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All Journal Jurnal Sistem dan Informatika Jurnal Sistem Informasi dan Bisnis Cerdas Register: Jurnal Ilmiah Teknologi Sistem Informasi RABIT: Jurnal Teknologi dan Sistem Informasi Univrab JURNAL MEDIA INFORMATIKA BUDIDARMA Jurnal Eksplora Informatika Abdimas Umtas : Jurnal Pengabdian kepada Masyarakat Jurnal SITECH : Sistem Informasi dan Teknologi Building of Informatics, Technology and Science Jurnal Teknologi Dan Sistem Informasi Bisnis Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat International Journal of Advances in Data and Information Systems Jurnal Pengabdian kepada Masyarakat Jurnal Abdi Masyarakat Indonesia International Journal Of Computer, Network Security and Information System (IJCONSIST) Journal of Computer Science and Informatics Engineering Jurnal Locus Penelitian dan Pengabdian Jurnal Sains dan Teknologi JOMPA ABDI: Jurnal Pengabdian Masyarakat Journal of Information System and Artificial Intelligence Journal Research of Social Science, Economics, and Management Jurnal Edukasi Pengabdian Masyarakat: EDUABDIMAS ABDINE :Jurnal Pengabdian Masyarakat
Albert Yakobus Chandra
Universitas Mercu Buana Yogyakarta
Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Nursing Public Health Social Sciences Other

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Measuring Resampling Methods on Imbalanced Educational Dataset’s Classification Performance Pratama, Irfan; Prasetyaningrum, Putri Taqwa; Chandra, Albert Yakobus; Suria, Ozzi
Register: Jurnal Ilmiah Teknologi Sistem Informasi Vol 10 No 1 (2024): January
Publisher : Information Systems - Universitas Pesantren Tinggi Darul Ulum

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26594/register.v10i1.3397

Abstract

Imbalanced data refers to a condition that there is a different size of samples between one class with another class(es). It made the term “majority” class that represents the class with more instances number on the dataset and “minority” classes that represent the class with fewer instances number on the dataset. Under the target of educational data mining which demands accurate measurement of the student’s performance analysis, data mining requires an appropriate dataset to produce good accuracy. This study aims to measure the resampling method’s performance through the classification process on the student’s performance dataset, which is also a multi-class dataset. Thus, this study also measures how the method performs on a multi-class classification problem. Utilizing four public educational datasets, which consist of the result of an educational process, this study aims to get a better picture of which resampling methods are suitable for that kind of dataset. This research uses more than twenty resampling methods from the SMOTE variants library. as a comparison; this study implements nine classification methods to measure the performance of the resampled data with the non-resampled data. According to the results, SMOTE-ENN is generally the better resampling method since it produces a 0,97 F1 score under the Stacking classification method and the highest among others. However, the resampling method performs relatively low on the dataset with wider label variations. The future work of this study is to dig deeper into why the resampling method cannot handle the enormous class variation since the F1 score on the student dataset is lower than the other dataset.
Sistem Pakar Penentuan Jenis Kulit Wajah Menggunakan Metode Dempster Shafer Kotimah, Kusnul; Chandra, Albert Yakobus
Jurnal Sains dan Teknologi (JSIT) Vol. 2 No. 1 (2022): January-April
Publisher : CV. Information Technology Training Center - Indonesia (ITTC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1077.557 KB) | DOI: 10.47233/jsit.v2i1.75

Abstract

Omah Milla is a beauty treatment center that provides services from head to toe. One of the existing facilities is consulting services to determine the right treatment, but until now the consultation facility is only served offline. In order to continue to develop in improving services, Omah Milla wants to present an online consultation system that can be accessed by everyone so that customers can consult at anytime and anywhere. In addition, the general public can also use this system to check facial skin types, so they don't need to hesitate to determine the type of facial skin and use the right skincare. In this study, an expert system was created to determine the type of facial skin. The method used was the dempster shader. The flow of using this system is firstly the user is asked to choose the symptoms experienced, then the system processes it by calculating the dempster shafer and the results of the skin type can be directly seen by the user. This system has gone through the functionality test phase and everything is running and functioning well. To determine the accuracy of the system, the researcher compared 50 data from experts with an expert system and this study has an accuracy value of 100%.
Sistem Pakar Diagnosa Tingkat Depresi Pada Lansia Di Balai Sosial Tresna Werdha Menggunakan Metode Certainty Factor AzhariMalindo, M.; Chandra, Albert Yakobus
Jurnal Sains dan Teknologi (JSIT) Vol. 1 No. 2 (2021): Jurnal Sains dan Teknologi (JSIT)
Publisher : CV. Information Technology Training Center - Indonesia (ITTC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jsit.v1i2.116

Abstract

Depressive disorder in the elderly is a clinical and public health issue that has yet to be addressed. The elderly who live at home with their families have better physical, psychological, and environmental health than those who live in orphanages. Mental health issues, particularly depression, frequently go undiagnosed in the elderly. This is because older people who are depressed often have physical symptoms like insomnia, loss of appetite, stomach problems, and headaches. When older people are depressed, their bodies tend to hurt more. It is hard to tell whether someone is complaining about their body or mind, so depression is often found too late. To anticipate these issues, an expert system was created that can take the place of an expert in solving the problem. A clinical psychologist is an expert in the field of elderly depression. This study classified elderly depression into three levels: mild depression, moderate depression, and major depression. This study was carried out with the help of a case study from the Tresna Werdha Pakem Social Center in Sleman, DI Yogyakarta.The Certainty Factor method was used to make an expert system for determining how depressed an older person is. This is because it is a sure thing based on evidence or an expert's opinion. The goal of developing an expert system for diagnosing depression in the elderly is for expert and non-expert officers to diagnose the level of depression in the elderly. Based on 10 elderly data that the system and experts have tested by applying the Certainty Factor method, the accuracy was 98%.
Analisis Perbandigan Kinerja Model CNN Resnet-50, VGG19 dan Mobilenet dalam Klasifikasi Penyakit pada Tamnaman Mete Bang Ritan, Febriyanto Maria; Chandra, Albert Yakobus
Jurnal Locus Penelitian dan Pengabdian Vol. 4 No. 8 (2025): JURNAL LOCUS: Penelitian dan Pengabdian
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/locus.v4i8.4261

Abstract

Penyakit pada tanaman jambu mete (Anacardium occidentale) seperti anthracnose, gumosis, leaf miner, dan red rust menjadi kendala utama yang mengancam produktivitas dan menyebabkan kerugian ekonomi bagi petani di Indonesia. Deteksi dini penyakit ini sangat penting untuk meningkatkan hasil panen dan keberlanjutan budidaya mete. Penelitian ini bertujuan untuk membandingkan kinerja tiga arsitektur Convolutional Neural Networks (CNN), yaitu ResNet50, VGG19, dan MobileNet, dalam mengklasifikasikan lima kategori penyakit pada tanaman mete menggunakan dataset citra digital. Metode yang digunakan meliputi pelatihan dan evaluasi ketiga model CNN dengan metrik akurasi, presisi, recall, dan F1-score sebagai ukuran performa. Hasil evaluasi menunjukkan bahwa model ResNet50 memberikan performa terbaik dengan akurasi 97,61%, diikuti oleh MobileNet dengan 95,67%, dan VGG19 dengan 92,57%. Kesimpulannya, ResNet50 direkomendasikan sebagai model yang paling efektif untuk klasifikasi penyakit pada tanaman mete karena kemampuannya memberikan hasil yang paling akurat dan konsisten. Penelitian ini memberikan kontribusi penting dalam pengembangan teknologi deteksi penyakit tanaman berbasis deep learning untuk mendukung pertanian modern.
Analisis Perbandingan Akurasi Model EfficientNetB0 dan Vision Transformer Dalam Klasifikasi Citra Motif Batik Giriloyo Sari, Ratna Puspita; Chandra, Albert Yakobus
Building of Informatics, Technology and Science (BITS) Vol 7 No 1 (2025): June (2025)
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v7i1.7343

Abstract

Batik is a cultural heritage owned by Indonesia and has been inaugurated by UNESCO on October 2, 2009. In this digital era, the variety of batik motifs must be preserved, especially in Giriloyo Batik Village located in Karang Kulon, Wukirsari, Imogiri Sub-district, Bantul. The complexity and diversity of batik motifs in the area require a modern technological approach to assist the accurate classification process. This study aims to compare the performance of the two current models, EfficientNetB0 and Vision Transformer, in classifying five classic batik motifs in Kampung Batik Giriloyo. This research method combines deep learning approach based on Convolutional Neural Network (CNN) and Transformer with training process from zero without transfer learning. The research stages used include dataset collection, prepocessing, augmentation, model building and training, evaluation and visualization of result comparison. Evaluation is done using accuracy, precision, recall, F1-score and inference time efficiency metrics. The final dataset amounted to 13,128 sliced batik images. The dataset is then divided into 3 main parts, namely training data by 80%, validation data by 10% and testing data by 10% of the total dataset. The final results showed that Vision Transformer achieved the best performance with testing accuracy reaching 99.85 and the EfficientNetB0 model gave an accuracy of 98.78% with stable efficiency. This research confirms that the Vision Transformer model is superior in extracting global patterns in complex batik motifs. This research also makes a real contribution to the utilization of artificial intelligence in cultural preservation through the classification of digital batik motifs and the development of a classic batik motif classification system in Giriloyo Batik Village.
COMPARISON OF SUPPORT VECTOR MACHINE RADIAL BASE AND LINEAR KERNEL FUNCTIONS FOR MOBILE BANKING CUSTOMER SATISFACTION ANALYSIS Putri Taqwa Prasetyaningrum; Nurul Tiara Kadir; Albert Yakobus Chandra; Irfan Pratama
IJCONSIST JOURNALS Vol 4 No 1 (2022): September
Publisher : International Journal of Computer, Network Security and Information System

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33005/ijconsist.v4i1.75

Abstract

Banking services using mobile banking applications, including Indonesian state bank (called BRI). A study on feedback regarding BRI services based on mobile applications was done. In order to compete with other banks, that is used to enhance and modernize the quality of BRI services provided to clients. Based on phenomena that occur in these situations. This study aims to classify comments from users of the BRI Mobile Banking Application on Google Play services into positive and negative comment sentiments. In this study, the Support Vector Machine (SVM) technique is utilized to determine between positive or negative reviews. The sentiment analysis of BRI google play data was carried out by comparing the Radial Basis Function (RBF) kernel function and the Linear kernel. As well as the experiment of adding feature selection, parameters, and n-grams for a period of two years, from January 1st,, 2017 to December 31st, 2018. The results of the study using the k-fold cross-validation test, the precision value of the SVM kernel linear is 90.80 percent and the SVM kernel RBF is 90.15 percent. In the RBF kernel, there are 1,816 positive classes and 1,455 negative classes. While the Linear kernel obtained a positive class of 1,734 and a negative class of 1,637.
IMPLEMENTASI LANDBOT SEBAGAI PENGHUBUNG DIALOGFLOW NLP DENGAN WEB INFORMASI KEPADA CIVITAS AKADEMIK Fransiska Natalia; Albert Yakobus Chandra
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 9 No 2 (2024): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v9i2.4262

Abstract

Saat ini banyak universitas telah menggunakan sistem Informasi web untuk menyampaikan Informasi. Namun, masih sering terjadi kendala yang dialami mahasiswa dan calon mahasiswa yaitu sistem yang masih memberikan Informasi secara general, kesulitan dalam mencari informasi terkait perkuliahan, serta unit atau kontak admin yang diperlukan untuk menangani kendala yang dihadapi calon mahasiswa baru , baik di jam kerja dan di luar jam kerja. Oleh karena itu, pada penelitian prototipe chatbot ini menggunakan sebuah platform berupa dialogflow dan landbot yang akan digunakan yaitu untuk mengatasi masalah yang dihadapi dan mempermudah para civitas akademik mendapatkan informasi. Adapun tahapan dalam pengembangan aplikasi chatbot ini yaitu analisis kebutuhan, desain, membuat prototipe, evaluasi dan rilis aplikasi. Metode yang digunakan dalam pembuatan chatbot ini yaitu Natural Language Processing (NLP).Proses pemberian pengetahuan dalam chatbot ini mencakup data terkait Informasi yang dibutuhkan sehingga apa yang ditanamkan dalam dialogflow dan landbot berguna untuk meningkatkan pemahaman konteks dan makna pertanyaan. Dalam hal ini pula, pelatihan model machine learning digunakan untuk meningkatkan keterampilan pemrosesan bahasa alami landbot. Berdasarkan hasil pengujian yang dilakukan aplikasi ini berjalan 100% dengan baik. Dalam hal ini menunjukan bahwa, chatbot ini mampu menjawab pertanyaan-pertanyaan yang diberikan, serta dapat mengenali pengetahuan yang telah diberikan sebelumnya.
ANALISIS SENTIMEN PUBLIK DI MEDIA SOSIAL TERHADAP KASUS DUGAAN KORUPSI IMPOR MINYAK PERTAMINA MENGGUNAKAN XGBOOST Dhea Ferdiana Merpatika; Albert Yakobus Chandra
Rabit : Jurnal Teknologi dan Sistem Informasi Univrab Vol 10 No 2 (2025): Juli
Publisher : LPPM Universitas Abdurrab

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36341/rabit.v10i2.6307

Abstract

Public sentiment analysis of the alleged corruption case of oil imports by PT Pertamina was carried out using a machine learning approach using the Extreme Gradient Boosting (XGBoost) algorithm. Data was obtained from user comments on Pertamina's official accounts on social media platforms X, Instagram, and TikTok during the period from February 1, 2025 to March 31, 2025. Comments collected through the scraping process were then processed through text preprocessing stages such as normalization, tokenization, filtering, and stemming. Feature representation was carried out using the Term Frequency-Inverse Document Frequency (TF-IDF) method to convert text data into numeric form. Each comment was manually labeled with sentiment into three categories, namely negative (0), neutral (1), and positive (2). The XGBoost model was trained with TF-IDF extracted data and evaluated using metrics such as accuracy, precision, recall, and f1-score. The evaluation results showed that the model was able to classify sentiment with good performance, with an accuracy value of 78% and an F1-score of 78%. The application of this method shows the effectiveness of the machine learning approach in understanding public perception of strategic issues in the national energy sector. The findings show that only 8% of positive sentiment on platform X, Instagram and TikTok indicates a crisis of public trust that needs to be responded to by Pertamina.
Pengembangan Website Galeri Produk UMKM sebagai Upaya Peningkatan Ekonomi Lokal di Kalurahan Bangunharjo Putry Wahyu Setyaningsih; Albert Yakobus Chandra; Irfan Pratama
Abdimas Galuh Vol 8, No 1 (2026): Maret 2026
Publisher : Universitas Galuh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25157/ag.v8i1.22244

Abstract

Program pengabdian ini dilaksanakan untuk menjawab kebutuhan penguatan promosi UMKM di Kalurahan Bangunharjo yang belum memiliki platform digital terintegrasi. Melalui pendekatan partisipatif, tim bersama mitra melakukan analisis kebutuhan, pengumpulan konten, perancangan antarmuka, serta pengembangan website galeri produk berbasis domain bangunharjo.id. Proses pengembangan melibatkan dokumentasi produk, penyusunan profil usaha, integrasi Google Maps, serta uji coba berulang guna memastikan kesesuaian dengan kebutuhan UMKM. Hasil implementasi menunjukkan bahwa website berfungsi efektif sebagai etalase digital yang menampilkan informasi UMKM secara terstruktur, sekaligus memperkuat identitas digital melalui elemen branding BUMKal dan penerapan prinsip UI/UX modern. Dampak program meliputi peningkatan kapasitas pemasaran, literasi digital pelaku UMKM, serta kredibilitas usaha lokal. Secara keseluruhan, platform ini menjadi instrumen strategis dalam mendukung penguatan ekonomi desa. Untuk ke depan, disarankan adanya pembaruan konten berkala dan integrasi lebih lanjut dengan media sosial serta fitur pemasaran digital.
Penerapan Aplikasi Literasi Media Baru Berbasis Web pada Guru-Guru MGBK Sleman Yogyakarta Haryadi Santoso, Didik; Setyaningsih, Rila; Yakobus Chandra, Albert
ABDINE: Jurnal Pengabdian Masyarakat Vol. 4 No. 2 (2024): ABDINE : Jurnal Pengabdian Masyarakat
Publisher : Institut Teknologi dan Bisnis Riau Pesisir

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52072/abdine.v4i2.1130

Abstract

New media memiliki kekuatan yang memberikan keleluasaan bagi para pengguna untuk memproduksi, mendistribusikan dan mengkonsumsi konten di ruang virtual. Namun, new media juga memiliki sisi yang memiliki efek dahsyat dan rentan bagi para penggunanya. Dalam konteks kehidupan dalam ruang virtual, new media pun dapat mempengaruhi banyak hal termasuk menimbulkan hate speech, cyber bullying, kecanduan game online, online sexual harrasment, judi online, cyberporn. Mitra pengabdian ini yaitu MGBK (Musyawarah Guru Bimbingan Konseling) wilayah kabupaten Sleman Yogyakarta. Berdasarkan observasi dan studi pendahuluan terdapat permasalahan yaitu: (1) Belum adanya pengetahuan dan pemahaman komprehensif tentang new media literacy. (2) Belum ada aplikasi new media literacy berbasis web yang dapat digunakan oleh para guru dan siswa (3) Belum adanya kemampuan dan keterampilan tentang new media literacy (4) Tidak adanya materi new media literacy dalam  kurikulum  pembelajaran. Tujuan pengabdian ini yaitu, Pertama, teimplementasikannya aplikasi berbasis web tentang new media literacy pada guru MGBK. Kedua, Peningkatan keterampilan new media literacy melalui pelatihan penggunaan aplikasi dan materi ajar new media literacy. Ketiga, Peningkatan pengetahuan, dan pemahaman tentang bermedia sosial yang sehat dan bijak, tentang digital ethic, digital culture dan digital skill. Keempat, Peningkatan akses layanan aplikasi new media literacy berbasis web agar dapat dimanfaatkan oleh guru melalui pendampingan penggunaan aplikasi
Co-Authors Adhien Kenya Estetikha Adi Slamet Priyadi Afit Setyo Nugroho Ahmad Iwan Fadli Albahry, Azizan AzhariMalindo, M. Bang Ritan, Febriyanto Maria Chatarina Lilis Suryani dewi, Ine shinta Dhea Ferdiana Merpatika Fransiska Natalia Haryadi Santoso, Didik Irfan Pratama Kusnul Kotimah, Kusnul Leonardi, M. Anjas Mardonius Wandi Pratama Murti, Siti Tamaroh Cahyono Musa, Rahmat Naili Inayah Wulandari Natalia, Fransiska Nurafiya, Nurafiya Nurul Tiara Kadir Nurul Tiara Kadir Prasetyaningrum, Putri Taqwa Pratama, Irfan Pusaka, Semerdanta Rahma Novita Alim Putri Ratna Puspita Sari, Ratna Puspita Rila Setyaningsih Setyaningsih, Putry Wahyu Setyaningsih, Rila Suria, Ozzi Taqwa Prasetyaningrun, Putri Wirawan Galeh Pradhana