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All Journal International Journal of Electrical and Computer Engineering Jurnal Teknoin JURNAL SISTEM INFORMASI BISNIS Jurnal Buana Informatika Bulletin of Electrical Engineering and Informatics Journal of Education and Learning (EduLearn) Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) JUTI: Jurnal Ilmiah Teknologi Informasi Jurnal Algoritma Jurnal Teknologi Informasi dan Ilmu Komputer Jurnal Transformatika Journal of Information Systems Engineering and Business Intelligence Khazanah Informatika: Jurnal Ilmu Komputer dan Informatika Register: Jurnal Ilmiah Teknologi Sistem Informasi InfoTekJar : Jurnal Nasional Informatika dan Teknologi Jaringan Sistemasi: Jurnal Sistem Informasi Journal of Applied Geospatial Information JOIV : International Journal on Informatics Visualization Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi 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 Jurnal Sisfokom (Sistem Informasi dan Komputer) GUIDENA: Jurnal Ilmu Pendidikan, Psikologi, Bimbingan dan Konseling Indonesian Journal of Computing and Modeling JURIKOM (Jurnal Riset Komputer) Jurnal Informatika JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Journal of Information Systems and Informatics Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Jurnal Abdi Insani Abdimasku : Jurnal Pengabdian Masyarakat Aiti: Jurnal Teknologi Informasi Budapest International Research and Critics Institute-Journal (BIRCI-Journal): Humanities and Social Sciences Jurnal Teknik Informatika (JUTIF) Journal of Applied Data Sciences JOINTER : Journal of Informatics Engineering IJECS: Indonesian Journal of Empowerment and Community Services International Journal of Community Service Jurnal Impresi Indonesia Jurnal Nasional Teknik Elektro dan Teknologi Informasi Magistrorum et Scholarium: Jurnal Pengabdian Masyarakat Jurnal Rekayasa elektrika Jurnal INFOTEL Scientific Journal of Informatics JuTISI (Jurnal Teknik Informatika dan Sistem Informasi)

Kristoko Dwi Hartomo

Universitas Kristen Satya Wacana

Author-ID : 276989

Religion Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry 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 Mathematics Mechanical Engineering Medicine & Pharmacology Nursing Physics Public Health Social Sciences Other

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Triangular Fuzzy Numbers-Based MADM for Selecting Pregnant Mothers at Risk of Stunting Wiwien Hadikurniawati; Kristoko Dwi Hartomo; Irwan Sembiring; Hindriyanto Dwi Purnomo; Ade Iriani
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 3 (2023): Juni 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i3.4966

Stunting is caused by a lack of proper nutrition before and after birth. This research paper identifies and measures the risk of stunting during pregnancy and make recommendations for ranking pregnant women at risk. These aims to provide appropriate treatment and action to reduce mothers giving birth to children at risk of stunting. To make the optimal choice, the selection procedure for pregnant women at risk of giving birth to stunted children considers a variety of factors, including maternal age, maternal nutrition, arms circumference, hemoglobin, parity, birth interval, height, baby weight, and body mass index (BMI). Decision-maker’s expectation to reduce uncertainty and imprecision are represented linguistically by triangular fuzzy numbers. The triangular fuzzy numbers arithmetic approach is used to determine the selection process output. The ranking is determined from the alternative with the most parameter values to the alternative with the fewest parameters. Based on the results of the calculation, it was determined that PM (Pregnant Mother) had the highest score and was ranked first. That pregnant mother was declared as pregnant mother who had the lowest risk of giving birth to stunted baby

Literature Review dan Survey Trend Teknologi Pengembangan Website untuk Website Skala Kecil Danny Sebastian; Irwan Sembiring; Eko Sediyono; Kristoko Dwi Hartomo
INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS : Journal of Information System Vol 7 No 2 (2023): INFORMATION SYSTEM FOR EDUCATORS AND PROFESSIONALS (Juni 2023)
Publisher : Lembaga Penelitian dan Pengabdian Masyarakat Universitas Bina Insani

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51211/isbi.v7i2.2147

Perkembangan website dari web 1.0 sampai dengan web 4.0 membuat banyak teknologi pengembangan website. Mulai dari Bahasa pemrograman, Frameworks, Content Management System (CMS), Static Site Generator (SSG), dan teknologi lain. Masing-masing teknologi pengembangan website memiliki karakteristik, kelebihan, dan kekurangannya masing-masing. Penelitian ini bertujuan untuk menganalisis perbedaan antara 2 teknologi pengembangan website yang banyak digunakan saat ini, yaitu menggunakan CMS dan menggunakan SSG. Ada 10 kriteria yang digunakan sebagai pembanding CMS dan SSG, yaitu komponen, jenis website, kecepatan layanan, fleksibilitas, security, source-control, development speed vs skala website, konten dinamis, admin page, dan hosting. Pendekatan SSG cocok untuk pengembangan aplikasi website dengan skala kecil atau website statis dengan sedikit interaksi dari pengguna. Pendekatan CMS cocok untuk pengembangan website skala menengah atau website dinamis dengan banyak interaksi dari pengguna. Berdasarkan hasil survey ke website upworks dan freelancer, trend SSG masih kalah dibandingkan dengan CMS.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51211/isbi.v7i2.2147

IPv6 flood attack detection based on epsilon greedy optimized Q learning in single board computer April Firman Daru; Kristoko Dwi Hartomo; Hindriyanto Dwi Purnomo
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i5.pp5782-5791

Internet of things is a technology that allows communication between devices within a network. Since this technology depends on a network to communicate, the vulnerability of the exposed devices increased significantly. Furthermore, the use of internet protocol version 6 (IPv6) as the successor to internet protocol version 4 (IPv4) as a communication protocol constituted a significant problem for the network. Hence, this protocol was exploitable for flooding attacks in the IPv6 network. As a countermeasure against the flood, this study designed an IPv6 flood attack detection by using epsilon greedy optimized Q learning algorithm. According to the evaluation, the agent with epsilon 0.1 could reach 98% of accuracy and 11,550 rewards compared to the other agents. When compared to control models, the agent is also the most accurate compared to other algorithms followed by neural network (NN),Â K-nearest neighbors (KNN), decision tree (DT), naive Bayes (NB), and support vector machine (SVM). Besides that, the agent used more than 99% of a single central processing unit (CPU). Hence, the agent will not hinder internet of things (IoT) devices with multiple processors. Thus, we concluded that the proposed agent has high accuracy and feasibility in a single board computer (SBC).

Sentiment Analysis of Simobi Plus Mobile Application Using Naïve Bayes Classification Stevan Hamonangan Hardi; Kristoko Dwi Hartomo
JURNAL MEDIA INFORMATIKA BUDIDARMA Vol 7, No 3 (2023): Juli 2023
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/mib.v7i3.6300

Sinar Mas Bank is one of many banks operating in Indonesia. Quite a few people use Sinar Mas Bank's services as their bank of choice for their day-to-day transactions. By popular demand, Sinar Mas Bank serves users of banking services by creating an M-banking application. The M-banking application created by Bank Sinar Mas is called Simobi Plus Mobile Banking. There are already 52.3 thousand reviews regardings this application on the Google Play Store platform. Among these are positive and negative reviews from customers who use the application for their daily transactions. In reviews that use 1-5 star ratings, many people are misled by giving different ratings than the given stars. Many customers who leave 5-star app reviews, but comments on these reviews contain negative words. As a result, the application developer becomes confused because the comments given do not match the rating given by the user. Comments that are not in accordance with the rating given can involve the developer of the application to make improvements or development for the application. Therefore, Research should be conducted using techniques and analytics to categorize the user comments into several groups. This study uses sentiment analysis using the Naive Bayes method to capture positive and negative sentiments for comments on the Simobi Plus mobile banking application on the Google Play store, so that these sentiments have the appropriate value. The accuracy scores for the negative class, positive class, recall, and mood analysis are used to evaluate the test. The resulting value has an accuracy of 99%, which is almost perfect. The precision value was 100%, whereas the recall class produced a value of 98% (positive class: negative). And the AUC value is 0.980.

Prediksi Saham Multi-Industri Menggunakan Deep Transfer Learning Ezra Julang Prasetyo; Kristoko Dwi Hartomo
JURNAL INFOTEL Vol 15 No 2 (2023): May 2023
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v15i2.941

After the Covid-19 pandemic, the number of investors in Indonesia has proliferated. In managing a good stock portfolio, investors need the right strategy too. One approach that can be applied is to predict stock movements by considering the company's industrial sector. This paper proposed a new framework for applying deep transfer learning for stock forecasting in multi-industry. The model used in the framework is a combined algorithm between Gated Recurrent Unit (GRU) and Long-Short Term Memory (LSTM). The author built the pre-trained model using Indeks Harga Saham Gabungan (IHSG) and transferred it to predict Indonesia's stock indexes based on industry classification (IDX-IC) as the measurer of stock movement in multiple industries. The outcomes reveal that this framework produces good model predictions and can be used to help analyze the evaluation of the pre-trained model to conduct transfer learning stock prediction in different industries efficiently. The model built using the IHSG indexes can predict stock prices best in the energy, technology, and industrial sectors.

Analisis Sentimen Terhadap Pengaruh Minat Belanja Berdasarkan Komentar di Marketplace Menggunakan Metode Recurrent Neural Network (RNN) Gerry Santos Lasatira; Kristoko Dwi Hartomo; Irwan Sembiring
Jurnal Sistem Informasi Bisnis Vol 13, No 2 (2023): Volume 13 Nomor 2 Tahun 2023
Publisher : Diponegoro University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21456/vol13iss2pp112-119

Product reviews on the marketplace can provide useful information if they are properly processed. Product review analysis can be performed by merchants to obtain information that can be used to evaluate products and services. It is not enough to look at the number of stars in product review analysis activities; it is also necessary to look at the entire contents of the review comments to determine the intent of the review. This can be done manually in small quantities, but in large quantities, the system is more efficient. In order to understand the intent of the reviews, a system that can effectively analyze many reviews is required. Using the Recurrent Neural Network (RNN) method, this study aims to analyze sentiment on the influence of shopping interest based on comments in the marketplace. The RNN model is trained to recognize positive and negative sentiments using data from the marketplace. The sentiment analysis results will be used to assess the impact on user shopping interest in the marketplace. Sentiment analysis was performed in this study using the RNN method in the GRU/LSTM training model with epochs. The researcher determined the epoch to achieve high accuracy. The data used for model training and testing is separated into training and testing data before it is used. A comparison of 80% of training data and 20% of test data is used to split data. This study uses a training model with 77 epochs and a batch size of 128 to create a system that automatically calculates comment sentiment in the marketplace with a 100% accuracy value and determines positive and negative sentiments.

Implementasi dan Pelatihan Aplikasi Manajemen Aset Gereja Berbasis Progressive Web Application Kristoko Dwi Hartomo; Nina Setiyawati; Dwi Hosanna Bangkalang
ABDIMASKU : JURNAL PENGABDIAN MASYARAKAT Vol 6, No 3 (2023): September 2023
Publisher : LPPM UNIVERSITAS DIAN NUSWANTORO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62411/ja.v6i3.1560

Kegiatan Pengabdian kepada Masyarakat (PkM) ini dilakukan dengan melakukan proses implementasi serta pelatihan aplikasi manajemen aset di Gereja Protestan Maluku (GPM) Jemaat Ihamahu-Betfage. Unit Sekolah Minggu GPM Jemaat Ihamahu-Betfage terus bertumbuh dan membutuhkan aplikasi manajemen aset untuk mengelola dan mengarsipkan aset-aset yang dimiliki. Tahapan PkM ini adalah perencanaan dan pelaksanaan yang melibatkan dosen serta mahasiswa Universitas Kristen Satya Wacana serta Guru-guru Sekolah Minggu. Tahap pelaksanaan diawali dengan setting server dan implementasi aplikasi manajemen aset gereja yang menerapkan teknologi Progressive Web Application sehingga memiliki kelebihan reliabel, cepat, dan menarik. Pelatihan dilakukan dengan metode workshop selama satu hari. Berdasarkan evaluasi yang dilakukan pasca pelatihan didapatkan bahwa kegiatan PkM ini telah berjalan efektif dengan aplikasi yang diimplementasikan mudah digunakan dan membantu proses manajemen aset unit Sekolah Minggu.

Enhancing Multi-Output Time Series Forecasting with Encoder-Decoder Networks Kristoko Dwi Hartomo; Joanito Agili Lopo; Hindriyanto Dwi Purnomo
Journal of Information Systems Engineering and Business Intelligence Vol. 9 No. 2 (2023): October
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jisebi.9.2.195-213

Background: Multi-output Time series forecasting is a complex problem that requires handling interdependencies and interactions between variables. Traditional statistical approaches and machine learning techniques often struggle to predict such scenarios accurately. Advanced techniques and model reconstruction are necessary to improve forecasting accuracy in complex scenarios. Objective: This study proposed an Encoder-Decoder network to address multi-output time series forecasting challenges by simultaneously predicting each output. This objective is to investigate the capabilities of the Encoder-Decoder architecture in handling multi-output time series forecasting tasks. Methods: This proposed model utilizes a 1-Dimensional Convolution Neural Network with Bidirectional Long Short-Term Memory, specifically in the encoder part. The encoder extracts time series features, incorporating a residual connection to produce a context representation used by the decoder. The decoder employs multiple unidirectional LSTM modules and Linear transformation layers to generate the outputs each time step. Each module is responsible for specific output and shares information and context along the outputs and steps. Results: The result demonstrates that the proposed model achieves lower error rates, as measured by MSE, RMSE, and MAE loss metrics, for all outputs and forecasting horizons. Notably, the 6-hour horizon achieves the highest accuracy across all outputs. Furthermore, the proposed model exhibits robustness in single-output forecast and transfer learning, showing adaptability to different tasks and datasets. Conclusion: The experiment findings highlight the successful multi-output forecasting capabilities of the proposed model in time series data, with consistently low error rates (MSE, RMSE, MAE). Surprisingly, the model also performs well in single-output forecasts, demonstrating its versatility. Therefore, the proposed model effectively various time series forecasting tasks, showing promise for practical applications. Keywords: Bidirectional Long Short-Term Memory, Convolutional Neural Network, Encoder-Decoder Networks, Multi-output forecasting, Multi-step forecasting, Time-series forecasting

Pelatihan penggunaan sistem manajemen aset gereja untuk peningkatan tata kelola administrasi di GMIM jemaat anugerah paslaten Tomohon Nina Setiyawati; Dwi Hosanna Bangkalang; Kristoko Dwi Hartomo
SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan Vol 8, No 1 (2024): March
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jpmb.v8i1.21294

AbstrakDigitalisasi tata kelola gereja merupakan bagian penting untuk mendukung tata kelola administrasi gereja. Saat ini, Gereja Masehi Injili di Minahasa (GMIM) Jemaat Anugerah Paslaten Tomohon berproses mengimplementasikan teknologi dalam tata kelola administrasi gereja secara menyeluruh dimana salah satunya adalah pengelolaan aset. Pada kegiatan Pengabdian kepada Masyarakat (PkM) ini dilakukan pelatihan sistem manajemen aset gereja. Pelatihan dilakukan pada bulan Agustus 2023 dengan metode ceramah dan praktik. Fokus pelatihan pada fungsi pendaftaran dan penambahan aset, perubahan status aset, dan pengawasan kondisi aset. Peserta pelatihan terdiri dari Pendeta Jemaat, Majelis, Admin Teknologi Informasi, dan Koster GMIM Jemaat Anugerah Paslaten. Dari hasil pengujian kepada 14 peserta pelatihan, didapatkan hasil 91%. Hal ini dapat diinterpretasikan bahwa peserta pelatihan sangat setuju Sistem Manajemen Aset Gereja diperlukan untuk pengelolaan aset dan mempermudah dalam mendokumentasikan aset gereja. Kata kunci: sistem manajemen aset gereja; pengelolaan aset; tata kelola administrasi gereja. AbstractDigitalization of church governance is an important part of supporting church administrative governance. Currently, the Evangelical Christian Church in Minahasa (GMIM) Congregation Anugerah Paslaten Tomohon is in the process of implementing technology in overall church administration, one of which is asset management. In this Community Service (PkM) activity, training was carried out on the church asset management system. Training will be conducted in August 2023 using lecture and practical methods. Focus training on the function of registering and adding assets, changing asset status, and monitoring asset condition. The training participants consisted of the Congregation Pastor, Council, Information Technology Admin, and GMIM Koster of the Anugerah Paslaten Congregation. From the results of testing on 14 training participants, the results were 91%. This can be interpreted to mean that the training participants strongly agree that the Church Asset Management System is needed to manage assets and make it easier to document church assets. Keywords: church asset management system; asset management; church administrative governance.

Co-Authors Ade Iriani Adyatma Andhika Bagaskara Agus Bambang Nugraha Ahmad Ashifuddin Aqham Alexandra, Andrea Cellista Allu, Roy Armus Andeka Rocky Tanaamah Andreas Arga Rinjani Saputro Andriana, Myra Angelia Destriana Anggara Cahya Putra Anita Sulistiawati Anthony Y.M. Tumimomor April Firman Daru Ariany Mahastanti, Linda Ariel Kristianto Arthur, Christian Aruperes, Viveca Grivenda Aryanata Andipradana Baali, Gabriel Megfaden Kenisa Brilliananta Radix Dewana Chandra Husada Danny Manongga Danny Sebastian Dearmelliani Tarigan Desyandri Desyandri Dewi, Stefani Fransisca Dian Widiyanto Chandra Diky Candra Muria Pratama Djoko Hartanto Dwi Anggono Winarso Suparjo Putra Dwi Hosanna Bangkalang Eko Sediyono Enik Muryanti Estie Grace Melisa Sinulingga Evangs Evi Maria Evi Maria Evi Maria Ezra Julang Prasetyo Faudisyah, Alfendio Alif Gerry Santos Lasatira Gladiola Lavinia Ambayu Gogo Krisatyo Hanna Arini Parhusip Hanna Prillysca Chernovita Hindriyanto Dwi Purnomo Indrajaya, Denny Irwan Sembiring Ismanto, Bambang Ismanto Joanito Agili Lopo Joanito Agili Lopo Johan Jimmy Carter Tambotoh Joshua Rondonuwu Josua Josen Alexander Limbong Karina Bianca Lewerissa Kevin Benedictus Simarmata Kevin Hendra William Kevin Stevian Hermawan Kezia Sharent Kodoati Kuncoro, Wreda Agung Kurniawan, Timothy Arif Linda Ariany Mahastanti Lobo, Murry Albert Agustin Lutfi Rahmawati Magdalena Ariance Ineke Pakereng Martin Setyawan Martin Teddy Sihite Matheus Supriyanto Rumetna Mila Chrismawati Paseleng Mozad Timothy Waluyan Muflihanto, Ezar Juan Muhammad Rizky Ramadhan Muhammad Sholikhan Neilin Nikhlis Nicolas Evander Suhandi Nina Setiyawati Nining Fitriani nuranto, bogo Nurrokhman Nurrokhman Nuzhah Al Waaidhoh Penidas Fodinggo Tanaem Prakoso, Hendri Suryo Pramudhita Tunjung Seta Prasianto, Kornelius Reinand Purnomo, Andreas Wisnu Adi Purwanto Purwanto Raditya Ditto Aryaputra Radius Tanone Radjawane, Samy Rahmat Abadi Suharjo Raymond Elias Mauboy Rizaldi, Alexander Sandy Pratama Septian Silvianugroho Sinulingga, Yedija Sada Ukurta Sri Yulianto Sri Yulianto Joko Prasetyo Sri Yulianto Prasetyo Stevan Hamonangan Hardi Suhandi, Nicolas Evander Suryasatriya Trihandaru Sutarto Wijono T. Arie Setiawan P Takakobi, Michael Richard Teguh Wahyono Theopillus J. H. Wellem Tri Harjani Tri Wahyuningsih Triloka Mahesti Tumbade, Marcho Oknivan Wahab, Nur Haliza Abdul Wibowo, Mars Caroline Winarko, Edi Wiwien Hadikurniawati Yessica Nataliani Yohan Maurits Indey Zenitha Eunike Tridinatha

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