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All Journal Teknika JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jurnal Informatika Kaputama (JIK) Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) JINAV: Journal of Information and Visualization Rambideun : Jurnal Pengabdian Kepada Masyarakat International Journal of Engineering, Science and Information Technology Jurnal Tika jeti Brilliance: Research of Artificial Intelligence Aptekmas : Jurnal Pengabdian Kepada Masyarakat Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Teknologi Terapan and Sains 4.0 Jurnal Pendidikan Sains Indonesia (Indonesian Journal of Science Education) MEUSEURAYA : JURNAL PENGABDIAN MASYARAKAT Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Rini Meiyanti
Universitas Malikussaleh
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Clustering of Futsal Interest Level Among Students K-Means Method Bagaswara, Faris; Muthalib, Muchlis Abd; Meiyanti, Rini
International Journal of Engineering, Science and Information Technology Vol 5, No 3 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i3.879

Abstract

Futsal is a small field sport with a time of 20 minutes per round. Malikussaleh University is one of the universities that initiated Futsal as a health sport for its students. To determine students' interest in Futsal, clustering was carried out using the K-Means method on 100 students of the Faculty of Engineering involved in this study. This research proposal uses five variables: time variables, field facilities, motivation, environment, and plans. This study aims to help students at Malikussaleh University of Engineering find out what level of interest students have in Futsal. Grouping is based on data mining to determine the pattern of each sequence. Data mining includes tracking patterns, classification, association, outlier detection, clustering, regression, and forecasting. This study also led to an innovative grouping system using the Python programming language and MySQL as a database. The K-Means Clustering algorithm used in this grouping system states that out of 100 Malikussaleh University students, 20 people are students who have a professional player futsal interest level (C1), 28 students have a regular player futsal interest level (C2), five students have a Beginner player futsal interest level (C3), 47 students have an amateur player futsal interest level (C4). The study results showed that 20% were professional, 28% were regular, 5% were beginner, and 47% were amateur players. These results indicate that the interest in Futsal for Malikussaleh University students is still minimal, so encouragement is needed for students to participate in futsal activities.
Mathematics Adventure: Game Edukasi Interaktif untuk Meningkatkan Pemahaman Matematika Siswa Sekolah Dasar Retno, Sujacka; Agusniar, Cut; Meiyanti, Rini; Fitria, Rahma
Jurnal Malikussaleh Mengabdi Vol. 4 No. 1 (2025): Jurnal Malikussaleh Mengabdi, April 2025
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jmm.v4i1.22233

Abstract

Program pengabdian masyarakat ini bertujuan untuk meningkatkan kualitas pembelajaran matematika di SD Negeri 28 Sawang, Aceh Utara, melalui pengembangan dan implementasi game edukasi berbasis teknologi, Mathematics Adventure. Game ini dirancang untuk siswa kelas III dengan tujuan membantu mereka memahami konsep operasi bilangan bulat, seperti penjumlahan, pengurangan, perkalian, dan pembagian, melalui pendekatan yang interaktif dan menyenangkan. Kegiatan ini melibatkan analisis kebutuhan pengguna, pengembangan game menggunakan platform Unity, pelatihan bagi guru, serta implementasi dan evaluasi langsung kepada siswa. Hasil evaluasi menunjukkan bahwa penggunaan Mathematics Adventure berhasil meningkatkan minat dan motivasi siswa dalam belajar matematika, dengan 90% siswa menunjukkan antusiasme yang lebih besar dan peningkatan pemahaman konsep sebesar 20%. Guru juga merasakan manfaat signifikan dari media pembelajaran ini, yang dinilai efektif dalam menyampaikan materi matematika dengan cara yang lebih menarik. Melalui program ini, siswa tidak hanya memperoleh pengalaman belajar yang lebih menyenangkan tetapi juga mengembangkan keterampilan digital dasar. Diharapkan kegiatan ini dapat menjadi inspirasi untuk pengembangan lebih lanjut media pembelajaran berbasis teknologi, serta mendorong kolaborasi yang berkelanjutan antara pendidik dan pengembang.
Determining Eligibility for Smart Indonesia Program (PIP) Recipients Using the Backpropagation Method Rizkya, Ghinni; Nurdin, Nurdin; Meiyanti, Rini
Journal of Applied Informatics and Computing Vol. 9 No. 4 (2025): August 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i4.9733

Abstract

The government provides financial assistance, educational opportunities, and expands access for students from poor or vulnerable families through the Smart Indonesia Program (PIP). At Madrasah Ibtidaiyah Negeri 20 Bireuen, the selection process for underprivileged students is still carried out manually by homeroom teachers by collecting data on students and their parents. This study aims to design, implement, and evaluate a classification method using the Backpropagation Neural Network to determine the eligibility of PIP scholarship recipients. The dataset consists of 309 entries, comprising 217 training data and 92 testing data, collected from MIN 20 Bireuen students between 2021 and 2023. The attributes used include father's occupation, mother's occupation, father's income, mother's income, number of dependents, number of vehicles, home ownership status, and card ownership status. Prior to training, the data were normalized using Min-Max scaling. The model was built with one hidden layer using a hard-limit activation function and a learning rate of 0.01. The classification results are categorized as "Eligible" and "Not Eligible". The model achieved an accuracy of 98%, precision of 100%, recall of 95%, and F1-score of 97%.
Perbandingan Multifaktor Evaluation dan Fuzzy Analytic Hierarchy Process pada Kualitas Biji Kopi Meiyanti, Rini; Asrianda, Asrianda; Azmi, Win
Jurnal Teknik Informatika dan Sistem Informasi Vol 11 No 2 (2025): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v11i2.9741

Abstract

The development of information technology in the agricultural sector is crucial, including in determining coffee bean quality. This research implements a comparison of decision support systems (DSS) using the Multifactor Evaluation Process (MFEP) and Fuzzy Analytic Hierarchy Process (FAHP) methods to assess coffee bean quality based on moisture content, Trase, defects, color, aroma, and bean size. The results show that FAHP has an accuracy of 77%, higher than MFEP with an accuracy of 71%. Thus, FAHP is more effective in determining the farmers with the best coffee beans, thereby helping to improve the economic well-being of farmers and cooperatives.
Comparison of K-Means and K-Medoids Methods in Clustering High Population Density Areas in Bireuen Regency Andri Alfitra; Nurdin, Nurdin; Meiyanti, Rini
JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Vol. 9 No. 1 (2025): Issues July 2025
Publisher : Universitas Medan Area

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31289/jite.v9i1.15602

Abstract

This study examines the population density distribution in Bireuen Regency by applying two clustering algorithms, namely K-Means and K-Medoids, to demographic data from 2019 to 2023. Three main variables were used: total population, number of ID card holders (KTP), and number of households (KK). The clustering results identified three primary groups: very dense, dense, and not dense. Districts such as Kota Juang, Jeumpa, and Peusangan consistently fell into the very dense category, while districts like Pandrah, Gandapura, and Makmur tended to be classified as not dense. Cluster quality was evaluated using the Davies-Bouldin Index (DBI). The evaluation results showed that the K-Means algorithm performed better in most years analyzed, particularly in 2020 with the lowest DBI value of 0.3906. Meanwhile, in 2023, K-Medoids outperformed K-Means, with a DBI value of 0.7724. These findings indicate that K-Means is more effective in handling homogeneous data, whereas K-Medoids is more adaptive to data containing outliers or irregular patterns. Overall, the choice of clustering method depends on the characteristics of the data used. The results provide a spatial overview of population distribution that can support regional planning and data-driven public policy. These findings are expected to serve as a basis for more targeted and equitable regional development planning. For future research, it is recommended to expand the analysis by including additional variables such as area size and socioeconomic indicators, as well as optimizing the number of clusters using methods like the Elbow method or Silhouette Score.
Method Design of an IoT-Based Automatic Pest Repellent System Prototype for Agriculture Kamaruzzaman, Hilda Zulfira; Ula, Munirul; Meiyanti, Rini
Journal of Applied Informatics and Computing Vol. 9 No. 5 (2025): October 2025
Publisher : Politeknik Negeri Batam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30871/jaic.v9i5.10632

Abstract

Indonesia, as an agricultural country, still faces serious challenges in the farming sector, particularly pest attacks from birds and insects that significantly reduce rice productivity and may lead to crop failure. The use of traditional methods and chemical pesticides is considered ineffective and has negative impacts on health and the environment. This study aims to design a prototype of an automated pest repellent system for agriculture based on the Internet of Things (IoT) that is environmentally friendly, energy-efficient, and easy to operate by local farmers. The research method employed a prototyping approach, which includes problem identification, hardware and software design, testing, and system evaluation. The device consists of a NodeMCU ESP32 microcontroller, a PIR sensor to detect pest movement, relay, ultrasonic speaker, electric net, and solar panel as the main power source. Testing on a miniature rice field model showed that the system could detect pest movement at a distance of approximately 5 meters and automatically activate the ultrasonic speaker with a range of 50–100 meters to repel birds, and the electric net to catch insects at night. Energy consumption is primarily supplied by the solar panel, and a fully charged battery can power the system for about 3 hours without sunlight. The detection success rate reached more than 85% with consistent actuator response. This system has proven to reduce pesticide dependency, is environmentally friendly, and has the potential to increase rice farming efficiency.
PKM Peningkatan Kesadaran Etika Dalam Penggunaan Media Sosial Kalangan Santri Dayah Nurul Iman di Gampong Alue Bungkoh Kecamatan Pirak Timu Rahman, Arief; Meiyanti, Rini; Malasyi, Syibral; Maryana, Maryana; Muhammad, Muhammad; Pratama, Angga
Jurnal Malikussaleh Mengabdi Vol. 2 No. 2 (2023): Jurnal Malikussaleh Mengabdi, Oktober 2023
Publisher : LPPM Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/jmm.v2i2.14830

Abstract

Pentingnya Meningkatkan Kesadaran Etika Penggunaan Media Sosial di Kalangan Santri Dayah Nurul Iman sangat berguna dalam memilah berita. Hasil survei menunjukkan bahwa banyak masyarakat Indonesia yang menerima berita hoax setiap harinya dan harus bijak dalam menggunakan media dalam berinteraksi. Pengabdian ini bertujuan untuk menghindari / mengurangi penyebaran berita bohong dan etika dalam menyadarkan penggunaan media sosial di kalangan Santri Dayah Nurul Iman. Media online serta faktor penghambat dan pendukung dalam melaksanakan upaya pencegahan bahaya penyebaran berita bohong serta dampaknya terhadap media online jika salah memilih berita. Tujuan dari layanan ini adalah untuk membahas peraturan terkait berita bohong atau hoax dan dampaknya terhadap pelaku tindak pidana penyebaran berita hoax terhadap beberapa pihak yang turut terlibat dalam penyebaran berita bohong. Hasil dari pengabdian ini adalah meningkatnya kesadaran dan pemahaman pengetahuan santri di Dayah Nurul Iman mengenai berita hoax, ada sebagian masyarakat yang mengetahui apakah itu berita hoax atau bukan, dan ada juga yang sudah mengetahui bahwa berita tersebut adalah hoax. penyebaran melalui penyebaran berita tidak benar dan hal ini sudah ada dalam undang-undang dan ada strategi untuk mencegah berita menyebar luas
PEMANFAATAN AIR CUCIAN BERAS UNTUK PEMBUATAN PUPUK ORGANIK DI DESA KENINE KABUPATEN BENER MERIAH Anshar, Khairul; Muhammad; Ginting, Zainuddin; Muarif, Agam; Mulyawan, Rizka; Meiyanti, Rini
Aptekmas Jurnal Pengabdian pada Masyarakat Vol 7 No 1 (2024): APTEKMAS Volume 7 Nomor 1 2024
Publisher : Politeknik Negeri Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36257/apts.v7i1.6304

Abstract

Rice washing water is generally not used and considered as waste. The elements contained in rice washing water are nutrients needed for plants. From this fact, rice washing water waste has the potential to be used as liquid organic fertilizer for plants. In general, rice washing water from households in Kenine Village, Wih Pesam District, Bener Meriah Regency is disposed of without being used properly, such as being thrown away or directly watered on plants. On the one hand, the area is increasingly using inorganic fertilizers on plants, including the main commodity crop, namely coffee. Based on these problems, community service activities were carried out in Kenine Village, Bener Meriah Regency through counseling activities to make organic fertilizer for the village community to use rice washing water waste as the main ingredient with molasses and EM4 as an alternative solution to the use of commercial chemical fertilizers which are much more economical and secure from the organic side.
Unjuk Kerja Algoritma Support Vector Machine (SVM) dan Naïve Bayes Dalam Pengklasifikasian Berita Hoaks Pada Twitter Tentang Aksi Cepat Tanggap (ACT) Hasan Dalimunthe, Amir; Munirul Ula; Rini Meiyanti
Jurnal Elektronika dan Teknologi Informasi Vol 5 No 2 (2024): September 2024
Publisher : LPPM-UNIKI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5201/jet.v5i2.400

Abstract

Twitter merupakan satu dari banyaknya media sosial yang populer di kalangan masyarakat.  Terkadang informasi yang beredar di twitter merupakan berita palsu yang tidak dapat dibuktikan kebenarannya (hoaks). Penelitian ini menggunakan algoritma Naïve Bayes dan Support Vector Machine (SVM) untuk menentukan berita yang beredar di platfrom twitter mengenai Aksi Cepat Tanggap (ACT) termasuk ke dalam berita hoaks atau berita faktual. Proses klasifikasi dimulai dengan pengumpulan data dengan Teknik Scraping dan setelah itu dilakukan pelabelan untuk mengklasifikasi data latih. Data yang telah diberi label kemudian diproses melalui text pre-processing dan dilanjutkan dengan klasifikasi menggunakan metode Naïve Bayes dan Support Vector Machine (SVM). Jumlah data yang digunakan dalam penelitian ini sebanyak 1425 data dan dibagi ke dalam kategori fakta dan kategori hoaks. Pada proses klasifikasi algoritma Naïve Bayes mendapat nilai akurasi 66,76%, presisi 70,13%, dan recall 58,38%. Sedangkan hasil evaluasi klasifikasi Support Vector Machine (SVM) memiliki tingkat akurasi 65,22%, presisi 71,37%, dan recall 50,84%. Sehingga dapat disimpulkan performa algoritma Naïve Bayes memiliki performa yang lebih bagus dari algoritma Support Vector Machine.
Analysis of Gender-Based Computational Thinking Skills through Project Base Learning (PjBL) Programming Learning Using Fuzzy Method Fitri*, Zahratul; Safriana, Safriana; Meiyanti, Rini; Faisal, Muhammad; Mamat, Rizalman Bin
Jurnal Pendidikan Sains Indonesia Vol 12, No 1 (2024): JANUARY 2024
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24815/jpsi.v12i1.34798

Abstract

Learning Evaluation is carried out to determine the level of competence possessed by students. Computational Thinking is a learning approach used to improve students' cognitive thinking. Gender-based education is important to be implemented in all educational institutions because men and women have equal rights in obtaining education. Female students are often considered to have more weaknesses in learning technical practices than men, so it is expected to advance the thinking of students, especially gender equality between men and women in thinking in order to be able to compete in the world of work. This study aims to train how to think in solving problems using several techniques in Project Base Learning (PjBL)-based programming learning whose learning evaluation results between male and female students are analyzed using Tsukamoto's Fuzzy Inference method. The results obtained were the development of computational thinking of students totaling 40 people including 20 men and 20 women obtained 4 male students and 3 female students with "very high" scores, 5 male students and 5 female students obtained "High" scores, 8 male students and 12 female students obtained "Medium" scores, 2 male students obtained "Low" grades, while 1 male student obtained a score of "Very Low". This proves that the implementation of the concept of computational thinking in project-based learning (PjBL) programming learning can increase the level of thinking skills of students in doing learning.
Co-Authors Agam Muarif Aidilof, Hafizh Al Kautsar Andri Alfitra Angga Pratama Anggara, Aji Ar Razi Arief Rahman Asrianda Asrianda Azmi, Win Bagaswara, Faris Bustami Bustami Chaliza Nur, Wan Amalia Cut Agusniar Cut Lika Mestika Sandy Cut Lika Mestika Sandy Dahlan Abdullah Eva Darnila Fasdarsyah Fasdarsyah Fatayati, Nufus Fitri*, Zahratul Fuadi, Wahyu Hafidh Rafif, Teuku Muhammad Hamsi, Widia Harahap, Ilham Taruna Harahap, Lina Mardiana Hasan Dalimunthe, Amir Kamaruzzaman, Hilda Zulfira Kautsar, Al Khairul Anshar Lidya Rosnita Lina Mardiana Harahap Mamat, Rizalman Bin Maryana Maryana, Maryana Muhammad Muhammad Faisal Muhammad Ikhwani Muhammad Muaz Munauwar Muhammad Muhammad Mulyawan, Rizka Munirul Ula Muthalib, Muchlis Abd Mutia Zahara Na'syakban, Irvan Nunsina, Nunsina Nurdin Nurdin Rahma Fitria Rahma Fitria, Rahma Ramadhani, Putri Yesi Ramazani, Ayu Rara Audia Utami Rizkya, Ghinni Ruzanna, Arina Safriana Safriana Safwandi Safwandi Sandy, Cut Lika Mestika Sujacka Retno Syibral Malasyi, Syibral Wahyu Fuadi Yesy Afrillia Zainuddin Ginting Zalfie Ardian Zara Yunizar