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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Techno.Com: Jurnal Teknologi Informasi CESS (Journal of Computer Engineering, System and Science) JOIV : International Journal on Informatics Visualization Sinkron : Jurnal dan Penelitian Teknik Informatika JOURNAL OF INFORMATICS AND TELECOMMUNICATION ENGINEERING Jurnal Teknoinfo Riau Journal of Empowerment Jurnal Informatika Kaputama (JIK) Jusikom: Jurnal Sistem Informasi Ilmu Komputer JATI (Jurnal Mahasiswa Teknik Informatika) JTIK (Jurnal Teknik Informatika Kaputama) Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Journal of Computer Networks, Architecture and High Performance Computing Jurnal Anugerah: Jurnal Pengabdian Kepada Masyarakat Bidang Keguruan dan Ilmu Pendidikan INCODING: Journal of Informatics and Computer Science Engineering Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Ilmiah Teknik Informatika & Elektro (JITEK) JUSTINDO (Jurnal Sistem dan Teknologi Informasi Indonesia)
Rizki Muliono
Universitas Medan Area
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Social Sciences Other

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Rancang Bangun Aplikasi Penerjemah Bahasa Indonesia Bahasa Nias Menggunakan Algoritma Levensthein Distance Laia, Aldi Irfan; Muliono, Rizki
INCODING: Journal of Informatics and Computer Science Engineering Vol 4, No 1 (2024): INCODING APRIL
Publisher : Mahesa Research Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34007/incoding.v4i1.469

Abstract

In this context, there is a need for the development of a translator application that can translate between Indonesian and Nias languages. The aim of this research is to design and build an Android-based translator application that can translate text from Indonesian to Nias and vice versa.In this study, the Levenshtein Distance algorithm was used as a method to perform the translation process. This algorithm uses the calculation of the distance between two strings to identify the similarities and differences between words in Indonesian and Nias. Thus, the Levenshtein Distance can be used to produce accurate and relevant translation results.The design and development of the translator app was done using the Android platform as the development base. The application is designed to provide an intuitive and easy-to-use user interface, thus allowing users to quickly and efficiently translate texts into Indonesian and Nias languages. During the development process, the translator application was tested to ensure good quality and performance. The test results showed that the translation application was capable of producing accurate translations in accordance with the context of the Indonesian language and the Nias language. In conclusion, the research successfully designed and built an Android-based Indonesian-Nias language translator application using the Levenshtein Distance algorithm. This application is expected to be a useful tool in facilitating communication between Indonesian-speaking users and the Nias language. This research also contributed to the development of Nias-based translator applications that were still limited in previous literature.
Analisis Persebaran Penyakit di Wilayah Menggunakan Algoritma K-Means Berbasis Data Kunjungan Fasilitas Kesehatan Suhaira, Zatin; Muliono, Rizki
INCODING: Journal of Informatics and Computer Science Engineering Vol 5, No 2 (2025): INCODING OKTOBER
Publisher : Mahesa Research Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34007/incoding.v5i2.983

Abstract

This study aims to analyze the distribution of diseases based on patient visit data to various healthcare facilities using the K-Means clustering method. The research data were obtained secondarily from the Kaggle platform, namely the ‘Healthcare Dataset’, which contains patient information, including healthcare facility attributes, medical conditions, and other related data. The determination of the optimal number of clusters was carried out using the Elbow Method, while the quality of clustering was evaluated with two internal metrics, namely the Silhouette Score and the Davies–Bouldin Index (DBI). The clustering results produced three main clusters with distinct characteristics. The first cluster was dominated by patients diagnosed with arthritis in the age group of 55–59 years with blood type O+. The second cluster showed a predominance of obesity in the age group of 35–39 years with blood type AB+, while the third cluster indicated cancer cases in the age group of 65–69 years with blood type O-. The evaluation resulted in a Silhouette Score of 0.5349 and a DBI of 0.5830, indicating that the clustering quality is fairly good, with compact and well-separated clusters. These findings not only highlight variations in disease distribution across healthcare facilities but also provide a foundation for mapping disease patterns and supporting strategic decision-making in public health..
JARINGAN SYARAF TIRUAN PENGENALAN POLA HURUF DENGAN JARINGAN HEBB Muliono, Rizki; Lubis, Juanda Hakim
JTIK (Jurnal Teknik Informatika Kaputama) Vol. 2 No. 1 (2018): Volume 2, Nomor 1, Januari 2018
Publisher : STMIK KAPUTAMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59697/jtik.v2i1.672

Abstract

Pengenalan pola karakter dalam ilmu artifisial intelegen merupakan metode yang sangat bekembang cepat dan terus dikembangkan hingga saat ini, kebutuhan akan keamanan informasi dan sekuritas sebuah informasi ataupun device bisa di block dengan menggunakan sebuah sistem yang tertanam sebuah kemampuan ataupun fitur dalam pengenalan pola. Model ini bisa diterapkan baik pada pegenalan pola wajah, pola sidik jari. Dalam artikel ini akan di bahas tentang analisi pengenalan pola sederhana dengan menggunakan jaringan syaraf tiruan yaitu metode hebbian. Dengan dua pola awal sebagai pengetahuan atau learningbase nya dan kemudian diuji dengan pola – pola inputan baru yang akan di cek kemiripannya dengan kedua pola learning base apakah di kenali sebagai pola satu atau sebagai pola dua. Dengan menggunakan 25 variabel input dan bias 1 dengan nilai bobot awal 0, pola U dan S di inisialisasi dengan karakter x bernilai 1 dan karakter o bernilai -1 dengan output bipolar, U tareget 1 dan S target -1, fungsi f(net) adalah 1 jika Y >= 0 dan -1 jika Y < 0. Jaringan yang telah terbentuk dari dua pola awal yang telah di kenali kemudian weigh jaringan di test dengan pola 6, 3, U’ dan 8 maka di dapat hasil adalah pola 6 dan 3 dikenali atau mendekati mirip S dan U’ mendekati U.
Co-Authors -, Muhathir Akbar Siregar, Muhammad Alwi, Buchori Bunaya Arthavia Sitorus Darkani, M. Farhan Dedi Sahputra Effiati Juliana Hasibuan Esrayanti Simanjuntak Fikri, Ridho Ahmad Harahap , Ryanda Fadillah Hasibuan, Samsul Abdul Rahman Sidik Hasudungan, Andre Hidayah, Safrina Ida Royani Irfansyah Iswandi Iswandi Juanda Hakim Lubis Juanda Hakim Lubis Laia, Aldi Irfan Marischa Elveny, Marischa Marpaung, Febriady Merri Hafni Muhammad Farhan Darkani Muhammad Hamdani Santoso Muhathir Muhathir Muhathir Muhathir, Muhathir Muhathir, Muhathir Nanda Novita, Nanda Napisah, Napisah Nurul Hidayani Nurul Khairina Nurul Khairina Prasetyo , Dewo Putri, Riza Dwi Razaq, Faisal Sandy, Boy Siahaan, Ricardo Fransdoli Siregar, Yusril Izza Haholongan Sitopu, Essay Puspita Sri Juwita Sri Wahyuni Suhaira, Zatin Supriatno, Supriatno Susilawati Susilawati Susilawati Susilawati, Susilawati Theofil Tri Saputra Sibarani Tino Hermanto Y. Syah, Rahmad B. Yopan Rahmad Aldori Zebua, Meniati Zulfikar Sembiring Zulfikar Sembirirng