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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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IoT-Based Smart Air Conditioner as a Preventive in the Post-COVID-19 Era: A Review Saputra, Dhanar Intan Surya; Suarnatha, I Putu Dody; Mahardika, Fajar; Wijanarko, Andik; Handani, Sitaresmi Wahyu
Journal of Robotics and Control (JRC) Vol 4, No 1 (2023)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v4i1.17090

Abstract

The Internet of Things (IoT) refers to physical objects with sensors, computing power, software, and other technologies that communicate and exchange data with other devices, platforms, and systems over the Internet or other communication networks. Remarkable developments in IoT have paved the way for new possibilities, enabling the creation and automation of innovative services and advanced applications and constituting a collection of crucial enabling technologies for smart homes. In this New-Normal Era, the concept of an IoT-based Smart Air Conditioner (AC) as a Preventive Effort against COVID-19 is a proposed innovation and application. The Smart AC is designed based on the analysis of existing problems and is equipped with literature obtained in the study. The purpose of this study is to review the research literature on IoT-enabled Smart AC to emphasize the main trends and open problems of integrating IoT technology to create sustainable and efficient Smart homes. The IoT-based Smart AC was designed and equipped with air quality filter features, human sensors, temperature control, voice control, Cloud Storage, and Solar Panel services that can be controlled via smartphone devices. From the framework and study results, the IoT offers many benefits. The IoT-based Smart AC concept is one step ahead of existing AC products.
VTUBER PERSONAS IN DIGITAL WAYANG: A REVIEW OF INNOVATIVE CULTURAL PROMOTION FOR INDONESIAN HERITAGE Hermawan, Hellik; Subarkah, Pungkas; Utomo, Anwar Tri; Ilham, Fatah; Saputra, Dhanar Intan Surya
Jurnal Pilar Nusa Mandiri Vol. 20 No. 2 (2024): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Pe
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/pilar.v20i2.5921

Abstract

This study investigates the integration of VTuber into Wayang Digital as a strategic initiative to promote Indonesian cultural heritage. By leveraging advanced technologies such as real-time motion capture and artificial intelligence (AI), the project aims to enhance the animation quality and interaction of VTuber, creating a more immersive and engaging experience for audiences. The research focuses on three key aspects: VTuber integration's effectiveness in attracting international audiences, optimizing real-time motion capture for high-quality animation, and applying AI algorithms to create adaptive, responsive interactions between VTubers and their viewers. Through these innovations, the study aims to enrich the narrative and visual appeal of Wayang Digital, making it more accessible and appealing to a diverse global audience. The findings show that integrating advanced technologies enhances Wayang Digital's storytelling, aesthetics, and effectiveness as a powerful tool for cultural promotion. AI-enabled adaptive interactions create a personalized viewer experience, deepening audience connections with the traditional art form. High-quality animation preserves and effectively communicates Wayang's cultural nuances to audiences, enhancing its impact and cultural promotion. This study underscores the importance of continuous technological innovation and strategic implementation in the preservation and globalization of Indonesian heritage through digital media, suggesting that the future of cultural preservation lies in the seamless integration of tradition with cutting-edge technology.
Evaluasi Aplikasi Raileo Melalui Analisis Sentimen Ulasan Playstore Dengan Metode Naive Bayes Junianto, Haris; Arsi, Primandani; Kusuma, Bagus Adhi; Saputra, Dhanar Intan Surya
SINTECH (Science and Information Technology) Journal Vol. 7 No. 1 (2024): SINTECH Journal Edition April 2024
Publisher : Prahasta Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31598/sintechjournal.v7i1.1505

Abstract

Abstrak The Raileo application is a staffing platform owned by PT. KAI, functions as a personnel data management system. Effective application development requires data as a basis, and one source of data that can be utilized is user reviews. User reviews provide valuable information regarding application performance, user needs, and security aspects. However, challenges arise in managing review data which often contains sarcasm, creating ambiguous meaning and lowering accuracy levels. This research proposes a solution by applying sentiment analysis using Naive Bayes logarithms to 1047 Raileo review data. This method produces an accuracy rate of 94%, with positive and negative sentiment classification. The research results show the words that appear most frequently in Raileo reviews, such as "eror", "sulit", "titik presensi", "titik absen", "titik lokasi", "bug", "lemot," "gagal", "mantap", "bagus", "oke", "mudah", "mempermudah", "mantul", "lengkap","keren","ok", "inovatif", "inovasi", "semoga", "sukses", dan "membantu". These words can be used as a key to analyze all the sentiments contained in the review. In addition, this research identifies "presence point" as the highest negative sentiment word that needs attention in further development. From this sentiment analysis research, the Raileo application produces the highest sentiment value, namely positive sentiment
cARica: enhancing travelling experiences in wonosobo through location-based mobile augmented reality Saputra, Dhanar Intan Surya; Murjiatiningsih, Lilis; Hermawan, Hellik; Handani, Sitaresmi Wahyu; Wijanarko, Andik
Journal of Soft Computing Exploration Vol. 4 No. 1 (2023): March 2023
Publisher : SHM Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52465/joscex.v4i1.97

Abstract

Wonosobo, as a Regency in Central Java Province, Indonesia, has attractions including the Dieng Plateau Theater Kalianget, and Menjer Lake. The research is intended to provide more experience for tourists who visit the tour through Location-Based Mobile Augmented Reality (MAR), an application we developed, cARica. This application includes experience travelling in Wonosobo and is aware of other information displayed through AR content. It was an alternative medium for tourism promotion to be easy, attractive, and inexpensive. It is a practical guide to attract tourists to visit tourist sites. In its development, we use the prototyping method so that each stage is carried out under the procedures that have been prepared. To get the point of Interest (PoI) points of tourist sites, use Global Positioning System (GPS) data taken through Google Maps to get the Latitude and Longitude of each object. The results of this study present that cARica is a Location-Based Mobile Augmented Reality service platform that can be accessed using an Android smartphone and has three-dimensional animated character content with the Wonosobo regency icon. cARica is a form of innovation in providing exceptional services and experiences for tourists and has the potential to be continuously developed.
Sales Forecasting Analysis Using Trend Moment Method: A Study Case of a Fast Moving Consumer Goods Company in Indonesia Fauzan, Ammar; Rahayu, Dania Gusmi; Handayani, Annisa; Tahyudin, Imam; Saputra, Dhanar Intan Surya; Purwadi, Purwadi
Journal of Information Technology and Cyber Security Vol. 1 No. 1 (2023): 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.7572

Abstract

The market of Fast-Moving Consumer Goods (FMCG) companies in Indonesia is enormous. Unilever has 400 brands in more than 190 countries, making it a global business that is as influential in the consumer product market as it is in Indonesia. Sales forecasting at this company is very useful for planning expenses and the company's total costs on the business strategy. This study uses trend moment method to forecast the sales and earnings of Unilever Indonesia companies at the end of the year. This article aims to test the performance of the trend moment method calculation on the prediction of net sales and profits in FMCG companies. At the end of the analysis process, it can be concluded that forecasting using trend moment method is going very well. This indicator of success is shown by the error level of MAPE, which is below 10%.
Comparison of Conversational Corpus and News Corpus on Gender Bias in Indonesian-English Transformer Model Translation Wijanarko, Andik; Al Haura, Adzkiyatun Nisa; Puspitaningrum, Indar; Saputra, Dhanar Intan Surya
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.918

Abstract

Gender bias in machine translation is a significant issue that affects text translation and gender perception, often leading to misunderstandings, such as the tendency to default to using male pronouns. For example, the word "dia" in Indonesian is often translated as "he" rather than "she," even when the context suggests otherwise, as seen in the case of President Megawati. Reducing this bias requires ongoing research, particularly in understanding how different corpora affect translation accuracy. Studies have shown that formal news corpora, which have less gender bias, produce different results compared to conversational corpora that are more informal and exhibit gender bias. This research uses a training dataset of the Indonesian-English conversational parallel corpus from Open Subtitles, which contains many gendered pronouns. Additionally, a news corpus from Tanzil, with fewer gendered words, was also used. These corpora were sourced from Opus, widely used by previous researchers. For the testing dataset, biographies of female presidents were used, which are often translated as masculine by popular machine translation systems by default. Each corpus was trained using a Transformer model, resulting in a translation model. Each sentence from the generated translations was then detected for gender, and compared with the gender of sentences from the test data to evaluate accuracy. The results showed that the accuracy of gender translation from the conversational corpus was 84%, while the news corpus achieved an accuracy of 8%.
Clustering Sugar Content in Children's Snacks for Diabetes Prevention Using Unsupervised Learning Darmayanti, Irma; Saputra, Dhanar Intan Surya; Saputri, Inka; Hidayati, Nurul; Hermanto, Nandang
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.932

Abstract

Diabetes is a chronic health problem with increasing prevalence, especially among children, due to the consumption of sugary foods/beverages. This study aims to cluster children's snack products based on sugar content using unsupervised learning by combining Hierarchical Clustering and K-Means algorithms optimized using Silhouette Score. This combined approach utilizes Hierarchical Clustering to determine the optimal value (????) of K-Means, ensuring the efficiency and accuracy of data clustering. A total of 157 sample data were effectively clustered with K-means. The test results with Silhouette Score yielded the highest value of 0.380 for 2 clusters, while 3 clusters scored 0.350 and 0.277 for 4 clusters. For this reason, 2 clusters better represent the homogeneity of the data in the cluster, although it has not reached the ideal condition. Further analysis showed that high sugar and calorie content in sugary drinks, including milk, could increase blood glucose levels. These findings can be the basis for the development of consumer-friendly nutrition labels. However, support is needed from the government to create a labelling policy to ensure the sustainability of implementation in the community as an educational effort to prevent the risk of diabetes in children.
Unlocking the Potential of OLT for Startup ISPs in Indonesia: Challenges and Strategies Mustofa, Dinar; Saputra, Dhanar Intan Surya; Kusuma, Velizha S; Aminuddin, Afrig; Wirasto, Anggit; Apitiadi, Satyo Dwi
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Universitas Bina Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.943

Abstract

This study explores the implementation of Optical Line Terminal (OLT) technology by Internet Service Providers (ISPs) startups in underserved and remote areas of Indonesia, examining its effectiveness, challenges, and opportunities. The research reveals that OLT technology can significantly improve internet service quality, with measurable increases in speed (up to 30%) and reliability (20% improvement), especially in rural areas. However, ISP startups face several technical challenges, including inadequate fiber optic infrastructure, high initial investment costs, and the complex geographical conditions across Indonesia’s diverse islands. Regulatory barriers, such as lengthy licensing processes and inconsistent policies, further hinder the deployment of OLT technology. Despite these challenges, the study identifies key opportunities for ISP startups to overcome these obstacles. Collaboration with government initiatives like the Palapa Ring and the potential integration with 5G and IoT technologies can reduce costs and accelerate network deployment. Additionally, leveraging existing infrastructure enables faster expansion of broadband services, particularly in remote regions. The research also finds that ISP startups adopting OLT technology can significantly narrow the digital divide by expanding service coverage in underserved areas, with a noted 25% increase in digital inclusion. These findings offer valuable insights for policymakers and business leaders, informing strategies to optimize OLT technology and foster a more equitable digital transformation across Indonesia, particularly in expanding access to broadband internet in marginalized regions.
Eksplorasi Sentimen Publik terhadap Film "˜Dirty Vote"™ melalui Metode Naïve Bayes dan Logistic Regression Junianto, Haris; Saputro, Rujianto Eko; Kusuma, Bagus Adhi; Saputra, Dhanar Intan Surya
JEPIN (Jurnal Edukasi dan Penelitian Informatika) Vol 10, No 3 (2024): Volume 10 No 3
Publisher : Program Studi Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26418/jp.v10i3.78520

Abstract

Tahun 2024 merupakan tahun politik bagi masyarakat Indonesia, di mana mereka menggunakan hak pilih untuk menentukan pemimpin pemerintahan selama lima tahun ke depan. Dalam konteks ini, pendidikan politik menjadi sangat penting, terutama bagi warga yang kurang memahami seluk-beluk politik dan proses pemilihan umum. Menyadari pentingnya pemahaman tersebut, sekelompok akademisi menciptakan film berjudul "Dirty Vote" dengan tujuan meningkatkan kesadaran masyarakat mengenai proses pemilu serta meminimalisir potensi pelanggaran.Penelitian ini bertujuan untuk mengevaluasi opini publik terkait film "Dirty Vote" dengan menggunakan dua model klasifikasi, yaitu Naive Bayes dan Logistic Regression. Penelitian ini melibatkan beberapa tahap, mulai dari pengumpulan data melalui scraping komentar dari platform YouTube, preprocessing data, analisis eksploratif (Exploratory Data Analysis), hingga pengujian performa model menggunakan teknik K-fold Cross Validation, serta visualisasi data menggunakan Word Cloud. Dalam penelitian ini, sebanyak 8888 data komentar dianalisis menggunakan teknik pemrosesan bahasa alami untuk mengukur sentimen publik terhadap film tersebut. Hasil analisis menunjukkan bahwa algoritma Naive Bayes mengidentifikasi 91,30% sentimen positif dan 8,70% sentimen negatif, sedangkan algoritma Logistic Regression memberikan hasil yang lebih tinggi, dengan sentimen positif sebesar 95,65% dan negatif sebesar 4,35%. Dari segi performa, Logistic Regression terbukti lebih unggul dengan akurasi mencapai 95,5%, sedangkan Naive Bayes memiliki akurasi sebesar 91,1%. Pengujian performa dilakukan melalui satu kali pengujian penuh serta delapan kali pengujian dalam berbagai kondisi data, dengan evaluasi kinerja menggunakan ROC dan AUC. Hasil penelitian ini menunjukkan bahwa kedua algoritma memberikan evaluasi positif terhadap film "Dirty Vote", dengan Logistic Regression memberikan hasil yang lebih akurat.
COMPARISON OF LOGISTIC REGRESSION AND RANDOM FOREST IN SENTIMENT ANALYSIS OF DISDUKCAPIL APPLICATION REVIEWS Junianto, Haris; Saputro, Rujianto Eko; Kusuma, Bagus Adhi; Saputra, Dhanar Intan Surya
Jurnal Teknik Informatika (Jutif) Vol. 5 No. 6 (2024): JUTIF Volume 5, Number 6, Desember 2024
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2024.5.6.1802

Abstract

Civil registration administration institutions such as Disdukcapil have an important role in carrying out government functions, in supporting the smooth running of administrative services the Government presents the Disdukcapil Mobile Application platform which aims to provide efficient and fast services to the community regarding various population administration needs. Sentiment analysis of user reviews on the Play Store for the Disdukcapil application is needed to understand user perceptions and needs, as well as to improve service quality and application development. In this study, researchers conducted sentiment analysis using 2 algorithms, namely: Logistic Regression and Random Forest, which after comparing by testing the two algorithms with test data of 18810 user review data from PlayStore, obtained the performance results of each algorithm as follows: 90% accuracy, 91% precision, 89% recall, and f1 90% for the performance results of the Logistic Regression algorithm, while for the performance results of the Random Forest algorithm accuracy 89%, precision 92%, recall 86% and f1-score 89%. From these results the Logical Regression algorithm has better performance than the Random Forest algorithm.
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