Article Per Year (5 Year)
p-Index From 2020 - 2025
0.562
P-Index
This Author published in this journals
All Journal JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Journal of Computer Science and Informatics Engineering
Feriantano Sundang Pranata
Universitas Negeri Padang
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health Social Sciences Other

Published : 4 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search

 1 
Sistem Pakar Diagnosis Penyakit Jamur pada Manusia Menggunakan Input Suara Berbasis Android Feriantano Sundang Pranata; Jufriadif Na’am; Sumijan
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 3 No 3 (2019): Desember 2019
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (443.3 KB) | DOI: 10.29207/resti.v3i3.1187

Abstract

Fungal skin disease is a type of disease that is often suffered people in the tropics. Phenomena in the community often assume that this disease will heal by itself. However, if left the effects of fungal skin disease can worsen the sufferer condition. The importance of early detection and treatment is very necessary, but this requires patients go to hospital or doctor so that patients spend a lot of time and money. For this reason, was build an android expert system with speech to early diagnose fungal skin diseases. From this initial diagnosis will save time and money and provide alternative prevention for sufferers. The method used in this study is the Certainty Factor of 20 patients. The accuracy of the test results to the system compared to the results of the doctor's diagnosis is 95%. So that, this expert system can be an early alternative in diagnose fungal skin diseases in humans.
Automatic Feature Extraction of Marble Fleck in Digital Beef Images to Support Decision Preferences Pranata, Feriantano Sundang; Adif, Anjjani Mardhika; Na'am, Jufriadif
JOIV : International Journal on Informatics Visualization Vol 9, No 1 (2025)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.9.1.2813

Abstract

Beef is one of the essential food ingredients to meet human nutritional needs. These nutrients are fundamental to the growth and development of the human body. The primary nutrient found in beef is protein. The nutritional value of protein in beef can be observed by the quality of the beef itself. An indicator of the protein level is the amount of marbling or white streaks in the meat. Marbling is characterized by a marble-like pattern in the meat layers. This study aims to process beef images to automatically identify marbling. The data processed is secondary data obtained from Kaggle.com, consisting of 60 images with a resolution of 800 by 800 pixels. This study develops a highly subjective method to produce fast and accurate classification. The processing stages used are pre-processing, segmentation, and extraction. The automatic stage is in the extraction, by developing a filtering algorithm. The results of this study can identify the marbling fleck ratio of each beef image very well, where each beef image has marbling flecks. The area of marbling flecks varies greatly depending on the quality of the meat, with the lowest quality having a ratio of 1.0% and the highest being 71.39%. This ratio level becomes an indicator in determining the quality of the meat, which is the primary preference in making accurate decisions in selecting meat quality. Thus, this study can serve as an indicator in determining the appropriate meat preference choice.
Transformasi evaluasi pembelajaran berbasis AI: Pelatihan Chatbot AI bagi Pendidik SMPN 9 Payakumbuh Saputra, Indra; Hayatunnufus, Hayatunnufus; Dewi, Siska Miga; Putri, Elviza Yeni; Mahniza, Melda; Reflianto, Reflianto; Pranata, Feriantano Sundang
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 9, No 3 (2025): May
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v9i3.30792

Abstract

AbstrakPerkembangan teknologi kecerdasan buatan (Artificial Intelligence/AI) telah membuka peluang baru dalam dunia pendidikan, khususnya dalam proses evaluasi pembelajaran. Namun, di lapangan masih banyak guru yang belum memiliki pemahaman dan keterampilan yang memadai dalam memanfaatkan teknologi ini secara optimal. Kondisi ini juga ditemukan di SMPN 9 Payakumbuh, di mana sebagian besar guru masih menggunakan metode evaluasi konvensional yang kurang fleksibel, memakan waktu, dan belum mencerminkan kemampuan siswa secara akurat. Program Kemitraan Masyarakat (PKM) ini dilaksanakan untuk meningkatkan kompetensi guru dalam melakukan evaluasi pembelajaran berbasis AI, khususnya melalui pemanfaatan Chatbot AI seperti ChatGPT. Kegiatan pelatihan dilaksanakan pada 24 Agustus 2024 di SMPN 9 Payakumbuh, diikuti oleh 31 guru dari berbagai mata pelajaran. Metode pelatihan meliputi ceramah, diskusi, demonstrasi, dan praktik langsung. Materi difokuskan pada penggunaan ChatGPT untuk menyusun soal, menganalisis jawaban siswa, memberikan umpan balik otomatis, serta merancang evaluasi berbasis interaksi percakapan. Hasil kegiatan menunjukkan bahwa peserta mampu menyusun instrumen evaluasi digital berbasis ChatGPT dan menunjukkan antusiasme tinggi terhadap penggunaan AI dalam pembelajaran. Disarankan agar pelatihan ini dilanjutkan secara berkala dan disertai dengan pendampingan untuk mendukung implementasi berkelanjutan di kelas. Kata kunci: Chatbot AI; evaluasi pembelajaran; ChatGPT; kompetensi guru; pelatihan. The rapid advancement of Artificial Intelligence (AI) has introduced new opportunities in the field of education, particularly in the area of learning assessment. However, many teachers, including those at SMPN 9 Payakumbuh, still rely on conventional evaluation methods that tend to be time-consuming, inflexible, and less accurate in reflecting students' competencies. This Community Partnership Program (PKM) was implemented to enhance teachers’ competencies in AI-based assessment by utilizing chatbot technology, specifically ChatGPT. The training was conducted on August 24, 2024, involving 31 teachers from various subject areas. The training methods included lectures, discussions, demonstrations, and hands-on practice. The content focused on the use of ChatGPT to design assessment questions, analyze student responses, provide automated feedback, and develop interactive, conversation-based evaluations. The results indicated that participants were able to develop AI-based digital assessment instruments and demonstrated high enthusiasm for integrating AI into teaching practices. It is recommended that similar training be conducted regularly and supported with mentoring to ensure sustainable implementation in classrooms. Keywords: Chatbot AI; learning assessment; ChatGPT; teacher competence; professional training.
Beach Tourism Destination Recommendation System in Padang City Using the ROC-MOORA Method Feriantano Sundang Pranata; Yuke Permata Lisna; Retnaningtyas Susanti
Journal of Computer Science and Informatics Engineering Vol 4 No 3 (2025): July
Publisher : Ali Institute of Research and Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55537/cosie.v4i3.1216

Abstract

Padang City's tourism sector has great potential, but there is no data-based destination recommendation system for beach tourism. This study develops a recommendation system using the Rank Order Centroid (ROC) and Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) methods. The system evaluates 10 alternative beaches based on five criteria: entrance fees, safety, operating hours, facilities, and cleanliness. Criteria weights are determined objectively using ROC, while destination rankings are calculated using MOORA. The results show that destination A4 obtained the highest score (Yi = 0.3015). This system is proven to be able to provide objective recommendations and can be implemented in the form of a web application to support the decisions of tourists and destination managers. This study contributes to the integration of the ROC-MOORA method in the tourism domain based on decision support systems.
Co-Authors Adif, Anjjani Mardhika Dewi, Siska Miga Hayatunnufus Hayatunnufus Indra Saputra Jufriadif Na`am, Jufriadif Melda Mahniza Na'am, Jufriadif Reflianto, Reflianto Retnaningtyas Susanti Sumijan Yeni Elviza Febrianti Yuke Permata Lisna