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All Journal JURNAL PENGABDIAN KEPADA MASYARAKAT Journal of Information Technology and Computer Science (JOINTECS) Jurnal Sains Dan Teknologi (SAINTEKBU) Zero : Jurnal Sains, Matematika, dan Terapan INFOKUM Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE) Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Teknologi Informasi dan Komunikasi Syntax: Journal of Software Engineering, Computer Science and Information Technology Instal : Jurnal Komputer JUSTIN (Jurnal Sistem dan Teknologi Informasi) Journal of Mathematics and Scientific Computing With Applications Journal of Computer Science and Informatics Engineering Abdimas Indonesian Journal DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Jurnal Ilmiah Teknik Informatika dan Komunikasi Journal Of Informatics And Busisnes JENTIK Jurnal Ilmiah Research Student Jurnal Ilmu Komputer dan Sistem Informasi Jurnal Media Teknik Elektro dan Komputer
Mhd Ikhsan Rifki
Universitas Islam Negeri Sumatera Utara
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Physics Social Sciences

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Optimizing the use of sewing materials to maximize production output Rakhmawati, Fibri; Rifki, Mhd Ikhsan; Husein, Ismail; Cipta, Hendra; Lubis, Riri Syafitri; Sari, Rina Filia
Abdimas Indonesian Journal Vol. 5 No. 2 (2025)
Publisher : Civiliza Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59525/aij.v5i2.1043

Abstract

This Community Service Program aims to optimize the use of sewing materials to maximize production output at Rumah Jahit Nila through the application of a linear programming model in the allocation and use of sewing materials in planning and maximizing production output. The implementation methods include mapping processes and data requirements and formulating a linear programming model relevant to the scale of Nila Sewing House MSMEs, as well as training and live demonstrations using QM as software to determine optimization solutions. The evaluation was conducted on 15 participants using a 1–4 Likert scale instrument with four assessment indicators, namely, training content, presenter's subject-matter expertise, event facilities, and benefits of the program. Descriptive analysis showed an overall average of 3.43 on a scale of 4, with a percentage level of 85.8%, which is in the Very Good category. In order, the indicator achievements are Presenter’s Subject-Matter Expertise = 3.53 (88.33%), Benefits of the Program = 3.47 ( 86.67%), Training Content = 3.40 (85.00%), and Event Facilities = 3.33 (83.33%). These results confirm that the competence of the speakers and the relevance of the benefits are the main strengths, while the content and facilities of the activities are areas for priority improvement. This program has successfully improved participants' technical capacity in modeling and implementing linear program-based raw material optimization, while also providing a foundation for operational implementation to reduce waste and increase throughput.
PEMODELAN ALGORITMA AHP DAN SMART PADA SISTEM REKOMENDASI PENERIMA BANTUAN RUMAH LAYAK HUNI DI DESA SIALAMBUE Hasibuan, Bunga Lestari; Hasibuan, Muhammad Siddik; Rifki, Mhd.Ikhsan
JURNAL TEKNOLOGI INFORMASI DAN KOMUNIKASI Vol. 15 No. 2 (2024): September
Publisher : UNIVERSITAS STEKOM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/jtikp.v15i2.894

Abstract

The Livable Home Assistance Program is determined by the Government based on Government Regulation Number 12 of 2021, namely looking at the walls of the house, roof of the house, bathroom, floor of the house and floor area of ​​the house. Sialambue Village is one of the places that receives this program, because the conditions in Sialambue Village also make it possible to participate in this program. Therefore, data collection needs to be done more objectively to get accurate data collection results. So this research was carried out using the AHP and SMART algorithms by applying them to the Matlab application
Web-Based Document Archiving Information System In Commission C DPRD Of North Sumatra Province Syamia, Nanda; Lubis, Amalina Shadrina; Nur Hera Zabni; Rifqi, Mhd Ikhsan
SAINTEKBU Vol. 16 No. 01 (2024): Vol. 16 No. 01 January 2024
Publisher : KH. A. Wahab Hasbullah University

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Commission C DPRD of North Sumatra Province is a commission that operates in the financial sector. In Commission C DPRD, the relationship between the budget and documents is closely related because documents are often used as a tool to record, track and present financial information. These documents assist Commission C in monitoring, evaluating and making decisions related to regional financial management. The document is an important reference to ensure transparency, accountability and efficiency of budget management in accordance with policies and community needs. The existence of documents is usually important because they record or record information that can be accessed and used as a reference in the future. Document management within Commission C DPRD of North Sumatra province still faces several obstacles, including manual processes that are vulnerable to human error, the time required to search for documents, and the risk of document loss or damage. Seeing this problem, a new system is needed that utilizes technology in the current era to deal with several obstacles related to document management. The aim is to design and implement a web-based document archiving information system at Commission C DPRD of North Sumatra province to increase efficiency, security and readability of information in document management. The research methods used in this study are Research and Development. Research and Development Research and development (R&D). This system was built by modeling several UML diagrams such as use case diagrams, activity diagrams, and class diagrams. It is hoped that Commission C DPRD of North Sumatra province can optimize document management performance and make a positive contribution to improving service quality and transparency within this institution.
IMPLEMENTASI SISTEM PAKAR DENGAN NAIVE BAYES DAN CERTAINTY FACTOR UNTUK DIAGNOSIS STROKE Theofil Rizky Fazry; Mhd Furqan; Mhd. Ikhsan Rifki
Jurnal Manajemen Teknologi Informatika Vol. 3 No. 3 (2025): Jurnal Manajemen Teknologi Informatika
Publisher : JENTIK

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70038/jentik.v3i3.177

Abstract

Stroke merupakan penyakit dengan risiko tinggi terhadap kematian dan kecacatan permanen. Penelitian ini bertujuan membangun program aplikasi sistem pakar guna mengklasifikasikan jenis-jenis stroke melalui penerapan algoritma Naive Bayes dan Certainty Factor. Data penelitian diperoleh melalui wawancara dengan pakar pada RSU Full Bethesda serta studi literatur. Perancangan sistem difokuskan untuk mengidentifikasi lima varian stroke, diantaranya Transient Ischemic Attacks, stroke hemoragik intraserebral, stroke hemoragik subarachnoid, stroke iskemik trombolitik, dan stroke iskemik emboli. Implementasi dilakukan berbasis PHP dengan MySQL serta diuji menggunakan blackbox. Evaluasi diagnosis pasien menunjukkan Naive Bayes menghasilkan probabilitas 52,82% pada stroke hemoragik intraserebral pasien 1, sedangkan Certainty Factor memberikan hasil 100% pada beberapa jenis stroke. Hasil ini membuktikan Naive Bayes lebih fokus pada satu penyakit, sementara Certainty Factor lebih fleksibel dalam menampilkan kemungkinan beberapa penyakit. Sistem ini diharapkan menjadi alat bantu diagnosis awal yang efektif bagi tenaga medis.
Optimizing the use of sewing materials to maximize production output Rakhmawati, Fibri; Rifki, Mhd Ikhsan; Husein, Ismail; Cipta, Hendra; Lubis, Riri Syafitri; Sari, Rina Filia
Abdimas Indonesian Journal Vol. 5 No. 2 (2025)
Publisher : Civiliza Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59525/aij.v5i2.1043

Abstract

This Community Service Program aims to optimize the use of sewing materials to maximize production output at Rumah Jahit Nila through the application of a linear programming model in the allocation and use of sewing materials in planning and maximizing production output. The implementation methods include mapping processes and data requirements and formulating a linear programming model relevant to the scale of Nila Sewing House MSMEs, as well as training and live demonstrations using QM as software to determine optimization solutions. The evaluation was conducted on 15 participants using a 1–4 Likert scale instrument with four assessment indicators, namely, training content, presenter's subject-matter expertise, event facilities, and benefits of the program. Descriptive analysis showed an overall average of 3.43 on a scale of 4, with a percentage level of 85.8%, which is in the Very Good category. In order, the indicator achievements are Presenter’s Subject-Matter Expertise = 3.53 (88.33%), Benefits of the Program = 3.47 ( 86.67%), Training Content = 3.40 (85.00%), and Event Facilities = 3.33 (83.33%). These results confirm that the competence of the speakers and the relevance of the benefits are the main strengths, while the content and facilities of the activities are areas for priority improvement. This program has successfully improved participants' technical capacity in modeling and implementing linear program-based raw material optimization, while also providing a foundation for operational implementation to reduce waste and increase throughput.
Klasifikasi Kualitas Benih Sawit Menggunakan Metode Naïve Bayes di PPKS Marihat Batubara, Qisti Azraladiba; Rifki, Mhd. Ikhsan
Jurnal Media Teknik Elektro dan Komputer Vol 2 No 2 (2025): Jurnal Media Teknik Elektro dan Komputer
Publisher : Yayasan Pendidikan Al-Yasiriyah Bersaudara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65371/metrokom.v2i2.133

Abstract

Oil palm is one of the important plantation commodities in Indonesia, so seed quality is a major factor in production success. The main problem in the field is that seed quality determination is still done manually, which takes a long time and is prone to human error. Therefore, this study aims to minimize human error and support decision-making in determining planting priorities for superior seeds through the classification of oil palm seed quality using the Naïve Bayes algorithm. The model was built based on three main parameters, namely moisture content, storage room humidity, and seed storage duration. The results were labeled as low, medium, and high quality categories. Testing results using an 80% of data training (130 data) and 20% of data testing (32 data) model splitting, that the Naïve Bayes model produced an accuracy of 91% from 162 dataset. The classification results showed that 38 data points fell into the low quality category, 55 into the medium category, and 56 into the high category. The research results should be more oriented towards statements regarding the ability of Naïve Bayes to classify palm oil seed types, so that it can be used as a model recommendation in palm oil determination.
Klasifikasi Prestasi Siswa MAN 2 Labuhanbatu Melalui Komponen Indeks Prestasi Belajar Menggunakan Klaster K-Means Rasyid, Abdul; Rifki, Mhd Ikhsan
Jurnal Media Teknik Elektro dan Komputer Vol 2 No 2 (2025): Jurnal Media Teknik Elektro dan Komputer
Publisher : Yayasan Pendidikan Al-Yasiriyah Bersaudara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.65371/metrokom.v2i2.135

Abstract

Optimal utilization of academic data is an important requirement in supporting data-based learning decision making. One approach that can be used is Educational Data Mining (EDM) through clustering techniques to map students' academic abilities. This study aims to apply the K-Means Clustering algorithm in grouping students based on exam score patterns in one subject at MAN 2 Labuhanbatu Utara. The data used consists of daily scores, midterm scores, and final exam scores of 11th grade students, which were processed through pre-processing, data normalization, and clustering analysis stages. The determination of the optimal number of clusters was carried out using the Elbow method with the Within Cluster Sum of Squares (WCSS) indicator. The results showed that the three-cluster configuration was the most representative grouping structure, which could be interpreted as groups of students with high, medium, and low academic performance, respectively. The differences in centroid values between clusters indicate significant and structured variations in academic achievement. These findings prove that the K-Means algorithm is effective for mapping student learning groups objectively without requiring initial labels. The clustering results are expected to serve as a basis for teachers and schools in designing more adaptive learning strategies tailored to students' ability characteristics.
Penerapan Algoritma K-Nearest Neighbors untuk Prediksi Negara-Negara Asia Berpotensi Lolos Piala Dunia 2026 Andrian Sahputra; Ilka Zufria; Mhd Ikhsan Rifki
DEVICE : JOURNAL OF INFORMATION SYSTEM, COMPUTER SCIENCE AND INFORMATION TECHNOLOGY Vol 7, No 1: JUNI 2026
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/device.v7i1.8589

Abstract

Penelitian ini bertujuan menerapkan algoritma K-Nearest Neighbors dalam memprediksi potensi kelolosan negara-negara Asia dari babak ketiga kualifikasi menuju putaran final Piala Dunia 2026. Data yang digunakan terdiri atas 36 data historis kualifikasi Piala Dunia periode 2014–2022 sebagai data latih dan 18 data peserta kualifikasi zona Asia tahun 2026 sebagai data uji. Pendekatan yang digunakan adalah kuantitatif dengan teknik data mining berdasarkan klasifikasi. Tahapan penelitian meliputi pengumpulan data, pra-pemrosesan melalui pembersihan dan transformasi fitur menjadi rasio kinerja, normalisasi data, serta pemodelan menggunakan algoritma K-Nearest Neighbors. Hasil evaluasi menunjukkan bahwa model dengan parameter k = 4 menghasilkan akurasi sebesar 83,33%, dengan performa yang baik pada kategori lolos dan tidak lolos, meskipun kategori play-off menunjukkan hasil yang lebih rendah. Nilai rata-rata makro untuk presisi , recall , dan f1-score masing-masing sebesar 0,79, 0,77, dan 0,77. Hasil prediksi menunjukkan enam negara berpotensi lolos langsung, empat negara berada di posisi play-off, dan delapan negara lainnya tidak lolos. Temuan ini menunjukkan bahwa algoritma K-Nearest Neighbors memiliki kemampuan yang cukup baik dalam memprediksi kelolosan tim berdasarkan kinerja historis.
Use of Data Visualization Techniques in Bioinformatics for Time-Based Gene Expression Pattern Analysis M. Khalil Gibran; Mhd Ikhsan Rifki; Amir Saleh
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 5 No. 2 (2025): Mei 2026
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v5i2.373

Abstract

This study explores data visualization techniques in bioinformatics for analyzing time-series gene expression patterns. It examines how different visualization approaches support the interpretation of large-scale temporal gene expression data. A dataset comprising 4,381 genes across 24 time intervals was analyzed using heatmaps, Principal Component Analysis (PCA), volcano plots, and dendrograms. Heatmaps were used to observe expression correlations, PCA was applied to reduce dimensionality, volcano plots identified differentially expressed genes between conditions, and dendrograms grouped genes with similar expression profiles. The PCA results showed that the first two principal components accounted for 42.32% of the total variance, indicating that these components captured a substantial but not complete portion of the data structure. Volcano plot analysis detected differentially expressed genes based on log2 fold change > 1 and p-value < 0.05, while dendrogram visualization revealed several major clusters with comparable temporal expression patterns. Overall, the findings suggest that combining multiple visualization methods can improve the exploratory analysis of temporal gene expression data by clarifying patterns, highlighting potentially relevant genes, and supporting further biological interpretation. Rather than serving as standalone evidence for clinical application, these visual approaches provide a useful analytical foundation for subsequent validation, biomarker investigation, and large-scale omics research.  
Co-Authors Abdul Halim Hasugian Abdul Rasyid Adha Hasibuan, Aidillia Afandi Sahputra Aidil Akbar Simatupang Aidil Halim Lubis Ali Darta Amir Saleh Andilala Andrian Sahputra Aulia, M. Arif Batubara, Qisti Azraladiba Dwi Prapita Sari Dysa Handira F, Muhammad Bagas Fadhillah Lubis, Muhammad Arif Fauzi Kurniawan Gibran, M. Khalil Haikal, Baginda Fikri Harjo, William Lutfir Rahman Harun Al Rasyid Hasibuan, Ainun Mardiah Hasibuan, Bunga Lestari Hendra Cipta Ikhwan, Ali Ilka Zufria Inneke Putri Ismail Husein, Ismail Julianti, Miranda Khairul Azis Khalil Gibran, M. Klause Roder Lubis, Amalina Shadrina Lubis, Nur Azizah M. Khalil Gibran M. Khalil Gibran Mhd Furqan Mhd Furqan Muhamad Alda Muhammad Ezar Raditya Muhammad Ikhsan Muhammad Ikhsan Muhammad Siddik Hasibuan Muhammad, Faisal Nasution, Fadhilah Ramadhani Nur Hera Zabni Ong, Russell Pulungan, Miftahul Rizky Rakhmawati, Fibri Rambe, M. Riski Andika Rina Filia Sari, Rina Filia Rini Halila Nasution Riri Syafitri Lubis Salim Salim Siahaan, Ahmad Taufik Al Afkari SIHOMBING, JULIANA SION Suhardi, Suhardi Syamia, Nanda Theofil Rizky Fazry Yusuf Ramadhan Nasution