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All Journal CSRID Servis : Jurnal Pengabdian dan Layanan kepada Masyarakat
Selamat Subagio
Universitas Al Washliyah Labuhanbatu
Religion Civil Engineering, Building, Construction & Architecture Computer Science & IT Environmental Science Other

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PENINGKATAN KECAKAPAN DIGITAL MASYARAKAT MELALUI PELATIHAN KOMPUTER DAN INTERNET SEHAT DI PANGKATAN Samsir; Abdul Hakim Dalimunthe; Selamat Subagio; Rahmad Aditiya; Reagen Surbakti Saragih; Syafaruddin Munthe
Servis : Jurnal Pengabdian dan Layanan kepada Masyarakat Vol. 4 No. 2 (2026): Juni
Publisher : CV. Nature Creative Innovation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58641/servis.v4i2.233

Abstract

Masyarakat di Desa Sennah, Kecamatan Pangkatan masih menghadapi keterbatasan dalam mengakses dan memanfaatkan teknologi digital secara optimal. Kegiatan pengabdian kepada masyarakat ini bertujuan untuk meningkatkan kecakapan digital warga melalui pelatihan komputer dasar dan penggunaan internet sehat. Metode yang digunakan meliputi ceramah interaktif, demonstrasi langsung, dan praktik terbimbing selama tiga hari pelatihan intensif. Peserta juga mendapat panduan cetak dan akses ke modul digital sebagai bahan belajar mandiri. Hasil kegiatan menunjukkan peningkatan signifikan dalam pemahaman peserta terkait pengoperasian perangkat komputer, browsing internet aman, serta literasi digital seperti mengenali hoaks dan menjaga privasi daring dengan skor rata-rata awal 40,4 menjadi 80,6. Sebanyak 88% peserta menyatakan merasa lebih percaya diri menggunakan teknologi digital setelah mengikuti pelatihan. Kegiatan ini diharapkan menjadi landasan bagi program literasi digital berkelanjutan di tingkat desa kecamatan Pangkatan kabupaten Labuhanbatu.
Sistem Pakar Identifikasi Hama Tanaman Perkebunan Menggunakan Metode Analytical Hierarchy Process (AHP) Yusup Anwar Siregar; Selamat Subagio; Wita Ferwati
CSRID (Computer Science Research and Its Development Journal) Vol. 18 No. 1 (2026): Februari 2026
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.18.1.2026.46-58

Abstract

Plantation crops such as oil palm, rubber, tea, and coffee are susceptible to pest attacks that can reduce crop productivity. The process of pest identification in the field often encounters obstacles due to limited experts and response time. This study aims to build an expert system based on the Analytical Hierarchy Process (AHP) method to help identify pests based on symptoms and severity of attacks. The AHP method is used to form a decision hierarchy, compile a pairwise comparison matrix, calculate priority weights, and conduct consistency tests. Alternative pests described include planthoppers, stem borers, leaf rollers, stink bugs, and rats, with categories of light and heavy attack levels. The calculation results show the highest composite value in the light category of 0.50717 and heavy of 0.25065. Validation of 15 test cases shows a system accuracy level of 93.33% compared to experts. Usability testing obtained a learnability value of 92.88%, efficiency of 92%, memorability of 94%, error of 94%, and satisfaction of 88.6%. These results indicate that the system is suitable for use as a tool for early identification of plantation pests.
Sistem Pakar Diagnosis Kerusakan Rambut Berbasis Web Menggunakan Metode Certainty Factor Tisna Destiana; Samsir; Selamat Subagio
CSRID (Computer Science Research and Its Development Journal) Vol. 18 No. 1 (2026): Februari 2026
Publisher : LPPM Universitas Potensi Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22303/csrid-.18.1.2026.83-97

Abstract

This study develops a web-based expert system for diagnosing hair damage using the Certainty Factor (CF) method to support early self-assessment and treatment recommendations. The knowledge base consists of five types of hair damage and five main symptoms with expert-validated belief weights. The CF method is applied to compute diagnostic confidence based on symptom combinations selected by users. System evaluation was conducted using test-case scenarios and numerical CF calculations. The results show that for three dominant symptoms, the system produces a CF value of 0.952, indicating a 95.2% confidence level. The novelty of this study lies in the expert-weighted knowledge modeling, transparent CF numerical analysis, and inference aggregation correction evaluation. The system can serve as an initial consultation tool before professional diagnosi.
Co-Authors Abdul Hakim Dalimunthe Rahmad Aditiya Reagen Surbakti Saragih Samsir Syafaruddin Munthe Tisna Destiana Wita Ferwati Yusup Anwar Siregar