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All Journal JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal SOLMA JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Ilmiah Sinus Jurnal Informatika Kaputama (JIK) Jurnal Mantik Jurnal Informasi dan Teknologi JTIK (Jurnal Teknik Informatika Kaputama) G-Tech : Jurnal Teknologi Terapan Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Teknik Informatika (JUTIF) Jurnal Tika Multica Science and Technology JUSTIN (Jurnal Sistem dan Teknologi Informasi) Brilliance: Research of Artificial Intelligence Indonesian Community Journal Sisfo: Jurnal Ilmiah Sistem Informasi SAGA: Journal of Technology and Information Systems Journal Of Artificial Intelligence And Software Engineering Jurnal Medika: Medika Science: Indonesian Journal of Science

Ananda Faridhatul Ulva

Universitas Malikussaleh

Author-ID : 2546702

Agriculture, Biological Sciences & Forestry Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Sistem Klasifikasi Tingkat Kelayakan Lahan Tanaman Padi Menggunakan Pengujian Naïve Bayes Dan K-Nearest Neighbor Di Kabupaten Aceh Utara Berbasis Web Angga Pratama; Eka Susanti; Ananda Faridhatul Ulva
Jurnal Tika Vol 7 No 3 (2022): Jurnal Teknik Informatika Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim Bireuen - Aceh

Cultivation of food crops has a significant role in the lives of Indonesian citizens, especially to fulfill their daily food needs. Efforts to cultivate rice plants often face obstacles, one of which is in ensuring the suitability of the soil, therefore the determination of the land at the planting stage or the land to be selected is not suitable land (unproductive), so that agricultural yields will not be maximum and will cause losses (financial). which is pretty big. The goal to be obtained in the concept of a classification system for the level of feasibility of rice plant land is to make it easier for farmers, residents and governments to make decisions by determining the feasibility of rice plant land. The method used in the classification system for decision support is the Naïve Bayes and K-Nearest Neighbor testing methods for comparison in efficient decision making. In rice, it is adjusted by calculating the value of criteria such as land characteristics, namely air temperature, rainfall, humidity, soil texture, pH, drainage and soil height. The results help farmers to make it easier to analyze land conditions for rice plants and increase rice production yields in North Aceh Regency

Peningkatan Kemampuan dan Keterampilan Teknologi Informasi Guru SD IT Al-Alaq Dewantara Aceh Utara dalam Penggunaan Software Microsoft Office Ananda Faridhatul Ulva; Desvina Yulisda; Rizky Putra Fhonna; Rahma Fitria; Himmatur Rijal
I-Com: Indonesian Community Journal Vol 3 No 2 (2023): I-Com: Indonesian Community Journal (Juni 2023)
Publisher : Fakultas Sains Dan Teknologi, Universitas Raden Rahmat Malang

Guru yang profesional memilki kemampuan dalam mengadaptasi dari perkembangan ilmu, khususnya pada teknologi informasi. SD IT Al Alaq Dewantara, sebuah sekolah di Aceh Utara yang memiliki guru-guru masih kurang mahir terhadap perkembangan teknologi informasi yaitu pada software Microsoft Office seperti pembuatan daftar isi, daftar pustaka, pembuatan presentasi yang interaktif dan menarik untuk anak-anak, serta pengolahan angka serta hasil evaluasi belajar anak dan pelaporan keuangan lainnya. Tujuan dari pegabdian ini meningkatkan profesionalitas seorang pendidik dalam bidang Teknologi Informasi dan Komunikasi. Metode pelaksanaan kegiatan pengabdian terdiri dari metode 2 (dua) pendekatan yaitu pendekatan edukatif yang fokus kepada mitra pengabdian dan tim pengbadian serta pendekatan partisipatif adanya kegiatan dalam penyusunan program, implementasi program dan evaluasi kegiatan. Dari hasil pelaksanaan pengabdian ini, terlihat perubahan yang signifikan terhadap wawasan dan ilmu pengetahuan yang didapat oleh para mitra pengabdian yaitu memberikan dampak adanya peningkatan dan kemampuan dalam penggunaan Microsoft Office.

Audit Capability Level Sipd Menggunakan Cobit 2019 Domain Align Plan And Organize Di Bappeda Kota Lhokseumawe Angga Pratama; Ananda Faridhatul Ulva; Eza Pradanta Sitepu
Jurnal Tika Vol 7 No 1 (2022): Jurnal Teknik Informatika Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim Bireuen - Aceh

The audit at the SIPD Bappeda of Lokseumawe City must be reviewed to see the efficiency and integrity of the company, for that it is necessary to audit the Capability level of the SIPD Bappeda of Lokseumawe City. The SIPD Capability Level audit was conducted with the aim of mapping the Capability Level of the I&T service and support process at the Lokseumawe City Bappeda. This SIPD Capability Level audit uses the Cobit 2019 Domain APO (Align, Plan and Organize) framework with a capability level calculation so that based on the results, recommendations for strategic goals will be found for the company for further development. Based on the current capability level obtained, the overall value is 2.527 and is at level 2 capability, namely Managed Process, meaning that the Lokseumawe City Bappeda has reached the implementation process and will later be determined according to the implementation process that has been implemented in this process in accordance with the Align, Plan and Domain processes. Organized at COBIT 2019. The 2019 COBIT model is also considered to be able to handle changes in governance and I&T Management in the company well.

Aplikasi Pengukuran Penggunaan Prebiotik untuk Tanaman Jagung di Kabupaten Aceh Utara Menggunakan Metode Fuzzy Tsukamoto Berbasis Web Angga Pratama; Maulida Hasbi; Ananda Faridhatul Ulva
Jurnal Ilmiah SINUS Vol 21, No 2 (2023): Volume 21 No. 2 Juli 2023
Publisher : STMIK Sinar Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30646/sinus.v21i2.707

Corn, along with rice and wheat, is one of the world's most significant food crops. Crop failures are a common concern for farmers, and one of the causes is the use of unsuitable fertilizers, which can limit the growth of organs and plant structure as a whole. Because good corn plant growth and high yields require the use of good and appropriate fertilizer for corn plants, this system is designed to recommend fertilization for plants based on the variables required by plants, namely soil pH, air temperature, humidity, rainfall, rainy days, altitude area, solar radiation, and land area, as determined by the agricultural service. Where each value is calculated using a specified set of each criterion, namely little, medium, and high. The outcomes of these computations are the final result of this decision system, namely suggestions for fertilizer usage in liters to assist farmers in analyzing fertilizer use for corn plants in North Aceh District. As in prior works, Tsukamoto's fuzzy technique is applied in this decision-making system to handle data values with a very high level of uncertainty or ambiguity.

IMPLEMENTASI MACHINE LEARNING DENGAN MODEL CASE BASED REASONING DALAM MENDAGNOSA GIZI BURUK PADA ANAK Mutammimul Ula; Ananda Faridhatul Ulva; Mauliza Mauliza
Jurnal Informatika Kaputama (JIK) Vol 5 No 2 (2021): Volume 5, Nomor 2, Juli 2021
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jik.v5i2.267

Upaya pencegahan permasalahan stunting kepada masyarakat khususnya pada ibu-ibu dengan pemberian masukan khususnya masyarakat aceh utara akan pentingnya pemenuhan gizi pada balita agar terhindat dari stunting. Kekurangan gizi menjadi pokok permasalahan yang dialami balita di Indonesia. Peran Rumah Sakit dan Dinas Kesehatan diperlukan dalam melihat jumlah gizi buruk pada balita khususnya di Aceh. Dalam penelitian ini penting dilakukan implementasi machine learning dengan model case based reasoning dalam mendiagnosa gizi buruk pada anak dalam melihat pengelompokkan balita yang teridentifikasi stunting atau tidak dengan menggunakan teknologi system pakar Case Based Reasoning yang dimodelkan dalam dalam mesin learning yang dilihat dari data riwayat gizi yang kemudian dimasukkan kedalam model pengujian Machine Learning dalam mendeteksi gizi buruk pada balita. Hal ini dapat mengurangi stunting yang ada di setiap wilayah, gampong dan kecamatan dari tiap Puskesmas yang ada di kabupaten aceh utara. Tujuan Penelitian ini adalah Untuk mengetahui pendeteksian gizi buruk balita pada Rumah Sakit Cut Meutia Kab. Aceh Utara. Hasil penelitian ini adalah dapat mendiagnosa gizi buruk pada balita dengan menggunakan metode casedbase reasoning dan hasil sistem yang dibangun dapat digunakan sebagai acuan untuk memantau tumbuh kembangnya bayi/balita. adapun variabel yang dimasukkan adalah nama, umur balita, jenis kelamin, tinggi badan dan berat badan, kemudian machine learning mencari kasus yang terdekat untuk melihat nilai yang paling mendekati dalam problem stunting. hasil nya adalah Nilai nya adalah Similarity (x, K001) 1,00, Similarity (x, K008), 0,66Similarity (x, K010), 0,64.

APLIKASI GAME PUZZLE HURUF HIJAHIYAH UNTUK ANAK-ANAK BERBASIS ANDROID Ananda Faridhatul Ulva; Chairul Akbar
JTIK (Jurnal Teknik Informatika Kaputama) Vol. 5 No. 2 (2021): Volume 5, Nomor 2, Juli 2021
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jtik.v5i2.411

Mobile device technology is growing rapidly, especially with the emergence of smartphones with the Android operating system. Users in this case can download various basic applications available easily on the google play store. But most of them are available in less educational game form. In fact, it often has negative consequences for users, especially for children who are still unable to distinguish positive and negative. Early childhood education stages tend to be interested in games that are easy to play and have an attractive visual appearance with a variety of colors and varied images that attract attention. This stage will also make it easier to remember the lesson. Therefore, researchers made a puzzle game application that can provide entertainment and education to users, especially children. This android based hijaiyah letter puzzle game application was built using Construct 2 converted with Phonegap into an Apk file. The application of this application is by installing a puzzle game application on a smartphone with the specifications of the Android operating system version 5.1+ (lollipop).

Development of GPS Track and Trace System in Dewantara Smart City Application to Realise Mobile-based Good Governance and Clean Government Ananda Faridhatul Ulva; Kurniawati Kurniawati; Desvina Yulisda
SAGA: Journal of Technology and Information System Vol. 1 No. 3 (2023): August 2023
Publisher : CV. Media Digital Publikasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58905/saga.v1i3.179

Smart cities with GPS track and trace implementation have great potential to achieve good and clean governance. This technology enables the government to gather and analyse real-time data concerning mobility, public assets, and the allocation of funds. With precise and transparent information, the government can enhance efficiency, accountability, and responsiveness to the needs of the public. The primary goals of this application are to promote transparency, improve the management of community activities, and encourage community engagement. The approach employed in the creation and development of this smart city application follows the waterfall method. This methodology simplifies the system's initial development and its potential for future enhancements. The results from implementing and testing the smart city system, utilizing usability testing, yield scores exceeding 3, specifically 3.56. This indicates that both government officials and the community find the system and application highly user-friendly

IMPLEMENTATION OF MACHINE LEARNING USING THE K-NEAREST NEIGHBOR CLASSIFICATION MODEL IN DIAGNOSING MALNUTRITION IN CHILDREN Mutammimul Ula; Ananda Faridhatul Ulva; Ilham Saputra; Mauliza Mauliza; Ivan Maulana
Multica Science and Technology Vol 2 No 1 (2022): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v2i1.326

The problem faced today is the lack of nutrition for children which causes stunting. One way to prevent stunting problems is to provide input to the community in Aceh for the importance of providing adequate nutrition for children. This study classifies toddlers who are identified as stunting with the K-NN model technology which is modeled in machine learning, the results are grouped. The purpose of this study was to determine the detection of malnutrition in toddlers and to classify data on malnutrition in toddlers using the k-means clustering method and the system that was built could be used as a reference to monitor the growth and development of children. Then in classifying malnutrition in children based on the results of the nutritional status criteria in toddlers, it can be known based on the index of Body Weight for Age (W/U), Height for Age (TB/U), and Weight for Height (W/TB). by entering data values from weight, height and gender of toddlers. The purpose of this study was to determine the detection of malnutrition under five at the Cut Meutia Hospital Kab. North Aceh. The process in the initial data analysis of Mr. ID, baby's name, gender, age, weight (kg), height (cm), the data to be classified for training data are 40 children in each region / village. In the assessment of nutritional status, it is classified as Malnutrition less than 3 SD or 70%, Malnutrition - 3 SD to < - 2 SD or 80%, Good Nutrition -2 SD to +2 SD, Over Nutrition >+2 SD. The results of the final score obtained are euclidean distance with a value of 1.3 with a ranking of malnutrition, age 1.6 months, weight (weight) 0.852, TB (height) 4.556 with euclidean distance with a value of 1.3 with a low ranking. For the second test data, age is 2.8 months, BB (weight) 0.222, TB (height) 4.556 with Euclidean distance with a value of 1.3 with a good rating of 0.778. The results of this study can be classified in children to children for each region in each region, village and sub-district of each Puskesmas in North Aceh Regency

APPLICATION OF MACHINE LEARNING IN PREDICTING CHILDREN'S NUTRITIONAL STATUS WITH MULTIPLE LINEAR REGRESSION MODELS Mutammimul Ula; Ananda Faridhatul Ulva; Mauliza; Muhammad Abdullah Ali; Yumna Rilasmi Said
Multica Science and Technology Vol 2 No 2 (2022): Multica Science and Technology
Publisher : Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/mst.v2i2.363

Forecasting is an important part of making plans and making decisions that can predict future events. Forecasting techniques in this study used multiple linear regression. This study aims to predict the number of cases of child nutritional status in children in each region. The purpose of this study was to see the results of predicting the number of children's nutritional status in each region and to make it easier to predict children's nutrition. The research method includes the analysis of the system built and the design of machine learning applications using the Multiple Linear Regression method. Then the system built can help predict the nutritional status of children in Aceh quickly, precisely, and accurately. The data used is data on the nutritional status of children in 2018, 2019, and 2020. Based on the results of forecasting for 2021 based on data obtained in previous years, the predicted results of total nutritional status in 2021 are 449,0912126. The results of this study indicate that the linear regression method obtains the best model results by being able to predict the implementation of machine learning.

Prediksi Harga Emas Menggunakan Algoritma Regresi Linear Berganda Dan Support Vector Machine (SVM) Sinambela, Reza Syahputra; Ula, Munirul; Ulva, Ananda Faridhatul
JUSTIN (Jurnal Sistem dan Teknologi Informasi) Vol 12, No 2 (2024)
Publisher : Jurusan Informatika Universitas Tanjungpura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/justin.v12i2.73386

Emas merupakan komoditas krusial dalam ekonomi global dan investasi yang populer. Harganya dipengaruhi oleh beragam faktor termasuk permintaan pasar, stabilitas ekonomi, inflasi, dan pergerakan mata uang, menjadikannya pelindung nilai dalam ketidakpastian ekonomi. Penelitian ini bertujuan untuk memprediksi harga emas dengan menggunakan metode Regresi Linear Berganda dan Support Vector Machine (SVM) serta membandingkan akurasinya. Regresi linear adalah alat analisis data yang cepat, sementara SVM adalah algoritma yang menggabungkan konsep komputasi yang ada. Hasil penelitian menunjukkan bahwa keduanya mampu memprediksi harga emas dengan akurasi tinggi, di mana Regresi Linear Berganda mencapai akurasi sebesar 99,72% dan SVM sebesar 98,07%. Dalam penelitian ini, Regresi Linear Berganda unggul berdasarkan nilai Mean Absolute Percentage Error (MAPE).

Co-Authors Abdi Zulfikri Alimul Haq, Nur Amalia, Fatihah Indah Andriani, Dela Angga Pratama Angga Pratama Apriyulida, Fitri Aulia, Keysha Bahrul Ulumul Haq Chairil Anwar Chairul Akbar Cut Meurah Nurul ‘Akla Dahlan Abdullah Desvina Yulisda Dhani, Saniah Eka Susanti Eka Susanti Eza Pradanta Sitepu Fadhliani Fadhliani, Fadhliani Fajar Tri Tri Anjani Fidyati, Fidyati Habib Muharry Yusdartono Hafizh Al Kautsar Aidilof Himmatur Rijal Ikhwani, Muhammad Ikhwani ilham - sahputra Ilham Saputra Ivan Maulana Kurniawati Kurniawati Lianita, Ervi M Taufiq Hariadi Masriadi Maulida Hasbi Mauliza Mauliza Mauliza Mauliza Mauliza Mauliza Mauliza Mauliza, Ade Mochamad Ari Saptari Muhammad Abdullah Ali Muhammad Abdullah Ali Muhammad Zikri Mukti Qamal Munirul Ula Mutammimul Ula Muzakir Nur Nazimah Nazimah Nunsina, Nunsina Nur Alimul Haq Nur, Muzakir Nurdin Nurdin Nurhasanah Nurhasanah Nurhasanah Rahma Fitria Rahma Fitria, Rahma Reyhan Achmad Rizal Ridwan Ridwan Rizki Setiawan Rizky Putra Fhonna Saptari, Mochamad Ari Setiawan, Rizki Sinambela, Reza Syahputra Syafitri, Siska Aulia Ulumul Haq, Bahrul Wardana, Ade Bagus WULANDARI Yesy Afrillia Yulisda, Desvina Yumna Rilasmi Said Yumna Rilasmi Said Yunia Silfitri yusliana, yusliana Zahratul Fitri, Zahratul Zuhra, Elviza

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