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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Ilmu dan Teknologi Kelautan Tropis IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Informatika Jurnal Penelitian dan Evaluasi Pendidikan JURNAL SISTEM INFORMASI BISNIS Proceedings of KNASTIK Jurnal Simetris Elkom: Jurnal Elektronika dan Komputer TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) Scientific Journal of Informatics Proceeding SENDI_U Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika JOIN (Jurnal Online Informatika) JOIV : International Journal on Informatics Visualization International Journal of Artificial Intelligence Research INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JURNAL MEDIA INFORMATIKA BUDIDARMA Faktor Exacta INOVTEK Polbeng - Seri Informatika MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Aptisi Transactions on Management JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Aptisi Transactions on Technopreneurship (ATT) EDUMATIC: Jurnal Pendidikan Informatika Magisma: Jurnal Ilmiah Ekonomi dan Bisnis Progresif: Jurnal Ilmiah Komputer JATI (Jurnal Mahasiswa Teknik Informatika) Journal Sensi: Strategic of Education in Information System Indonesian Journal of Electrical Engineering and Computer Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Abdimasku : Jurnal Pengabdian Masyarakat INFOKUM Aiti: Jurnal Teknologi Informasi Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences Jurnal Kependidikan: Jurnal Hasil Penelitian dan Kajian Kepustakaan di Bidang Pendidikan, Pengajaran dan Pembelajaran Startupreneur Business Digital (SABDA Journal) Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Dimensi DKV Seni Rupa dan Desain Jurnal Ilmiah Sains Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat IT-Explore: Jurnal Penerapan Teknologi Informasi dan Komunikasi Eduvest - Journal of Universal Studies CENDEKIA PENDIDIKAN Jurnal Rekayasa elektrika Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi) Journal of Technology Informatics and Engineering Jurnal Informatika: Jurnal Pengembangan IT Jurnal Pendidikan Teknologi Informasi (JUKANTI) INTERNAL (Information System Journal) Pendekar: Jurnal Pendidikan Berkarakter Blockchain Frontier Technology (BFRONT) Scientific Journal of Informatics Jurnal Lentera Edukasi Greenation International Journal of Law and Social Sciences BACA: Jurnal Dokumentasi dan Informasi International Journal of Information Technology and Business JuTISI (Jurnal Teknik Informatika dan Sistem Informasi) Jurnal DIMASTIK International Journal of Marketing and Digital Creative (IJMADIC) JOT
Danny Manongga
Universitas Kristen Satya Wacana
Aerospace Engineering Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Civil Engineering, Building, Construction & Architecture 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 Neuroscience Physics Social Sciences Transportation Other

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Sentiment Analysis of e-Government Service Using the Naive Bayes Algorithm Winny purbaratri; Hindriyanto Dwi Purnomo; Danny Manongga; Iwan Setyawan; Hendry Hendry
MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer Vol. 23 No. 2 (2024)
Publisher : Universitas Bumigora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30812/matrik.v23i2.3272

Abstract

E-Government which involves the use of communication and information technology to provide Public services have three obstacles. One of these obstacles is the implementation of e-Government by autonomous regional governments is still carried out individually. Apart from that, implementing the website regions are also not supported by efficient management systems and work processes, this is partly the case This is largely due to the lack of preparation of regulations, procedures and limited resources man. Apart from that, many local governments consider implementing e-Government only involves developing local government websites. More precisely, the implementation of e-Government It is only limited to the maturity stage and ignores the three other important stages that need to be completed. The aim of this research is to determine the level of public approval for government application services. This research uses the Naive Bayes Classifier approach as the methodology. The data sources used in this research consist of user reviews and comments obtained from Google Play Store. The results of this investigation produce a level of precision The highest is achieving a score of 83%. Additionally it shows an accuracy rate of 83%,levelcompleteness is 100%, and F-measure is 90.7%.
CRYPTO NARRATIVES SENTIMENT ANALYSIS ON BITCOIN PRICE PREDICTION USING THE NAIVE BAYES METHOD Nuryadi, Didik; Manongga, Daniel H.F.; Sembiring, Irwan
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 2 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i2.6116

Abstract

Globalization affects many aspects of human life with consequences that may be positive or negative. Advances in information technology, which significantly assist many human activities, are one of the ele-ments affected. As a new product of financial technology, cryptocur-rency has revolutionized the global payment system. Bitcoin has expe-rienced significant price increases in recent years, often caused by eco-nomic and psychological market factors. Sentiment analysis of the bitcoin crypto narrative is essential for understanding market behavior and predicting price trends because market sentiment has been proven to influence bitcoin price movements. Therefore, this research aims to investigate the crypto sentiment narrative regarding Bitcoin price movements using a sentiment analysis approach with the Naïve Bayes classification method. The dataset used in this research comes from crypto narratives that are considered to influence bitcoin price move-ments, which were collected from October 2022 to April 2024. This re-search succeeded in classifying the data tested using 10-fold cross-validation testing, with an average of 76.13%. The precision score for the positive opinion class was 63.92%, and the precision score for the negative opinion class reached 81.77%. The average recall value for the positive class was 61.69%, and for the negative class, it reached 83.12%. This data shows that Naïve Bayes is quite good at analyzing crypto sentiment narratives regarding bitcoin price movements.
Analysis Of Spotify Top Songs During Covid-19 Pandemic Atmoko Nugroho; Danny Manongga; Hindriyanto Dwi Purnomo; Hendry Hendry
International Journal of Marketing and Digital Creative Vol. 1 No. 2 (2023): International Journal of Marketing and Digital Creative
Publisher : Research Synergy Foundation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31098/ijmadic.v1i2.1565

Abstract

During the COVID-19 pandemic, many behaviors or habits have changed, especially in the internet audio-visual field which has increased significantly, one example is Spotify as an audio service provider. Not all songs on Spotify are popular or in the Top Songs. This study aims to examine whether there were differences in popular songs during the pandemic and before the pandemic and to determine the relationship between factors of popular songs on Spotify during the COVID-19 pandemic. The method used is to fetch Spotify songs via the API (Application Programming Interface) with the Spotify Python library. The features obtained are compared with the boxplot. The correlation between the Danceability and Energy features is obtained which ranges from 0.5-0.7, while the other features require further preprocessing because the values are not the same and are empty. This shows that every song that is considered good Danceability and Energy ranges from 0.5 to 0.7, regardless of singer, genre, or other song features.
ANALISIS PENERAPAN TIK BERBASIS PRINSIP TOTAL QUALITY MANAGEMENT DI SMP NEGERI 4 SENTANI Andreas Resdianto; Danny Manongga; Stefanus Relmasira
Jurnal Lentera Edukasi Vol. 4 No. 1 (2026): Edisi Maret
Publisher : Bakti Cendekia Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70305/jle.v4i1.204

Abstract

Penelitian ini bertujuan menganalisis penerapan Teknologi Informasi dan Komunikasi (TIK) di SMP Negeri 4 Sentani melalui perspektif Total Quality Management (TQM). Latar belakang penelitian adalah pentingnya integrasi TIK tidak hanya sebagai alat, tetapi sebagai bagian dari sistem manajemen mutu untuk peningkatan layanan pendidikan secara berkelanjutan. Menggunakan pendekatan kualitatif dengan metode studi kasus, penelitian ini menjadikan SMP Negeri 4 Sentani sebagai subjek penelitian. Pengumpulan data dilakukan melalui wawancara, observasi, dan studi dokumen dengan informan kunci meliputi kepala sekolah, koordinator TIK, dan guru. Hasil penelitian menunjukkan adanya komitmen kepemimpinan dan upaya perbaikan berkesinambungan dalam pemanfaatan TIK, yang sejalan dengan prinsip TQM. Namun, tantangan utama terletak pada aspek keterlibatan total (total involvement) di mana masih terdapat kesenjangan kompetensi TIK antar guru. Diskusi menunjukkan bahwa penerapan TIK di sekolah ini menunjukkan elemen-elemen TQM, namun belum terintegrasi secara holistik. Keberhasilan implementasi sangat bergantung pada budaya perbaikan berkelanjutan dan dukungan kepemimpinan yang kuat.
Cyberpreneurial Mindset as a Driver of Digital Startup Success in Emerging Digital Economies Danny Manongga; Ivan Kovac; Muhtarom Muhtarom
Startupreneur Business Digital (SABDA Journal) Vol. 5 No. 1 (2026): April
Publisher : Pandawan Sejahtera Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33050/sabda.v5i1.1046

Abstract

The rapid expansion of the digital economy has intensified competition among digital startups, yet high failure rates indicate that technological access alone is insufficient to ensure long-term success. While prior studies emphasize digital innovation and technological capability, limited research explains how the cyberpreneurial mindset functions as a strategic intangible resource that drives sustainable startup performance. Grounded in the Resource-Based View (RBV) and Dynamic Capability Theory (DCT), this study investigates how cyberpreneurial mindset dimensions of digital adaptability, opportunity recognition, innovation orientation, and calculated risk-taking contribute to digital startup success through the mediating role of strategic agility. This research addresses the gap concerning the cognitive behavioral foundations of digital entrepreneurial performance in emerging digital ecosystems. A quantitative approach was em- ployed using survey data collected from founders and top managers of digital startups. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to test both direct and mediating relationships among constructs. The findings demonstrate that cyberpreneurial mindset significantly influences digital startup success, particularly through digital adaptability and innovation orientation. The study concludes that cyberpreneurial mindset rep- resents a valuable, rare, and inimitable intangible resource that strengthens a startup’s dynamic capabilities, enabling firms to sense, seize, and transform opportunities in volatile digital environments. This research contributes theoretically by integrating RBV and Dynamic Capability Theory into cyberpreneurship literature and provides managerial implications for digital entrepreneurs seeking sustainable growth in emerging economies.
Sentiment Analysis Kepercayaan Publik Terhadap Pertamina Pada Media Berita di YouTube Alrafi Syammajaya; Daniel H. F. Manongga
Journal of Information System Research (JOSH) Vol 7 No 4 (2026): July 2026
Publisher : Forum Kerjasama Pendidikan Tinggi (FKPT)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/josh.v7i4.10574

Abstract

Public trust in PT Pertamina (Persero) is reflected in public opinion expressed on social media, particularly through the comment sections of news videos on YouTube. This study aims to analyze public sentiment toward Pertamina based on comments posted on YouTube news videos in order to identify the distribution of positive, negative, and neutral opinions. The data were collected using the YouTube Data API through a web crawling process and subsequently processed using several text preprocessing techniques, including cleaning, case folding, word normalization, tokenization, and stopword removal. Sentiment labeling was performed automatically using the VADER Sentiment method, which classified the comments into three categories: positive, negative, and neutral. Feature extraction was then conducted using the Term Frequency–Inverse Document Frequency (TF-IDF) method. The classification process compared the performance of three Naïve Bayes variants, namely Gaussian Naïve Bayes, Multinomial Naïve Bayes, and Bernoulli Naïve Bayes. Of the 56,868 comments that were successfully crawled, 22,527 comments were successfully collected. The sentiment labeling results revealed that neutral sentiment dominated the dataset, accounting for 95.89% of all comments, followed by positive sentiment at 2.86% and negative sentiment at 1.25%. The experimental results demonstrated that Multinomial Naïve Bayes achieved the best performance with an accuracy of approximately 95%, outperforming Bernoulli Naïve Bayes (approximately 92%) and Gaussian Naïve Bayes (approximately 79%). This superior performance is attributed to the compatibility of the Multinomial Naïve Bayes algorithm with TF-IDF feature representation, which is based on word frequency. The findings of this study are expected to provide valuable insights for Pertamina and policymakers in formulating more responsive and effective public communication strategies.
Comparative Analysis of YOLOv8s and Faster R-CNN for High-Resolution UAV RGB Oil Palm Health Detection: Accuracy versus Inference Speed Trade-Off Kristia Yuliawan; Danny Manongga; Hendry Hendry
Journal of Applied Data Sciences Vol 7, No 3: September 2026
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v7i3.1430

Abstract

Accurate and rapid detection of oil palm health conditions using UAV imagery is essential for supporting precision agriculture and large-scale plantation monitoring. However, challenges such as overlapping canopies, complex background textures, varying illumination, and severe class imbalance often reduce the reliability of automated detection systems. This study presents a comparative evaluation between YOLOv8s, a one-stage object detector, and Faster R-CNN, a two-stage detector, for identifying healthy and unhealthy oil palm trees using high-resolution UAV RGB imagery. The dataset consists of 2,303 annotated images collected from drone surveys and divided into training (70%), validation (20%), and testing (10%) subsets under a controlled experimental design. Both models were trained and evaluated using identical preprocessing pipelines and annotation formats to ensure fairness in comparison. Performance was assessed using precision, recall, F1-score, mean Average Precision (mAP@50 and mAP@50–95), and inference time. Experimental results show that YOLOv8s achieves superior performance with 0.987 precision, 0.998 recall, 0.977 mAP@50–95, and extremely fast inference speed of 1.1 ms per image. In contrast, Faster R-CNN achieves comparable detection accuracy at 0.981 precision and 0.993 recall but with significantly higher computational cost, reaching 875 ms per image. These findings indicate that YOLOv8s provides an optimal balance between accuracy and efficiency, making it more suitable for real-time UAV-based monitoring systems, while Faster R-CNN is more appropriate for offline and high-precision analytical tasks. The study contributes a standardized benchmarking framework for deep learning-based oil palm health detection and provides practical insights for selecting appropriate models in smart agricultural applications.
Decision support system in machine learning models for a face recognition-based attendance system Joseph Teguh Santoso; Danny Manongga; Hendry Hendry
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 23, No 2: April 2025
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v23i2.26412

Abstract

This research aims to develop a predictive model using face recognition-based attendance data and integrating decision support system (DSS) theory with machine learning (ML) techniques to identify high-performing teachers at vocational high schools (SMKs). The novelty of this research lies in integrating theory with the use of face recognition data and ML algorithms to predict and identify high-performing teachers, thereby enhancing decision-making processes and teacher performance management in SMK schools. The dataset consists of SMK teachers' attendance data obtained through a face recognition attendance system, totaling 998 entries. This research employs sensitivity analysis concepts from DSS theory and classification approaches from ML models utilizing support vector machine (SVM), decision trees (DT), and random forest (RF). The models are trained and tested on Google Colab using Python, with data distribution guided by the Pareto principle. The research findings indicate that integrating DSS theory with ML contributes to innovation and benefits in improving decision-making and teacher performance management by successfully predicting high-performing teachers. Evaluation results show the highest accuracy rate of 98% with the RF model, making it the best predictive model compared to the other two models.
IMPLEMENTASI TOTAL QUALITY MANAGEMENT (TQM) UNTUK PENINGKATAN MUTU BERKELANJUTAN DI LEMBAGA PENDIDIKAN Michael Alan Hirdi Pukada; Stefanus Christian Relmasira; Danny Manongga
Pendekar : Jurnal Pendidikan Berkarakter Vol. 3 No. 4 (2025): Agustus : Jurnal Pendidikan Berkarakter
Publisher : LPPM Politeknik Pratama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/1179

Abstract

Di tengah tantangan global dan tuntutan peningkatan mutu pendidikan, lembaga pendidikan memerlukan kerangka kerja manajemen yang sistematis untuk memastikan relevansi dan daya saing. Penelitian ini bertujuan untuk menganalisis dan merumuskan model implementasi Total Quality Management (TQM) yang komprehensif sebagai strategi untuk peningkatan mutu berkelanjutan di lembaga pendidikan. Dengan menggunakan metode kualitatif melalui pendekatan studi pustaka, penelitian ini mengumpulkan, menganalisis, dan mensintesis berbagai literatur primer dan sekunder yang relevan. Temuan utama menunjukkan bahwa implementasi TQM yang efektif harus didasarkan pada lima pilar yang saling terintegrasi: kepemimpinan transformasional yang visioner, perencanaan strategis yang berpusat pada pelanggan, manajemen proses pembelajaran yang berfokus pada keterlibatan siswa, kolaborasi dengan seluruh pemangku kepentingan, serta siklus evaluasi dan perbaikan berkelanjutan. Implikasi dari penelitian ini adalah bahwa TQM menawarkan sebuah model holistik yang memungkinkan lembaga pendidikan untuk tidak hanya memenuhi standar, tetapi juga membangun budaya mutu yang adaptif dan inovatif, sehingga mampu menghasilkan peningkatan kualitas layanan dan hasil pendidikan secara signifikan dan berkelanjutan.
Evaluation of the Implementation of the Independent Curriculum at SMP Negeri 8 Ambon Using the Discrepancy Model Flawelna Falerery Pesulima; Daniel H. F. Manongga; Yari Dwikurnaningsih
Greenation International Journal of Law and Social Sciences Vol. 4 No. 1 (2026): (GIJLSS) Greenation International Journal of Law and Social Sciences (March - A
Publisher : Greenation Research & Yayasan Global Resarch National

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.38035/gijlss.v4i1.791

Abstract

The curriculum is a crucial component in education that needs to be continuously updated to keep pace with current developments. Curriculum changes help ensure that the education provided not only meets current standards but also supports the holistic development of students' skills and character. This evaluation study uses the Discrepancy Model to assess differences between actual conditions and established standards. This study aims to analyze the design, installation, process, and results of the Independent Curriculum implementation at SMP Negeri 8 Ambon. The method used is an evaluative method with a qualitative descriptive approach. This study was conducted at SMP Negeri 8 Ambon. The research subjects were the principal, the Deputy Head of Curriculum, teachers, and students. Three data collection techniques were used: interviews, observation, and document studies. Data validation used source and technique triangulation, while data analysis followed the Miles and Huberman model. The results of the study show that the Curriculum Design, Curriculum Implementation, Installation, and Curriculum Results are in accordance with the standards set out in the Minister of Education, Culture, Research and Technology Regulation Number 12 of 2024 regarding the implementation of the Independent Curriculum in educational institutions.
Co-Authors Abas Sunarya, Po Abdi Samuel Mango Ade Iriani Adhe Ronny Julians Adriyanto Juliastomo Gundo Agni Isador Harsapranata Agung Wibowo Albert Kriestian Novi Adhi Nugraha Aldi Lasso Alrafi Syammajaya Andreas Resdianto Angela Atik Setiyanti Anton Hermawan Antonius Mbay Ndapamuri Anumi, Maria Grassella Anwar, Ananda Pradana Putra April Lia Hananto Apriliasari, Dwi Ardaneswari, Awanda Arny Lattu Astriyer J. Nahumury Atmoko Nugroho Ayu Sanjaya, Yulia Putri Baihaqi, Kiki Ahmad Bani, Benediktus Benediktus Bani Budhi Kristianto Budi Santoso Cahyaningtyas, Christian Charitas Fibriani Cut Amalia Saffiera Daniawan, Benny Daniel D. Kameo Darmawan Utomo Dendy Kurniawan Destiyani, Gati Dian Widiyanto Chandra Dwi Hosanna Bangkalang Efendy, Rifan Eko Nur Hermansyah Eko Sediyono Elfira Umar Elmanda, Vonda Erwianta Gustial Radjah Erwien Christianto Evangs Mailoa Evi Maria Faturahman, Adam Fauzi Ahmad Muda Filimdity, Elsa K. Flawelna Falerery Pesulima Florentina Tatrin Kurniati Frederik Samuel Papilaya Girinzio, Iqbal Desam Gunawan Gunawan Hanita Yulia Harry Agustian Henderi Hendry Hendry . Hendry Hendry Hendry, - Henry Adhi Sulistyo Herdin Yohnes Madawara Hindriyanto Dwi Purnomo Huda, Baenil I Ketut Suada Indrastanti Ratna Widiasari Irwan Sembiring Ivan Kovac Ivanna K. Timotius Iwan Setiawan Iwan Setyawan Johan Jimmy Carter Tambotoh Joko Siswanto Joseph Teguh Santoso Julianingsih, Dwi Julians, Adhe Ronny Krismiyati Kristia Yuliawan Kristoko Dwi Hartomo Lelatobur, Lovely Ezverenzha Lorna Yertas Baisa Lukman Santoso Madawara, Herdin Yohnes Mango, Abdi Samuel Martza Merry Swastikasari Michael Alan Hirdi Pukada Muhamad Yusup Muhammad Ryza Awwali , Sulartopo, Muhammad Ryza Awwali , Muhtarom Nina Setiyawati Nuryadi, Didik Panja, Eben Penidas Fodinggo Tanaem Perdana, Eric Megah Po Abas Sunarya Prasetia, Yoga Agung Prasetio, Nanda Wiryawan Priatna , Wowon Pudjajana, Andre Maureen Purnomo, Hendryanto Dwi Qurotul Aini Qurotul Aini Radius Tanone Rahardja.,M.T.I.,MM, Dr. Ir. Untung Ravensca Matatula Ravensca Matatula Reinhard Alfaries Saemani Reni Veliyanti Rimes Jopmorestho Malioy Rissal Efendi Rivort Pormes Rivort Pormes Rivort Pormes, Rivort Roy Rudolf Huizen Runtulalo, Yahya Supit Saian, Septovan Dwi Suputra Santoso, Joseph Teguh Santoso, Nuke Puji Lestari Selfiana Pandie Sophia Tri Satyawati Sri Yulianto Joko Prasetyo Stefanus Christian Relmasira Suharyadi Sulistyo, Henry Adhi Sutarto Sutarto Sutarto Wijono Swastikasari, Martza Merry Takumi Sase Theopillus J. H. Wellem Tri Wahyuningsih Tukino Tukino, Tukino Untung Rahardja Victor Peter Lodewyk Duan Willson Mangoki Winny purbaratri Winsy C.D Weku Wiwien Hadikurniawati Yari Dwikurnaningsih Yerik Afrianto Singgalen Yessica Nataliani Yohana Andianti Yudo Devianto