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All Journal Teknika Techno.Com: Jurnal Teknologi Informasi Jurnal Informatika PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Jurnal Teknologi Informasi dan Ilmu Komputer CESS (Journal of Computer Engineering, System and Science) JURNAL PENGABDIAN KEPADA MASYARAKAT Jurnal Ilmiah KOMPUTASI Sistemasi: Jurnal Sistem Informasi JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING IT JOURNAL RESEARCH AND DEVELOPMENT Indonesian Journal of Artificial Intelligence and Data Mining JRST (Jurnal Riset Sains dan Teknologi) Jurnal Teknovasi : Jurnal Teknik dan Inovasi Mesin Otomotif, Komputer, Industri dan Elektronika JOURNAL OF APPLIED INFORMATICS AND COMPUTING Jusikom : Jurnal Sistem Komputer Musirawas ALGORITMA : JURNAL ILMU KOMPUTER DAN INFORMATIKA JISTech (Journal of Islamic Science and Technology) Jurnal Teknologi Sistem Informasi dan Aplikasi JSiI (Jurnal Sistem Informasi) IJISTECH (International Journal Of Information System & Technology) Journal on Education JOURNAL OF SCIENCE AND SOCIAL RESEARCH Jurnal Teknik Elektro dan Komputer TRIAC Jurnal Riset Informatika INFOMATEK: Jurnal Informatika, Manajemen dan Teknologi METIK JURNAL Jurnal Ilmiah Ilmu Komputer Fakultas Ilmu Komputer Universitas Al Asyariah Mandar Jurnal Mantik Journal of Information Systems and Informatics INFOKUM U-NET Jurnal Teknik Informatika Journal of Computer Networks, Architecture and High Performance Computing Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknik Informatika (JUTIF) IJISTECH Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) Jurnal Computer Science and Information Technology (CoSciTech) International Journal of Artificial Intelligence and Robotics (IJAIR) Jurnal Pendidikan dan Teknologi Indonesia Journal La Multiapp KLIK: Kajian Ilmiah Informatika dan Komputer Jurnal Info Sains : Informatika dan Sains Jurnal IPTEK Bagi Masyarakat Journal of Computer Science and Informatics Engineering Journal Of Human And Education (JAHE) Prisma Sains: Jurnal Pengkajian Ilmu dan Pembelajaran Matematika dan IPA IKIP Mataram International Conference on Sciences Development and Technology Innovative: Journal Of Social Science Research Jurnal Pengabdian Masyarakat VISA: Journal of Vision and Ideas Cosmic Jurnal Teknik
Muhammad Siddik Hasibuan
Universitas Islam Negeri Sumatera Utara
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities 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 Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

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Prototype of pH and Water Temperature Control System in Discus Fish Farming Using IoT-based Sugeno Fuzzy Ahmad al-Badawi, Abdullah; Ikhsan, Muhammad; Siddik Hasibuan, Muhammad
International Journal of Artificial Intelligence & Robotics (IJAIR) Vol. 6 No. 1 (2024): May 2024
Publisher : Informatics Department-Universitas Dr. Soetomo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25139/ijair.v6i1.7524

Abstract

Challenges in cultivating discus fish often arise from abrupt pH and temperature fluctuations attributed to manual and sluggish intervention. An IoT-based prototype for automatic pH and water temperature regulation was developed to address this. The study aimed to evaluate the efficacy of the prototype in controlling pH levels and water temperature and to explore the application of IoT-based fuzzy logic in discus fish cultivation. Test data from the implemented tools and sensors revealed an error comparison value of 0.0132% and an accuracy level of 99.986% for pH measurement. In comparison, temperature sensing yielded an error value of 0% with 100% accuracy. The IoT-based fuzzy Sugeno system demonstrated regular and effective operation in regulating pH and water temperature in discus fish cultivation, showcasing superiority over manual handling systems in mitigating sudden environmental changes.
Comparison of Apriori and FP-Growth Algorithms in Analyzing Association Rules Mitha Rosadi; Muhammad Siddik Hasibuan
PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Vol. 12 No. 2 (2024): September 2024
Publisher : LPPM Universitas Islam 45 Bekasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33558/piksel.v12i2.9965

Abstract

The problem objectives of this research include the following: To implement Apriori and FP-Growth Algorithms in determining the comparison of association rules and To build a jupyter notebook application model in determining the comparison of association rules of Apriori and FP-Growth Algorithms. This research compares Apriori and FP-Growth algorithms in analyzing association rules, with a focus on implementation and model development in Jupyter Notebook. Through manual calculation using 10 transaction data samples and testing on 38,765 groceries data entries from Kaggle, differences were found in the lift results between itemsets. Apriori algorithm often shows a negative relationship between items, while FP-Growth gives a similar interpretation but with slightly different lift values, showing a different influence in the relationship between items. In addition, FP-Growth proved to be more efficient with a much faster execution time (5.2757 seconds) than Apriori (185.9585 seconds), especially in handling large datasets. The results of this study indicate that the selection of an appropriate algorithm should consider the characteristics of the dataset and the purpose of the analysis.
Model rapid application development dalam pengembangan sistem informasi pengarsipan surat Harahap, Raihan; Muhammad Fadiga; Fadhli Rizqi Haidar Pane; Muhammad Siddik Hasibuan
Computer Science and Information Technology Vol 4 No 3 (2023): Jurnal Computer Science and Information Technology (CoSciTech)
Publisher : Universitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/coscitech.v4i3.6267

Abstract

Archiving is essential in managing a collection of documents. Although archiving is now available in a web-based form, there are still agencies that use letter archives in a conventional way. This study was made to develop a web-based letter archive application for one of the government institutions in Medan, i.e. the Secretariat of the North Sumatra DPRD. This study uses two types of methods, namely research methods and system development methods. The research method used is a qualitative method with a research design in the form of observation and literature study. In addition, the system development method used is rapid application development (RAD). In addition, to design the application, researchers used XAMPP software to create MySQL as the database, JavaScript, PHP and Visual Studio Code as the programming language, as well as HTML and CSS to organize the web display. After that, the application is tested with the black box testing method. The results show that overall the features on the user function properly.
Literasi Digital : Pemanfaatan dan Penggunaan E-Library Menggunakan Software SLiMS" di Desa Denai Lama, Pantai Labu-Deli Serdang Zufria, Ilka; Hasugian, Abdul Halim; Suhardi; Hasibuan, Muhammad Siddik; Lubis, Aidil Halim; Armansyah
Jurnal Pengabdian Masyarakat Vol. 1 No. 1 (2022): Juni 2022
Publisher : Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/japamas.v1i1.7

Abstract

Information technology has developed very rapidly and covers various fields. The field of education is one area that is influenced by information technology. Both in the formal learning process at school and non-formal in the form of training outside of school. The form of participation from universities, especially the Computer Science study program, FST UIN North Sumatra Medan, in this community service activity is to provide skills training in the field of information technology in the form of digital literacy and the use of SLiMS software to the Circle Community Reading Park (TBM), Denai Lama Village, Labu Beach. Deli Serdang, North Sumatra which was held with the theme "Digital Literacy: Utilization and Use of E-Library Using SLiMS Software".
Determining the Main Priority in the Assessment of Hollywood Horror Films by Applying the AHP and SAW Methods Hasibuan, Muhammad Siddik; Irawan, Muhammad Dedi; Pratama, Dian Agus; Yudhistira, Yudhistira
International Conference on Sciences Development and Technology The 1st ICoSDTech 2021
Publisher : International Conference on Sciences Development and Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (382.555 KB)

Abstract

Film is one of the many modern communication media that is very effective to be used as a medium of entertainment as well as a place to convey moral messages that can influence the audience both from the aspect of attitude, point of view of thought and also insight. For this reason, the production house is required to continue to create a film of the highest quality. Because the proliferation of these types of horror films makes it difficult for viewers to determine which Hollywood horror film is the best version, this is also one of our goals in designing a web-based system. In this case study, the Analytical Hierarchy Process (AHP) and Simple Additive Weighting (SAW) methods are used to determine the best priority for each alternative assessment. The assessment procedure is based on predetermined criteria. The criteria used as assessment provisions are budget, film duration, audience rating, film rating, film awards and film revenues. The method used is to compare the AHP and SAW methods as well as the results of calculations from the system. The results of the discussion include the stages of assessment and comparison of each method used and are able to appoint the best alternative in the selection of Hollywood horror films.
Lobster Sales Prediction Using Adaptive Neuro Fuzzy Inference System (ANFIS) In Simeulue District Sandira, Sri Delwis; Kurniawan, Rakhmat; Hasibuan, Muhammad Siddik
IJISTECH (International Journal of Information System and Technology) Vol 7, No 6 (2024): The April edition
Publisher : Sekolah Tinggi Ilmu Komputer (STIKOM) Tunas Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/ijistech.v7i6.339

Abstract

The rapid progress of technology and information is making the challenges of the past become a tantalizing reality of the fourth industrial revolution. Rapid technological progress is marked by major developments in all aspects of life, such as economics, education, health, social and cultural. In the economic world, increasingly sophisticated technological developments will help the work of business actors and force them to innovate and be creative in improving the quality, capacity and products produced. With the vast lobster market, lobster demand experiences a sharp increase every year along with an increase in prices which will provide profits for fishermen in Simeulue. Therefore, predictions of lobster sales are quite important for fishermen in Semeulue to predict lobster sales that will be marketed abroad and domestically the following day, so that fishermen can estimate the lobster seeds or lobster catch needed optimally. In the prediction process The sales data obtained is in the form of a sales history report from 2017 to 2022, then the data obtained will be calculated using the adaptive neuro fuzzy inference system (ANFIS) to then obtain sales prediction results for the following year. And using MAPE calculations with the results of lobster sales training data calculations, the accuracy yields above 99% with a value of 0.0000168031. Therefore, this research will discuss predictions of lobster sales using the adaptive neuro fuzzy inference system (ANFIS) in Simeulue Regency.
Clustering Daerah Rawan Angin Puting Beliung Pada Kabupaten Di Sumatera Utara Dengan Algoritma K-Means Ramadhan, Rizky Syahrul; Rakhmat Kurniawan R; Muhammad Siddik Hasibuan
Jurnal Ilmiah Komputasi Vol. 23 No. 2 (2024): Jurnal Ilmiah Komputasi : Vol. 23 No 2, Juni 2024
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32409/jikstik.23.2.3578

Abstract

Provinsi Sumatera Utara merupakan daerah dengan topografi yang berbeda-beda di tiap kabupatennya dimana terdiri dari dataran tinggi, dataran rendah, pegunungan dan pantai. Dengan keadaan seperti itu sering terjadi bencana alam salah satunya angin puting beliung. Masalah yang terjadi adalah bagaimana mengetahui daerah yang rawan angin puting beliung agar mengurangi kerugian dan korban jiwa. Salah satu cara yang dapat dilakukan adalah untuk mengetahui daerah yang rawan angin puting beliung adalah dengan menggunakan teknik data mining. Adapun metode yang digunakan dalam penelitian ini adalah algoritma k-means clustering. Algoritma k-means clustering dapat mengelompokkan data yang memiliki karakteristik yang sama menjadi satu kelompok dan data yang memiliki karakteristik yang berbeda dikelompokkan menjadi kelompok lainnya. Data yang digunakan yaitu parameter angin puting beliung dari 33 kabupaten/kota dan 181 column data. Hasilnya diperoleh cluster 0 atau daerah dengan potensial rawan bencana angin puting beliung rendah sebanyak 19 daerah dan cluster 1 atau daerah dengan potensial rawan bencana angin puting beliung tinggi sebanyak 14 daerah.
Classification of Watermelon Ripeness Levels Using HSV Color Space Transformation and K-Nearest Neighbor Method Efendi, Ayu Mahriza Agustin; Sriani, Sriani; Hasibuan, Muhammad Siddik
Journal of Computer Networks, Architecture and High Performance Computing Vol. 6 No. 3 (2024): Articles Research Volume 6 Issue 3, July 2024
Publisher : Information Technology and Science (ITScience)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/cnahpc.v6i3.3999

Abstract

Watermelons had high appeal due to their sweet taste, refreshing nature, and numerous benefits. However, consumers often faced difficulties in selecting suitable fruit because of the subtle differences between fully ripe and half-ripe watermelons. One important indicator of a watermelon’s ripeness was the yellowish pattern on its skin. In this study, the proposed use of digital image processing methods, specifically the HSV Color Space Transformation, was aimed at extracting watermelon images and employing the K-Nearest Neighbor (K-NN) method to classify them into two categories: "Ripe" and "Half-Ripe." HSV (Hue Saturation Value) was a color extraction method used to convert colors from the RGB model. The Hue component indicated the type of color, Saturation measured the purity of the color, and Value measured the brightness of the color on a scale from 0 to 100%. In this research, the K-Nearest Neighbor (K-NN) method was applied to classify watermelon images based on the extraction of skin color features. This method compared a new image (test data) with training images to determine classification based on the nearest distance with a parameter of k=3. The data used consisted of 120 images, with 92 images used as training data and 28 images as test data. Experimental results showed an accuracy of 89%, with 25 images correctly classified and 3 images misclassified.
Implementation of a Convolutional Neural Network Algorithm in Classifying Vegetable Freshness Based on Image Handira, Dysa; Hasibuan, Muhammad Siddik
Journal La Multiapp Vol. 5 No. 4 (2024): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v5i4.1461

Abstract

The purpose of this work is to apply CNN algorithm to a real problem of vegetable freshness identification using image data. Quantitative approach was used for this study and the data source was obtained from Kaggle; it is referred to as Fresh and Stale Images of Fruits and Vegetables with 2,604 images, four categories in total. The CNN model architecture consisted of a basic organization of four successive convolutional layers with associated max-pooling layers that aimed at capturing hierarchical feature representations of the input images. This model was trained using the Adam’s optimizer for 20 iterations with the batch size of 32. Pre-processing of data included image augmentations such as scaling, rotation, flipping which improved the performance of the model. The assessment was done using Confusion Matrix approach and the results show that the proposed system achieved an accuracy of 95%, with a precision of 94%, recall of 93% and F1-score of 93%. From this it can be concluded that the CNN model proposed has achieved the objective of distinguishing fresh and non-fresh vegetables with enough precision to assist in the automation of quality control in agriculture. The conclusion that can be drawn from this study is that AI especially CNNs could be of big help in increasing accuracy and decreasing human factors in the large scale production of food.
Analysis of the Corpus with Naïve Bayes in Determining Sentiment Labeling Aulia, M. Arif; Hasibuan, Muhammad Siddik
Journal La Multiapp Vol. 5 No. 4 (2024): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v5i4.1465

Abstract

The raw form of data is also an issue that creates a lot of problems while attempting to extract useful insight, thus requiring the use of NLP algorithms for text mining. This paper discusses sentiment analysis, with emphasis on user comments regarding cars on the microblog X that was formerly known as Twitter, work which employs Naïve Bayes Algorithm in text categorisation. The steps involved are the formation of the corpus and use of InsetLexicon dictionary for sentiment analysis with the help of weighted keywords and then going through pre-processing of the text data that includes cleaning, normalization and tokenization. The Naive Bayes algorithm estimates the probability of text under positive or negative sentiment class. The work shows that the “Comfortable” component of car reviews obtained the highest score in terms of recall, precision, and F1-score, which equals 0.83, 0.85, and 0.563, and the second set consists of 87 instances overall including an overall data set accuracy of 71%. The result validates the use of lexicon-based sentiment analysis in specific domain and at the same time exposes the weakness of the Naive Bayes, especially with complex word dependencies. Further studies should incorporate more advanced models and suitable dictionaries which facilitate sentiment analysis in ever-shifting online media settings.
Co-Authors Abdul Halim Hasugian Ahmad Affandi Rasyad Nasution Ahmad al-Badawi, Abdullah Aidil Halim Lubis Aidil Halim Lubis Ali Darta Ananda, Rizkika Andi Andi Anisa Simanjuntak Armansyah Asti, Dini Aulia Nurhasanah, Dhea Aulia, Dhinanda Aulia, M. Arif Bela Sapitri Br Sembiring, Trisna Amanda Dicky Adityanta Sinuraya Efendi, Ayu Mahriza Agustin Erwin Nasution Fadhli Rizqi Haidar Pane Fatih Muhammad, Aji Haikal, Baginda Fikri Hamzah, Aldiva Handira, Dysa Harahap, Parlindungan Harahap, Raihan Hasibuan, Bunga Lestari Heri Santoso Hisbullah, Riki Hotmaidah Harahap Hutabarat, Dio Wahyu Habibi Ichsan Rafisyah Ilka Zufria Indah Permata Sari Ivan Prayuda Khairani Ritonga, Putri Kurniawan, Riski Askia Lestari, Rika Dinda Lipantri Mashur Gultom Lorena, Ayu Lubis, Muhammad Taufik Hakim Lubis, Putri Natasya Mahdiania, Diania Marpaung, Devi Aryani Mhd Furqan Mhd Ikhsan Rifki Mitha Rosadi Mrg, Ricky Aulia Muhammad Abi Muzaki Muhammad Dedi Irawan Muhammad Fadiga Muhammad Ikhsan Muhammad Zulfahmi Nasution Mukhairi Rizal, Muhammad Nasution, Yusuf Ramadhan Naufal, Rahmad Piramida, Piramida Pratama, Dian Agus Rahman, Anisa Rahmat Kurniawan Rahmat Kurniawan R Rakhmat Kurniawan R Ramadhan, Rizky Syahrul Rangkuti, M. Naufal Reza Adhitya Budiman Riska Hasibuan Rizkika Ananda Rosadi, Mitha Sandira, Sri Delwis Selian, Suci Nadillah Serdano, Akbar Sholihin, Sazili Siagian, Qori Azmi Ayasy Sinuraya, Dicky Adityanta Siregar, Putri Aprilia Sita Kirana Atikah Siti Nurhaliza Sofyan Sri Wahyuni Sriani Sriani Suendri Suhardi Suhardi Suhardi, Suhardi Supiyandi Supiyandi Syahputra, Surya Syahputri, Cindy Novi Syaqila, Saidatus Tanjung, Tajuddin Tarigan, Mayang Safhira Triase Triase, Triase Utomo, Imam Yudhistira, Yudhistira Yusuf Karim Rambe Yusuf Ramadhan Nasution Yusuf Ramadhan Nasution, Yusuf Ramadhan