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All Journal JOIV : International Journal on Informatics Visualization Equilibrium: Jurnal Ilmiah Ekonomi, Manajemen dan Akuntansi
Aviv Yuniar Rahman
Universitas Widyagama Malang, Indonesia
Computer Science & IT Economics, Econometrics & Finance

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Classification of Tempeh Maturity Using Decision Tree and Three Texture Features - Istiadi; - Faqih; Aviv Yuniar Rahman; Dean Ariesta Aziz; April Lia Hananto; Sarina Sulaiman; Candra Zonyfar
JOIV : International Journal on Informatics Visualization Vol 6, No 4 (2022)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30630/joiv.6.4.983

Abstract

Tempe is an average food from Indonesia, eaten in Indonesia. Even today, tempe is around the world, and vegans around the world use tempeh as a meat substitute. This study plans to work on the accuracy of tempe characterization by utilizing the three-element extraction technique and the choice tree arrangement strategy. This research uses a decision tree method with three texture features in its classification. The results obtained indicate that this method has the highest Gabor channel level, including extraction, which is 71% accuracy, the split proportion is 10;90 and the lowest is 60% with parted balance of 90:10. The most important level value of GCLM extraction precision is 86% with a split proportion of 90;10 and the lowest price level and 60% level with a split ratio of 10;90 for Wavelet including the highest extraction rate price is 77%. It can be said that from the extraction of three elements, GLCM is the element extraction with the highest value from Gabor and Wavelet, including extraction at a split proportion of 10:90 by 86%. The test shows the Featured Tree highlight designation. The extraction technique was superior to different strategies for interaction characterization of tempe development quality. In the next research, improve the accuracy performance so that it can reach 100% using the CNN deep learning method. Then you can also add Support Vector Machine (SVM) and Naive Bayes methods based on the GLCM Extraction feature.
SYSTEMATIC LITERATURE REVIEW (SLR) UNTUK KELESTARIAN PARIWISATA: MENGINTEGRASIKAN PENGEMBANGAN SUMBER DAYA MANUSIA, MODEL MANAJEMEN, DAN TEKNOLOGI BIG DATA Adya Hermawati; Nasharuddin Mas; Aviv Yuniar Rahman
Equilibrium : Jurnal Ilmiah Ekonomi, Manajemen dan Akuntansi Vol 14, No 2 (2025): September
Publisher : Lembaga Penerbitan dan Publikasi Ilmiah (LPPI) Universitas Muhammadiyah Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35906/equili.v14i2.2549

Abstract

ABSTRAKPenelitian ini bertujuan untuk mengkaji strategi holistik dalam meningkatkan keberlanjutan industri pariwisata di Jawa Timur melalui pendekatan Systematic Literature Review (SLR). Fokus utama terletak pada integrasi Human Resource Development (HRD), manajemen strategis, dan pemanfaatan teknologi big data dalam mendukung daya saing dan keberlanjutan sektor pariwisata, khususnya pada tingkat UKM. Metode SLR digunakan untuk mengidentifikasi dan menganalisis literatur ilmiah yang relevan, kemudian divisualisasikan menggunakan VOSviewer guna memetakan keterkaitan antar konsep kunci. Hasil penelitian menunjukkan bahwa variabel orientasi kewirausahaan, kapabilitas pemasaran, dan keberlanjutan pariwisata merupakan komponen utama yang saling berinteraksi dalam pengembangan model konseptual pariwisata berkelanjutan. Melalui pendekatan variable mining dan relationship mining, penelitian ini menghasilkan model berbasis data yang aplikatif sebagai dasar pengambilan kebijakan dan strategi pengembangan pariwisata di masa depan.ABSTRACTThis study aims to examine holistic strategies for improving the sustainability of the tourism industry in East Java through a Systematic Literature Review (SLR) approach. The main focus is on the integration of Human Resource Development (HRD), strategic management, and the use of big data technology to support the competitiveness and sustainability of the tourism sector, particularly at the SME level. The SLR method is used to identify and analyze relevant scientific literature, which is then visualized using VOSviewer to map the relationships between key concepts. The research findings indicate that the variables of entrepreneurial orientation, marketing capabilities, and tourism sustainability are the primary components that interact in the development of a conceptual model for sustainable tourism. Through variable mining and relationship mining approaches, this study produced a data-driven model that is applicable as a basis for policy-making and future tourism development strategies.
Co-Authors - Faqih Adya Hermawati April Lia Hananto Candra Zonyfar Dean Ariesta Aziz Istiadi Nasharuddin Mas Sarina Sulaiman