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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
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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Pengelolaan Perlindungan Data Pribadi Menggunakkan MongoDB Change Streams Untuk Sistem Notifikasi Real-Time Kurniawan, Timothy Arif; Hartomo, Kristoko Dwi
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.v10i2.6134

Abstract

Perkembangan teknologi memberikan dampak positif maupun dampak negatif bagi masyarakat. Salah satu bentuk dampak negatif perkembangan teknologi adalah munculnya aktivitas pencurian data. Hal tersebut merupakan aktivitas yang dapat menghambat kegiatan masyarakat khususnya kalangan organisasi atau perusahaan. Penelitian ini bertujuan untuk membuat sebuah aplikasi pengelolaan data yang dapat menampilkan riwayat aktivitas operasi data yang terjadi pada collection serta menampilkan response dari proses pengelolaan data dalam bentuk message notifikasi realtime. Untuk mendukung proses pengembangan aplikasi yang diinginkan, maka dibutuhkan teknologi yang dapat dimanfaatkan sebagai pendukung pengembangan aplikasi dan teknologi utama yang digunakkan adalah MongoDB Change Streams dan Websockets. Lalu untuk memastikan aplikasi telah bekerja sesuai dengan requirements user dan juga planning, maka aplikasi akan melalui tahap pengujian black box. Penelitian ini menghasilkan sebuah aplikasi pengelolaan data dengan notifikasi realtime serta riwayat log berbasis web. Dengan aplikasi tersebut, user dapat mengelola data serta melakukan pemantauan terhadap seluruh aktivitas pengelolaan data yang terjadi pada collection sehingga hal tersebut dapat mencegah terjadinya aktivitas pencurian data.
RISK MANAGEMENT ANALYSIS OF E-KOHORTKIA APPLICATION USING ISO 31000 FRAMEWORK IN SOUTH CENTRAL TIMOR DISTRICT HEALTH OFFICE Allu, Roy Armus; Hartomo, Kristoko Dwi
JUTI: Jurnal Ilmiah Teknologi Informasi Vol. 22, No. 2, July 2024
Publisher : Department of Informatics, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j24068535.v22i2.a1201

Abstract

The E-KohortKIA application is a web-based application launched by the Indonesian Ministry of Health for use in Puskesmas and Health Offices throughout Indonesia as a solution to various problems caused by manual use of the KIA Cohort. This application can be accessed via computer or smartphone and is currently being implemented by the South Central Timor District Health Service for Maternal and Child Health (KIA) services. In using this application, various possible risks can occur that can disrupt application performance, therefore it is necessary to carry out a risk management analysis. The aim of this research is to determine various possible risks that could occur in implementing the E-KohortKIA application and to carry out risk treatment for these possible risks. This research uses qualitative methods by collecting data through interviews and observations, as well as data processing and risk management analysis using the ISO 31000 framework including the risk assessment stage and risk treatment stage. The results of this research found 23 possible risks, most of which were due to system and infrastructure factors. These possible risks include 13 possible low level risks, 8 possible medium level risks, and 2 possible high level risks. There are 2 possible risks that have a high and maximum level of risk severity so that they have the potential to disrupt or inhibit or even stop application performance. This research also provides recommendations for risk treatment proposals for various possible risks and can be used by users to maintain application performance.
Evaluation of an Information System using the PIECES Framework: A Case Study of the Inventory Administration Information System (SIAP) of the North Sulawesi Provincial Government Aruperes, Viveca Grivenda; Hartomo, Kristoko Dwi
SISTEMASI Vol 14, No 2 (2025): Sistemasi: Jurnal Sistem Informasi
Publisher : Program Studi Sistem Informasi Fakultas Teknik dan Ilmu Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v14i2.5041

Abstract

This study evaluates user satisfaction with the Inventory Administration Information System (SIAP) in North Sulawesi Province using the PIECES Framework and provides recommendations for improvement. The PIECES Framework was chosen due to its proven effectiveness in assessing satisfaction, identifying issues, and guiding system development. This framework consists of six variables: Performance, Information & Data, Economic, Control & Security, Efficiency, and Service. The sample size was determined using Slovin's formula, involving 36 administrators from government offices. Data was collected through questionnaires measured on a Likert scale. The results indicate overall user satisfaction across all six variables. However, some weaknesses were identified, particularly in the Performance and Control & Security variables.
Pemanfaatan WebGIS untuk Pemetaan Wilayah Rawan Longsor Kabupaten Boyolali dengan Metode Skoring dan Pembobotan Muhammad Sholikhan; Sri Yulianto Joko Prasetyo; Kristoko Dwi Hartomo
Jurnal Teknik Informatika dan Sistem Informasi Vol 5 No 1 (2019): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v5i1.1588

Abstract

WebGIS is an online-based application of Geographic Information System, this application is a combination of web design and web mapping. WebGIS is mainly used for publishing map-based spatial information. Therefore, the author utilized webGIS, in order to mapping area that prone to landslides by using scoring and weighting methods. Parameters that used in this paper referring to the estimation model by Puslittanak in 2004, the parameters were rainfall, rock type, slope, land use, and type of soil maps. The determination of area prone to landslides was carried out by multiplying score by weight for each parameter, subsequently, the result was added up according to the reference of Puslittanak. The result of this study indicates that there are 4 sub-districts with high disaster-prone level, the sub-districts are Ampel, Cepogo, Musuk, and Selo. The final result of the map processed into a webGIS by applying Google maps service and framework bootstrap; the webGIS can be accessed by internet browser.
Rancang Bangun Sistem Informasi Geografis Rekomendasi Cagar Budaya Menggunakan Metode Analytic Hierarchy Process Nicolas Evander Suhandi; Kristoko Dwi Hartomo; Penidas Fiodinggo Tanaem
Jurnal Teknik Informatika dan Sistem Informasi Vol 6 No 2 (2020): JuTISI
Publisher : Maranatha University Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28932/jutisi.v6i2.2593

Abstract

Salatiga City is a town located in the province of Central Java. In this town, there can be found many cultural heritage buildings that were built in the mid-18th century to 1940. Potential visitors would increase easier if a geographic information system is built. Tourists who visit can access the website to select or search for cultural heritage that they want to visit, therefore the availability of a geographic information system that provides information and data on the location of cultural heritage in digital maps is needed. The system must also consider aspects of the cultural heritage rating, the price of admission, and the condition of the cultural heritage to provide recommendations on which cultural heritage to be visited. Therefore the geographic information system of cultural heritage recommendations uses the analytical hierarchy process (AHP) method which can calculate multi- criteria, multi alternatives, and provides cultural heritage recommendations. This system combines geographic information system as a provider of cultural heritage information and AHP decision support system to assist tourists in choosing cultural heritage.
Implementation and Training of Congregation Data Management Application at GPID Eben Haezer Palu Bangkalang, Dwi Hosanna; Evangs; Setiyawati, Nina; Hartomo, Kristoko Dwi; Pakereng, Magdalena Ariance Ineke
IJECS: Indonesian Journal of Empowerment and Community Services Vol. 6 No. 1 (2025)
Publisher : Universitas Veteran Bangun Nusantara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32585/ijecs.v6i1.5953

Abstract

Congregation data collection at GPID Eben Haezer is still done manually. This causes a lot of congregation data to be unsynchronized between the written data and the actual data. In addition, it also results in inefficient administrative services to the congregation. The vision of church digitalization also raises its own problems for the church, namely the unpreparedness of the church's human resources (HR) in digital capabilities. This Community Service (PkM) activity is to help and facilitate GPID Eben Haezer in implementing congregation data management applications and mentoring training in the process of adopting technology in church governance. The training activity was attended by 7 church admins and was carried out after the stages of formulating partner needs, adjusting and implementing the application. After the training, the application usability was measured using the System Usability Scale (SUS) and a score of 83 was obtained, indicating that the implemented application was EXCELLENT and ACCEPTABLE.  Keywords: Congregation Data Collection Application; Digital Skills; Training; System Usability Scale
Analisis Metode Klasifikasi Nasabah Potensial dalam Membuka Deposito Jangka Panjang Melalui Telemarketing Menggunakan Metode Gradient Boosting Classifier Takakobi, Michael Richard; Hartomo, Kristoko Dwi
Jurnal Impresi Indonesia Vol. 4 No. 5 (2025): Indonesian Impression Journal (JII)
Publisher : Riviera Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58344/jii.v4i5.6688

Abstract

Penelitian ini bertujuan untuk melihat klasifikasi nasabah dalam membuka sebuah deposito jangka panjang. Penelitian ini akan menggunakan algoritma Machine Learning, yaitu Gradient Boosting Classifier. Dataset yang digunakan diambil dari arsip dataset UC Irvine Machine Learning Repository yang mencangkup 41.188 sampel dengan 20 variabel. Dataset Kampanye bank di Portugal menggunakan metode penawaran dilakukan secara jarak jauh atau tidak langsung yang biasa disebut dengan Telemarketing. Nasabah dalam dataset terdiri dari berbagai latar belakang. Penelitian memberikan hasil baik dalam klasifikasi menggunakan metode Gradient Boosting Classifier, metode ini dikombinasikan dengan teknik random oversamping untuk mengatasi data imbalance. Penelitian menghasilkan nilai ROC-AUC sebesar 0.81. Hasil penelitian juga memberikan informasi yang dapat digunakan dalam pengambilkan Keputusan terkait dengan kampanye telemarketing selanjutnya. Penelitian ini merekomendasikan penerapan model ini untuk meningkatkan efisiensi telemarketing dengan menargetkan nasabah berpotensi, sekaligus mengurangi biaya operasional.
BiLSTM OptiFlow: an enhanced LSTM model for cooperative financial health forecasting Maria, Evi; Wahyono, Teguh; Dwi Hartomo, Kristoko; Purwanto, Purwanto; Arthur, Christian
Bulletin of Electrical Engineering and Informatics Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i3.8653

Abstract

This paper presents bidirectional long short-term memory (BiLSTM) OptiFlow, an optimized deep learning model designed to predict the financial health of cooperatives using key financial ratios: debt to equity ratio (DER), net profit margin (NPM), and return on equity (ROE). By leveraging a BiLSTM architecture combined with an optimal decayed learning rate, this model aims to enhance forecasting accuracy. The proposed model was tested against three established methods—recurrent neural network (RNN), long short-term memory (LSTM), and gated recurrent unit (GRU)—and evaluated using mean absolute error (MAE), mean absolute percentage error (MAPE), and mean squared error (MSE) metrics. Results indicate that BiLSTM OptiFlow outperforms the other models across all key indicators. This research offers a robust approach to cooperative financial forecasting, with significant implications for decision-making processes in cooperative management.
Implementasi Model ARIMA untuk Peramalan Reorder Point dalam Supply Chain Management Alexandra, Andrea Cellista; Hartomo, Kristoko Dwi
JURIKOM (Jurnal Riset Komputer) Vol 12, No 3 (2025): Juni 2025
Publisher : Universitas Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/jurikom.v12i3.8639

Abstract

This research analyzes the patterns and trends of reorder points in inventory management over a two-year period (2023-2024), utilizing weekly time series data generated from daily data resampling. The ARIMA (Autoregressive Integrated Moving Average) method was applied to forecast future reorder point values. An Augmented Dickey-Fuller (ADF) stationarity test revealed that the initial data was non-stationary but became stationary after a single differencing operation. Parameter identification using Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) plots indicated that the ARIMA(1,1,1) model was the best choice, based on the lowest Akaike Information Criterion (AIC). Model accuracy was evaluated using Mean Absolute Percentage Error (MAPE), yielding a value of 0.02%, signifying an excellent level of prediction accuracy. Consequently, the ARIMA model is demonstrated to be reliable for forecasting reorder points, supporting more precise decision-making in inventory management.
A Dual-Fusion Hybrid Model with Attention for Stunting Prediction among Children under Five Years Hadikurniawati, Wiwien; Hartomo, Kristoko Dwi; Sembiring, Irwan; Arthur, Christian
Journal of Applied Data Sciences Vol 6, No 3: September 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v6i3.831

Abstract

Malnutrition remains a persistent global health challenge, especially among children under five. Traditional assessment methods often rely on static anthropometric measures, which are limited in capturing complex growth patterns. This study aims to develop a robust classification model for predicting the nutritional status of children under five years old, addressing the critical public health challenge of stunting. The model contributes to the growing need for accurate, data-driven early detection systems in child health monitoring by introducing a hybrid framework that combines deep learning and classical machine learning techniques. The proposed approach integrates automatically extracted features from a One-Dimensional Convolutional Neural Network (1D-CNN) with classical anthropometric indicators. These combined features are processed through an additive attention mechanism, highlighting the most informative attributes. The attention-weighted representation is then classified using an ensemble stacking method that aggregates predictions from multiple base classifiers, including decision trees, nearest neighbor algorithms, support vector machines, etc. Synthetic Minority Over-sampling Technique (SMOTE) is applied to the training dataset to mitigate data imbalance, particularly the underrepresentation of severe and moderate malnutrition cases. The research utilizes a dataset comprising 2,789 records of children under five years old collected from community health posts in Indonesia. Data preprocessing included cleaning, normalization, and gender encoding. The model’s performance was evaluated using 5-fold cross-validation and measured by accuracy, precision, recall, and area under the curve metrics. The results show that the proposed model achieved an average accuracy of 99.70% and an area under the curve of 99.99%. An ablation study further demonstrated the significant contribution of each component, feature extraction, fusion mechanism, and ensemble classifier to the final performance. This approach reveals a robust and scalable solution for early nutritional status prediction in healthcare settings.
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