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All Journal MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer JSiI (Jurnal Sistem Informasi) Jurnal Ilmiah Sinus METIK JURNAL Jurnal Mantik Jurnal Vokasi G-Tech : Jurnal Teknologi Terapan INFOKUM Jurnal Sistem Informasi dan Sains Teknologi JINAV: Journal of Information and Visualization International Journal of Engineering, Science and Information Technology Jurnal Informatika dan Teknologi Komputer ( J-ICOM) Jurnal Tika Multica Science and Technology JUSTIN (Jurnal Sistem dan Teknologi Informasi) Brilliance: Research of Artificial Intelligence Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Malikussaleh Mengabdi Jurnal Pengabdian Nasional (JPN) Indonesia Gameology and Multimedia Expert Jurnal Solusi Masyarakat (JSM)
Veri Ilhadi
Universitas Malikussaleh
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Expert System Application for Identification of Chili Plant Diseases Using Forward Chaining and Oreste Methods Muthmainnah; Rizky Putra Fhonna; Safwandi; Veri Ilhadi
INFOKUM Vol. 10 No. 1 (2021): Desember, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (768.782 KB)

Abstract

Chili is a plant that has an important role in human life. Apart from being a source of vitamins, chili can also be used as a mixture of food and medicine. In the implementation of planting, chili plantings often fail, including crop failure due to various kinds of diseases. However, to find out the type of disease that attacks it requires an expert / agricultural expert, while in handling chili plant diseases it is often time-constrained due to the limited knowledge of the farmers and the lack of an expert who is an expert in this field who can go directly to farmers. Therefore, to overcome the problems of farmers, a system that has knowledge like an expert in this case has knowledge of the symptoms and diseases of chili plants. To answer this problem, a web-based expert system application will be built. The design of this system uses the forward chaining and oreste method which is intended to assist farmers in diagnosing chili plant diseases. Expert systems are used in all fields, one of which is in the field of food crops. One of the benefits of expert systems in the field of food crops is that it makes it easier for farmers to detect diseases in chili plants so that farmers can find out the type of disease and how to handle it quickly without having to wait for experts who have competence in that field.
Online Sales Application Typical Cake Aceh Based On Android Veri Ilhadi; Eka Rahma; Sayed Fachrurrazi
Jurnal Mantik Vol. 5 No. 4 (2022): February: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

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Abstract

The development of smartphones makes mobile-based technology considered very effective and efficient for humans, this device has presented various advanced facilities that can help and facilitate every user in doing work and other needs. Among them is marketing a product, including the typical cake in an area. Aceh is one of the destinations for domestic and foreign tourists. Marketing of Aceh's specialty cakes is a fundamental problem experienced by many cake industries. In addition to the cake industry, consumers who want to buy also have obstacles including not knowing the place, price, and number to contact. So to bridge this problem, an application is made that can help the Acehnese cake industry to promote its products more widely throughout Indonesia. This application was built using the SDLC  Waterfall, making it easier for researchers to identify problems and design systems according to the needs of the typical Aceh cake sales application. There are several stages, namely requirements analysis, system design, coding, program testing, and program implementation. This Aceh Typical Cake Sales Application for the Province of Aceh was built based on Android with an attractive, effective, and efficient appearance, making it easier for users to run it. After the implementation of this application, the results obtained are that consumers can place orders in real-time, the transaction process is easier and faster, thereby increasing the marketing of Acehnese cakes.
Pendeteksian Masker Secara Real-Time Menggunakan Tensorflow Untuk Pencegahan Covid-19 di Prodi Sistem Informasi Universitas Malikussaleh Rizky Putra Fhonna; Yesy Afrillia; Veri Ilhadi; Jamalul Aqmal; Teuku M. Arief Afwan
G-Tech: Jurnal Teknologi Terapan Vol 6 No 2 (2022): G-Tech, Vol. 6 No. 2 Oktober 2022
Publisher : Universitas Islam Raden Rahmat, Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (350.423 KB) | DOI: 10.33379/gtech.v6i2.1689

Abstract

COVID-19 telah menyebabkan perubahan pada kebiasaan dan cara hidup dalam bermasyarakat. Kesehatan menjadi prioritas utama, berbagai upaya dilakukan termasuk penerbitan regulasi kesehatan sebagai respon dari angka kasus terinfeksi yang meningkat sangat signifikan pada bulan Mei 2020. Untuk memudahkan dalam mencegah penularan virus di Prodi Sistem Informasi Universitas Malikussaleh, dikembangkan suatu sistem Artificial Inteligent pendeteksi masker realtime pada civitas akademika baik itu Dosen, Staf dan Mahasiswa sebagai objek penelitian dengan menggunakan Tensorflow berbasis pemogarman Python dan model binary classifier terlebih dahulu membangun sebuah model data traning dengan binary classifier untuk kemudian dilakukan pendeteksian dan pengujian secara realtime. Hasil dari pengujian dapat mendeteksi dan membedekan citra wajah yang menggunakan masker dan tidak dengan tingkat akurasi tinggi, yaitu nilai Accuracy di 0.9984 dan nilai loss epoch sebesar 0.0086.
IMPLEMENTASI MODEL DECISION DALAM PENENTUAN PEGAWAI TERBAIK PADA BMKG MALIKUSSALEH MENGGUNAKAN SIMPLE ADDITIVE WEIGHTING Veri Ilhadi; Mutammimul Ula
Jurnal Sistem Informasi dan Sains Teknologi Vol 5, No 1 (2023): Jurnal SIstem Informasi dan Sains Teknologi
Publisher : Universitas Trilogi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31326/sistek.v5i1.1560

Abstract

The decision support system in the decision model is something that is needed in every institution, both private and government, this requires a high level of accuracy in the process. Employee performance appraisal is also a matter of great concern with several standard criteria. decision models can be used in the assessment process needed in a decision making. The model used is Simple Additive Weighting (SAW) which is carried out with the provisions of the criteria and also weighting. This website was built using the Python programming language and Flash (library). The research methodology is based on the BMKG Malikussaleh assessment system which still uses manual calculations, namely the admin calculates one by one based on an assessment. The methodology of this research is to include the overall employee criterion values which will be processed using the SAW model and the results displayed on the web to determine the ranking value of the BMKG malikussaleh employees. Furthermore, the results of the best employee performance assessment based on the criteria selected Siswanto who was in first place the best employee
Penerapan KNN Penentuan Pelanggan Baru PDAM dan Clustering K- Means Berdasarkan Wilayah Mutammimul Ula; Muthmainnah; Ridha Maulana; Veri Ilhadi
Jurnal Informatika dan Teknologi Komputer (J-ICOM) Vol 4 No 1 (2023): Jurnal Informatika dan Teknologi Komputer ( JICOM)
Publisher : E-Jurnal Universitas Samudra

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33059/j-icom.v4i1.7494

Abstract

The Regional Drinking Water Company (PDAM) Tirta Gunung Pase is a company that distributes and provides drinking water services for the entire region of Lhokseumawe and North Aceh. This research aims to find new customers by determining new pairs and grouping each area in determining clusters in each region. This makes it easier for leaders to view collections by customer ID and the number of household group usage. The research methodology is to collect data at PDAM Tirta Mon Pase, then look at the classification with the KNN model and group it with the K-Means method. A final result is a group of regular customers and non-permanent customers with the variable customer id, house class, and several occupants of the house, and the respective values are seen from UA with a value of 5, RB value of 4, RC value 3, RD value two and SB value 1 with test data using 15 samples. The results of testing the KNN model by entering the customer id 25768, occupants of houses in groups 5 and 4 are included in the class 2 classification. Meanwhile, the customer id is 41162 with the results of group 4 classification and class 1 occupants 3 class 1. Kmeans clustering results for households, businesses and industrial companies. K-Result, while the results of the K-means method contained three clusters which showed that cluster 1 was 46.07%, cluster 2 was 39.79%, and cluster 3 was 14.13%.
Aplikasi Penerjemahan Aceh-Indonesia Berbasis Android Angga Pratama; Veri Ilhadi; Rachmad Muharram
Jurnal Tika Vol 8 No 1 (2023): Jurnal Teknik Informatika Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim Bireuen - Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51179/tika.v8i1.1715

Abstract

The Aceh-Indonesian dictionary can be used as a starting point for learning the Acehnese language. A dictionary is usually synonymous with a book, which sometimes presents difficulties when carrying it anywhere. Now, as technology develops, dictionaries can be made via an Android application, which makes it easy for users to bring dictionaries anywhere. This Aceh-Indonesian Dictionary application was created using the Java programming language and SQlite as a database storage medium based on the results of the average value acquired. The Likert Scale Questionnaire stated that 63% of users agreed that the Aceh-Indonesian Dictionary application was useful for learning Acehnese vocabulary. -Indonesia
Penerapan Fuzzy Times Series dan Regresi Linier dalam Melihat Stok Ketersediaan Beras Sayed Fachrurrazi; Angga Pratama; Syukriah Syukriah; Veri Ilhadi
METIK JURNAL Vol 7 No 1 (2023): METIK Jurnal
Publisher : LPPM Universitas Mulia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47002/metik.v7i1.561

Abstract

Salah satu komoditas terbesar Indonesia adalah beras. Dimana Perum Bulog berperan penting dalam menyediakan cadangan beras bagi negara untuk menjaga stabilitas nasional Menjelang panen raya, Perum Bulog harus menyusun strategi stok beras yang terencana dengan baik agar tetap tersedia. Karena harga pasar beras yang tinggi akan memicu ekspor beras dari luar negeri, maka harga gabah bisa turun saat petani panen raya akibat ekspor beras dari luar negeri jika pasokan beras Bulog menjadi langka. Ketika permintaan pasar akan beras tidak dapat dipenuhi, biasanya muncul persoalan ini. Penelitian ini dilakukan untuk meramalkan produksi beras nasional untuk kepentingan. Data yang digunakan dalam penelitian ini adalah data produksi stok beras nasional yang diperoleh dari bps.id dari tahun 2018 sampai dengan tahun 2021. Dimana uji harga beras kualitas premium untuk AFER sebesar 0,74444% dan RMSE sebesar 8,9422. Peramalan harga beras kualitas sedang nilai error AFER sebesar 0,22927% dan RMSE sebesar 1,732. Dan pengujian beras tidak bermutu diperoleh nilai error AFER sebesar 0,23640 dan RMSE sebesar 09,09439. Pengujian dengan menggunakan metode regresi linier diperoleh hasil peramalan kualitas beras premium; kualitas menengah dan luar memiliki hasil peramalan yang sama dengan nilai 87,62%, dengan demikian forecasting untuk harga beras sangat baik. Selanjutnya terlihat bahwa nilai akurasinya diatas 80% yang sangat tinggi dengan melalui pengujian.
Sistem Pengambilan Keputusan Penentuan Kualitas Biji Kopi Ekspor Menggunakan Metode TOPSIS dan VIKOR (Studi Kasus : Biji Kopi Ekspor Pada Tiap Koperasi) Angga Pratama; Rizki Mela Kurnia; Veri Ilhadi
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.v21i2.689

Abstract

Coffee, which has grown to be one of the most popular traditional plantation crops, contributes significantly to the economics of a coffee-producing region. Central Aceh, Bener Meriah, and Gayo Highlands are three of Indonesia's largest coffee-producing districts. A number of standards must be met in order for coffee beans to be regarded high grade and fall into the category of quality beans. TOPSIS and VIKOR methods were utilized in this research to develop a decision support system for assessing the quality of exporting beans. This system generates a rating as an output based on input values and weights, with weight values that can be adjusted by the chosen criteria. The purpose of this research is to develop software for grading coffee beans based on user input such as bean flaws, water volume, bean size, bean color, and aroma. Moreover, after two methods had been evaluated, TOPSIS method with the results of Gayo Permata cooperative with Grade 1 Arabica Gayo Coffee was recognized as the most effective method. Based on the results of KBQ Baburrayan cooperative using Arabica Gayo Coffee, TOPSIS is closer to the ideal solution than the VIKOR approach.
Comparing Long Short-Term Memory and Random Forest Accuracy for Bitcoin Price Forecasting Munirul Ula; Veri Ilhadi; Zailani Mohamed Sidek
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol 23 No 2 (2024)
Publisher : LPPM Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i2.3267

Abstract

Bitcoin’s daily value fluctuations are very dynamic. Understanding its rapid and intricate price movements demands advanced techniques for processing complex data. This research aims to compare the accuracy of two machine learning methods, Random Forest (RF) and Long Short-Term Memory (LSTM), in predicting Bitcoin price. This research employs RF and LSTM algorithms to forecast Bitcoin prices using a two-year Yahoo Finance dataset. The evaluation metrics used were accuracy based on Mean Absolute Percentage Error (MAPE) and computational power (CPU-Z). As a result of this research, the LSTM model demonstrates higher accuracy compared to the RF model. MAPE reveals LSTM’s precision of 99.8% and RF’s accuracy of 90.1%. Regarding computational time and resources, RF shows slightly better performance than LSTM. The visual comparison further emphasizes LSTM’s better performance in predicting Bitcoin prices, highlighting its potential for informed decision-making in cryptocurrency trading. This research contributes valuable insights into the effectiveness, strengths, and weaknesses of LSTM and RF models in predicting cryptocurrency trends.
Analisis Evaluasi Kelayakan Kepuasan Siswa dalam Materi Pembelajaran dengan Model K-Nearest Neighbor Arief; Veri Ilhadi; Irma Yurni
Jurnal Tika Vol 9 No 1 (2024): Jurnal Teknik Informatika Aceh
Publisher : Fakultas Ilmu Komputer Universitas Almuslim Bireuen - Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51179/tika.v9i1.2746

Abstract

Evaluation of student satisfaction is an important component in the educational process. This research aims to assess the level of student satisfaction with learning material. The analysis used is satisfaction survey analysis in viewing variables, analyzing variables and quantitative data analysis. The importance of a personal approach in education, where effective teaching skills and quality interaction between teachers and students play a vital role in increasing learning satisfaction. The importance of the analysis shows that the KNN model has high accuracy in classifying student satisfaction levels. The research results show that student satisfaction is influenced by the relevance of the material, teaching methods, and interaction with the instructor. The results of this research provide recommendations for increasing student satisfaction including curriculum adjustments, teacher training, and development of more interactive learning materials. It is hoped that this research can provide valuable input for schools and educators in improving the quality of teaching and relationships with students. Analyze the KNN model to find the largest number of classes from the nearest neighbors and set that class as the test data class. In the ranking order there are more satisfied categories. So, data with rk = (5; 8; 8; 9) is included in the Satisfied category. analysis results: V1 is Dissatisfied with a value of 2, V2 with a Satisfied value of 2.828, V3 is Satisfied with a value of 3.464, V4 with a Dissatisfied value of 3.605 and finally V5 with Satisfied worth of 4.123.
Co-Authors - Fakhrurrazi Achmad Noerkhaerin Putra Afra, Liza Aidilof, Hafizh Al Kautsar Akbar, Jamalul Amanda, Diana Andrian, Deny Angelina, Difa Angga Pratama Angga Pratama ANNISA KARIMA Ardiansyah, Danil Arief Arief Rahman Arief Rahman Arif, Abdul Halim Arif, Rijalul Arifa, Tiara Minda Asran Asran Ayu Widari, Lis Bukhari, Fiona Burhanuddin Burhanuddin Chairil Anwar Cut Agusniar EDI YUSUF, EDI Edo Prandahlan Eka Rahma Emi Maulani Ezwarsyah Ezwarsyah F Saragih, Annisa Fakhruddin Ahmad Nasution Fakhrurrazi Hidayat, Amam Taufiq Ilham Sahputra Irma Yurni Irvan Na’syakban Irwansyah, Defi Jamalul Aqmal Khaira, Miftahul Khairul Amna, Khairul Kurniasi, Arni Astuti lia melani, lia Maulidin, Muhammad Misbahul Jannah Muhammad Gaffar Kamata MUHAMMAD HABIB Muhammad Muhammad Muharram, Rachmad Muliana Muliana Munirul Ula Mutammimul Ula MUTHMAINNAH Muthmainnah Muthmainnah Muthmainnah Muthmainnah Nazariah, Cut Pandiana, Annisa Putra Fhonna, Rizky Rachmad Muharram Rahma Fitria, Rahma Ridha Maulana Rizki Mela Kurnia Rizky Putra Fhonna Rosdiana Rosdiana Rosdiana Rosdiana Safwandi Safwandi Sahputra , Ilham Sahputra, Ilham Salahuddin Salahuddin Salamah Saptari, Mochamad Ari Sari, Indah Maulida Sayed Fachrurrazi Selian, Riko Ardiansyah Sidek, Zailani Mohamed Siti Fatimatun Zahro Sujacka Retno Sukiman, T. Sukma Achriadi Syukriah Syukriah Syukriah Syukriah, Syukriah Teuku M. Arief Afwan Ulya, Athiyatul Wahyu Fuadi Yesy Afrillia Yulisda, Desvina Yurni, Irma Zailani Mohamed Sidek Zohra, Siti Fatimah A Zuhra, Amna Zulfia , Anni