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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) IJCCS (Indonesian Journal of Computing and Cybernetics Systems) JURNAL SISTEM INFORMASI BISNIS Jurnal Peternakan Integratif Elkom: Jurnal Elektronika dan Komputer Journal of Education and Learning (EduLearn) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Prosiding SNATIF Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika JUITA : Jurnal Informatika Scientific Journal of Informatics Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan JOIN (Jurnal Online Informatika) JOIV : International Journal on Informatics Visualization AdBispreneur Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) International Journal of Artificial Intelligence Research INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi JIKO (Jurnal Informatika dan Komputer) JURNAL MEDIA INFORMATIKA BUDIDARMA Information System for Educators and Professionals : Journal of Information System SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI MATRIK : Jurnal Manajemen, Teknik Informatika, dan Rekayasa Komputer Jurnal Nasional Pendidikan Teknik Informatika (JANAPATI) Jurnal Informatika Aptisi Transactions on Management JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Aptisi Transactions on Technopreneurship (ATT) EDUMATIC: Jurnal Pendidikan Informatika Building of Informatics, Technology and Science Jurnal Mnemonic Journal Sensi: Strategic of Education in Information System Indonesian Journal of Electrical Engineering and Computer Science Abdimasku : Jurnal Pengabdian Masyarakat Computer Science and Information Technologies Jurnal Bumigora Information Technology (BITe) Aiti: Jurnal Teknologi Informasi Infotech: Journal of Technology Information Jurnal Teknologi Informasi dan Komunikasi Jurnal Teknik Informatika (JUTIF) Indonesian Journal of Applied Research (IJAR) Journal of Applied Data Sciences JOINTER : Journal of Informatics Engineering Jurnal Indonesia : Manajemen Informatika dan Komunikasi Journal of Information Technology (JIfoTech) Edutik : Jurnal Pendidikan Teknologi Informasi dan Komunikasi Nusantara of Engineering (NOE) Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat Jurnal Rekayasa elektrika Jurnal INFOTEL SmartComp Jurnal Indonesia : Manajemen Informatika dan Komunikasi Blockchain Frontier Technology (BFRONT) Scientific Journal of Informatics JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)
Irwan Sembiring
Universitas Kristen Satya Wacana
Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology 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 Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Analisis Perbandingan Sistem Pelaporan Kinerja Kementerian Dalam Negeri menggunakan Metode Usability Testing Ardaneswari, Awanda; Manongga, Daniel H.F; Sembiring, Irwan
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.v9i1.29565

Abstract

Performance Evaluation System for Apparatus Positions (Sikerja) is a web-based application owned by the Ministry of Home Affairs (MoHA), used to assess and measure the performance of civil servants across all units within MoHA. Currently, MoHA uses two versions of the Sikerja application: the old Sikerja and the new Sikerja. The purpose of this study is to compare the usability levels between 2 systems using the usability testing method, focusing on the performance input menu. The study employs a quantitative descriptive approach using a survey method involving 100 respondents from the Directorate General of Regional Governance, with a questionnaire as the research instrument. The questionnaire items are derived from the five usability indicators based on Jacob Nielsen's framework. The results of the validity and reliability tests on the questionnaire confirmed that it is valid and reliable. Subsequently, a descriptive analysis was conducted for each usability indicator. The analysis results show that the learnability score of the old Sikerja system is 3.24 (high), efficiency is 2.18 (moderate), memorability is 2.98 (moderate), errors is 1.88 (low), and satisfaction is 3,17 (high). On the other hand, the new Sikerja system has a learnability score of 2,23 (moderate), efficiency of 2.07 (moderate), memorability of 1.02 (low), errors of 2.77 (moderate), and satisfaction of 2.54 (moderate). It can be concluded that the new Sikerja system requires workflow simplification, increased user training and socialization, and regular evaluation for employees. These recommendations are expected to improve the usability score of the new Sikerja system within the Ministry of Home Affairs.
Pelatihan Data Science Pada 2024 Guru dan Siswa SMA/SMK Provinsi Nusa Tenggara Timur Manongga, Danny; Iriani, Ade; Kristianto, Budhi; Sembiring, Irwan; Hendry, -; Mailoa, Evangs; Setiyawati, Nina; Bangkalang, Dwi Hosanna
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 6, No 2 (2023): Mei 2023
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/ja.v6i2.1290

Abstract

Data menjadi aset paling berharga untuk organisasi mana pun karena dapat memandu pengambilan keputusan. Oleh karena itu kemampuan data science merupakan salah satu skill penting. Data science tergambarkan sebagai proses yang dimulai dari pengumpulan dan pengolahan, kemudian disajikan sebagai informasi yang berguna untuk pengambilan keputusan atau bermanfaat bagi pihak yang berkepentingan dengan data. Data science memiliki banyak fungsi dan manfaat dimana beberapa diantaranya adalah membantu menciptakan budaya keputusan berbasis data, mengurangi ketidakpastian dan meningkatkan konsistensi dan keandalan data. Melihat pentingnya kemampuan data science, maka Fakultas Teknologi Informasi bekerja sama dengan ASEAN Foundation serta Dinas Pendidikan dan Kebudayaan Provinsi Nusa Tenggara Timur (NTT) melakukan Pengabdian kepada Masyarakat (PkM) dalam bentuk pelatihan kepada 2024 guru dan siswa SMA/SMK Provinsi NTT sebagai bagian untuk mencetak talenta digital Indonesia. Pelatihan didukung oleh SAP yang merupakan perusahaan software dan teknologi yang berbasis di Jerman melalui platform SAP Analytics Cloud (SAC). PkM dilaksanakan secara daring dan luring. Guru dan siswa antusias mengikuti pelatihan ini terlihat dari hasil evaluasi yang bisa dikerjakan dengan baik oleh para peserta.
A Prototype of Decentralized Applications (DApps) Population Management System Based on Blockchain and Smart Contract Saian, Septovan Dwi Suputra; Sembiring, Irwan; Manongga, Daniel H. F.
JOIV : International Journal on Informatics Visualization Vol 8, No 2 (2024)
Publisher : Society of Visual Informatics

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62527/joiv.8.2.1861

Abstract

The Indonesian population reached 270,20 million in 2020. Each resident is equipped with various secret identities. The COVID-19 pandemic has made all activities use technology as a basis, causing residents' identities to be stored digitally. Some applications that keep these identities experience data leaks. However, with the advent of Web3 and its emphasis on decentralization through blockchain, a new era of secure data management is possible. Blockchain, with its inherent security features, ensures that data stored is secure, difficult to damage or lose due to mutual consensus. Every transaction is recorded, making it easy to carry out the audit process. Therefore, this research will design and implement prototype dApps for secure population management, leveraging the superior security of blockchain technology. The initial stage of research is to conduct a literature study. Furthermore, it is to create designs such as system, infrastructure, and activity diagrams. Then do the development of the dApps prototype. The last is testing using OWASP ZAP and cost analysis. A dApps prototype was implemented on a blockchain. Every transaction is recorded and publicly viewable through the Etherscan platform. Other data stored on a blockchain have gone through an AES-256 encryption process with the data owner's account key so that the owner can only see the data. The results of the tests performed show that there is no high-level warning. The cost analysis results show that the most used costs are when deploying smart contracts and making new data. For further development, it is implementing permissionless blockchain and multi-accounts.
Trends in sentiment of Twitter users towards Indonesian tourism: analysis with the k-nearest neighbor method Purnama Harahap, Eka; Dwi Purnomo, Hindriyanto; Iriani, Ade; Sembiring, Irwan; Nurtino, Tio
Computer Science and Information Technologies Vol 5, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v5i1.p19-28

Abstract

This research analyzes the sentiment of Twitter users regarding tourism in Indonesia using the keyword "wonderful Indonesia" as the tourism promotion identity. The aim of this study is to gain a deeper understanding of the public sentiment towards "wonderful Indonesia" through social media data analysis. The novelty obtained provides new insights into valuable information about Indonesian tourism for the government and relevant stakeholders in promoting Indonesian tourism and enhancing tourist experiences. The method used is tweet analysis and classification using the K-nearest neighbor (KNN) algorithm to determine the positive, neutral, or negative sentiment of the tweets. The classification results show that the majority of tweets (65.1% out of a total of 14,189 tweets) have a neutral sentiment, indicating that most tweets with the "wonderful Indonesia" tagline are related to advertising or promoting Indonesian tourism. However, the percentage of tweets with positive sentiment (33.8%) is higher than those with negative sentiment (1.1%). This study also achieved training results with an accuracy rate of 98.5%, precision of 97.6%, recall of 98.5%, and F1-score of 98.1%. However, reassessment is needed in the future as Twitter users' sentiment can change along with the development of Indonesian tourism itself.
Predicting students' success level in an examination using advanced linear regression and extreme gradient boosting Wahyuningsih, Tri; Iriani, Ade; Dwi Purnomo, Hindriyanto; Sembiring, Irwan
Computer Science and Information Technologies Vol 5, No 1: March 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v5i1.p29-37

Abstract

This research employs a hybrid approach, integrating advanced linear regression and extreme gradient boosting (XGBoost), to forecast student success rates in exams within the dynamic educational landscape. Utilizing Kaggle-sourced data, the study crafts a model amalgamating advanced linear regression and XGBoost, subsequently assessing its performance against the primary dataset. The findings showcase the model's efficacy, yielding an accuracy of 0.680 on the fifth test and underscoring its adeptness in predicting students' exam success. The discussion underscores XGBoost's prowess in managing data intricacies and non-linear features, complemented by advanced linear regression offering valuable coefficient interpretations for linear relationships. This research innovatively contributes by harmonizing two distinct methods to create a predictive model for students' exam success. The conclusion emphasizes the merits of an ensemble approach in refining prediction accuracy, recognizing, however, the study's limitations in terms of dataset constraints and external factors. In essence, this study enhances comprehension of predicting student success, offering educators insights to identify and support potentially struggling students. 
The role of gamification implementation in improving quality and intention in software engineering learning Wahyuningsih, Tri; Sediyono, Eko; Hartomo, Kristoko Dwi; Sembiring, Irwan
Journal of Education and Learning (EduLearn) Vol 18, No 1: February 2024
Publisher : Intelektual Pustaka Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/edulearn.v18i1.20823

Abstract

Gamification can make learning more fun and engaging for students. Software engineering can utilize gamification to help students learn and improve their skills from the complexity of software engineering. This study used quantitative research to examines perceived ease of use, student satisfaction, and perceived usefulness to measure gamification quality, which can have an impact on software engineering intention, namely intention, loyalty, and participation in following and understanding software engineering materials. The data was collected based on an online questionnaire survey, 90 data were collected and then measured and analyzed using SmartPLS 3. The results showed that perceived ease of use, student satisfaction, and perceived usefulness have a significant influence on gamification quality, which also leads to a positive impact on software engineering intention. This research guides teachers and educational institutions that gamification is very successful as a learning medium to simplify complex information to be more interactive.
Analysis of Attack Detection on Log Access Servers Using Machine Learning Classification: Integrating Expert Labeling and Optimal Model Selection Ridwan, Mohammad; Sembiring, Irwan; Setiawan, Adi; Setyawan, Iwan
Scientific Journal of Informatics Vol 11, No 1 (2024): February 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/sji.v11i1.49424

Abstract

Purpose: As the complexity and diversity of cyberattacks continue to grow, traditional security measures fall short in effectively countering these threats within web-based environments. Therefore, there is an urgent need to develop and implement innovative, advanced techniques tailored specifically to detect and address these evolving security risks within web applications.Methods: This research focuses on analyzing attack detection in log access servers using machine learning classification with two primary approaches: expert labeling integration and best model selection. Expert labeling determines whether log entries are safe or indicate an attack.Result: Validation in labeling was applied using different datasets to minimize errors and increase confidence in the resulting dataset. Experimental results show that the Decision Tree and Random Forest models have nearly identical accuracy rates, around 89.3%-89.4%, while the ANN model has an accuracy of 81%.Novelty: This study proposes a fusion of expert knowledge in labeling log entries with a rigorous process of selecting the best classification model. This integration has not been extensively explored in previous research, offering a novel approach to enhancing attack detection within web applications. The research contribution lies in the integration of expert security assessment and the selection of the best model for detecting attacks on server access logs, along with validating labels using various datasets from different log devices to enhance confidence in the analysis results.
PENGEMBANGAN APLIKASI PEMBELAJARAN IMERSIF BERBASIS VIRTUAL REALITY MENGGUNAKAN METODE MDLC DAN EVALUASI EUQ Ginting, Jusia Amanda; Sembiring, Irwan; Suryantara, I Gusti Ngurah; Mulyana, Teady Matius Surya; Alamsyah, Ferry
Infotech: Journal of Technology Information Vol 11, No 2 (2025): NOVEMBER
Publisher : ISTEK WIDURI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37365/jti.v11i2.426

Abstract

The advancement of technology in the field of Virtual Reality (VR) offers new opportunities for developing more interactive and immersive learning media. One of the main challenges in online learning is the low level of student engagement in the learning process, as well as the tendency for instructional methods to remain passive. Recognizing this gap and the need for a new technological approach that can encourage active participation, this study aims to develop a VR-based learning application called “FirstMetaClass”. This application is designed to simulate a virtual classroom environment to enhance students’ learning experiences. The application development process follows the Multimedia Development Life Cycle (MDLC) method. The quality of the user experience was evaluated using the Extended User Experience Questionnaire (EUQ). The respondents consisted of 42 university students who participated in the application trial and completed the evaluation questionnaire. The results of the study show that all EUQ dimensions achieved an average score above 4.0 on a 1–5 scale. These findings confirm that the “FirstMetaClass” application successfully provides a positive, engaging, and user-friendly learning experience, while creating a classroom atmosphere that closely resembles the real world and fosters a sense of presence for users.
Exploring Alternative Approaches for TwitterForensics: Utilizing Social Network Analysis to Identify Key Actors and Potential Suspects Sembiring, Irwan; Iriani, Ade; Suharyadi, Suharyadi
INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Vol 7 No 2 (2023): August 2023
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/intensif.v7i2.18894

Abstract

SNA (Social Network Analysis) is a modeling method for users which is symbolized by points (nodes) and interactions between users are represented by lines (edges). This method is needed to see patterns of social interaction in the network starting with finding out who the key actors are. The novelty of this study lies in the expansion of the analysis of other suspects, not only key actors identified during this time. This method performs a narrowed network mapping by examining only nodes connected to key actors. Secondary key actors no longer use centrality but use weight indicators at the edges. A case study using the hashtag "Manchester United" on the social media platform Twitter was conducted in the study. The results of the Social Network Analysis (SNA) revealed that @david_ornstein accounts are key actors with centrality of 2298 degrees. Another approach found @hadrien_grenier, @footballforall, @theutdjournal accounts had a particularly high intensity of interaction with key actors. The intensity of communication between secondary actors and key actors is close to or above the weighted value of 50. The results of this analysis can be used to suspect other potential suspects who have strong ties to key actors by looking.
Uji Perbandingan Akurasi Analisis Sentimen Pariwisata Menggunakan Algoritma Support Vector Machine dan Naive Bayes Susanti, Novita Dewi; Sediyono, Eko; Sembiring, Irwan
Nusantara of Engineering (NOE) Vol 3 No 2 (2016)
Publisher : Universitas Nusantara PGRI Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29407/noe.v3i2.12338

Abstract

Analisis sentimen saat ini banyak digunakan sebagai bahan untuk mengetahui opini masyarakat tentang suatu hal. Dengan menggunakan analisis sentimen kita dapat mengklasifikasikan data apakah data tersebut termasuk opini positif atau opini negatif. Paper ini membahas analisis sentimen untuk mengukur tingakat akurasi dari opini masyarakat pada suatu tempat wisata di Jawa Tengah dengan metode Naive Bayes dan Support Vektor Machine yang berguna untuk mengetahui nilai akurasi yang manakah yang lebih bagus dari dua metode yang digunakan tersebut. Ada beberapa metode yang bisa digunakan untuk mengklasifikasikan opini tersebut, namun dalam paper ini dipilih metode Support Vektor Machine dan metode Naive Bayes dengan alasan metode tersebut adalah metode yang paling banyak digunakan saat ini karena dapat menghasilkan nilai akurasi yang tinggi dari penelitian sebelumnya. Hasil yang didapatkan dari penelitian ini adalah berupa data perbandingan Precision, Recall dan Akurasi. Hasil precision pada NB adalah 65,97%, pada SVM 87,25%. Nilai Recall pada NB adalah 96,39%, pada SVM 80,60%. Nilai akurasi yang didapatkan pada NB 65,78%, pada SVM 76,47% Kata Kunci : Analisis sentimen, opini, klasifikasi, metode, Suport Vektor Machine, Naive Bayes, akurasi
Co-Authors Abas Sunarya, Po Ade Iriani Adi Setiawan Adriyanto Juliastomo Gundo Agus Sugiarto Agustinus, Ari Aji, Bintang Kristianto Alamsyah, Ferry Andriana, Myra April Lia Hananto Apriliasari, Dwi Ardaneswari, Awanda Arthur, Christian Astawa, I Wayan Aswin Dew Ayu Sanjaya, Yulia Putri Bayu Setyanto Pamungkas Bayu, Teguh Indra Budhi Kristianto Budhi Kristianto Budi Santoso Budi, Reza Setya Cahyaningtyas, Christian Daniawan, Benny Danny Manongga Danny Sebastian Dedy Prasetya Kristiadi Dwi Hosanna Bangkalang Dwi Setiawan Edi Suharyadi Efendy, Rifan Eko Sediono Eko Sediyono Eleazer Gottlieb Julio Sumampouw Elmanda, Vonda Erick Alfons Lisangan Esti Zakia Darojat Evangs Mailoa Evi Maria Faturahman, Adam Fauzi Ahmad Muda Fian Yulio Santoso Florentina Tatrin Kurniati Gallen cakra adhi wibowo Gerry Santos Lasatira Ginting, Jusia Amanda Girinzio, Iqbal Desam Gudiato, Candra Hamdan . Hany Makaruku, Yulian Hasnudi . Henderi Henderi . Hendry Hendry, - Henuk, Yusuf Leonard Herdin Yohnes Madawara Hindriyanto Dwi Purnomo Huda, Baenil Ignatius Agus Supriyono Ilham Hizbuloh Indrastanti Ratna Widiasari Iwan Setiawan Iwan Setiawan Iwan Setyawan Joko Listiawan Sukowati Joko Siswanto Joko Siswanto Jonas, Dendy Julians, Adhe Ronny Juneth Manuputty Krismiyati Kristoko D Hartomo Kristoko Dwi Hartomo Kusumajaya, Robby Andika Limbong, Josua Josen Alexander Manongga, Daniel H.F Manongga, Daniel H.F. Manongga, Daniel HF Marsyel Sampe Asang Marvelino, Matthew Mau, Stevanus Dwi Istiavan Maya Sari Merryana Lestari Migunani Migunani Mira Mira Mira Mohammad Ridwan Muhamad Yusup Nanle, Zeze Nazmun Nahar Khanom Nina Setiyawati Ninda Lutfiani Nining Fitriani Nugroho, Samuel Danny Nurtino, Tio Nuryadi, Didik Nurzainah Ginting Pamungkas, Bayu Setyanto Phillnov Yohanes Pinontoan Pinontoan, Phillnov Yohanes Priatna , Wowon Purbaratri, Winny Purnama Harahap, Eka Purnomo, Hidriyanto Dwi Putra, Yonathan Rahadi Qurotul Aini Qurotul Aini R. Suharyadi Rahardja.,M.T.I.,MM, Dr. Ir. Untung Raymond Elias Mauboy Rimes Jopmorestho Malioy Roy Rudolf Huizen Saian, Septovan Dwi Suputra Sandry Lanovela Pasaribu Santoso, Nuke Puji Lestari Sediyono, Eko - Setiawan Hakim Sri Ngudi Wahyuni Sri Ngudi Wahyuni, Sri Ngudi Sri Yulianto Joko Prasetyo Suharyadi Sulistio Sulistio Sumampouw, Eleazer Gottlieb Julio Supriadi, Candra Suryantara, I Gusti Ngurah Susanti, Novita Dewi Sutarto Wijono Suwijo Danu Prasetyo Teady Matius Surya Mulyana, Teady Matius Teguh Indra Bayu Teguh Wahyono Theopillus J. H. Wellem Tintien Koerniawati Tirsa Ninia Lina Tomasoa, Lyonly Tri Wahyuningsih Tri Wahyuningsih Tukino, Tukino Untung Rahardja Untung Rahardja Wibowo, Mars Caroline Wijaya, Angga Zakharia Wiwien Hadikurniawati Yerik Afrianto Singgalen Yessica Nataliani Yohan Maurits Indey Yohnes Madawara, Herdin Yulian Hany Makaruku