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Journal : MASALIQ: Jurnal Pendidikan dan Sains

Sistem Pakar Pemilihan Menu Diet Sesuai Kondisi Kesehatan Pasien Kusumadewi, Ni Putu Ari; Permana, Agus Aan Jiwa; Swari, Gusti Putu Ayu Mas Meita Pradnya; Yudhantara, Kadek Prasta; Mahagangga, Komang Adi Satya; Artha, I Komang Windra
MASALIQ Vol 5 No 3 (2025): MEI
Publisher : Lembaga Yasin AlSys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/masaliq.v5i3.5439

Abstract

Expert Systems, a branch of artificial intelligence, are designed to replicate decision-making capabilities of human experts. This study focuses on developing an Expert System for Diet Menu Selection Based on Health Conditions. The system aims to assist users in planning nutritious and balanced diets tailored to individual health profiles, thereby enhancing health management through clear and practical guidelines. The Forward Chaining inference method is employed to derive conclusions from known health data, while the Agile development methodology supports iterative progress, adaptability to changes, and active stakeholder involvement to ensure optimal functionality. Given the rising public awareness of healthy living, this system presents a practical and innovative alternative for individuals seeking to manage their dietary habits effectively—without the need for constant consultations with nutritionists.
Implementasi Metode Item-Based Collaborative Filtering dalam Rekomendasi Barang pada Aplikasi Mobile Go-BUMDes Arditya, I Putu Dion; Permana, Agus Aan Jiwa; Seputra, Ketut Agus
MASALIQ Vol 5 No 4 (2025): JULI
Publisher : Lembaga Yasin AlSys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/masaliq.v5i4.6569

Abstract

This study is motivated by the low public interest in shopping at BUMDes (village-owned enterprises), primarily due to geographical constraints, highlighting the need for digital innovation to improve service accessibility. The objective of this research is to develop the GO-BUMDes mobile application as a platform for product ordering and recommendation in Cau Belayu Village. The application employs an Item-Based Collaborative Filtering method to provide product recommendations based on item similarity. The development process followed the prototype methodology, while system testing involved white box and black box techniques, accuracy evaluation using MAE (Mean Absolute Error), and user experience assessment through UMUX (Usability Metric for User Experience). Test results showed an MAE value of 0.258, indicating a relatively high prediction accuracy, and a UMUX score of 85.78, reflecting excellent user comfort and satisfaction. The study concludes that GO-BUMDes has the potential to enhance access and facilitate digital transactions at BUMDes, while encouraging community participation in a technology-driven village economy. The practical implications of this research contribute to strengthening digital transformation in the local economic sector, particularly in rural areas.
Aplikasi untuk Deteksi dan Klasifikasi Motif Kain Tenun Timor Tengah Selatan berbasis ANFIS pada Platform Mobile di Provinsi NTT Naitboho, Okthen Orlanda; Kertiasih, Ni Ketut; Permana, Agus Aan Jiwa
MASALIQ Vol 5 No 5 (2025): SEPTEMBER
Publisher : Lembaga Yasin AlSys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/masaliq.v5i5.7052

Abstract

The woven fabric from South Central Timor (TTS), East Nusa Tenggara Province, holds significant cultural and symbolic value; however, the influx of similar-patterned fabrics from outside the region presents challenges in authenticity identification, particularly among the general public and younger generations. This study aims to develop a mobile application based on the Adaptive Neuro-Fuzzy Inference System (ANFIS) to detect and classify motifs of TTS woven fabric. Texture feature extraction was conducted using the Gray Level Co-occurrence Matrix (GLCM) method, applying six key parameters: contrast, dissimilarity, homogeneity, energy, correlation, and ASM. The ANFIS model was trained for two types of classification: fabric authenticity (authentic vs. non-authentic), achieving an average accuracy of 87.50%, and regional motif classification (Amanatun, Amanuban, and Mollo), with an accuracy of 78.00%. The application was developed using a prototyping method and integrated with the classification system via FastAPI services. Black-box testing confirmed that all application features functioned as designed, while usability testing using the Usability Metric for User Experience (UMUX) yielded a score of 87.92, indicating a high level of user comfort and ease of use. The study concludes that the ANFIS-based mobile application is effective as a supporting tool in preserving TTS woven fabric through the application of intelligent technology. Keywords: Mobile Application; TTS Woven Fabric; ANFIS; GLCM Texture Extraction; Image Classification
Co-Authors A. A. Gede Yudhi Paramartha Agus Halid, Agus Agus Seputra I Ketut Alkautsar, Yoga Rizky Arditya, I Putu Dion Artha, I Kadek Bayu Danu Artha, I Komang Windra Baskara Nugraha, I Gusti Bagus Darmayasa, Ngakan Nyoman DIATMIKA, KETUT TUTUR Elly Herliyani Erma Susanti Gede Aditra Pradnyana Gede Arya Ardivan Pratama Saputra Gede Nanda Ageng Nugraha Gede Saindra Santyadiputra Gede Wahyu Purnama Gunawan, I Gede Made Deny Surya I Gd Ny Werdyana Guna Mertha I Gusti Agung Putu Bagus Satria Wicaksana I Gusti Ayu Purnamawati I Gusti Ngurah Wikranta Arsa, I Gusti Ngurah I Kadek Nicko Ananda I Kadek Suranata I Ketut Gading I Ketut Purnamawan I Made Ardwi Pradnyana I Made Pageh I Made Putrama I Made Sukarsa I Made Sukarsa I Nyoman Laba Jayanta I Nyoman Saputra Wahyu Wijaya I Nyoman Saputra Wahyu Wijaya Ida Bagus Sebali Mahesa Yogi Ifdil Ifdil Ika Arfiani Kadek Wirahyuni Komang Setemen Kusuma, I Komang Arya Adi Kusumadewi, Ni Putu Ari Made Sudarma Made Sudarma Mahagangga, Komang Adi Satya Marta Dinata, Kadek Prima Giant Naitboho, Okthen Orlanda Ni Ketut Kertiasih Ni Luh Ita Purnami Ni Putu Dwi Sucita Dartini Ni Putu Novita Puspa Dewi Ni Wayan Marti Octavia, I Gusti Ayu Adiani Paholo Iman Prakoso pande sindu Pande, Satria Imawan Adi Putra Pande Pracasitaram, Gede Made Surya Bumi Pracasitaram, I Gede Made Surya Bumi Pramudya, Dewa Gede Bhaskara Pranadi Sudhana, I G P Fajar Puridiasta, I Gede Deindra Dwija Putrama, Made Putu Ony Andewi PUTU SUGIARTAWAN Rezania Agramanisti Azdy, Rezania Agramanisti Rukmi Sari Hartati Rukmi Sari Hartati Saputra Wahyu Wijaya Siami, M. Ikbal Sindu, I Gede Partha Sunia Raharja, I Made Swari, Gusti Putu Ayu Mas Meita Pradnya Tarigan, Thomas Edyson Widodo Prijodiprodjo Wijaya, I Gede Saputra Wahyu Winata, I Gede Arya Wirayani, Made Padmi Witjaksana, Putu Gede Dimas Yoga Rizky Alkautsar Yoga Sucipta, Gede Yudhantara, Kadek Prasta