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All Journal KARMAPATI (Kumpulan Artikel Mahasiswa Pendidikan Teknik Informatika) ISSN: 2252-9063 Jurnal Sistem Informasi dan Bisnis Cerdas Indonesian Journal of Information System Jurnal Eksplora Informatika SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Informatika Universitas Pamulang INTECOMS: Journal of Information Technology and Computer Science Jurnal DISPROTEK Compiler Jurnal ULTIMA InfoSys JUTEKIN (Jurnal Manajemen Informatika) INTEK: Informatika dan Teknologi Informasi Dharma Bakti JMAI (Jurnal Multimedia & Artificial Intelligence) Antivirus : Jurnal Ilmiah Teknik Informatika Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi JISKa (Jurnal Informatika Sunan Kalijaga) Technologia: Jurnal Ilmiah Informatika Jurnal Sistem informasi dan informatika (SIMIKA) JATI (Jurnal Mahasiswa Teknik Informatika) Jurnal Teknika JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Masyarakat Berdaya dan Inovasi Jurnal Sistem Komputer dan Informatika (JSON) Infotek : Jurnal Informatika dan Teknologi SKANIKA: Sistem Komputer dan Teknik Informatika Jurnal Teknik Informatika (JUTIF) Jurnal Restikom : Riset Teknik Informatika dan Komputer Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer) RESOLUSI : REKAYASA TEKNIK INFORMATIKA DAN INFORMASI Lumbung Inovasi: Jurnal Pengabdian Kepada Masyarakat Jurnal ABM Mengabdi International Journal of Community Service Society: Jurnal Pengabdian Masyarakat Konstelasi: Konvergensi Teknologi dan Sistem Informasi Jurnal Teknik Informatika Jurnal Informatika Teknologi dan Sains (Jinteks) Journal Of Information System And Artificial Intelligence Jurnal Sistem Informasi dan Bisnis Cerdas AMMA : Jurnal Pengabdian Masyarakat Jurnal Informatika: Jurnal Pengembangan IT Prosiding Seminar Nasional Pemberdayaan Masyarakat (SENDAMAS) Exhibition and Seminar on Science and Creative Technology – Al Azhar Proceeding International Journal of Informatics Engineering and Computing
Arita Witanti
Universitas Mercu Buana Yogyakarta
Religion Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Klasifikasi Buah dan Sayuran Segar atau Busuk Menggunakan Convolutional Neural Network Munfaati, Eka Aenun Nisa; Witanti, Arita
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 9 No. 1 (2024): Januari 2024
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2024.9.1.27-38

Abstract

Fresh fruits and vegetables contain many nutrients, such as minerals, vitamins, antioxidants, and beneficial fiber, superior to those found in rotten or almost rotten produce. On the other hand, fruits and vegetables that are nearly spoiled or already rotten have significantly lost their nutritional value. Rotten produce also harbors bacteria and fungi that can lead to infections and food poisoning when consumed. Convolutional Neural Network (CNN) offers a programmable solution for classifying fresh and rotten fruits and vegetables. Image processing using the TensorFlow library is employed in this classification process. During testing on the training data, the CNN achieved an accuracy of 90.42%. In comparison, the validation accuracy reached 94.21% when using the SGD optimizer, 20 epochs, a batch size 16, and a learning rate of 0.01. For the testing data, the accuracy obtained was 80.83%.
Sistem Pendukung Keputusan Dalam Pemilihan Smartphone dengan Metode SAW Natanael Dimas Randy; Arita Witanti
Resolusi : Rekayasa Teknik Informatika dan Informasi Vol. 4 No. 5 (2024): RESOLUSI May 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/resolusi.v4i5.1867

Abstract

The rapid development of technology in this era has a positive impact on people from various walks of life, including children, adults, and the elderly, who can all benefit from the technology available today. The positive impact of technology includes fast and easy access to information, which can be done anywhere, serving as a learning tool, helping to reduce stress, and even providing income opportunities. Smartphones, or smartphones, are one such technology that is almost owned by everyone because they are sophisticated and practical devices. Due to the increasing demand for smartphones, many companies are striving to produce them. Among the various smartphone brands available, Chinese brands are widely used by Indonesian people due to their competitive prices and specifications in the Indonesian market. The abundance of Chinese smartphones has led to confusion among consumers when choosing a smartphone that suits their needs in terms of specifications and price. In addressing this issue, researchers have developed a website to assist people in choosing smartphones using the Simple Additive Weighting decision support system method. There are 5 criteria and 30 alternatives in this system. People can adjust the criteria values to display results that meet their needs. After the calculation process, the smartphone name Realme 9 obtained a final score of 0.93, making it a viable choice for consumers when purchasing a smartphone.
Penerapan Sistem Pendukung Keputusan Untuk Rekomendasi Pemilihan VGA Terbaik 2024 Menggunakan Metode Weighted Product Krisna Bima Bagus Saputra; Arita Witanti
Resolusi : Rekayasa Teknik Informatika dan Informasi Vol. 4 No. 6 (2024): RESOLUSI July 2024
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/resolusi.v4i6.2010

Abstract

In recent years, the development of VGA technology has advanced rapidly, with various brands and models offering diverse specifications and features. Modern VGA cards are not only used for basic needs such as displaying images but also for more complex tasks like 3D graphics rendering, video editing, and gaming. This advancement provides consumers with many choices but also creates confusion in determining the VGA that best fits their needs and budget. Making the right decision in choosing a VGA becomes a particular challenge, especially for users without in-depth knowledge of technical specifications and VGA performance. Incorrect choices can lead to suboptimal computer performance, inefficient power usage, and user dissatisfaction. To address this issue, researchers have developed a web-based decision support system that recommends the best VGA selection using the Weighted Product method. This system performs calculations on 30 VGA data points based on 5 established criteria: price, memory capacity (VRAM), graphic resolution, power consumption, and number of supported monitors. The calculations reveal that the AMD Radeon RX 7900 XTX achieved the highest recommendation score at RSC Computer Store in Klaten, with a score of 0.058507812, followed by the NVIDIA GeForce RTX 4080 with a score of 0.058243034, and the AMD Radeon RX 7900 XT with a score of 0.055677317. This system demonstrates its effectiveness in providing accurate and beneficial recommendations for consumers in selecting a VGA according to their preferences and needs.
ANALISIS SENTIMEN MASYARAKAT INDONESIA MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE TENTANG PILPRES 2024 Alexander Radja Bria, Nyongki; Witanti, Arita
JATI (Jurnal Mahasiswa Teknik Informatika) Vol. 7 No. 6 (2023): JATI Vol. 7 No. 6
Publisher : Institut Teknologi Nasional Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36040/jati.v7i6.8184

Abstract

Pemilihan Umum Presiden (Pilpres) merupakan salah satu momen politik terpenting di Indonesia yang terjadi setiap lima tahun sekali. Lebih dari sekadar proses memilih kepala negara, Pilpres juga mencerminkan aspirasi, harapan, dan pandangan masyarakat terhadap pemerintahan dan arah negara. Dalam konteks ini, pemahaman mengenai sentimen masyarakat menjelang Pilpres 2024 menjadi hal yang penting. Penelitian ini difokuskan pada analisis sentimen terkait Pemilihan Presiden 2024 apakah cenderung positif, negatif, atau netral, dengan memanfaatkan data dari platform Twitter. Metodologi yang dipergunakan pada penelitian ini melingkupi tahap crawling data, pengolahan data, dan analisis sentimen. Data dikumpulkan menggunakan bahasa pemrograman Python pada aplikasi web Google Colab dengan menggunakan API Key Twitter. Metode klasifikasi SVM (Support Vector Machine) digunakan untuk mengklasifikasikan data. Dari hasil klasifikasi, didapatkan accuracy sebesar 65%, dengan kinerja yang lebih unggul dalam mengidentifikasi sentimen positif, mencapai precision 69%, recall 81%, dan f1-score 74%. Penelitian ini menggambarkan proses lengkap dari hasil pengumpulan data hingga klasifikasi sentimen menggunakan algoritma SVM. Hasilnya menunjukkan bahwa model cenderung lebih baik dalam mengidentifikasi sentimen positif dengan tingkat keakuratan yang cukup baik.
Pendampingan Guru “PAUD Bintang Bintang” untuk Menumbuhkan Karakter Sociopreneur Soeharto, Triana Noor Edwina Dewayani; Witanti, Arita; Rengganis, Domnina Rani Puna
Prosiding Seminar Nasional Pemberdayaan Masyarakat (SENDAMAS) Vol 1, No 1 (2022): Maret 2022
Publisher : UniversitasAl Azhar Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36722/psn.v1i1.3263

Abstract

Permasalahan yang dialami guru-guru PAUD adalah kegiatan yang diwadahi dalam “Kangen Dolan” belum berkembang optimal. Guru-guru Paud belum memiliki pengetahuan dan ketrampilan yang optimal untuk menjadikan kegiatan dalam Kangen Dolan menjadi kegiatan yang produktif. Guru- guru PAUD ingin menjadi pribadi yang kreatif, produktif, berdaya guna, dan menginspirasi guru-guru PAUD lain untuk mengembangkan dirinya. Berdasarkan hal tersebut maka solusi yang ditawarkan adalah memberikan pengetahuan tentang psikologi konsumen dan pemasaran, memberi pengetahuan dan ketrampilan tentang media online selain sebagai media pemasaran. Metode yang dilakukan diawali dengan membangun kerjasama dengan mitra, memberi pengetahuan dan pelatihan pemasaran berdasar psikologi konsumen dan pemasaran serta menggali produk unggulan berbasis kearifan lokal, membekali dengan kemampuan dasar teknologi informasi salah satunya dengan penggunaan Instagram supaya lebih efektif untuk pemasaran, dan sharing session berbagi ilmu dengan pakar sociopreneur. Keberhasilan yang dicapai “Kangen Dolam” setelah mengikuti kegiatan ini adalah guru memiliki pengetahuan tentang psikologi konsumen dan pemasaran sekaligus dapat dipraktekkan; memiliki pengetahuan dan ketrampilan tentang media online selain sebagai media pemasaran.Kata kunci: Pendampingan, Karakter, Sociopreneur
Implementasi Algoritma Apriori Dalam Menentukan Pola Pembelian Parfum Berbasis Website William, Haris; Witanti, Arita
Journal Of Information System And Artificial Intelligence Vol. 5 No. 1 (2024): Vol. 5 No. 1 (2024): Vol. 5 No. 1 (2024): Journal of Information System and Art
Publisher : Universitas Mercu Buana Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26486/jisai.v5i1.112

Abstract

Ada banyak toko yang membuka usaha penjualan produk wewangian, salah satunya adalah Evelyn Perfum, kondisi seperti ini membuat banyak persaingan di dunia bisnis. Maka dibuatlah sebuah sistem berbasis web dengan mengolah data transaksi penjualan menjadi informasi yang dapat membantu pemliki toko Evelyn Perfum dalam meningkatkat strategi penjualan. Sistem ini menggunakan algoritma apriori dengan metode Association Rules. Aturan asosiasi adalah salah satu teknik penambangan data yang digunakan untuk menentukan hubungan antara item dalam kumpulan data yang telah ditentukan sebelumnya. Sistem ini dapat menentukan kombinasi dari kumpulan itemset, pembentukan kaidah asosiasi 2 itemset atau 3 itemset, perhitungan nilai support dan nilai confidence. Berdasarkan tabel analisa data transaksi penjualan periode 1 Januari 2020 sampai dengan 18 Juli 2020 mengetahui 2 itemset tertinggi adalah Pale Angel Wk => Catty Parry sebesar 51,52%.
Klasifikasi Ras Kelinci Menggunakan Convolutional Neural Network (CNN) untuk Optimasi Sistem Identifikasi Visual Huda, Maasyaril Kirom Mi’Rojul; Witanti, Arita
Journal of Information System Research (JOSH) Vol 6 No 2 (2025): Januari 2025
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v6i2.6627

Abstract

Rabbits are mammals that come in many varieties with unique and diverse physical characteristics. Differentiating various types of rabbits, especially those with physical similarities and color patterns, is a challenge for some people because of their similar visual appearance. The purpose of this research is to develop a Convolutional Neural Network (CNN)-based rabbit breed classification system using MobileNetV3 architecture. A dataset of 1,500 images of three rabbit breeds (bligon, hyla, and new zealand white) was processed through resizing, augmentation, and normalization to improve data quality. The model was trained using Adam's optimizer with 97% accuracy on the validation data and 90% on the external dataset, showing good generalization ability. These results confirm the effectiveness of CNNs over manual methods in visual pattern recognition, while overcoming time constraints and human error. However, limitations in dataset variations, such as lighting and image capture angle, affect the generalization of the model. This research not only supports the efficiency of livestock management but also shows the great potential of AI application in Indonesia's livestock sector. Development of more diverse datasets and exploration of other model architectures are recommended for future performance improvements.
Sistem Pendukung Keputusan Penghuni Asrama Mahasiswa Kalimantan Tengah di Yogyakarta Menggunakan Metode Simple Additive Weighting (SAW) Mahmudie, Bagus; Witanti, Arita
Jurnal Informatika Vol 12, No 3: INFORMATIKA
Publisher : Fakultas Sains & Teknologi, Universitas Labuhanbatu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36987/informatika.v12i3.6824

Abstract

The Central Kalimantan Student Dormitory, located at Jalan Pakuningratan No.61 Yogyakarta, is one of the provincial dormitories established and funded by the regional government to serve as housing for students from outside the region who stay for a certain period. It is specifically intended for students currently studying, with a capacity of 24 rooms. Due to the limited number of rooms and the growing number of students from Central Kalimantan, which exceeds 24 individuals, the dormitory faces challenges in managing its residents. To assist dormitory managers in selecting suitable candidates for residency, the author conducted research on a web-based decision support system designed to streamline the selection process for Central Kalimantan students seeking accommodation at the dormitory in Yogyakarta. This system evaluates students based on criteria that reflect their eligibility to occupy a dormitory. By utilizing web-based decision support technology and employing the Simple Additive Weighting (SAW) method, the system processes various criteria, including data on prospective residents, academic readiness, adaptability, need for social support, and commitment to dormitory rules. With an accuracy rate of 93.3%, as determined by comparing original data, this system ensures a faster, more accurate, transparent, and efficient selection process based on objective data.
Strengthening Knowledge of AI-based applications to facilitate the preparation of learning media for teachers at TKIT Mekar Insani Minggiran Yogyakarta Witanti, Arita; Soeharto, Triana Noor Edwina Dewayani; Apriani, Nana
Society : Jurnal Pengabdian Masyarakat Vol 4, No 1 (2025): Januari
Publisher : Edumedia Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55824/jpm.v4i1.485

Abstract

Artificial intelligence (AI) technologies offer transformative opportunities in educational settings, particularly for teachers who are preparing interactive learning materials for early childhood education (ECE). However, challenges persist in their implementation, such as limited teacher knowledge, infrastructure barriers, and ethical concerns. This study aims to enhance teachers' knowledge at TKIT Mekar Insani, Yogyakarta, by providing training through mini workshops and supporting resources, such as refurbished computers. The program involved 25 teachers and included pre- and post-training evaluations. Results indicate a significant increase in teachers' ability to use AI-based tools, demonstrated by the production of engaging learning materials and improved confidence in integrating technology into their pedagogy. This initiative highlights the importance of bridging technology gaps in educational institutions and fostering continuous professional development.
ANALISIS SENTIMEN AKHIR MASA JABATAN PRESIDEN JOKOWI PADA MEDIA SOSIAL X MENGGUNAKAN NAÏVE BAYES Salsabilla, Fadiah Nur; Witanti, Arita
SKANIKA: Sistem Komputer dan Teknik Informatika Vol 8 No 1 (2025): Jurnal SKANIKA Januari 2025
Publisher : Universitas Budi Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36080/skanika.v8i1.3331

Abstract

Penelitian ini bertujuan untuk mengklasifikasikan sentimen terhadap Presiden Joko Widodo di Media Sosial X/Twitter pada masa akhir jabatannya. Metode yang digunakan adalah Complement Naïve Bayes (CNB) dengan penerapan SMOTE (Synthetic Minority Over-sampling Technique) untuk mengatasi masalah ketidakseimbangan data. Evaluasi dilakukan dengan dua variasi rasio data latih dan data uji, yaitu 90:10 dan 80:20. Pada rasio 90:10, model menunjukkan kinerja terbaik dengan mencapai 88% accuracy, precision, recall, dan f1-score. Namun, pada rasio 80:20, kinerja model mengalami penurunan dengan nilai 81% untuk semua metrik. Analisis sentimen menunjukkan bahwa sentimen negatif mendominasi, diikuti dengan sentimen netral dan positif, yang mencerminkan ketidakpuasan publik terhadap kebijakan-kebijakan tertentu pada periode akhir masa jabatan Presiden Jokowi.
Co-Authors Abdul Rahman Wahid Agus Tri Widiyanto Akhmad Muzaki Alexander Radja Bria, Nyongki Apriani, Nana Ardhian Yulihandra Hanum Ari Widiyatmoko Arnanda Nuryasa Asshiddiq, Muh. Hasbi Bangkit Sasangka Bowo Nugroho Dharmawan, Thoriq Didik Kurniawan Djaelani Sosanto Domnina Rani Puna Rengganis Eko Hariyanto Fatimah, Malida Fatkhurrahman Hazmi, Shadrina Heri Ardiansyah Herli Setiawan Herwinsyah Huda, Maasyaril Kirom Mi’Rojul Ibnu Fajar Shiddiq Indah Susilawati Insan, Fariq Maulana Jeffri, Derry Meilana Krisna Bima Bagus Saputra M. Abdurozik Mahendra Wahyu Prihantoro Mahmudie, Bagus Muh. Fahrurrozi Mukhamad Arifin Munfaati, Eka Aenun Nisa Mutaqin Akbar Nadiyah, Raden Ayu Salma Naftali Sulardi Natanael Dimas Randy Nesya Rogawati Novriansyah Rosi Nur Lestari Puji Oktavia, Feliana Ozzi Suria Pambudi, Wahyu Tities Parjono, Parjono Pramana Adi Setiawan Prasetyaningrum, Putri Taqwa Pusaka, Semerdanta Putry Wahyu Setyaningsih Recoba Abednego Davinci Reizandi, Dwisatya Rengganis, Domnina Rani Puna Rina Dwiarti Rizqi Oktafiani Rogawati, Nesya Sadikin, Arif Maulana Salsabilla, Fadiah Nur Saputra, David Saputro, Fredy Siti Mutia Candra Soeharto, Triana N.E.D Sowanya Ardi Prahara Subarjo subarjo, Subarjo Supatman Supatman Supatman Supatman, Supatman Tito Rikanto Triana Noor Edwina Dewayani Soeharto Triana Noor Edwina Dewayani Soeharto vanrika, adena reis Wahyu Setyaningsih, Putry Wahyu Tities Pambudi Wahyu Tities Pambudi Wibowo, Ibnu Surya Widarta Widarta, Widarta Widatama, Krisna William, Haris Wulandari, Erika Yetti Lutiyan Suprapto