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All Journal Riau Journal of Computer Science JURNAL MEDIA INFORMATIKA BUDIDARMA KOMIK (Konferensi Nasional Teknologi Informasi dan Komputer) Jurnal Sistem Informasi Kaputama (JSIK) IT (INFORMATIC TECHNIQUE) JOURNAL Reswara: Jurnal Pengabdian Kepada Masyarakat Journal of Computer Networks, Architecture and High Performance Computing Jurnal J-PEMAS JAIA - Journal of Artificial Intelligence and Applications JOMLAI: Journal of Machine Learning and Artificial Intelligence SATIN - Sains dan Teknologi Informasi ULINA: Jurnal Pengabdian kepada Masyarakat Jurnal Ilmu Komputer dan Sistem Informasi Jurnal Pengabdian Masyarakat Jurnal Penelitian Multidisiplin Bangsa
Leman, Dedi
Universitas Potensi Utama Medan
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Public Health Social Sciences

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Peningkatan Pemahaman Filosofi Batik melalui Pendekatan Logika Biner bagi Siswa SMK Tritech Informatika Medan Leman, Dedi; Rahman, Maulia
Reswara: Jurnal Pengabdian Kepada Masyarakat Vol 7, No 1 (2026)
Publisher : Universitas Dharmawangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46576/rjpkm.v7i1.7572

Abstract

Pengabdian masyarakat ini bertujuan untuk meningkatkan pemahaman dan apresiasi masyarakat, khususnya siswa dan guru di SMK Tritech Informatika Medan, terhadap motif batik sebagai warisan budaya nasional. Latar belakang kegiatan ini adalah adanya tren penurunan minat generasi muda terhadap batik, yang seringkali dianggap kuno dan kurang relevan. Banyak yang hanya mengenal batik sebatas pakaian tanpa memahami makna filosofis yang terkandung di dalamnya. Untuk mengatasi permasalahan tersebut, pengabdian ini mengusung pendekatan inovatif dengan mengajarkan cara "membaca" pola batik menggunakan konsep bahasa biner dan pola abstrak. Metode yang digunakan meliputi workshop interaktif, sesi demonstrasi, dan praktik langsung. Dalam workshop ini, peserta diperkenalkan pada cara mengurai motif batik ke dalam serangkaian kode biner yang sederhana, yang kemudian dikaitkan dengan makna filosofisnya. Hasil dari pengabdian ini menunjukkan peningkatan rata-rata skor pemahaman yang signifikan sebesar 64,2% (dari rata-rata pre-test 54,5 menjadi post-test 89,5; p<0.05). Peningkatan tersebut terbukti efektif dalam meningkatkan pemahaman peserta tentang makna simbolis motif-motif batik, seperti motif Parang dan Kawung. Selain itu, kegiatan ini berhasil menumbuhkan rasa bangga dan minat yang lebih besar terhadap batik, serta memberikan keterampilan dasar untuk menganalisis dan mengapresiasi keindahan motif batik dari perspektif yang berbeda dan lebih modern
leman, D Deteksi Penyakit Pada Daun Pisang dengan Penggunakan Algoritma Local Binary Pattern Dan K-Nearest Neighbor Dedi Leman; Obedh Eliezer Sidauruk
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 3 No. 2 (2024): Mei 2024
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v3i2.134

Abstract

Bananas are a type of fruit that has high production and is liked by many people. Mango productivity fluctuates from year to year. This is due to fluctuations in harvest area, plants that have not produced optimally, climate disturbances and attacks by various pests and diseases which are factors inhibiting banana growth and production in Indonesia. This identification will take a relatively long time and produce various diseases on banana leaves because humans have visual limitations in identifying, the level of fatigue and differences in opinion about diseases on banana leaves. The process of recognizing leaf patterns can be done by recognizing the characteristics of leaf structures such as leaf shape and texture. The method used in this research is Local Binary Pattern, an algorithm that can be used to classify based on images. In this study, 4 types of banana leaf diseases were used. Based on the results of the accuracy test, an accuracy value of 90.5% was obtained for the disease detection process on banana leaves for 10 pieces of data.
Sistem Cerdas Rekomendasi Klinik Pratama di Kota Medan Berbasis Data Mining Dengan Metode K-Means Untuk Pasien BPJS dan Umum Dedi Leman; Elvin Syahrin
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 3 No. 3 (2024): September 2024
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v3i3.144

Abstract

The growth in the number of clinics in Medan City, along with the increasing population, has triggered a need for more efficient and targeted healthcare services. However, patients often face difficulties in choosing clinics that meet their medical needs, especially BPJS Kesehatan users and general patients. This is due to the lack of information regarding the facilities, service quality, and optimal clinic locations. To address this issue, an Intelligent Clinic Recommendation System is needed to provide clinic suggestions based on patient profiles and needs. This study aims to develop a clinic recommendation system in Medan City using data mining techniques with the K-Means Clustering method. The K-Means method is employed to group clinics based on several important criteria, such as location, types of services, doctor availability, and the clinic's capability to accept BPJS patients as well as general patients. Patient data analyzed includes medical history, distance from the clinic, and service preferences. The results of the study show that the K-Means-based recommendation system can effectively cluster clinics and provide relevant recommendations according to patient profiles. This system not only helps patients choose the right clinic but also improves the efficiency of patient distribution in Klinik Pratama across Medan City. With the implementation of this system, it is expected that access to healthcare services will become more equitable and the quality of services will improve, both for BPJS and general patients.
Sistem Pendukung Keputusan Penentuan Instruktur Terbaik Dengan Kombinasi Metode GADA dan GRA Pada Tecnho Garage Dedi Leman
Jurnal Ilmu Komputer dan Sistem Informasi Vol. 4 No. 2 (2025): Mei 2025
Publisher : LKP Unity Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70340/jirsi.v4i2.193

Abstract

Instructors play a vital role in the success of training programs at non-formal education institutions such as Techno Garage. The selection of the best instructor has traditionally been conducted manually, making it prone to subjectivity and inconsistency in decision-making. To address this issue, this study designs a web-based decision support system that combines two multi-criteria decision-making methods: Grey Absolute Decision Analysis (GADA) and Grey Relational Analysis (GRA). The GADA method is used to assign relative weights to each criterion and prioritize alternatives based on absolute values, while the GRA method is applied to handle uncertainty and complex relationships among criteria. The evaluation criteria include attendance, length of service, participant feedback, and contributions to material development. The results demonstrate that the combination of GADA and GRA methods provides more objective and accurate recommendations in selecting the best instructor. This system enhances the efficiency, transparency, and accountability of the instructor selection process.
Co-Authors Adil Setiawan Akbar, Muhammad Barkah Cindy Paramitha Lubis Cindy Paramitha Lubis Dinda Hudayana Hsb Dini Ridha Dwiki Putri Edy Victor Haryanto Elvin Syahrin frans ikorasaki frans ikorasaki Harahap, Nurmahendra Hari Ramadhan Jenriko Sahat Sinaga M. Irfan Aldy Nasution Maulia Rahman Muhamad Rizky Fajar Utomo Muhammad Hari Ramadhan Nababan, Labuan Noprita Elisabeth S Obedh Eliezer Sidauruk Ramadhan, Hari Ratna Wardani Syahrin, Elvin