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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Dedikasi IPTEK The Journal of Engineering Techno.Com: Jurnal Teknologi Informasi TEKNOLOGI: Jurnal Ilmiah Sistem Informasi TELKOMNIKA (Telecommunication Computing Electronics and Control) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika Journal of Information Systems Engineering and Business Intelligence Register: Jurnal Ilmiah Teknologi Sistem Informasi Proceeding of the Electrical Engineering Computer Science and Informatics JOIN (Jurnal Online Informatika) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control DoubleClick : Journal of Computer and Information Technology JAST : Jurnal Aplikasi Sains dan Teknologi KOMPUTIKA - Jurnal Sistem Komputer PEDULI: Jurnal Imiah Pengabdian Pada Masyarakat Dialektika: Jurnal Ekonomi dan Ilmu Sosial Jurnal Repositor Journal of Community Service and Empowerment Jurnal Riset Pendidikan MIPA ALACRITY : Journal Of Education Jurnal Perempuan & Anak Jurnal Sintesis: Penelitian Sains, Terapan dan Analisisnya
Nur Hayatin
Universitas Muhammdiyah Malang
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PENINGKATAN LITERASI UNTUK GURU DAN SISWA SEKOLAH DASAR MELALUI PELATIHAN PENGGUNAAN APLIKASI ENSIKLOPEDIA ANAK Nur Hayatin
Jurnal Perempuan dan Anak Vol. 2 No. 1 (2019): Februari
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (393.337 KB) | DOI: 10.22219/jpa.v2i1.8316

Abstract

Keterampilan literasi menjadi pilar penting untuk masa depan pendidikan. Untuk itu membangun budaya literasi digital perlu melibatkan peran aktif masyarakat secara bersama-sama khususnya di lingkungan sekolah. Kegiatan ini bertujuan untuk meningkatkan literasi guru dan siswa sekolah dasar. Metode yang digunakan dalam kegiatan ini adalah berupa pelatihan atau training. Pelatihan literasi ditujukan kepada perwakilan guru dan siswa-siswi SDN 2 Bandungrejosari Malang yang terdiri dari guru dan murid kelas 5 dan 6. Pelatihan yang diberikan terkait dengan pengelolaan Ensiklopedia Anak dilakukan untuk melatih keterampilan dan kecakapan pengguna, baik secara teknik maupun praktis. Dari hasil pengumpulan dan analisa data melalui kuesioner, diketahui bahwa aplikasi ensiklopedia anak dapat membantu fleksibilitas dan efisiensi kegiatan sehari-hari khususnya untuk guru dan siswa SD terutama untuk kegiatan yang terkait dengan pendidikan dan pembelajaran sekolah. Sehingga dapat disimpulkan bahwa melalui kegiatan pelatihan literasi yang melibatkan guru dan siswa di sekolah dasar telah terbukti bahwa ada pengaruh positif terhadap kesadaran literasi di lingkungan sekolah. Sehingga kedepan kegiatan serupa dapat ditularkan ke sekolah-sekolah yang lain dengan harapan dapat memperluas realisasi program Gerakan Literasi Nasional yang dicanangkan pemerintah melalui Kemendikbud.
Expert System to Identify Risk Factors of Toddler’s Nutrition Status with Case Based Reasoning Meilisa Musnaimah; Aini Alifatin; Nur Hayatin
Jurnal Perempuan dan Anak Vol. 3 No. 1 (2020): Februari
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (301.702 KB) | DOI: 10.22219/jpa.v3i1.11810

Abstract

In 2012, Indonesia was the 5th most malnourished country in the world. This rank is affected by the population of Indonesia which ranked fourth in the world. Toddler malnutrition is a hot issue in Indonesia, and it is the basis of programs that supported by goverment to remedies these problems. The number of malnourished children in Indonesia is currently around 900 thousand people. The amount is 4.5 percent of the number of Indonesian children, which is 23 million people. For this reason it is important to predict the nutritional status of children so that preventive measures can be taken to reduce the number of malnutrition status in children in Indonesia. This study aims to apply the Modified K-Nearest Neighboar (M-KNN) method to identify risk factors for toddler nutritional status. The data used in this study is a combination of two types of data sources (primary and secondary data), where the data is obtained from posyandu in Malang. This study uses anthropometric assessment variables for weight and age. The steps taken include: data input, determination of the value of k, calculating the value of validity and the value of weight voting. Furthermore, to measure the performance of the proposed method, measurement is carried out by calculating the accuracy value of the predicted results. From the results of testing with variations in the value of k obtained an accuracy value of 75% using 295 nutritional status data of toddlers, with neighbors k which is the best value of k = 4.
Contraception Recommendations With Analytical Hierarchy Process (AHP) and Weighted Product Methods (WP) Audi Bayu Yuliawan; Nur Hayatin; Yufis Azhar
Jurnal Perempuan dan Anak Vol. 4 No. 1 (2021): Februari
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (501.796 KB) | DOI: 10.22219/jpa.v1i1.16337

Abstract

Planning Program (KB) as one way to reduce the high rate of pregnancy. Contraceptives used in family planning programs have various types. In addition to the presence of contraception for women, contraception is also available for men. It's just that the problem at this time, lack of knowledge will choose contraception in accordance with health conditions. The limited time, place and expertise of experts to always provide information is one of the obstacles to getting complete information. Decision Support System is a knowledge-based computer information system that is used to support decision making in a problem. This system will later use the Analytical Hierarchy Process method, this method is a method that makes decision makers to get priority scale or consideration of experience, views, intuition and original data. Not only that this system will also use the Weighted Product (WP) method to maximize the performance of AHP in ranking the final results. This application is made using the Android programming language with Android Studio as the platform. In this application will later display recommendations for selecting contraceptives that are suitable for a patient.
Identification of Women's Quality of Life Home Business Actors with Influencing Factors Thathit Manon Andini; Dini Kurniawati; Aini Alifatin; Nur Hayatin
Jurnal Perempuan dan Anak Vol. 5 No. 1 (2022): Februari
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/jpa.v5i1.20266

Abstract

The basic problem in women's empowerment that has occurred so far is the low participation of women in development. In addition, there are still various forms of discriminatory practices against women. In the social context, there are still gaps in the roles of men and women (Education, Health and public participation involvement). Susenas data (National Socio-Economic Survey) 2003 shows that the education level of Indonesian women is still low. If there are physical, mental, or social health problems, it can reduce the value of quality of life. When women are busy in fulfilling the family's economy, will their physical, mental and social conditions become healthy? Will their quality of life be maintained when they become the foundation of the family's economy? What are their quality of life indicators? This study aims to determine their quality of life associated with various factors (Health, education, economy, etc.). In this study, the researcher chose to use qualitative methods or descriptive analysis to identify and describe the quality of life of women entrepreneurs at home and the factors that influence them. From the results of the study, it can be seen from the personal data, The women who do home-based businesses are still of productive age, with minimal high school education. Their efforts can generate sufficient income to meet their needs. It can be concluded that the quality of life of the women is good, as well as mental conditions (self-satisfaction, self-motivation). The dominant factors in influencing mothers to run their businesses are educational factors, self-confidence in running their business, self-satisfaction and also feeling healthy, feeling safe.
Analisis Sentimen Media Sosial Twiiter terhadap RUU Omnibus Law dengan Metode Naive Bayes dan Particle Swarm Optimization Syukri Adisakti Dainamang; Nur Hayatin; Didih Rizki Chandranegara
Komputika : Jurnal Sistem Komputer Vol 11 No 2 (2022): Komputika: Jurnal Sistem Komputer
Publisher : Computer Engineering Departement, Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/komputika.v11i2.6037

Abstract

Social media is the most popular platform by the Indonesian people, starting from Facebook, Instagram and Twitter. Twitter is one of the most widely used social media, both for interacting with other people or looking for information or news that is trending topics, quickly various news or information spreads on Twitter such as issues that are currently trending, namely the Omnibus Law. , various responses given by twitter users regarding this policy that has been approved by the government. In this study, to classify the sentiments of the Indonesian people regarding the issue of Omnibus Law using the method Naïve Bayes and Particle Swarm Optimization (PSO) and divided into two test scenarios, the use of theAlgorithm Particle Swarm Optimization on Naive Bayes aims to optimize the accuracy results. The results obtained when using Naive Bayes based on Particle Swarm Optimization (PSO) are better than Naive Bayes. The best accuracy results are in scenario three with split 90% - 10% data using Naïve Bayes to get 85% results and using Naïve Bayes based on Particle Swarm Optimization the accuracy results change to higher 4% get 91% results, the amount in doing the split data is very influential on the results of the classification carried out. The response from the public is in the form of negative sentiment towards the Omnibus Law Bill.
Improvisasi Algoritma Dijkstra Pada Peringkasan Teks Otomatis Untuk Artikel Politik Giffari Zakawaly; Nur Hayatin; Vinna Rahmayanti Setyaning Nastiti
Jurnal Repositor Vol 5 No 2 (2023): Mei 2023 (In Press)
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/repositor.v5i2.1437

Abstract

Tidak jarang kita menemukan suatu informasi atau artikel yang terlalu panjang. Dan untuk mengatasi masalah tersebut, salah satu cara yang bisa digunakan yaitu peringkasan teks. Metode peringkasan teks yang yang saat ini banyak dan biasa digunakan bisa dikelompokkan ke dalam tiga kategori, dan salah satunya yaitu metode berbasis graf. Dan algoritma Dijkstra memiliki tahapan yang paling sederhana. Improvisasi dilakukan dengan cara menambahkan 3 fitur pembobotan lain yaitu word freuency, position, dan resemblance to the title. Improvisasi yang dilakukan tidak terlalu berpengaruh terhadap ringkasan yang dihasilkan oleh sistem. Hal ini ditunjukkan dengan nilai evaluasi ROUGE-1 tanpa improvisasi 0.48487 dan dengan improvisasi 0.47513.
Deteksi Konten Hoax Pada Media Berita Indonesia Menggunakan Multinomial Naïve Bayes Fatahillah Arsyad; Nur Hayatin; Christian Sri Kusuma Aditya
Jurnal Repositor Vol 5 No 4 (2023): November 2022
Publisher : Universitas Muhammadiyah Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22219/repositor.v5i4.1539

Abstract

Hoax news is a problem that needs to be addressed in Indonesia. Launching a report from Kominfo (Ministry of Communication and Information) in 2020 alone there were 3464 hoax news detected. considering the large number, it will be very difficult to identify every news that is in Indonesia, not quickly let alone comprehensively. Therefore, it takes a tool or system that can detect the news that is spread, quickly and efficiently. With this purpose, this research was carried out, using the method used by Multinomial Naïve Bayes (MNB). In previous studies, there are still some shortcomings that can be covered by improvisation. To improvise in the classification of hoax news, the MNB method was chosen for this study. MNB itself is a type of Naïve Bayes which is often used for text analysis where data is represented in the form of a word frequency vector. as a comparison rival for MNB, Gaussian Naïve Bayes will also be brought in for this research. with a total of 994 news data sourced from turnbackhoax.id and as a comparison this study also uses data from previous research which amounted to 250 news. The results obtained by the GNB method reach 94% accuracy and the highest accuracy for the MNB method is 96% which shows MNB is better.
Optimization of Sentiment Analysis for Indonesian Presidential Election using Naïve Bayes and Particle Swarm Optimization Nur Hayatin; Gita Indah Marthasari; Lia Nuarini
JOIN (Jurnal Online Informatika) Vol 5 No 1 (2020)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v5i1.558

Abstract

Twitter can be used to analyze sentiment to get public opinion about public figures to find a trend in positive or negative responses, especially to analyze sentiments related to presidential candidates in the 2019 election in Indonesia. Naïve Bayes (NB) can be used to classify tweet feed into polarity class negative or positive, but it still has low accuracy. Therefore, this study optimizes the Naïve Bayes algorithm with Particle Swarm Optimization (NB-PSO) to classify opinions from twitter feeds to get a good accuracy of public figures sentiment analysis. PSO used to select features to find optimization values to improve the accuracy of Naïve Bayes. There are four steps to optimize NB using PSO, i.e., initializing the population (swarm), calculate the accuracy value that matched with selected features, selected the best accuracy of classification, and updating position and velocity. From this study, the group of tweets was obtained based on the positive and negative sentiments from the community towards two Indonesia presidential candidates in 2019. The NB-PSO test shows the accuracy result of 90.74%. The result of accuracy increases by 4.12% of the NB algorithm. In conclusion, the inclusion of the Particle Swarm Optimization algorithm for Naïve Bayes classification algorithm gives a significant accuracy, especially for sentiment analysis cases.
Optimization of Sentiment Analysis for Indonesian Presidential Election using Naïve Bayes and Particle Swarm Optimization Nur Hayatin; Gita Indah Marthasari; Lia Nuarini
JOIN (Jurnal Online Informatika) Vol 5 No 1 (2020)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v5i1.558

Abstract

Twitter can be used to analyze sentiment to get public opinion about public figures to find a trend in positive or negative responses, especially to analyze sentiments related to presidential candidates in the 2019 election in Indonesia. Naïve Bayes (NB) can be used to classify tweet feed into polarity class negative or positive, but it still has low accuracy. Therefore, this study optimizes the Naïve Bayes algorithm with Particle Swarm Optimization (NB-PSO) to classify opinions from twitter feeds to get a good accuracy of public figures sentiment analysis. PSO used to select features to find optimization values to improve the accuracy of Naïve Bayes. There are four steps to optimize NB using PSO, i.e., initializing the population (swarm), calculate the accuracy value that matched with selected features, selected the best accuracy of classification, and updating position and velocity. From this study, the group of tweets was obtained based on the positive and negative sentiments from the community towards two Indonesia presidential candidates in 2019. The NB-PSO test shows the accuracy result of 90.74%. The result of accuracy increases by 4.12% of the NB algorithm. In conclusion, the inclusion of the Particle Swarm Optimization algorithm for Naïve Bayes classification algorithm gives a significant accuracy, especially for sentiment analysis cases.
Sentiment Analysis from Indonesian Twitter Data Using Support Vector Machine And Query Expansion Ranking Hasbi Atsqalani; Nur Hayatin; Christian Sri Kusuma Aditya
JOIN (Jurnal Online Informatika) Vol 7 No 1 (2022)
Publisher : Department of Informatics, UIN Sunan Gunung Djati Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15575/join.v7i1.669

Abstract

Sentiment analysis is a computational study of a sentiment opinion and an overflow of feelings expressed in textual form. Twitter has become a popular social network among Indonesians. As a public figure running for president of Indonesia, public opinion is very important to see and consider the popularity of a presidential candidate. Media has become one of the important tools used to increase electability. However, it is not easy to analyze sentiments from tweets on Twitter apps, because it contains unstructured text, especially Indonesian text. The purpose of this research is to classify Indonesian twitter data into positive and negative sentiments polarity using Support Vector Machine and Query Expansion Ranking so that the information contained therein can be extracted and from the observed data can provide useful information for those in need. Several stages in the research include Crawling Data, Data Preprocessing, Term Frequency – Inverse Document Frequency (TF-IDF), Feature Selection Query Expansion Ranking, and data classification using the Support Vector Machine (SVM) method. To find out the performance of this classification process, it will be entered into a configuration matrix. By using a discussion matrix, the results show that calcification using the proposed reached accuracy and F-measure score in 77% and 68% respectively.
Co-Authors Abdul Hadiy Dyo Fatra Abidatul Izzah Abidatul Izzah Izzah, Abidatul Izzah Adhi Bagus Setiawan Ahmad Al Ghivani Ahmad Dhana Renomi Ahmad Hifdhul Abror, Ahmad Hifdhul Aini Alifatin Aini Nurul Amarul Akbar Andhini, Thathit Manon Anggraini, Syadza Anisatu Thoyyibah Asep Rohman Audi Bayu Yuliawan Ayu Puji Lestari Basuki, Setio Bayu Mavindo Bayu Yuliawan, Audi Chastine Fatichah Chita Nauly Harahap Christian Sri Kusuma Aditya Christian Sri Kusuma Aditya Christian Sri Kusuma Aditya Dasa Ismaimuza Dede Nor Alfiansyah Deny Qutara Putra Diana Purwitasari Didih Rizki Chandranegara Dini Kurniawati Doni Yulianto Dwi A. P. Rahayu Dwi Arif Al-mubarok Dyah Hestiningtyas Dzur Rifqi Aziz Eko Budi Cahyono Elbert Setiadharma Evi D. Wahyuni Evi Dwi Wahyuni Fadil Ramadhan Farid Dadhee Fatahillah Arsyad Gama Wisnu Fajarianto Giffari Zakawaly Gita Indah Marthasari Hariyady, H. Hasbi Atsqalani Ika Rizki Anggraini Kharisma Muzaki Ghufron Kris Setyaningsih, Kris Kuntur, Soveatin Lia Nuarini M Syawaluddin Putra Jaya Maskur Maskur Maskur Maskur Mavindo, Bayu Meilina Agustina Meilisa Musnaimah Mentari Mas'ama Safitri Muhammad Rojib Saiful Musnaimah, Meilisa MUSTAMIN IDRIS Mustika Mentari Nasution, Annio Indah Lestari Nirindra Primavera Dirga Nugraha Nuryasin, Ilyas Prayogi Restia Saputra Putra, Deny Qutara Rahayu, Dwi A. P. Rellanti Diana Kristy Rellanti Diana Kristy Retno Firdiyanti Rima Mediana Mashita Rizal Rakhman Mustafa Rizky Ade Mahendra Rizky Heriawan Prayogo Tanjung Ruhaila Maskat S, Vinna Rahmayanti Saiful Arif, Mukhammad Rojib Sandy Young Sari Wahyunita Shofiyah Soveatin Kuntur Syadza Anggraini Syukri Adisakti Dainamang Taufik Nurahman Thathit Manon Andini Tiara Intana Sari Tri Fidriyan Arya Tsabitah Ayu Rahmawati Tutik Sulistyowati Veithzal Rivai Zainal Wahyuni, Evi D. Wicaksono, Galih Wasis Wildan Suharso Yogo Suwiknyo Yuda Munarko Yufis Azhar Yuniarti, Maulidya Zalfa Natania Ardilla