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All Journal JUITA : Jurnal Informatika Sinkron : Jurnal dan Penelitian Teknik Informatika CogITo Smart Journal JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Voice Of Informatics Jurnal Riset Informatika Informatika : Jurnal Informatika, Manajemen dan Komputer CSRID (Computer Science Research and Its Development Journal) SENSITEK E-JURNAL JUSITI : Jurnal Sistem Informasi dan Teknologi Informasi IT (INFORMATIC TECHNIQUE) JOURNAL Yumary: Jurnal Pengabdian kepada Masyarakat JUDIMAS (Jurnal Inovasi Pengabdian Kepada Masyarakat) Syntax: Journal of Software Engineering, Computer Science and Information Technology Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) INFOSYS (INFORMATION SYSTEM) JOURNAL Joong-Ki : Jurnal Pengabdian Masyarakat Information System and Data Science Joong-Ki PUBLIDIMAS CSRID Joong-Ki
Sinaga, Mikha Dayan
Universitas Satya Terra Bhinneka
Religion Aerospace Engineering Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Social Sciences Other

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Analisis Model Keputusan Dengan Metode TOPSIS untuk Menilai Kualitas Air Minum Isi Ulang Sinaga, Mikha Dayan; Hardiyanti, Yeni; Sembiring, Nita; Haryanto, Edy Victor; Nababan, Labuan; Sianturi, Charles Jhony Mantho
CSRID (Computer Science Research and Its Development Journal) Vol. 17 No. 1 (2025): Februari 2025
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.17.1.2025.20-32

Abstract

Water is one of the basic needs for every living thing, including humans. About three-quarters of our body consists of water and no one can survive more than 4-5 days without drinking water. Drinking water with clean quality is very important for the human body, because if the water drunk is not clean water, it will cause various diseases in the human body. Quality drinking water is very important for water depot businesses as one of the attractions in product marketing, if wrong in determining the quality of water, it will have an impact on decreasing marketing and sales of the business, so that business profits are not optimal. The problem that many drinking water depot business actors face today is the difficulty of determining suppliers of quality drinking water providers based on detection of drinking water quality so that the water produced is in accordance with health standards. The TOPSIS method (Technique for Order of Preference by Similarity to Ideal Solution) is one of the decision-making techniques that can be used to evaluate various alternatives based on predetermined criteria. The results of the study showed significant variations in the quality of refill drinking water among the samples tested. Based on the calculation using the TOPSIS method, Supplier A obtained the highest ranking with a preference score of 0.61493219, while Supplier 5 had the lowest ranking with a score of 0.16023232. This study emphasizes the importance of selecting a quality water provider and the need for stricter supervision from the government. The results of the study are expected to provide useful information for consumers and refill drinking water providers, as well as become a basis for further research in the field of water quality.
Pendampingan Pembuatan dan Editing Video Dokumentasi Pada Kegiatan Studi Banding Kecamatan Dolat Rayat Nita Sari Br Sembiring; Mikha Dayan Sinaga; Marlina Manurung; Erwin Ginting; Noprita Elisabeth Sianturi; Frinto Tambunan
Publikasi Pengabdian Masyarakat Vol 3 No 2 (2023): PUBLIDIMAS Vol. 3 No. 2 NOVEMBER 2023
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/publidimas.v3i2.249

Abstract

Kecamatan Dolat Rayat merupakan salah satu Kecamatan yang berada di Kabupaten Karo Provinsi Sumatera Utara. Kecamatan Dolat Rayat memiliki beberapa desa yang berpotensi dibuat menjadi Desa Wisata. Dalam proses untuk menjadi suatu Desa Wisata yang baik maka perlu dilakukan studi banding ke Desa Wisata yang telah terkenal atau yang telah sukses mendatangkan wisatawan. Desa Wisata Penglipuran yang terletak di Kabupaten Bangli merupakan salah satu Desa Wisata yang telah terkenal di Indonesia dan dapat menjadi contoh bagi pengembangan Desa Wisata di daerah lain. Kegiatan studi banding harus memiliki dokumentasi yang baik sehingga dapat dilihat dan dipahami kembali guna mencapai tujuan yang telah ditargetkan. Kegiatan pengabdian ini dimulai dengan sesi wawancara dengan beberapa staf Kecamatan Dolat Rayat tentang proses pengambilan video dan gambar dokumentasi serta cara untuk mengedit video dan gambar dokumentasi tersebut. Setelah proses wawancara dilakukan, diketahui masih ada beberapa staf yang belum mengetahui tentang tata cara pengambilan video dan gambar dokumentasi yang baik dan bagaimana cara untuk mengedit video dan gambar tersebut agar memperoleh hasil yang terbaik. Kegiatan pengabdian ini merupakan kegiatan pendampingan pembuatan dan editing video dalam kegiatan studi banding Kecamatan Dolat Rayat ke Desa Penglipuran, Kabupaten Bangli, Bali. Kegiatan ini bertujuan untuk menambah pengetahuan dan wawasan staf Kecamatan dalam proses pembuatan dan editing video dengan hasil yang terbaik.
Peningkatan Pemahaman Pegawai Kecamatan Dolat Rayat Terkait Aplikasi CapCut Melalui Pendampingan Pembuatan Video Dokumentasi Sembiring, Nita; Sinaga, Mikha Dayan; Manurung, Marlina; Sianturi, Charles Jhony Mantho; Ginting, Erwin
Publikasi Pengabdian Masyarakat Vol 4 No 2 (2024): PUBLIDIMAS Vol. 4 No. 2 NOVEMBER 2024
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/publidimas.v4i2.397

Abstract

The rapid development of information technology, especially in the field of multimedia, has changed the way we communicate and document various activities. The use of video as a means of documentation is now the main choice in conveying information, both in the personal sphere and government agencies. Dolat Rayat District, like many other districts, often carries out various activities and programs that involve the community. Some examples of activities that are often carried out include social events, community meetings, seminars, and infrastructure development projects. For the purpose of reporting and promoting these activities, good and easily accessible documentation is very important. The use of CapCut for making video documentation is very relevant because this application is available for free and easily accessible via mobile devices that are generally owned by district employees. In addition, the features in this application greatly support the creation of professional video documentation, although it does not require high video editing skills. However, most employees of Dolat Rayat District still do not master the techniques and understanding needed to make maximum use of this application. Through this assistance, it is hoped that there will also be an increase in employee capacity in utilizing technology to support their duties and responsibilities, as well as improving the quality of communication and reporting at the government level.
Analisis Kesehatan Tanaman Sawi (Brassica juncea L) Menggunakan Algoritma Random Forest Simanjuntak, Peter; Mikha Dayan Sinaga; Akbar Idaman; Muhammad Imam Zarkasyi
Jurnal SAINTIKOM (Jurnal Sains Manajemen Informatika dan Komputer) Vol 24 No 2 (2025): Agustus 2025
Publisher : PRPM STMIK TRIGUNA DHARMA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.53513/jis.v24i2.12131

Abstract

Penelitian ini membahas analisis kesehatan tanaman sawi (Brassica juncea L) menggunakan algoritma Random Forest. Data yang digunakan meliputi suhu, kelembapan tanah, dan intensitas cahaya, yang dikumpulkan secara periodik. Label status tanaman ditentukan berdasarkan ambang batas tertentu: “Sehat” jika kelembapan ≥ 60%, suhu antara 28–34°C, dan intensitas cahaya ≥ 700 lux; “Stres” jika kelembapan < 45% atau cahaya < 700 lux; serta “Perlu Disiram” untuk kondisi lainnya. Model Random Forest digunakan untuk mempelajari hubungan antara parameter lingkungan dan status tanaman. Hasil evaluasi menunjukkan tingkat akurasi yang tinggi, mengindikasikan bahwa algoritma ini efektif dalam mengklasifikasikan kondisi tanaman. Pendekatan ini dapat membantu petani dalam pengambilan keputusan berbasis data, sehingga meningkatkan efisiensi perawatan tanaman sawi.
Designing a Stunting Prediction Model Using Machine Learning to Support SDGs Achievement in Indonesia Sinaga, Mikha; Fujiati, Fujiati; Halawa, Darma
Sinkron : jurnal dan penelitian teknik informatika Vol. 9 No. 4 (2025): Articles Research October 2025
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v9i4.15296

Abstract

Stunting remains a major public health challenge in Indonesia, with national prevalence among children under five reaching 21.6% in 2022, according to the Ministry of Health. This condition, defined by the World Health Organization as a height-for-age less than -2 SD, is associated with long-term consequences including impaired cognitive development, reduced educational attainment, and diminished economic productivity. Addressing stunting is therefore critical to achieving Sustainable Development Goals (SDGs) related to hunger, health, and education. Despite multiple national initiatives, early identification of stunting risk is still limited by reliance on conventional, reactive surveillance methods. Recent advances in machine learning (ML) provide promising alternatives for proactive stunting prediction, with several studies reporting high predictive accuracy using ensemble methods, hybrid frameworks, and geographically weighted models. Building upon this evidence, the present study develops and evaluates ML models for stunting risk prediction using a large dataset of 10,000 records from North Sumatra, Indonesia. The dataset included three predictor variables—age, height, and weight—and a target variable, nutritional status (Normal, Stunted, Severely Stunted, Tall). Four algorithms were compared: K-Nearest Neighbors (KNN), Naïve Bayes, Decision Tree, and Random Forest. Performance was assessed using accuracy, precision, recall, F1-score, and ROC area, with 10-fold cross-validation ensuring robust estimation. Results demonstrated that Decision Tree (88.6% accuracy) and Random Forest (88.3% accuracy) outperformed KNN (84.7%) and Naïve Bayes (72%). ROC areas further confirmed the superiority of ensemble-based approaches, particularly Random Forest (0.979). Statistical significance was tested using McNemar’s test, revealing that Decision Tree and Random Forest achieved comparable performance (p = 0.651), both significantly outperforming KNN and Naïve Bayes (p < 0.05). This study contributes a context-specific evaluation of ML methods for stunting prediction in North Sumatra, emphasizing not only predictive accuracy but also interpretability to support health policy and program implementation. By bridging data-driven insights with actionable decision support, the proposed framework advances progress toward SDG-aligned strategies and provides a foundation for more targeted and preventive interventions in child nutrition and growth monitoring.
Enhancing Vocational High School Students’ Technological Competence through Python and Artificial Intelligence Mikha Dayan Sinaga; Zhafran Fatih Ananda; Akbar Idaman; Muhammad Irfan; Oswald Tobias Rafaello Siahaan
Yumary: Jurnal Pengabdian kepada Masyarakat Vol 6 No 4 (2026): Juni
Publisher : Penerbit Goodwood

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35912/yumary.v6i4.6407

Abstract

Purpose: This study aims to enhance the technological competence of vocational high school students through the introduction of Python programming and Artificial Intelligence (AI) to improve their digital literacy and computational thinking skills. Methodology: This study was conducted at Sekolah Menengah Kejuruan (SMK) Sultan Iskandar Muda, involving 44 tenth-grade vocational high school students. The program applied a quasi-experimental approach with a pretest–posttest design to measure students’ understanding before and after training. The training activities included lectures, demonstrations, and hands-on coding practice using Python 3.10, Google Colab, and Microsoft PowerPoint as learning tools. Data were collected through questionnaires, observations, and evaluation tests to measure the students’ knowledge of programming concepts and AI applications. Results: The results showed a significant improvement in students’ understanding after they participated in the training program. The average pretest score of 53.5 increased to 82.8 in the post-test. Students demonstrated better comprehension of Python programming concepts, including syntax, variables, data types, and input–output commands, as well as greater awareness of Artificial Intelligence applications in everyday life. Conclusions: The training program effectively improved students’ technological competence and increased their interest in learning programming and in emerging technologies. Limitations: The study was limited by the short training duration and differences in students’ initial knowledge levels. Contributions: This study contributes to vocational and technology education by providing a practical training model that can support the development of students’ digital literacy and readiness to face the challenges of the digital transformation era.
IMPLEMENTASI SISTEM INFORMASI PEMETAAN PADA SMK NEGERI DI KOTA MEDAN BERBASIS WEB Rendy Hari Perdana; Mikha Dayan Sinaga
Syntax : Journal of Software Engineering, Computer Science and Information Technology Vol 5, No 2 (2024): Desember 2024
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/syntax.v5i2.5505

Abstract

Pendidikan merupakan sebuah jalan usaha sadar dan sistematis untuk menciptakan situasi belajar mengajar dan jalan pembelajaran supaya peserta didik dapat secara aktif mengembangkan dirinya agar memiliki kemampuan spiritual keagamaan, pengendalian diri, karakter, kecerdasan, akhlak mulia serta keahlian yang diperlukan dirinya, masyarakat, bangsa dan Negara. Kota Medan memiliki 14 SMK Negeri yang tersebar di berbagai kecamatan. Sistem zonasi yang diterapkan oleh Pemerintah dalam proses seleksi penerimaan siswa baru membuat banyak Masyarakat mencari informasi tentang jarak rumah mereka ke sekolah SMK Negeri terdekat. Di beberapa daerah, terutama di wilayah terpencil atau pedesaan, distribusi sekolah SMK bisa sangat tidak merata. Beberapa daerah mungkin kekurangan akses ke sekolah yang menyediakan program pendidikan kejuruan, sementara daerah lain sudah memiliki banyak pilihan. Sekolah SMK memiliki banyak program studi atau jurusan yang berbeda, dan setiap jurusan mungkin memiliki fasilitas dan laboratorium yang berbeda pula. Mengelola dan memetakan fasilitas ini di setiap sekolah bisa sangat rumit, terutama bila tidak ada sistem yang jelas. Hasil yang diperoleh adalah Aplikasi pemetaan sekolah dapat membantu mengidentifikasi lokasi sekolah-sekolah yang ada, serta membantu pemerintah atau pihak terkait dalam merencanakan pembangunan atau penambahan sekolah di area yang membutuhkan dan Aplikasi pemetaan bisa menyediakan informasi secara detail tentang fasilitas yang tersedia di tiap jurusan, yang bisa membantu siswa dalam memilih jurusan yang tepat serta memudahkan pemerintah dalam pemantauan. Kata Kunci—Perancangan, Pemetaan, Web, SMK Negeri, Kota Medan ABSTRACT Education is a way of conscious and systematic effort to create teaching and learning situations and learning paths so that students can actively develop themselves so that they have religious spiritual abilities, self-control, character, intelligence, noble morals and skills needed by themselves, society, nation and state. . Medan City has 14 State Vocational Schools spread across various sub-districts. The zoning system implemented by the Government in the selection process for new student admissions has made many people look for information about the distance from their home to the nearest State Vocational School. In some areas, especially in remote or rural areas, the distribution of vocational schools can be very uneven. Some areas may lack access to schools that provide vocational education programs, while other areas already have many options. Vocational schools have many different study programs or departments, and each department may have different facilities and laboratories. Managing and mapping these facilities in each school can be very complicated, especially if there is no clear system. The results obtained are that the school mapping application can help identify the location of existing schools, as well as assist the government or related parties in planning the construction or addition of schools in areas that need it and the mapping application can provide detailed information about the facilities available in each department, which can help students choose the right major and make it easier for the government to monitor. Keywords— Design, Mapping, Web, State Vocational School, Medan City
PAKPAK LANGUAGE TRANSLATOR APPLICATION INTO INDONESIAN USING ALGORITHMBOYER MOORE BASED ON ANDROID Khairani Purba; Charles Jhony Mantho Sianturi; Mikha Dayan Sinaga; Nita Sari Sembiring; Erwing Ginting; Muhammad Fauzi
Jurnal Riset Informatika Vol. 4 No. 1 (2021): December 2021
Publisher : Kresnamedia Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1085.16 KB) | DOI: 10.34288/jri.v4i1.146

Abstract

The lack of preservation is also the knowledge of the Pakpak Language in Indonesia, which causes the Pakpak Language to be less preserved, especially for young people who continue to keep abreast of the times. This causes the process of globalization and urbanization which causes assimilation and acculturation, especially in urban areas. This situation triggers a new language that is very popular, especially for young people who unconsciously, it makes us lose our identity as a society that has tribes and customs each – and the emergence of international and national schools that require students to speak foreign languages. Therefore, learning is needed to preserve Pakpak Language. By making a Pakpak to Indonesian translator application that uses the Android Based Boyer Moore algorithm. This translator application was made for the introduction of the PakpakLangugae to the wider community so that the sustainability of the Pakpak Language is maintained and this translator application can translate the Pakpak Language into Indonesian or vice versa based on the prevailing Pakpak – Indonesian dictionary.
Comparative Evaluation of Ensemble Machine Learning Models for Child Stunting Prediction Using Routine Anthropometric Data in Indonesia Mikha Dayan Sinaga; Ratna Sri Hayati; Novriza Rahayu
JUITA: Jurnal Informatika JUITA Vol. 14 Issue 2, July 2026
Publisher : Department of Informatics Engineering, Universitas Muhammadiyah Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30595/juita.v14i2.29709

Abstract

Child stunting remains a major public health challenge in Indonesia and continues to hinder progress toward the Sustainable Development Goals (SDGs), particularly in child health and nutrition. Early identification of at-risk children is therefore essential to support timely interventions. While previous machine learning studies on stunting prediction commonly incorporate socioeconomic, environmental, and behavioral variables, comparative evaluations based exclusively on routinely collected anthropometric indicators remain limited, particularly within Indonesian primary healthcare settings. This study evaluates the predictive performance of multiple machine learning models for stunting classification using only anthropometric and early-life growth indicators. A dataset consisting of 1,000 child records—including age, birth weight, birth length, current weight, current length, and breastfeeding status—was analyzed using Logistic Regression, Decision Tree, Random Forest, Support Vector Machine, and Gradient Boosting algorithms. The dataset was partitioned using an 80:20 stratified train–test split, while five-fold cross-validation was applied during model development to improve robustness and reproducibility. Experimental results demonstrate that ensemble-based methods outperform single classifiers, with Gradient Boosting achieving the highest predictive performance (accuracy = 0.90, F1-score = 0.90, AUC = 0.93). Feature importance analysis reveals that birth length, birth weight, current weight, and age are among the most influential predictors of stunting risk. These findings suggest that machine learning models built solely on routinely collected anthropometric indicators can provide a practical, scalable, and data-driven approach for early stunting detection in Indonesian primary healthcare systems.
Co-Authors Akbar Idaman Alan Prayogi Ananda, Zhafran Fatih Asbon Hendra Azhar Charles Jhony Mantho Sianturi Charles Jhony Mantho Sianturi Charles Jhony Mantho Sianturi, Charles Jhony Mantho Daniel Kristian Pangaribuan Dian Prayetno Edy Victor Haryanto Edy Victor Haryanto, Edy Victor Ega Refredo Banurea Erwin Ginting Erwin Ginting Erwing Ginting Frinto Tambunan Frinto Tambunan Fujiati ., Fujiati Ginting, Erwin Ginting, Erwin Halawa, Darma Hardiyanti, Yeni Khairani Purba Manurung, Marlina Marlina Manurung Muhammad Fauzi Muhammad Imam Zarkasyi Muhammad Irfan Muhammad Siddik Nababan, Labuan Nita Sari Br Sembiring Nita Sembiring Noprita Elisabeth Sianturi Novriza Rahayu Oswald Tobias Rafaello Siahaan Ratih Adinda Destari Ratna Sri hayati Rendy Hari Perdana Ria Eka Sari Sembiring, Nita Sianturi, Charles Jhony Mantho Sianturi, Charles Jhony Mantho Simanjuntak, Peter Jaya Negara Yudi Yudi