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All Journal Information System for Educators and Professionals : Journal of Information System Jurnal Nasional Teknologi Komputer Jurnal Hasil Pengabdian Masyarakat (JURIBMAS) Indonesian Journal of Education And Computer Science Electronic Integrated Computer Algorithm Journal Jurnal Bakti Nusantara
Ramadhanu Ginting
POLITEKNIK NEGERI MEDAN
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Medicine & Pharmacology Social Sciences Other

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Pelatihan Pemanfaatan Website terhadap Pemahaman Pemilihan PTN Siswa SMK Negeri 14 Medan Ramadhanu Ginting; Fristi Riandari; Afrisawati Afrisawati; Indri Sulistianingsih; Ade Rizka; Virdyra Tasril
Jurnal Bakti Nusantara Vol. 3 No. 3 (2026): Jurnal Bakti Nusantara
Publisher : Pustaka Media Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63763/jutira.v3i3.150

Abstract

Pemilihan perguruan tinggi negeri (PTN) merupakan tahap krusial bagi siswa sekolah menengah kejuruan (SMK), namun masih ditemukan keterbatasan pemahaman siswa dalam mengakses dan memanfaatkan informasi digital terkait jalur seleksi serta pemilihan program studi. Kondisi ini menunjukkan adanya kesenjangan literasi digital yang berpotensi mempengaruhi ketepatan pengambilan keputusan pendidikan. Kegiatan pengabdian ini bertujuan untuk meningkatkan pemahaman siswa melalui pelatihan pemanfaatan website sebagai media informasi pemilihan PTN di SMK Negeri 14 Medan. Metode yang digunakan adalah pendekatan kuantitatif dengan desain pre-test dan post-test yang melibatkan 16 siswa. Tahapan kegiatan meliputi pemberian pre-test, sosialisasi, pelatihan pemanfaatan website, serta evaluasi melalui post-test. Hasil menunjukkan adanya peningkatan rata-rata nilai siswa dari 56,25 pada pre-test menjadi 83 pada post-test dengan persentase peningkatan sebesar 47,1%. Temuan ini mengindikasikan bahwa pelatihan pemanfaatan website efektif dalam meningkatkan pemahaman siswa terkait pemilihan PTN. Dengan demikian, pemanfaatan website sebagai media edukasi dapat menjadi solusi dalam meningkatkan literasi digital serta mendukung pengambilan keputusan pendidikan yang lebih tepat bagi siswa SMK.
Sistem Pakar Berbasis Web Dalam Penentuan Pemilihan Jurusan Vokasi menggunakan Metode Certainty Factor Rahmat Widia Sembiring; Ramadhanu Ginting; Rizky Maulidya Afifa; Fristi Riandari; Afrisawati Afrisawati
INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System Vol 10 No 2 (2025): INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS (Desember 2025)
Publisher : Lembaga Penelitian dan Pengabdian kepada Masyarakat Universitas Bina Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51211/isbi.v10i2.3806

Abstract

The selection of a study program in higher vocational education is a crucial stage that can determine the future career development of students. In practice, many high school and vocational school graduates still face difficulties in choosing a program that aligns with their interests, talents, and potential. This research presents the design and implementation of a web-based expert system that serves as a decision-support tool for recommending vocational study programs by applying the Certainty Factor method. The Certainty Factor method is employed to measure the level of expert confidence in the facts or criteria provided by users, thereby generating a degree of certainty in the recommendation process. The system is developed with a web-based interface to ensure broad accessibility, ease of use, and interactivity for students. The experimental results indicate that the proposed expert system can assist in mapping students’ program preferences more objectively and systematically based on their individual characteristics. Therefore, this system is expected to serve as an alternative decision-support instrument in determining vocational study programs and contribute to improving the accuracy of educational pathway selection in accordance with students’ potential.
Komparasi Metode Certainty Factor dan Dempster Shafer untuk Mendiagnosa Penyakit Autis Ramadhanu Ginting; Fristi Riandari; Afrisawati; Weno Syechu; Rizky Maulidya Afifa; Rama Prameswara Ritonga
Indonesian Journal of Education And Computer Science Vol. 3 No. 1 (2025): INDOTECH - April 2025
Publisher : PT. INOVASI TEKNOLOGI KOMPUTER

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.60076/indotech.v3i1.1212

Abstract

Penelitian ini membahas perancangan sistem yang bertujuan untuk menangani masalah autisme pada anak-anak. Autisme merupakan gangguan yang mempengaruhi kemampuan individu, terutama dalam hal interaksi sosial. Dalam konteks ini, sistem pakar digunakan untuk mentransfer keahlian seorang pakar ke dalam bentuk algoritma yang dapat digunakan untuk diagnosis.Penelitian ini menganalisis dua metode dalam sistem pakar, yaitu Certainty Factor dan Dempster Shafer, yang ditujukan untuk mendiagnosis autisme pada anak. Tujuan utama penelitian ini adalah untuk mengevaluasi dan menentukan metode mana yang paling efektif untuk diimplementasikan dalam aplikasi yang dapat membantu mengklasifikasikan anak-anak dengan autisme.Hasil komparasi menunjukkan bahwanya metode Certainty Factor mencapai tingkat probabilitas di atas 95 %, dibandingkan dengan metode Dempster Shafer dalam komparasi 2 metode yang penulis lakukan. Temuan ini memberikan wawasan yang signifikan mengenai efektivitas kedua metode, serta kontribusi mereka dalam pengembangan sistem pakar untuk diagnosis autisme. Diharapkan penelitian ini dapat menjadi referensi untuk solusi yang lebih baik dalam bidang kesehatan mental anak.
Transformasi Digital Pengelolaan Data Produksi dan Keuangan Usaha Jamur Tiram Berbasis Dashboard Analitik Virdyra Tasril; Fristi Riandari; Hikmah Adwin Adam; Ramadhanu Ginting; Donny Sanjaya
JURIBMAS : Jurnal Hasil Pengabdian Masyarakat Vol 5 No 2 (2026): Oktober 2026
Publisher : LKP KARYA PRIMA KURSUS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62712/juribmas.v5i2.1695

Abstract

Sukamaju Farm is a micro-scale oyster mushroom enterprise in Deli Serdang Regency that manages 9,000 baglogs across nine racks, yet its production and financial records remain manual and unstructured. As a result, per-rack productivity is not monitored, baglog rotation relies on the owner's memory, and net profit cannot be calculated accurately. This community service program aimed to digitally transform the partner's business recording and analysis through mentoring in the use of an analytics dashboard consisting of a per-rack production module, a baglog life-cycle module, and a financial module. A participatory approach was applied in four stages—preparation, socialization, intensive mentoring, and evaluation and sustainability—involving three participants. Achievement was measured through knowledge pre- and post-tests and an independent competency test. The results show that the mean knowledge score increased from 80.0 to 91.1 with an N-gain of 0.56 (moderate category), and all three participants were declared competent in operating the three modules independently. The program equipped the partner to make data-driven business decisions, although the employees' ability to interpret financial reports still needs strengthening.
Perbandingan Metode Teorema Bayes dan Dempster Shafer Menentukan Status Gunung Berapi Ramadhanu Ginting; Fristi Riandari; Afrisawati Afrisawati; indri Sulistianingsih
Jurnal Nasional Teknologi Komputer Vol 5 No 3 (2025): Juli 2025
Publisher : CV. Hawari

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61306/jnastek.v5i3.274

Abstract

Penelitian ini membahas perbandingan dua metode dalam sistem pakar yang digunakan untuk menganalisis status aktivitas gunung berapi. Gunung berapi merupakan struktur geologis yang terbentuk akibat pergerakan magma dari dalam bumi ke permukaan melalui erupsi, yang biasanya disertai pelepasan lava, gas, dan material vulkanik lainnya. Sistem pakar dalam konteks ini bertujuan mentransformasikan pengetahuan seorang ahli ke dalam bentuk algoritma komputasional yang mampu melakukan diagnosis secara otomatis. Dua metode yang dianalisis dalam penelitian ini adalah Teorema Bayes dan Dempster Shafer. Tujuan utama dari studi ini adalah mengevaluasi efektivitas kedua metode dalam menentukan status gunung berapi dan mengidentifikasi metode yang paling akurat untuk diimplementasikan dalam aplikasi sistem pakar. Hasil analisis menunjukkan bahwa metode Dempster Shafer memiliki tingkat akurasi sebesar 98%, lebih tinggi dibandingkan dengan metode Teorema Bayes dalam konteks data gejala yang diuji. Temuan ini menunjukkan bahwa Dempster Shafer lebih unggul dalam klasifikasi status gunung berapi pada kasus ini, serta memberikan kontribusi terhadap pengembangan sistem pakar yang andal dalam mendukung pengambilan keputusan di bidang geologi dan mitigasi bencana alam
Design of NLP-Based Chatbot for Academic Services at Politeknik Negeri Medan Indri Sulistianingsih; Ramadhanu Ginting; Ade Rizka; Brema Arihta Siregar
Electronic Integrated Computer Algorithm Journal Vol. 3 No. 2 (2026): VOLUME 3, NO 2: APRIL 2026
Publisher : Yayasan Asmin Intelektual Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62123/enigma.v3i2.163

Abstract

The development of artificial intelligence technology has encouraged the use of chatbots in various sectors, including higher education. These chatbots can increase interaction, provide learning support, and facilitate the delivery of information automatically. This study aims to design a chatbot that functions as a virtual assistant in an educational environment, with an emphasis on increasing interaction between users and the system. The methods used include a systematic approach in designing interfaces, natural language processing (NLP), and testing the responsiveness of chatbots to user needs. From the literature review conducted, it is evident that chatbots make a positive contribution to learning motivation, student engagement, and the efficiency of the learning process, especially in the context of online learning. However, the current system is limited to predefined academic queries and does not yet handle complex academic advising, financial inquiries, or counseling support. The hope of this study is to provide guidance in developing educational chatbots that are effective, flexible, and able to adapt to user needs in the post-pandemic era.
A Dempster-Shafer-Based Expert System for Personalized Higher Education Major Recommendation Rahmat Widia Sembiring; Ramadhanu Ginting; Afrisawati Afrisawati; Fristi Riandari; Indri Sulistianingsih
Electronic Integrated Computer Algorithm Journal Vol. 4 No. 1 (2026): VOLUME 4, NO 1: OCTOBER 2026
Publisher : Yayasan Asmin Intelektual Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62123/enigma.v4i1.237

Abstract

Selecting a study program at a State University (Perguruan Tinggi Negeri/PTN) is a decision that many senior high school students approach without a systematic review of their interest, aptitude, achievement, and career goals, a gap made more pressing by the limited counseling capacity available at most schools. Earlier expert systems for major recommendation have relied on Forward Chaining or Certainty Factor, methods that combine evidence into a single rule outcome or scalar confidence without explicitly representing the uncertainty left by incomplete evidence. This study developed and implemented a web-based expert system, Peta Kampus, that applies Dempster-Shafer evidence theory to generate a personalized major recommendation from a student's answers to a structured questionnaire. The knowledge base was constructed with school counselors and an education practitioner into 275 evidence-linked questions covering 55 majors across 21 faculties, each carrying an expert-assigned belief value. The system was built on a native PHP Model-View-Controller architecture with MySQL as the data store, and its inference engine combines successive evidence using Dempster's rule of combination while tracking residual uncertainty and evidentiary conflict. The system was verified through Black Box Testing of its functional modules, with all 15 tested scenarios passing, and evaluated through an accuracy comparison against three independent evaluators (school principal and two guidance counselors, 90% average agreement across 30 cases) and a User Acceptance Test administered to 30 students, which returned an overall satisfaction score of 94.8%. The resulting system gives students and counselors a belief-and-plausibility-based recommendation that is more transparent than a single deterministic score.
Co-Authors Ade Rizka Ade Rizka Afrisawati Afrisawati Afrisawati Afrisawati Afrisawati Brema Arihta Siregar Donny Sanjaya Fristi Riandari Fristi Riandari Hikmah Adwin Adam Indri Sulistianingsih Indri Sulistianingsih Rahmat Widia Sembiring - Rama Prameswara Ritonga Rizky Maulidya Afifa Virdyra Tasril Virdyra Tasril Weno Syechu