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All Journal Teknika JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal SOLMA 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 Journal of Mathematics Instruction, Social Research and Opinion Jurnal Pendidikan Sains Indonesia (Indonesian Journal of Science Education) MEUSEURAYA : JURNAL PENGABDIAN MASYARAKAT Jurnal Malikussaleh Mengabdi Journal of Advanced Computer Knowledge and Algorithms Gameology and Multimedia Expert JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Proceedings of International Conference on Multidisciplinary Engineering (ICOMDEN)

Rini Meiyanti

Universitas Malikussaleh

Author-ID : 2616592

Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Astronomy Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Transportation Veterinary Other

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Sentiment Analysis of the MK Decision Trial of the Result of the 2024 President and Vice President General Election on Social Media X Using the Support Vector Machine Method Anggara, Aji; Nurdin, Nurdin; Meiyanti, Rini
International Journal of Engineering, Science and Information Technology Vol 4, No 4 (2024)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v4i4.591

Support Vector Machine (SVM) is a method of machine learning often used in classification and regression issues, especially in the classification of commentary reviews on social media such as Twitter. The Constitutional Court (MK) has the authority to resolve disputes resulting from the general election, including the 2024 presidential election. As an institution that maintains fairness and transparency in the democratic process, the Constitutional Court's decisions are often at the center of public attention and debate, especially on social media. In the 2024 general election, various allegations of fraud led to protests from several parties who felt aggrieved. The final and binding Constitutional Court's decision is expected to resolve the conflict that arises, but it often does not satisfy all parties, causing political and social tensions. This conflict can be reflected through public opinion expressed on social media, such as Twitter, where various responses and sentiments to the decision are essential analysis materials. This Research uses the Support Vector Machine (SVM) algorithm with a dataset of 1383 review comments divided by an 80:20 ratio for training and testing. The system was implemented using the Python programming language, with evaluations showing the highest accuracy at 61.00%, precision at 61.00%, and recall at 62.00%. This study aims to analyze public sentiment regarding the Constitutional Court's decision using the SVM method and identify the tendency of public opinion as positive, negative, or neutral. Through this study, it is expected that a deeper understanding of the public's perception of the Constitutional Court's decision is obtained. In addition, this Research is likely to contribute to developing sentiment analysis methods in the future and provide a basis for recommendations for the Constitutional Court in handling election result disputes better.

Clustering Agricultural Productivity by Type and Results Using K-Medoids Method in Districts North Aceh Zahara, Mutia; Fuadi, Wahyu; Meiyanti, Rini
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.699

This research aims to develop a web-based application that can cluster sub-districts in North Aceh District based on the type and yield of agricultural productivity, focusing on increasing the ease of visualization and data analysis by users. The method applied in this research is K-Medoids, a clustering technique used to group sub-districts based on high, medium, and low harvest levels. The application will use data from the North Aceh District Agriculture Office, covering 2021 to 2023, including various food crops such as rice, corn, peanuts, green beans, cassava, sweet potatoes, and soybeans. This research will analyze the sub-district name, type of agriculture, year of production, planting area, and harvest area to identify clusters of sub-districts with similar agricultural yield patterns. The system is developed using the PHP programming language to facilitate implementation and data access by stakeholders. As an evaluation tool for clustering results, the Davies-Bouldin Index (DBI) is used to measure the quality of clustering results. The results of this study are expected to provide insights into agricultural productivity in North Aceh District and assist policymakers in designing more effective strategies to increase agricultural yields, especially in low-yielding sub-districts. In addition, this application also provides an interactive platform for users to analyze agrarian data quickly and efficiently.

Pelatihan Pembuatan Media Pembelajaran Online dan Perakitan Komputer Pada Sekolah di Desa Paloh Lada Kecamatan Dewantara Bustami, Bustami; Muhammad, Muhammad; Yunizar, Zara; Rosnita, Lidya; Meiyanti, Rini; Afrillia, Yesy; Hafidh Rafif, Teuku Muhammad; Harahap, Ilham Taruna
MEUSEURAYA - Jurnal Pengabdian Masyarakat Vol.1 No.2 (Desember 2022)
Publisher : Pusat Penelitian dan Pengabdian Kepada Masyarakat STAIN Teungku Dirundeng Meulaboh

Pesatnya perkembangan teknologi informasi saat ini secara tidak langsung juga “memaksa” kita untuk dapat mengikuti perkembangannya, bukan hanya bagi kita yang memang bergerak di bidang IT, namun juga bagi kita yang bergerak disemua bidang, salah satunya di bidang Pendidikan. Teknologi informasi menjadi kebutuhan primer bagi kita yang membutuhkan efisiensi dalam berkegiatan. Guru dan siswa juga merasakan langsung bagaimana teknologi berperan dalam kegiatan Pendidikan, pembelajaran secara daring di masa covid menjadi puncak dari pemanfaatan teknologi didunia Pendidikan. Salah satu point penting dari kegiatan pembelajaran daring adalah pemanfaatan media pembelajaran daring, misalnya google classroom. Kegiatan pengabdian ini bertujuan untuk membantu Guru dan juga siswa/I memanfaatkan teknologi dalam kegiatan pembelajaran. Kegiatan pengabdian ini terdiri dari dua kegiatan besar, yaitu Pelatihan pembuatan media pembelajaran online yang diberikan kepada para guru dan kegiatan pelatihan perakitan komputer dan instalasi komputer kepada para murid. Kegiatan ini dilakukan pada MTsS Jabal Nur dan MTsN 2 Aceh Utara, Kecamatan Dewantara, Kab. Aceh Utara. Output dari kegiatan ini adalah Jurnal yang di submit pada Jurnal Rambieden dan Publikasi media massa. Selain itu, kegiatan ini juga memberikan pemahaman pada para guru dalam pemanfaatan media pembelajaran online dan dapat diterapkan dalam kegiatan pembelajran, sedangkan bagi siswa, kegiatan pelatihan ini memberikan pengetahuan pada mereka tentang perkembangan teknologi informasi.

Developing Prototype Model Based on Analysis of The People at The Center of Mobile App Development (PACMAD) on The Panel Harga Pangan Application Fitria, Rahma; Meiyanti, Rini; Aidilof, Hafizh Al Kautsar; Ruzanna, Arina; Hamsi, Widia; Na'syakban, Irvan
JINAV: Journal of Information and Visualization Vol. 5 No. 2 (2024)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.jinav3115

The increasing demand on mobile applications to monitor and analyze market trends in the food industry necessitates a focus on usability to ensure that these tools are functional and user-friendly. The Panel Harga Pangan app, which is widely utilized by traders, consumers, and policymakers, provides essential information on food prices across many marketplaces. However, as its user base grows, correcting usability concerns becomes increasingly important to its sustained effectiveness and customer happiness. This article looks into the implementation of the People At The Center Of Mobile Application Development (PACMAD) usability concept on the panel harga pangan app and finally proposed the prototype to similar application. The PACMAD model, designed specifically for mobile applications, evaluates usability based on seven key criteria: effectiveness, efficiency, satisfaction, learnability, memorability, mistakes, and cognitive load. The application's effectiveness is approximately (62.5%), including efficiency (73.27%), satisfaction (64%), learnability (65.78%), memorability (70.93%), errors (68.59%), and cognitive load (72.72%). The study's findings show that the application has an average score of 68%, indicating that the program is neither particularly successful or satisfying. Issues such as less efficiency and higher error frequency diminish the overall user experience. The research includes specific recommendations for improving the app's usability, such as redesigning the user interface and optimizing onboarding processes. These findings aim to improve the user experience, ensuring that the panel harga pangan remains a reliable and user-friendly tool for its varied audience. The findings have significant consequences for applying the PACMAD model to other mobile agriculture applications.

Performance of K-Nearest Neighbor Algorithm and C4.5 Algorithm in Classifying Citizens Eligible to Receive Direct Cash Assistance in Bandar Mahligai Village Chaliza Nur, Wan Amalia; Abdullah, Dahlan; Meiyanti, Rini
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.752

Direct Cash Assistance, commonly called BLT, is one of the many programs the Indonesian government held to reduce the poverty rate of the Indonesian population. This study compares the KNN and C4.5 methods to determine the eligibility of residents eligible to receive Direct Cash Assistance in Bandar Mahligai Village. This study began with collecting resident data from the Bandar Mahligai village office. Then, the data obtained was taken into several attributes to be used in the classification process, namely the name of the head of the family, KK number, NIK, number of dependents, occupation, income, and monthly expenses. After the data is collected, the data will be classified using the KNN and C4.5 algorithms. There is a significant difference between the two algorithms in the classification process; the KNN algorithm by looking for the nearest neighbor data value, in this study, the K value = 9, while the C4.5 algorithm by building a decision tree from the attribute values taken based on resident data used as training data. The classification results of the two methods will be compared using a confusion matrix to obtain a higher accuracy technique. The results of testing using a confusion matrix for both algorithms are the accuracy produced by the KNN and C4.5 algorithms in classifying residents eligible for Direct Cash Assistance (BLT) of 90% in the system that has been built. The results of comparing the KNN and C4.5 algorithms for this study show that the KNN algorithm is better because the accuracy level reaches 90% in manual and system calculations. While the C4.5 method only gets 85% for the accuracy of its manual calculations, it receives an accuracy level of 90% in the system that has been built.

Implementation of Complex Proportional Assessment Method in Determining Prioritization of Beneficiary Groups Fish Seeds in Lhokseumawe City Ramadhani, Putri Yesi; Safwandi, Safwandi; Meiyanti, Rini
International Journal of Engineering, Science and Information Technology Vol 5, No 1 (2025)
Publisher : Malikussaleh University, Aceh, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52088/ijesty.v5i1.754

The fisheries sector in Lhokseumawe City has an essential role in the regional economy, but the limited allocation of fish seed assistance requires an efficient and objective decision-making system (SPK). This research applies the Complex Proportional Assessment (COPRAS) method to prioritize groups of fish seed aid recipients. COPRAS was chosen because it can handle quantitative and qualitative criteria and produce a clear ranking of alternatives. The system evaluates criteria such as pond area, number of members, pond condition, and group age. The results showed that the Tani Mandiri group had the highest utility value = 1, while Tani Maju Berkah obtained the lowest value = 0.655. The COPRAS method effectively provided accurate and transparent recommendations in determining beneficiaries. Implementing this system is expected to help the Lhokseumawe City Marine, Fisheries, Agriculture, and Food Service Office allocate fairer and more targeted assistance, as well as increase the fisheries sector's productivity in the area. This research also contributes to developing technology-based decision-making systems to support government policies.

Implementation of Promethee II Method in the Productivity of Superior Vegetables in Sub-Districts in Northern Aceh Meiyanti, Rini; Kautsar, Al; Fatayati, Nufus
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 6, No 1 (2025)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v6i1.22392

This research aims to determine sub-districts with superior vegetable productivity in North Aceh using the PROMETHEE II Method. This method is used in decision support systems to help analyze various criteria related to vegetable productivity, such as planting area, harvest area, added planting area, and total production. The research data was taken from 23 sub-districts in North Aceh covering various types of vegetables, such as chili, tomato, long bean, and eggplant, for the year 2023. Through analysis using the PROMETHEE Method, this research produced a ranking of sub-districts based on Net Flow values that reflected the level of productivity of each sub-district. The results show that sub-districts Tanah Luas has the highest vegetable productivity with a Net Flow value of 3.0608, while sub-districts Tanah Pasir is at the lowest position with a value of -2.2172. With these results, the research provides recommendations to the local government and farmer groups to focus on improving productivity in the low-ranked sub-districts. In conclusion, the PROMETHEE II Method provides accurate and objective results in analyzing vegetable productivity in various sub-districts and can be used as a decision-making tool related to strategies for improving vegetable agriculture in North Aceh. Therefore, the results of this study are expected to be used as guidelines in planning strategies to increase agricultural productivity in North Aceh.

Klastering Sayuran Unggulan Menggunakan Algoritma K-Means Lina Mardiana Harahap; Wahyu Fuadi; Lidya Rosnita; Eva Darnila; Rini Meiyanti
Jurnal Teknik Informatika dan Sistem Informasi Vol 8 No 3 (2022): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v8i3.5277

Horticulture, especially vegetables, has great potential to be developed because it becomes a source of income for the community and small farmers in each region because Indonesia is called an agrarian country with most of them working in agriculture. Mandailing Natal Regency is the district with the largest area in North Sumatra province, but Mandailing Natal has not been able to outperform vegetable crop production in North Sumatra. Data mining methods can find interesting and invisible patterns in data sets. One of the methods is the K-Means clustering algorithm which groups data into clusters based on the similarity of data characteristics. In this study, vegetable data was clustered which aims to determine the potential commodities in each area in Mandailing Natal Regency, plants that have potential in the area will be maintained and their production increased, while vegetable crops whose production is still low will be a priority to increase their production. The research method used in this study was to collect vegetable data from the Badan Pusat Statistik in the form of data on harvested area, production, plant area, and new planting area. In addition, data collection was carried out by conducting theoretical studies in journals. The results of clustering superior vegetables using the K-Means Algorithm are in the form of potential grouping into 3 clusters, namely low, medium, and high clusters and the output is a web-based system in its application. The results of the clustering analysis were obtained with each total data of 69 data, namely big chili with C1 81%, C2 16% and C3 3%. Cayenne C1 29%, C2 48% and C3 23%. Long Beans C1 26%, C2 38% and C3 36%. Kale C1 39%, C2 36% and C3 25%. Eggplant C1 43%, C2 29% and C3 28%. Tomato C1 41%, C2 58% and C3 1%.

RANCANGAN APLIKASI PERPUSTAKAAN BERBASIS ANDROID DI PERPUSTAKAAN UNIVERSITAS MALIKUSSALEH Meiyanti, Rini
Jurnal Teknologi Terapan and Sains 4.0 Vol 3 No 2 (2022): Jurnal Teknologi Terapan & Sains
Publisher : Universitas Malikussaleh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29103/tts.v3i2.8275

Universitas Malikussaleh adalah sekolah perguruan tinggi yang didirikan di Lhokseunawe. Universitas ini sangat berkembang namun perpustakaan yang ada tidak cukup memadai untuk menampung mahasiswa yang banyak. Untuk mengatasi hal ini diperlukan sebuah software perpustakaan yang berbasis android dan bersifat mobile. Metode pengembangan pada laporan ini yaitu metode waterfall. Metode pendekatan yang digunakan pada laporan ini yaitu Object Oriente. Pembuatan sistem ini juga memanfaatkan beberapa alat bantu perancangan sistem seperti Use Case. Perangkat lunak yang digunakan untuk membangun sistem ini adalah Android Studio dan basis data SQLite. Sistem informasi yang dibangun oleh penulis diharapkan dapat digunakan untuk melancarkan system perpustakaan untuk mempermudah mahasiswa untuk membaca buku dan meminjam buku di perpustakaan Universitas Malikussaleh Lhokseumawe.Keywords: Perancangan Aplikasi, Perpustakaan, Use Case, Android

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

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.

Co-Authors Agam Muarif Aidilof, Hafizh Al Kautsar Andri Alfitra Angga Pratama Anggara, Aji Ar Razi Arief Rahman Asrianda Asrianda Ayu Ramazani Azmi, Win Azwir, Andrea Micola 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 Habib Muharry Yusdartono 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 M. Raiyan Firdaus Mamat, Rizalman Bin Maryana Maryana, Maryana Muhammad Muhammad Faisal Muhammad Ikhwani Muhammad Muaz Munauwar Muhammad Muhammad Mukhlis Abdul Muthalib Mulyawan, Rizka Munirul Ula Muthalib, Muchlis Abd Muthiah Riani Harahap Mutia Zahara Na'syakban, Irvan Nunsina, Nunsina Nurdin Nurdin Rahma Fitria Rahma Fitria, Rahma Ramadhani, Putri Yesi Rangkuti, Haris Yunanda Rara Audia Utami Rizal, Reyhan Achmad Rizkya, Ghinni Ruzanna, Arina Safriana Safriana Safwandi Safwandi Safwandi Said Fadlan Anshari Sandy, Cut Lika Mestika Serlina, Serlina Sujacka Retno Sukiman, T. Sukma Achriadi Syibral Malasyi, Syibral Wahyu Fuadi Yesy Afrillia Zahratul Fitri, Zahratul Zainuddin Ginting Zalfie Ardian Zara Yunizar

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