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All Journal AMIKOM ICT AWARD 2010 Jurnal Simetris TEKNOLOGI: Jurnal Ilmiah Sistem Informasi Jurnal Buana Informatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) Proceeding Seminar LPPM UMP Tahun 2014 Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal Informatika dan Multimedia Jurnal Pilar Nusa Mandiri SINTECH (Science and Information Technology) Journal Applied Information System and Management Journal of Innovation in Business and Economics EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Journal of Information Systems and Informatics Journal of Robotics and Control (JRC) IJECA (International Journal of Education and Curriculum Application) Community Development Journal: Jurnal Pengabdian Masyarakat Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Jurnal AbdiMas Nusa Mandiri Journal of Soft Computing Exploration Jurnal Pendidikan dan Teknologi Indonesia Jurnal Pengabdian Masyarakat : Pemberdayaan, Inovasi dan Perubahan Jurnal Ilmiah IT CIDA : Diseminasi Teknologi Informasi Jurnal Pengabdian Masyarakat Jurnal Ilmu Komputer dan Teknologi (IKOMTI) Journal of Practical Computer Science (JPCS) Journal of Artificial Intelligence and Digital Business Inspiration: Jurnal Teknologi Informasi dan Komunikasi Jurnal Abdimastek (Pengabdian Masyarakat Berbasis Teknologi) Journal of Information Technology and Cyber Security Jurnal Manajemen Informatika, Sistem Informasi dan Teknologi Komputer (JUMISTIK) Journal of Informatics and Interactive Technology (JIITE) Jurnal Teknologi Riset Terapan
Dhanar Intan Surya Saputra
Program Studi Teknik Informatika, STMIK AMIKOM Purwokerto Jl. Letjen Pol Sumarto Watumas Purwanegara Purwokerto, Banyumas 53123
Religion Aerospace Engineering Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Mechanical Engineering Physics Public Health Social Sciences Other

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Comparative Analysis of Data Balancing Techniques for Machine Learning Classification on Imbalanced Student Perception Datasets Saekhu, Ahmad; Berlilana, Berlilana; Saputra, Dhanar Intan Surya
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 2 (2025): JUTIF Volume 6, Number 2, April 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.2.4286

Abstract

Class imbalance is a common challenge in machine learning classification tasks, often leading to biased predictions toward the majority class. This study evaluates the effectiveness of various machine learning algorithms combined with advanced data balancing techniques in addressing class imbalance in a dataset collected from Class XI students of SMK Ma'arif 1 Kebumen. The dataset, comprising 300 instances and 36 features, includes textual attributes, demographic information, and sentiment labels categorized as Positive, Neutral, and Negative. Preprocessing steps included text cleaning, target encoding, handling missing data, and vectorization. Four sampling techniques—SMOTE, SMOTE + Tomek Links, ADASYN, and SMOTE + ENN—were applied to the training data to create balanced datasets. Nine machine learning algorithms, including CatBoost, Extra Trees, Random Forest, Gradient Boosting, and others, were evaluated using four train-test splits (60:40, 70:30, 80:20, and 90:10). Model performance was assessed using metrics such as accuracy, precision, recall, F1-score, and AUC- ROC. The results demonstrate that SMOTE + Tomek Links is the most effective balancing technique, achieving the highest accuracy when paired with ensemble algorithms like Extra Trees and Random Forest. CatBoost also delivered competitive performance, showcasing its adaptability in imbalanced scenarios. The 90:10 train-test split consistently yielded the best results, emphasizing the importance of adequate training data for model generalization. This study highlights the critical role of data balancing techniques and robust algorithms in optimizing classification performance for imbalanced datasets and provides a framework for future research in similar contexts.
Pengembangan Jaringan Internet dalam Mendukung Pembelajaran di SD Negeri 2 Kebondalem Mustofa, Dinar; Prayoga, Agung; Pandega, Dimas Marsus; Wirasto, Anggit; Saputra, Dhanar Intan Surya
Jurnal Pengabdian Masyarakat - PIMAS Vol. 3 No. 2 (2024): Mei
Publisher : LPPM Universitas Harapan Bangsa Purwokerto

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35960/pimas.v3i2.1423

Abstract

Perkembangan teknologi informasi dan komunikasi yang pesat saat ini telah memberikan dampak signifikan pada berbagai aspek kehidupan manusia, termasuk dalam bidang pendidikan. SDN 2 Kebondalem, sebuah Lembaga Pendidikan Negeri di Kabupaten Banjarnegara, menghadapi keterbatasan akses internet di wilayah pedesaan tempat sekolah berada. Meskipun telah menerapkan jaringan internet, cakupannya saat ini terbatas pada bagian TU dan Ruang Guru. Keterbatasan ini menghambat guru dalam mengakses materi pembelajaran dan modul, menghambat proses pembelajaran di sekolah tersebut. Kegiatan Pengabdian pada masyarakat ini bertujuan untuk mengembangkan jaringan internet di seluruh area sekolah guna mendukung proses pembelajaran di SDN 2 Kebondalem. Perbaikan ini diharapkan dapat mempermudah pertukaran data, meningkatkan efisiensi penggunaan perangkat, serta meningkatkan kapasitas guru dan siswa melalui penerapan sistem pembelajaran daring.
Design of Instagram Comic Strips for Learning Media in Elementary School Iriane, Rara; Saputra, Dhanar Intan Surya; Indarto, Debi; Handani, Sitaresmi Wahyu; Indartono, Kuat
IJECA (International Journal of Education and Curriculum Application) Vol 5, No 3 (2022): December
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/ijeca.v5i3.11719

Abstract

Information was obtained based on the writer's interviews with the principal at SD Negeri   1 Rawalo elementary school. During the pandemic, students' interest in learning at SD Negeri 1 Rawaloelementary school was relatively low, especially for grade IV students. Especially for Mathematics, Natural Sciences, Social Sciences, Citizenship Education and Indonesian Language. Student interest is low during the pandemic because the learning media is less attractive. The principal wants engagingengaging learning media in the form of comics, such as on Instagram that is easily accessible while studying at home. This media is applied to increase student interest in learning during a pandemic, which must be by the characteristics of the material and learning objectives. Based on this background, the writer was inspired to make a digital comic as a learning medium for elementary school students in grade IV at SD Negeri 1 Rawaloelementary schoolschoolelementary school. The goal is the creation of comic learning media at SD Negeri 1 Rawaloelementary school. The system development method consists of three stages. The pre-production stage, the production stage, and the post-production stage.  The pre-production stage, at this stage is a process that includes determining ideas, themes and preparing storyboards. Storyboards are made with two-dimensional images of learning materials. At the production stage, comic character drawings are designed ,given backgrounds and coloring for characters using CorelDraw software. Then at the post production stage, the comic editing process begins using Adobe Photoshop software, starting from setting color balancing, giving shading, merging with comic text, after which the comics are exported and distributed on Instagram. In this research the evaluation of satisfaction learning media was carried out through a questionnaire and the questionnaire was calculated. The results of testing the comic learning media concluded that as many as 79.06%,  of and included in the category agree in the application of digital comics as a learning medium for grade IV at SD Negeri 1 Rawaloelementary school. And the post-production stage. The results of testing the comic learning media concluded that as many as 79.06%, of and included in the category agree with the application of digital comics as a learning medium for grade IV at SD Negeri 1 RawaloElementary school. And the post-production stage. The results of testing the comic learning media concluded that as many as 79.06% of and included in the category agree with the application of digital comics as a learning medium for grade IV at SD Negeri 1 RawaloElementary school.
Analisis Sentimen Ulasan Co-Pilot Google Play dengan SVM, Neural Network, dan Decision Tree Najibulloh, Imam Kharits; Tahyudin, Imam; Saputra, Dhanar Intan Surya
Jurnal Pendidikan Informatika (EDUMATIC) Vol 9 No 1 (2025): Edumatic: Jurnal Pendidikan Informatika
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v9i1.29673

Abstract

Sentiment analysis is a technique used to understand user opinions through product or service reviews. The purpose of this research is to compare three classification methods, namely Support Vector Machine (SVM), Neural Network (NN), and Decision Tree (DT) in analyzing the sentiment of users of the Indonesian-language Microsoft Co-Pilot application taken from the Google Play Store. The dataset consists of 20,000 reviews, which first went through preprocessing such as normalization, tokenization, stopwords removal, and stemming. The three methods we used in this study have a Multilayer Perceptron (MLP) architecture with three hidden layers and a ReLU activation function, as well as a dropout regularization technique to avoid overfitting. Model evaluation was conducted using accuracy, precision, recall, and F1-score, with the results showing that NN achieved the highest accuracy of 95.5%, followed by SVM with 95.4% and DT with 92.1%. The advantage of the NN method lies in its ability to recognize more complex patterns in Indonesian, especially in handling informal text and code-mixing. This research contributes to the development of Artificial Intelligence (AI)-based applications by providing insights into the effectiveness of classification methods in Indonesian sentiment analysis, which is important for improving service quality and the development of NLP technology in Indonesia. The practical implications of this research can be used in the development of AI-based applications that are more responsive to user sentiment.
Analisis Sentimen Ulasan Film pada Dataset IMDB menggunakan Algoritma Naive Bayes Zhafira, Alya; Afifah, Nurul; Anditya Putri, Shifa; Marhalatun, Viva; Surya Saputra, Dhanar Intan
Jurnal Manajemen Informatika, Sistem Informasi dan Teknologi Komputer (JUMISTIK) Vol 4 No 1 (2025): Jurnal Manajemen Informatika, Sistem Informasi dan Teknologi Komputer (JUMISTIK)
Publisher : STMIK Amika Soppeng

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70247/jumistik.v4i1.139

Abstract

ABSTRACT This study examines sentiment analysis of movie reviews from online platforms using a dataset obtained from Kaggle. The dataset consists of 50,000 reviews spanning various films, which are used to identify user sentiment, either positive or negative. After preprocessing the data to clean and prepare it, the Naïve Bayes algorithm is applied to classify the reviews based on their sentiment. Naïve Bayes was chosen due to its proven capability in text classification and its simplicity in implementation. The model’s evaluation was conducted using a confusion matrix and a classification report, resulting in an accuracy of 86.25%. Furthermore, the precision, recall, and F1-score values, each reaching 86%, indicate a good balance in the model’s ability to classify both positive and negative sentiments. These results confirm that Naïve Bayes is an efficient and effective algorithm for sentiment analysis of movie reviews. This research provides a valuable contribution to the field of sentiment analysis, particularly in understanding public opinion towards cinematic works. Additionally, the findings open up the potential use of this model in the development of sentiment-based recommendation systems, which can be applied across various online entertainment platforms. Keywords:Sentiment Analysis, Movie Reviews, Naïve Bayes, Kaggle Dataset   ABSTRAK   Penelitian ini mengkaji analisis sentimen terhadap ulasan film daring menggunakan dataset yang diperoleh dari platform Kaggle. Dataset ini terdiri dari 50.000 ulasan yang mencakup berbagai film, yang digunakan untuk mengidentifikasi sentimen pengguna, apakah positif atau negatif. Setelah melalui tahap preprocessing untuk membersihkan dan mempersiapkan data, algoritma Naïve Bayes diterapkan untuk mengklasifikasikan ulasan berdasarkan sentimennya. Naïve Bayes dipilih karena kemampuannya yang terbukti dalam klasifikasi teks dan kesederhanaannya dalam implementasi. Evaluasi model dilakukan menggunakan confusion matrix dan classification report, yang menghasilkan akurasi sebesar 86,25%. Selain itu, nilai precision, recall, dan F1-score yang masing-masing mencapai 86% menunjukkan keseimbangan yang baik dalam kemampuan model untuk mengklasifikasikan sentimen positif dan negatif. Hasil ini mengonfirmasi bahwa Naïve Bayes adalah algoritma yang efisien dan efektif dalam analisis sentimen ulasan film. Penelitian ini memberikan kontribusi penting dalam bidang analisis sentimen, khususnya dalam memahami opini publik terhadap karya sinematik. Selain itu, hasil yang diperoleh membuka potensi penggunaan model ini dalam pengembangan sistem rekomendasi berbasis sentimen, yang dapat diterapkan di berbagai platform hiburan online.     Kata kunci: Analisis Sentimen, Ulasan Film, Naïve Bayes, Dataset Kaggle
PELATIHAN PENGGUNAAN SPSS UNTUK ANALISIS DATA PENELITIAN TERINDEKS SCOPUS Saputra, Dhanar Intan Surya; Widiastuti, Sri; Muratno, Muratno; Soumena, Fadly Yashari; Sudarso, Hendra; Riny, Riny
Community Development Journal : Jurnal Pengabdian Masyarakat Vol. 5 No. 6 (2024): Vol. 5 No. 6 Tahun 2024
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/cdj.v5i6.37089

Abstract

Pelatihan Penggunaan SPSS untuk Analisis Data Penelitian Terindeks Scopus diadakan sebagai respons terhadap meningkatnya kebutuhan akan keterampilan analisis data yang akurat dan sesuai standar internasional di kalangan peneliti. Publikasi ilmiah yang terindeks di jurnal bereputasi seperti Scopus membutuhkan metodologi analisis yang tepat, yang hanya dapat dicapai dengan pemahaman mendalam tentang perangkat lunak statistik seperti SPSS. Pelatihan ini diikuti oleh 32 peserta yang berasal dari berbagai latar belakang akademik dan profesional, bertujuan untuk membekali mereka dengan keterampilan analisis yang dibutuhkan dalam menyusun penelitian berkualitas tinggi. Metode pelatihan mencakup penyampaian materi secara sistematis, praktik langsung dengan studi kasus, dan evaluasi akhir untuk mengukur pemahaman peserta. Hasil menunjukkan peningkatan signifikan dalam pemahaman dan keterampilan peserta dalam menggunakan SPSS, terutama dalam hal pemilihan uji statistik yang tepat dan interpretasi data. Kesimpulannya, pelatihan ini efektif dalam membantu peserta meningkatkan kualitas penelitian mereka, yang diharapkan dapat memenuhi standar publikasi internasional. Hasil ini menegaskan pentingnya pelatihan teknis yang terstruktur untuk mendukung kemampuan analisis data yang lebih baik di kalangan peneliti.
PEMANFAATAN MEDIA SOSIAL SEBAGAI SARANA PROMOSI PADA BISNIS JAMUR CRISPI FEN CLAIRE Anisa, Kholifatun; Saputra, Dhanar Intan Surya; Diningrum, Dwi Fatma; Nuraini, Eka
Jurnal Pengabdian Masyarakat Berbasis Teknologi Vol 2 No 1 (2021): VOLUME 2. NO 1. APRIL 2021
Publisher : ISB Atma Luhur

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32736/abdimastek.v2i1.1080

Abstract

Perkembangan internet saat ini terjadi sangat pesat, pertukaran informasi pun menjadi semakin mudah dan cepat. Hal ini yang membuat masyarakat cenderung lebih menggunakan internet untuk melakukan komunikasi. Media sosial memiliki banyak manfaat dalam kehidupan sehari-hari, tidak terkecuali untuk melakukan bisnis. Untuk bisnis, media sosial dapat dijadikan sebagai alat untuk melakukan promosi suatu produk. Tujuan penelitian adalah untuk mengetahui bagaimana memanfaatkan media sosial sebagai mdeia promosi suatu produk agar dapat dijangkau oleh konsumen, hambatan apa yang ada ketika menggukanan media sosial untuk promosi suatu produk makanan , dan solusi apa yang sebaiknya dilakukan dalam memanfaatkan media sosial sebagai media promosi. Metode menggunakan penelitian kualitatif deskriptif. Hasil penelitian menunjukkan bahwa, terdapat beberapa hambatan dalam pemanfaatan media sosial sebagai media promosi, dan terjawabnya hambatan dari pemanfaatan media sosial sebagai media promosi  oleh FEN Claire bersama melalui solusi yang dilakukan.
Analisis Kinerja Kualitas Layanan Jaringan Internet dengan HTB dan OLT Menggunakan Wireshark di Media Computindo Mustofa, Dinar; Saputra, Dhanar Intan Surya; Apitiadi, Satyo Dwi
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 11 (2025): JPTI - November 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.911

Abstract

Penelitian ini mengkaji kinerja Quality of Service (QoS) pada jaringan internet dengan menggunakan perangkat Home Telecom Box (HTB) dan Optical Line Terminal (OLT). Tujuan dari penelitian ini adalah untuk mengevaluasi perbandingan kinerja kedua perangkat berdasarkan empat parameter utama QoS, yaitu Throughput, Packet Loss, Delay, dan Jitter. Pengukuran dilakukan dengan menggunakan aplikasi Wireshark selama 10 menit dalam kondisi penggunaan normal, seperti membuka media sosial, streaming video, dan mengunduh file. Hasil penelitian menunjukkan bahwa OLT memiliki kinerja yang lebih baik dibandingkan HTB pada semua parameter yang diuji, dengan Throughput yang lebih tinggi, Packet Loss yang lebih rendah, Delay yang lebih cepat, dan Jitter yang lebih stabil. Hasil memberikan wawasan penting bagi penyedia layanan internet dalam memilih perangkat yang lebih efisien untuk meningkatkan kualitas layanan, terutama pada kondisi penggunaan jaringan yang padat. Oleh karena itu, perangkat OLT terbukti lebih optimal dalam mendukung jaringan yang stabil dan efisien.
Co-Authors Adam Prayogo Kuncoro Aditya Pratama Afrig Aminuddin Agus Pramono Al Haura, Adzkiyatun Nisa Alamsyah, Rizki Albana, Ilham Amalina, Siti Nahla Amin, M. Syaiful Ammar Fauzan, Ammar Andik Wijanarko, Andik Andina, Anisa Nur Anditya Putri, Shifa Anisa, Kholifatun ANNISA HANDAYANI Apitiadi, Satyo Dwi Aprilia, Kharisma Arief Adhy Kurniawan Arsi, Primandani Baetisalamah, Nadiva Amelia Berlilana Berlilana Dewi Cantika, Nourma Islam Diningrum, Dwi Fatma Efendi, Alvin Junio Ilham Eldas Puspita Rini, Eldas Puspita Ely Purnawati, Ely Fadly Yashari Soumena Fariha, Zulfia Nur Ferdianto, Dwi Angga Hafshah, Luqyana Nida Hellik Hermawan Hendra Sudarso Hidayat, Muhammad Taufik Nur Hiiyatin, Dewi LaeIa I Putu Dody Suarnatha Ilham, Fatah Imam Tahyudin Indarto, Debi Iriane, Rara Irma Darmayanti Junianto, Haris Khoirudin, Muhamad Affan Kuat Indartono Kusuma, Bagus Adhi Kusuma, Velizha S Kusuma, Velizha Sandy Maghfira, Rahajeng Sasi Mahardika, Fajar Mahendra, Duta Aditya Marhalatun, Viva Miftahus Surur, Miftahus Muhammad Afif Muliasari Pinilih, Muliasari Muratno, Muratno Murjiatiningsih, Lilis Mustofa, Dinar Najibulloh, Imam Kharits Nandang Hermanto Nanjar, Agi Nugroho, Bagus Aji Nur Hasanah Nuraini, Eka Nurul Hidayati Pandega, Dimas Marsus Prayoga, Agung Priangga, Melaya Puji Hastuti Pujianto , Dimas Eko Purwadi Purwadi Puspitaningrum, Indar Rahayu, Dania Gusmi Rahman Rosyidi Ramadhan, Muhammad Bintang Ranggi Praharaningtyas Aji Riesna, Deby Mega Rizkia Riny, Riny Riyanto Riyanto Riyanto Rujianto Eko Saputro Saekhu, Ahmad Saputra, Alfin Nur Aziz Saputri, Febryka Wulan Saputri, Inka Setiawan, Endri Sitaresmi Wahyu Handani, Sitaresmi Wahyu Sri Widiastuti, Sri Subarkah, Pungkas Taqwa Hariguna Udianti, Asih Utomo, Anwar Tri Winanto, Deden Wirasto, Anggit Wiwik Handayani Yusmedi Nurfaizal Zhafira, Alya