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All Journal Cakrawala Pendidikan Jurnal Buana Informatika PROCEEDING IC-ITECHS 2014 SMATIKA Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) INTEGER: Journal of Information Technology Network Engineering Research Operation [NERO] SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Scientific Journal of Informatics Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Indonesian Journal of Electrical Engineering and Computer Science Indonesian Journal of Instructional Media and Model Jurnal Pengabdian Masyarakat Asia Jurnal Teknik Informatika (JUTIF) Indonesian Journal of Engagement, Community Services, Empowerment and Development (IJECSED) International Journal of Community Service Jurnal Masyarakat Madani Indonesia Jurnal Informatika Polinema (JIP) Journal of Information Technology and Cyber Security Jeskovsia (Jurnal Desain Komunikasi Visual Asia) Jurnal ilmiah teknologi informasi Asia Smatika Jurnal : STIKI Informatika Jurnal
Suastika Yulia Riska
Institut Teknologi Dan Bisnis Asia Malang
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Medicine & Pharmacology Nursing Public Health Social Sciences Other

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High-accuracy classification of banana varieties using ResNet-50 and DenseNet-121 architectures Riska, Suastika Yulia; Sulistyo, Danang Arbian; Siti Maharani, Farah Shafiyah
Indonesian Journal of Electrical Engineering and Computer Science Vol 39, No 1: July 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v39.i1.pp322-335

Abstract

Bananas are a popular fruit in Indonesia due to their affordability, availability, and rich nutritional content. Identifying different banana types is crucial for consumption and processing, yet some types are difficult to distinguish visually. This study aims to classify banana types using convolutional neural network (CNN) architectures, specifically ResNet-50 and DenseNet-121. The dataset consists of five banana classes, which were processed using preprocessing techniques to enhance image quality prior to model training. The results demonstrate that the proposed models can classify banana types with high accuracy. The research methodology includes data collection, preprocessing, CNN model implementation, and performance evaluation using a confusion matrix. The dataset was split into training and testing sets in an 80:20 ratio, with validation data extracted from the training set in a 90:10 ratio. The models were trained on the training data, validated with validation data, and tested on the testing data to assess final performance. The study concludes that the CNN architectures employed are effective in classifying banana types, with the DenseNet-121 model achieving 93.02% accuracy, outperforming the ResNet-50 model, which achieved 92.44%. These results indicate that the models can capture essential features from banana images and produce accurate predictions.
Early Detection of Student Problems Through a Knowledge-Based Systems-Based Counseling Approach Rahmawati, Nisrina Salsabil; Riska, Suastika Yulia
Journal of Information Technology and Cyber Security Vol. 3 No. 1 (2025): January
Publisher : Department of Information Systems and Technology, Faculty of Intelligent Electrical and Informatics Technology, Universitas 17 Agustus 1945 Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30996/jitcs.12617

Abstract

Higher education is an important phase in an individual's academic development, but it is often characterized by challenges such as academic pressure, time management, and student mental health. To overcome these problems, this research aims to develop a technology-based Counseling Expert System with a Forward Chaining approach to detect student problems and provide relevant solutions. The system is designed and implemented as a web-based platform that can be accessed anytime and anywhere, allowing students to answer questions related to the problems faced by students. The answers are processed in a knowledge base that is integrated with an inference engine to produce diagnosis and solution recommendations. The results of system testing using 30 data samples show results that are in accordance with expert judgment. This expert system can identify six types of student problems, such as laziness, skipping classes, adaptation difficulties, difficulty doing final assignments, decreased Grade Point Average (GPA or IP), and potential dropout, by considering 32 causal factors grouped into academic, time management, emotional, and social environment categories. This research proves that the Forward Chaining-based Counseling Expert System is effective as a flexible solution to support student well-being and better student academic achievement.
Early Stroke Disease Prediction Based on Lifestyle Factors Applied with Machine Learning Suastika Yulia Riska; Lia Farokhah
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 9 No 5 (2025): October 2025
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v9i5.6495

Abstract

Stroke prediction has many supporting features and variables. Some forecasts focus more on health or elements that are already present. Predicting stroke risk by identifying habitual factors provides more advantages for preventive action. In addition, the complexity of features or variables is a concern in predicting stroke risk. In this study, we used a public dataset from Kaggle with 10 features or variables. In this study, we propose to collaborate algorithms and preprocessing in feature selection using Pearson Correlation and Principal Component Analysis (PCA) dimension reduction to unravel the complexity of variables and data processing computing. This aims to predict stroke risk more simply. The results of the experiment show that feature selection using Pearson Correlation between features and labels produces maximum results using 5 features out of 10 provided features. This approach produces the best performance on the Naïve Bayes, Iterative Dichotomiser Tree (ID3), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Logistic Regression with 100% accuracy and reduces features by 50% to support the reduction of the complexity of prediction variables and data processing computing.
Ontology-Based Recommender Systems for E-Learning and Multimedia: A Systematic Literature Review Across Domains Riska, Suastika Yulia; Patmanthara, Syaad; Widiyaningtyas, Triyanna
Indonesian Journal of Instructional Media and Model Vol 7 No 2 (2025): Indonesian Journal of Instructional Media and Model
Publisher : Universitas Veteran Bangun Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32585/ijimm.v7i2.7405

Abstract

The rapid expansion of digital content across various sectors has led to an overwhelming influx of data, highlighting the need for advanced recommendation systems. Traditional methods such as Collaborative Filtering (CF) and Content-Based Filtering (CBF) face limitations like data sparsity and the Cold Start problem, which affect the accuracy of recommendations. This study explores the use of ontologies in enhancing recommendation systems, aiming to overcome these challenges by providing a semantic framework for better item and user representation. A Systematic Literature Review (SLR) methodology was employed to analyze research from 2021 to 2025, focusing on the application of ontologies in e-commerce, healthcare, education, and employment. The findings demonstrate that ontologies improve recommendation relevance, diversity, and explainability, especially in addressing the Cold Start problem. However, challenges in implementation and interpretation remain. This research contributes to the field by emphasizing the potential of integrating ontologies with Knowledge Graphs (KG) and Graph Neural Networks (GNN) to create hybrid models that enhance the accuracy and transparency of recommendations, guiding future advancements in recommendation systems.
Language Diplomacy Through BIPA: An Indonesian Language Training Program For NEUST Philippines Students Lailatul Aqromi, Nur; Yulia Riska, Suastika; T. Bantug, Emilsa; Febrindasari, Chyndy
International Journal Of Community Service Vol. 5 No. 4 (2025): November 2025 ( Indonesia - Thailand - Malaysia - Timor Leste - Philippines )
Publisher : CV. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51601/ijcs.v5i4.930

Abstract

This community engagement program was initiated in response to the linguistic needs of foreign students from the Nueva Ecija University of Science and Technology (NEUST), Philippines, who required Indonesian language proficiency to participate effectively in a student exchange program with the Institute of Technology and Business Asia Malang, Indonesia. The partner institution faced two primary challenges: the absence of a practical and systematic Indonesian language training program for foreign learners and the limited initial language competence among NEUST students. Interestingly, structural similarities between Tagalog and Indonesian—particularly in basic morphemes and affixation patterns—offered a promising foundation for language acquisition. The program aimed to introduce fundamental Indonesian language proficiency equivalent to BIPA Level 4, focusing on communicative competence in academic and social contexts. It was conducted online through five sessions, including one orientation, four core training sessions based on the Task-Based Language Teaching (TBLT) approach, and one evaluation session. The learning materials were adapted from Sahabatku Indonesia – BIPA 4, published by the Ministry of Education and Culture. The outcomes demonstrated significant improvement in participants’ linguistic competence, reflected in higher evaluation scores and active engagement throughout the training. Additional outcomes included online media publications and the adoption of the developed modules as sustainable BIPA teaching materials at NEUST. Overall, this initiative represents an effort in Indonesian language diplomacy, contributing to the strengthening of academic mobility and intercultural collaboration across Southeast Asia.
Pengolahan Nilai Berbasis Database Di MTS Miftahul Ulum Wonokoyo Setyorini Setyorini; Suastika Yulia Riska; Fadhli Almu'ini Ahda; Rina Dewi Indah Sari
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 5 No 02 (2015): Smatika Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v5i02.92

Abstract

Kegiatan yang dilakukan merupakan sosialiasi penggunaan software pengolah nilai siswa dan penggunaan software pendataan guru dan siswa berbasis database. Software berbasis database dibangun menggunakan microsoft access. Software pengolahan nilai dapat mempermudah wali kelas untuk melakukan perangkingan dalam satu kelas di mata pelajaran yang sama. Tujuan adanya perangkingan ini adalah untuk memberikan reward kepada siswa yang memiliki prestasi. Sehingga siswa tersebut dapat termotivasi untuk terus meningkatkan prestasinya dan dapat memotivasi teman-teman lain untuk lebih berprestasi.
Klasifikasi Bumbu Dapur Indonesia Menggunakan Metode K-Nearest Neighbors (K-NN) Suastika Yulia Riska; Lia Farokhah
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 11 No 01 (2021): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v11i01.568

Abstract

Seasoning is one of the most important elements in a dish. Indonesian herbs or spices have a very wide variety of types. Mistakes in choosing spices have a big effect on the taste of the dish. Image processing is a branch of science in the field of technology that can be used to recognize image objeks captured by the camera. This study will classify the types of spices that are almost similar, namely ginger, galangal, turmeric and kencur. The classification method used is K-Nearest Neighbor (K-NN). In this study we tested how to split training data and data testing, namely 66.7%: 33.33%, 75%: 25% and 90%: 10%. The sharing of training data and testing data uses 90%: 10% has the greatest average accuracy compared to other distribution methods. The selection of K = 3 or K = 5 has an average accuracy that is almost the same in all methods of split training data and testing data, namely 64.66%: 65%. At K = 1 it has a fairly high accuracy compared to the previous K, which is 73%.
Penerapan Algoritma K-Means untuk Klasterisasi Produksi Tanaman Perkebunan di Indonesia Reda Maulidina; Suastika Yulia Riska
SMATIKA JURNAL : STIKI Informatika Jurnal Vol 13 No 02 (2023): SMATIKA Jurnal : STIKI Informatika Jurnal
Publisher : LPPM UBHINUS MALANG

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32664/smatika.v13i02.991

Abstract

Plantation crop production is one of the main sectors in increasing people's income. Data on plantation products held by the Central Statistics Agency (BPS) is in the form of raw data, namely the production results of each province each year. This makes it quite difficult for the government to identify provinces that have the potential to produce crops. By clustering plantation crop production results, it will be easier for the government to identify provinces that have the potential to produce plantation crops. In this research there were 3 plantation crop production, namely coconut, coffee and cocoa. The data used is data for 2017 – 2021 which consists of 29 provinces. From the 3 plantation crop production, the data was collected using the K-Means Algorithm Data Mining technique. The results of this research are groupings which are divided into 2 clusters obtained from the Sum of Squared Error (SSE) calculation with a minimum value of 279261.63, namely low production and large production. Based on the results of the K-Means Algorithm calculations, it was found that coconut production had a small production cluster of 24 provinces, a large cluster of 5 provinces, for coffee a small production cluster of 23 provinces was obtained, a large production cluster was 6 provinces, and for cocoa a small production cluster was obtained of 23 provinces. , a cluster of 6 provinces.
Penguatan Nasionalisme pada Era Digital melalui Game Mobile Edukatif Bilingual bagi Siswa Inklusif Abdul Aziz Muslim; Widya Adhariyanty Rahayu; Suastika Yulia Riska
Jurnal Masyarakat Madani Indonesia Vol. 4 No. 4 (2025): November
Publisher : Alesha Media Digital

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59025/b3rdg674

Abstract

SD Muhammadiyah 4 Kota Malang sebagai lembaga pendidikan berbasis inklusif menghadapi tantangan signifikan dalam pelaksanaan pembelajaran, terutama dengan pendekatan konvensional yang kurang adaptif bagi siswa slow learner. Untuk mengatasi permasalahan tersebut, diusulkan inovasi berupa pengembangan media pembelajaran digital melalui game mobile edukatif bilingual bertema nasionalisme. Kegiatan ini bertujuan memperkuat wawasan kebangsaan sekaligus meningkatkan keterampilan bahasa Inggris siswa inklusif. Metode pelaksanaan menerapkan pendekatan berbasis komunitas yang melibatkan guru, orang tua, dan pakar pendidikan dalam tahapan identifikasi kebutuhan, perancangan hingga implementasi serta evaluasi game interaktif. Pelatihan bagi guru dan sosialisasi untuk orang tua turut diberikan guna memastikan optimalisasi pemanfaatan media baru ini di sekolah dan di rumah. Hasil kegiatan menunjukkan game “Nusantaraku” dapat meningkatkan motivasi belajar, pemahaman konsep nasionalisme, dan keterampilan bahasa Inggris, yang tercermin dari partisipasi aktif siswa, respon positif guru dan orang tua, serta kenaikan hasil evaluasi belajar. Kendala utama berupa keterbatasan perangkat digital dan kebutuhan pelatihan lanjutan bagi guru, namun secara umum kegiatan berhasil membawa perubahan nyata dalam proses pembelajaran yang lebih inklusif, menyenangkan, serta mendorong partisipasi seluruh pihak sekolah.
Perbandingan Hasil Evaluasi Algoritma K-Means dan K-Medoid Berdasarkan Kunjungan Wisatawan Mancanegara ke Indonesia Riska, Suastika Yulia; Farokhah, Lia
INTEGER: Journal of Information Technology Vol 8, No 1 (2023): Maret
Publisher : Fakultas Teknologi Informasi Institut Teknologi Adhi Tama Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31284/j.integer.2023.v8i1.3659

Abstract

Kegiatan Pariwisata merupakan salah satu kegiatan yang dapat mempengaruhi tingkat perekonomian suatu negara. Kegiatan pariwisata yang dapat menarik minat wisatawan mancanegara masuk ke Indonesia menjadi salah satu kontribusi pendapatan untuk Negara Indonesia. Berdasarkan data dari BPS menunjukkan adanya penurunan yang signifikan dari jumlah wisatawan mancanegara yang datang ke Indonesia. Tujuan penelitian ini adalah untuk membentuk kelompok negara-negara berdasarkan jumlah wisatawan mancanegara yang masuk ke Indonesia dari yang paling banyak hingga yang paling sedikit. Kemudian hasil pengelompokkan tersebut dapat digunakan sebagai acuan pemerintah untuk menerapkan strategi yang tepat untuk meningkatkan antusias wisatawan datang ke Indonesia. Algoritma yang digunakan untuk proses clustering adalah K-Means dan K-Medoids, dengan menerapkan nilai k=2, k=3, dan k=5. Proses evaluasi digunakan metode davies bouldin index. Hasil cluster terbaik dalam kasus ini adalah dengan menggunakan Algoritma K-Means dengan k=5, dan dengan hasil nilai davies bouldin index -0.302.
Co-Authors A.A. Ketut Agung Cahyawan W Abdul Aziz Muslim Abdul Aziz Muslim Achmad Noercholis Adriani Kala'lembang Adriani Kala’lembang Adriani Kala’lembang Agustinus Susanto, Syalomiele Pratama Ahda, Fadli Almu'ini Amin, Angger Nur Aqromi , Nur Lailatul BUKHORI, MOHAMMAD Fadhli Almu'ini Ahda Fadhli Almu’iini Ahda Fadilla Cahyaningtyas Faqih, Luthfi Ramdhan Farokah, Lia Farokhah, Lia Febrindasari, Chyndy Ginardi, R.V. Hari Hakkun Elmunsyah Hanif, Rifki Jaenal Arifin Justita Dura Kala'lembang, Adriani Lailatul Aqromi, Nur Laili Cahyani Lilis Widayanti Mufidatul Islamiyah, Mufidatul Muhammad Imron Rosadi Muhammad Imron Rosadi Nanik Suciati Nanik Suciati Nira Rusanti Prasetya, Hafid Arjul Prasetyo, Bima Puji Subekti R. V. Hari Ginardi Rahmawati, Nisrina Salsabil Reda Maulidina Restu Andra Ahmad Saeroji Rina Dewi Indah Sari Rina Dewi Indahsari Samsul Arifin Setyorini Setyorini Siti Maharani, Farah Shafiyah Siti Nurul Afiyah Siti Sendari Suci Imani Putri Sulistyo, Danang Arbian Sunu Jatmika, Sunu Syaad Patmanthara T. Bantug, Emilsa Triyanna Widiyaningtyas Vivi Aida Fitria Widya Adhariyanty Rahayu Widya Adhariyanty Rahayu Yogatama, Ahmad Nizar Yogie Susdyastama Putra Yudistira Arya Sapoetra