially when the dataset was in a balanced state. Therefore, the SMOTE-Tomek Links oversampling technique is recommended for dealing with unbalanced sentiment datasets.
Implementation of Certainty Factor Method for Identification of Pest Types on Dendrobium Based on Expert Systems Muhammad Innuddin; Hairani Hairani; Ida Putu Andika
Sistemasi: Jurnal Sistem Informasi Vol 12, No 2 (2023): 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.v12i2.2469

Abstract

Orchid is an ornamental plant that has high aesthetic value with a variety of attractive colors on its flowers and has high economic value. One of the problems in the cultivation of orchids is the problem of pests that can inhibit growth and reduce the aesthetics of orchid plants. Not only that, the shortage of orchid plant experts can be a trigger for delays in identifying the types of pests on orchids, resulting in poor growth quality and even crop failure. Early identification is needed so that handling is fast so that the quality of growth is good. The solution offered by this research is the implementation of the certainty factor method for identifying web-based types of pests on dendrobium orchids. The stages of this research consist of knowledge acquisition, knowledge modeling, implementation, and accuracy testing. Based on the test results of 32 data, the certainty factor method can identify exactly 29 data and the rest are identified incorrectly, resulting in an accuracy of 90.6%. Thus, the certainty factor method can be used to identify the type of pest on orchids because it has very good accuracy.
Exploring Customer Purchasing Patterns: A Study Utilizing FP-Growth Algorithm on Supermarket Transaction Data Hairani Hairani; Juvinal Ximenes Guterres
International Journal of Engineering and Computer Science Applications (IJECSA) Vol 3 No 1 (2024): March 2024
Publisher : Universitas Bumigora Mataram-Lombok

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/ijecsa.v3i1.3874

Abstract

The need to analyze consumer purchasing patterns using association techniques also lies in the increasingly fierce competition in the retail market. Supermarkets face the challenge of understanding their customers' buying patterns. By utilizing association techniques, supermarkets can identify customer buying trends and quickly and appropriately adjust their strategies. Thus, analyzing consumer purchasing patterns using association techniques is no longer an option but an urgent need for supermarkets that want to survive and thrive in a changing market. Therefore, this study aimed to analyze purchasing patterns in supermarkets using the FP-Growth method to understand purchasing behavior and identify relevant patterns from transaction data. The method used in this research was the FP-Growth association method to create association rules from customer transaction data. The findings of this research were the use of the FP-Growth method in analyzing supermarket customer purchasing patterns, which obtained 10 association rules for 2 itemsets and 11 association rules for 3 itemsets based on a minimum Support value of 30% and a minimum Confidence of 70%. The association rules generated by the FP-Growth method on 2 itemsets and 3 itemsets simultaneously bring up items often purchased by customers with the same pattern, namely Cooking Oil, Eggs, Flour, and Candy. This research concludes that the association rules formed can be used as a benchmark by supermarkets in preparing stock items and making strategies to increase sales for more profit.
Augmented Rice Plant Disease Detection with Convolutional Neural Networks Hairani, Hairani; Widiyaningtyas, Triyanna
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 8 No 1 (2024): February 2024
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v8i1.21168

Abstract

The recognition and classification of rice plant diseases require an accurate system to generate classification data. Types of rice diseases can be identified in several ways, one of which is leaf characterization. One method that has high accuracy in identifying plant disease types is Convolutional Neural Networks (CNN). However, the rice disease data used has unbalanced data which affects the performance of the method. Therefore, the purpose of this research was to apply data augmentation to handle unbalanced rice disease data to improve the performance of the Convolutional Neural Network (CNN) method for rice disease type detection based on leaf images. The method used in this research is the CNN method for detecting rice disease types based on leaf images. The result of this research was the CNN method with 100 epochs able to produce an accuracy of 99.7% in detecting rice diseases based on leaf images with a division of 80% training data (2438 data) and 20% testing data (608 data). The conclusion is that the CNN method with the augmentation process can be used in rice disease detection because it has very high accuracy.
Mediation Role of Affective Commitments The Effect Of Organizational Justice on Innovativeo Behavior : Survey at SMK 01 Muhammadiyah Yogyakarta Hairani, Hairani; Tjahjono, Heru Kurnianto; Wahyuningsih, Rr. Sri Handari
Jurnal Manajemen Bisnis Vol. 10 No. 2 (2023): September
Publisher : Pusat Penerbitan dan Publikasi Ilmiah, FEB, Universitas Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33096/jmb.v10i1.493

Abstract

This study examines the effect of distributive justice, procedural justice, and interactional justice on affective commitment and innovative behavior. The sample of this study was 127 teachers of SMK 01 Muhammadiyah Yogyakarta. The research method uses the SEM method and uses the AMOS IBM SPSS analysis tool. The results showed that distributive justice, procedural justice and interactional justice had a positive effect on innovative behavior either directly or through the mediation of affective commitment variables. A high level of distributive justice, procedural justice, and interactional justice will increase the innovative behavior of teachers. However, the effect of distributive justice, procedural justice, and interactional justice on innovative behavior will be higher through affective commitment variables
Meningkatkan Kesadaran Masyarakat Terhadap Lingkungan Melalui Kegiatan Trash Festival And Art Exhibition Arfa, Muhammad; Haryono, Haryono; Hairani, Hairani; Fatimatuzzahra, Fatimatuzzahra; Madani, Miftahul; lnnuddin, Muhammad
ADMA : Jurnal Pengabdian dan Pemberdayaan Masyarakat Vol 3 No 2 (2023): ADMA: Jurnal Pengabdian dan Pemberdayaan Masyarakat
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/adma.v3i2.2596

Abstract

The purpose of this research is to respond to the impact of waste on the environment through art festivals and exhibitions, workshops, music festivals and photography competitions. The results of the activity were very effective in inviting all parties to jointly protect the environment from waste and increasing public awareness to dispose of waste in its place, collaboration between the government and the Zero Waste program and several waste bank communities and the VIBE community. very effective every year as a form of shared responsibility to reduce waste accumulation in West Nusa Tenggara.
Pola Pikir & Kebiasaan Ibu Hamil dalam Mengkonsumsi Obat Herbal selama Pandemi Covid-19 di Lingkungan Karang Pule Triandini, I Gusti Agung Ayu Hari; Hairani, Hairani
Jurnal Ilmiah Kebidanan Indonesia Vol 12 No 02 (2022): Jurnal Ilmiah Kebidanan Indonesia (Indonesian Midwifery Scientific Journal) Uni
Publisher : Q PRESS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33221/jiki.v12i02.1478

Abstract

Herbal traditional medicine is a plant that has medicinal properties and has been clinically proven or based on the experience of previous people. In Asian countries, 80% of the population uses traditional medicine as an alternative to health. In Indonesia there are many people who consume herbal medicines such as herbs, around 61.87% women and 33.3% of them are pregnant women. The pregnant women are one of the special groups that are high risk to the COVID-19. The purpose of this study was to determine the level of knowledge and behavior of pregnant women about the consumption of herbal medicines during pregnancy during the COVID-19 pandemic in the Karang Pule environment in 2021. This type of research was a descriptive study. The research design used was a cross sectional method with data collection techniques, namely in-depth interviews, and distributing questionnaires. From the results of the study, it was found that the level of knowledge of respondents about consuming herbal medicines during pregnancy was in the sufficient category (50%), and the behavior of respondents in consuming herbal medicines during pregnancy was also in the sufficient category (66.7%).
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