Article Per Year (5 Year)
p-Index From 2021 - 2026
2.765
P-Index
This Author published in this journals
All Journal JUTI: Jurnal Ilmiah Teknologi Informasi JURNAL ELEKTRO ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Journal of Information System Jurnal Ilmiah Universitas Batanghari Jambi CogITo Smart Journal Science and Physics Education Journal (SPEJ) MITRA: Jurnal Pemberdayaan Masyarakat Jurnal Mantik Jurnal Optimalisasi Jurnal Media Teknik dan Sistem Industri Journal of Industrial Engineering and Operation Management (JIEOM) Abdimisi Jurnal Pendidikan dan Teknologi Indonesia Industrika : Jurnal Ilmiah Teknik Industri International Journal of Multidisciplinary Research and Literature (IJOMRAL) RJOCS (Riau Journal of Computer Science) Jurnal Pengabdian Masyarakat Charitas Metris: Jurnal Sains dan Teknologi LATAR, Jurnal Arsitektur Integrasi: Jurnal Ilmiah Teknik Industri
Maria Angela Kartawidjaja
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Humanities Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Physics Public Health Social Sciences Other

Published : 25 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 25 Documents
Search

 1   2   3 
IMPLEMENTATION OF HUE SATURATION INTENSITY (HSI) COLOR SPACE TRANSFORMATION ALGORITHM WITH RED, GREEN, BLUE (RGB) COLOR BRIGHTNESS IN ASSESSING TOMATO FRUIT MATURITY Yanto`, Budi; Maria Angela Kartawidjaja; Ronald Sukwadi; Marsellinus Bachtiar
RJOCS (Riau Journal of Computer Science) Vol. 9 No. 2 (2023): RJOCS (Riau Journal of Computer Science)
Publisher : Fakultas Ilmu Komputer, Universitas Pasir Pengaraian

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30606/rjocs.v9i2.2428

Abstract

Tomatoes, as a type of vegetable or fruit, are often susceptible to damage, making handling them a complex challenge. Distinguishing between fresh and damaged tomatoes is very important, considering the significant impact on nutritional value and economic aspects. Traditional approaches via visual inspection have proven to be less efficient and inconsistent in their detection accuracy. To overcome this challenge, the use of images is a vital solution for distinguishing ripe, half-ripe and unripe tomatoes. In this context, HSI (Hue, Saturation, Intensity) calculations are applied to measure RGB color and room transformations. Images are extracted in jpg format, saved as training data, and this method is implemented using the Python programming language and GUI interface design in MATLAB. The research results show the HSI value for each class, with the ripe tomato class having an average hue of 0.0051 – 0.026, saturation 0.1862 – 0.3291, and intensity 0.0975 – 0.7522. Half-ripe tomatoes have hue 0.0208 – 0.0848, saturation 0.1346 – 0.5746, and intensity 0.1056 – 0.4714, while immature tomatoes have hue 0.0174 – 0.0689, saturation 0.0474 – 0.2072, and intensity 0.0595 – 0.3203. The integration of the HSI algorithm steps with the RGB color space provides an additional dimension to color analysis, which has the potential to increase the accuracy of tomato ripeness detection.
SPArc-subset general-purpose microprocessor design and implementation in field programmable gate array Bachri, Karel Octavianus; Alexander, Justin; Osmond, Edbert; Widawati, Enny; Kartawidjaja, Maria Angela
Jurnal Mantik Vol. 8 No. 3 (2024): November: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v8i3.5681

Abstract

This paper focuses on designing a 32-bit Reduced Instruction Set Computer (RISC) Scalable Processor Architecture (SPArc) subset gener al purposes processor. The design process covers instructions selection, Register Transfer Notation (RTN) design, Datapath Design, and Control Unit Design. Basic integer instruction was selected. Datapath was designed along with the RTN with a five-stage pipeline with direct connection between stages. This design was then validated using functionality simulation test and implemented in Field Programmable Gate Array (FPGA). The performance of the processor was measured using thermal report, power report, and time report. Functional test shows that the Processor can execute instructions as designed, which are Arithmetic/Shift/Logic, Control Transfers, and Memory access instructions. It was validated with the register content and signal generated in each stage. The design was also successfully implemented in FPGA with the maximum clock of 58 MHz as the synthesis report shows. Thermal report shows the thermal properties of the design, which shown the acceptable thermal margin of 56.9 ?C and junction temperature of 28.1 ?C. The power report shows the low power consumption of 0.266 W, which consists of dynamic power of 0.173 W and static power of 0.093 W. This work enables further development and to be used as master processor in System on Chip design of special purpose processors like cognitive processors
Predicting Stock Market Trends Based on Moving Average Using LSTM Algorithm Permana, Rizki Surya; Mahyastuty, Veronica Windha; Budiyanta, Nova Eka; Bachri, Karel Octavianus; Kartawidjaja, Maria Angela
CogITo Smart Journal Vol. 10 No. 2 (2024): Cogito Smart Journal
Publisher : Fakultas Ilmu Komputer, Universitas Klabat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31154/cogito.v10i2.648.486-495

Abstract

Prediction of the stock market is highly needed to assist traders in making decisions. Many methods are used by traders to predict this such as technical analysis and moving averages. Moving averages predict stock trends based on the past data of the stock. The disadvantage of using a moving average analysis is the delay in crossover signals. As a solution, a deep learning technique known as LSTM is applied to the moving average strategy in this paper. In this research, the BBCA stock dataset spanning from 2010 to 2018 was utilized. The data was segmented into two parts: 2010-2017 for training data and 2018 for testing data. The training process employed Long Short-Term Memory (LSTM) networks, with the subsequent results being combined with moving average crossover techniques. Validation results indicate that BBCA shows a relatively minimal error. BBCA's average MAPE is 1.1%, and its RMSE is 65.402, classifying it within the "Highly Accurate Forecasting" category. Various combinations of moving average crossovers were tested during model training, with the combination of SMA05 and SMA50 for BBCA yielding the highest profit potential. Stocks that exhibit a downward trend are more likely to incur substantial losses. The model can predict the reversal of trends by predicting the trading signal given by the moving averages.
Kompresi Sinyal EKG menggunakan Teknik Parameter Extraction ALIWARGA, CINTHIA; PRAMUDITA, ALOYSIUS ADYA; KARTAWIDJAJA, MARIA ANGELA
ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika Vol 7, No 2: Published May 2019
Publisher : Institut Teknologi Nasional, Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26760/elkomika.v7i2.308

Abstract

ABSTRAKSistem healthcare IoT menyebabkan peningkatan trafik komunikasi dan jumlah penyimpanan data. Elektrokardiogram (EKG) adalah salah satu alat yang berperan penting dalam healthcare IoT. Pasien yang mengalami kelainan jantung perlu dipantau oleh EKG dalam periode waktu lama sehingga menghasilkan data dalam jumlah yang sangat besar. Kompresi data mampu menjadi solusi masalah di atas. Penelitian ini melakukan kompresi sinyal EKG menggunakan metode parameter extraction untuk satu siklus sinyal dari dua belas pasien yang dipilih secara acak. Hasil penelitian menunjukkan bahwa kinerja kompresi baik, ditunjukkan oleh nilai Compression Ratio (CR) 6,24 dan Mean Square Error (MSE) 0,0018.Kata kunci: IoT, EKG, kompresi data, parameter ekstraction. ABSTRACTHealthcare IoT causing higher data communication traffic and storage. Electrocardiogram (ECG) is one of the important device in healthcare IoT. Patient whose have heart abnormality needs ECG monitoring for long period of time, this causing a big data size. Data compression become one of the solutions for this problem. This research focused on data compression using parameter extraction method for one cycle ECG signal from twelve patients.This research has a good result with Compression Ratio (CR) 6,24 and Mean Square Error (MSE) 0,0018.Keywords: IoT, ECG, data compression, parameter extraction
USULAN SISTEM PERPARKIRAN DAN PENENTUAN KEBUTUHAN LAHAN PARKIR DI UNIVERSITAS “X” DENGAN MENGGUNAKAN MODEL ANTRIAN DAN SIMULASI Arisandhy, Vivi; Suhada, Kartika; Rexivio, Derys Christian; Kartawidjaja, Maria Angela; Sukwadi, Ronald
Journal of Industrial Engineering and Operation Management (JIEOM) Vol 7, No 2 (2024)
Publisher : Universitas Islam Kalimantan Muhammad Arsyad Al Banjari Banjarmasin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31602/jieom.v7i2.16079

Abstract

Penelitian mengenai sistem perparkiran dan sistem antrian telah banyak dilakukan sebelumnya. Namun penelitian yang membahas sistem perparkiran yang berpengaruh ke sistem antrian dan perhitungan kebutuhan lahan parkir belum banyak dilakukan. Panjangnya antrian mobil di depan Gerbang 2 Universitas “X” banyak dikeluhkan mahasiswa dan mengganggu kelancaran arus lalu lintas depan kampus. Oleh karena itu, akan diusulkan sistem perparkiran dan penentuan kebutuhan lahan parkir di universitas tersebut. Langkah pertama yang dilakukan adalah pengujian kesamaan rata-rata untuk laju kedatangan mobil dan lama waktu parkir antar rentang waktu dan antar hari dengan SPSS. Selanjutnya dilakukan penentuan distribusi laju kedatangan mobil dan lama waktu parkir, lama waktu pelayanan manless dan loket keluar dengan Stat Fit. Kemudian dibuat model simulasi sistem antrian saat ini dan usulan dengan program Promodel. Dengan melakukan perubahan lokasi pintu masuk, posisi manless dan loket operator keluar, terjadi penurunan lama waktu menunggu sebesar 95,88% di manless Gedung A, 42,31% di manless Gedung B, 79,40% di drop-off point dan panjang antrian maksimum di depan gerbang masuk menurun sebesar 91,40%. Kebutuhan maksimum lahan parkir Gedung B adalah 394 mobil. Dengan diijinkannya parkir paralel, lahan parkir dapat menampung 392 mobil. Oleh karena kekurangan lahan hanya sebesar 2 mobil, maka lahan parkir Gedung B yang ada saat ini masih mencukupi kebutuhan.Kata Kunci:  Antrian, Lahan Parkir, Manless, Sistem Perparkiran, Simulasi
Pengembangan Game Kesiapsiagaan Kebakaran di Kampus Menggunakan Metode MDLC untuk Meningkatkan Kesadaran Mahasiswa Bata, Julius; Sutanto, Daniel Denis; Ghozali, Theresia; Wijayanti, Linda; Mulyadi, Melisa; Kartawidjaja, Maria Angela
Jurnal Pendidikan dan Teknologi Indonesia Vol 5 No 2 (2025): JPTI - Februari 2025
Publisher : CV Infinite Corporation

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jpti.576

Abstract

Rendahnya kesiapsiagaan mahasiswa terhadap situasi darurat kebakaran di lingkungan kampus merupakan masalah yang signifikan, terutama karena kurangnya pelatihan formal dan pemahaman terkait protokol keselamatan. Penelitian ini bertujuan untuk mengembangkan game simulasi kebakaran berbasis teknologi yang dirancang untuk mempersiapkan mahasiswa dalam menghadapi situasi darurat kebakaran. Pengembangan dilakukan dengan metode Multimedia Development Life Cycle (MDLC), game ini berfokus pada jalur evakuasi, lokasi alat pemadam api ringan (APAR), dan skenario kebakaran yang realistis. Hasil pengujian menunjukkan bahwa fitur game berfungsi optimal, dan 30 mahasiswa yang menjadi responden memberikan tanggapan positif terhadap aspek pembelajaran, interaksi, visualisasi, dan relevansi peristiwa dalam game dengan dunia nyata. Hasil ini menunjukkan bahwa game simulasi yang dikembangkan tidak hanya memberikan pengalaman imersif tetapi juga mampu meningkatkan pemahaman dan kesiapsiagaan mahasiswa terhadap situasi darurat kebakaran. Penelitian ini memberikan kontribusi signifikan dalam pengembangan metode pembelajaran interaktif untuk manajemen resiko bencana di kebakaran di lingkungan pendidikan tinggi.
Segmentasi Pelanggan Menggunakan K-Means Clustering: Menganalisis Metrik RFM untuk Strategi Pemasaran YUNITA, IKA; Ali, Puti Retno; Kartawidjaja, Maria Angela; Sukwadi, Ronald
Jurnal Media Teknik dan Sistem Industri Vol 9, No 1 (2025)
Publisher : Universitas Suryakancana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35194/jmtsi.v9i1.4452

Abstract

Means clustering algorithm for customer segmentation in the retail sector. The background of the research is based on the need to gain a deeper understanding of customer behavior in order to develop more effective Customer Relationship Management (CRM) strategies tailored to each customer segment. The data used in this study was collected from sales transactions over a period of three years, from April 1, 2021, to August 23, 2023, totaling 62,677 transactions. The primary objective is to enhance CRM strategies by categorizing customers based on their purchasing behavior. The K-Means algorithm was employed to group customers according to their RFM values, while the Elbow Method and Silhouette Analysis were used to determine the optimal number of clusters. As a result, customers were classified into three main segments: General Development, General Maintenance, and Important Maintenance. Each segment is characterized by a unique combination of recency, frequency, and monetary values, providing insights into targeted marketing approaches. Short-term strategies include personalized promotions and targeted campaigns to encourage repeat purchases and increase the average order value. Long-term initiatives focus on developing loyalty programs and VIP services to enhance customer retention and lifetime value. These findings emphasize the effectiveness of data-driven CRM strategies in optimizing customer engagement and profitability in the competitive retail landscape. Penelitian ini mengkaji penerapan analisis RFM (Recency, Frequency, Monetary) dan algoritma clustering K-Means dalam melakukan segmentasi pelanggan di sektor ritel. Latar belakang penelitian ini didasarkan pada pentingnya memahami perilaku pelanggan secara lebih mendalam untuk menyusun strategi Customer Relationship Management (CRM) yang lebih efektif dan disesuaikan dengan kebutuhan masing-masing segmen pelanggan. Data yang digunakan berasal dari transaksi penjualan selama periode tiga tahun, yakni dari 1 April 2021 hingga 23 Agustus 2023, dengan total sebanyak 62.677 transaksi. Tujuan utama penelitian ini adalah untuk meningkatkan strategi CRM melalui pengelompokan pelanggan berdasarkan perilaku pembelian mereka. Algoritma K-Means digunakan untuk mengklasifikasikan pelanggan berdasarkan nilai RFM, sementara Metode Elbow dan Analisis Silhouette diterapkan untuk menentukan jumlah cluster yang optimal. Berdasarkan hasil analisis, pelanggan terbagi menjadi tiga segmen utama: General Development, General Maintenance, dan Important Maintenance. Masing-masing segmen ditentukan oleh kombinasi unik dari nilai recency, frequency, dan monetary, yang memberikan wawasan dalam menentukan strategi pemasaran yang lebih tepat sasaran. Strategi jangka pendek mencakup promosi yang dipersonalisasi dan kampanye yang ditargetkan untuk mendorong pembelian berulang dan meningkatkan nilai rata-rata pesanan. Sedangkan inisiatif jangka panjang berfokus pada pengembangan program loyalitas dan layanan VIP untuk meningkatkan retensi pelanggan serta nilai seumur hidup mereka. Hasil penelitian ini menegaskan efektivitas strategi CRM berbasis data dalam mengoptimalkan keterlibatan pelanggan dan profitabilitas perusahaan di lingkungan ritel yang kompetitif.
Penerapan Metode Hybrid Waterfall-RAD pada Sistem Antrian Web untuk Optimalisasi Layanan di Pengadilan Negeri Bale Bandung Senubekti, Mamok Andri; Kartawidjaja, Maria Angela; Adyana, Gede Bagia Wijaya
JOINS (Journal of Information System) Vol. 10 No. 1 (2025): Edisi Mei 2025
Publisher : Fakultas Ilmu Komputer, Universitas Dian Nuswantoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33633/joins.v10i1.12668

Abstract

Penelitian ini bertujuan mengoptimalkan pelayanan publik melalui pengembangan sistem antrian real-time berbasis web di Pengadilan Negeri Bale Bandung, yang sebelumnya menghadapi masalah antrian tidak terorganisir dan waktu tunggu lama akibat sistem manual. Metode pengembangan menggabungkan model Waterfall untuk struktur tahap linier dan pendekatan Rapid Application Development (RAD) untuk iterasi cepat berbasis partisipasi pengguna. Analisis kebutuhan dilakukan secara deskriptif untuk memetakan proses antrian eksisting, dilanjutkan dengan desain sistem berbasis framework CodeIgniter 3 dan MySQL. Implementasi mencakup antarmuka responsif, manajemen antrian otomatis, notifikasi suara, dan pembaruan status real-time. Hasil penelitian menunjukkan bahwa sistem mampu menyederhanakan proses antrian, meningkatkan transparansi melalui pemantauan antrian secara langsung, serta mengurangi waktu tunggu secara signifikan. Keberhasilan ini didukung oleh integrasi metode hibrida Waterfall-RAD yang memadukan kekuatan dokumentasi formal dan pengembangan adaptif. Temuan ini menegaskan pentingnya transformasi digital dalam layanan publik untuk meningkatkan akuntabilitas institusi peradilan, serta memberikan kerangka kerja yang dapat diadopsi oleh instansi pemerintah lain dengan konteks serupa.
Segmented least recently used cache replacement simulator Wijaya, Marvin Chandra; Kartawidjaja, Maria Angela; Edmund, Kyle
Jurnal Mantik Vol. 9 No. 1 (2025): May: Manajemen, Teknologi Informatika dan Komunikasi (Mantik)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/mantik.v8i5.6201

Abstract

The block replacement process in the memory cache is an essential technique in computing systems to improve the efficiency of data retrieval from high-speed memory. Various caching algorithms have been developed to speed up data retrieval access in the memory cache, including Least Recently Used (LRU), Least Frequently Used (LFU), and First In First Out (FIFO). This study aims to develop a simulator by combining the LRU and LFU methods called Segmented Least Recently Used (SLRU), which is able to process data retrieval from the memory cache more efficiently. Experiments on the simulation program created were carried out on 10 random data groups to determine the effectiveness of each block replacement algorithm. Based on the test results, SLRU had the best performance, with an average hit ratio of 71.4%, followed by LRU (67%), LFU (62%), and FIFO, which showed the lowest hit ratio performance with a hit ratio of 55.8%. The advantage of SLRU lies in dividing cache segmentation into two segments: the probationary segment (LRU) and the protected segment (LFU). Based on the experiment results, it was concluded that SLRU has more efficient results in handling dynamic data access patterns than other algorithms.
Pelatihan Mikrokontroler Dasar Arduino UNO dan Simulasi Tinkercad Gideon Manalu, Ferry Rippun; Wijayanti, Linda; Mulyadi, Melisa; Ghozali, Theresia; Sereati, Catherine Olivia; Kartawidjaja, Maria Angela
Jurnal Pengabdian Masyarakat Charitas Vol. 4 No. 02 (2024): Jurnal Pengabdian Masyarakat Charitas
Publisher : Program Studi Teknik Industri, Fakultas Teknik, Universitas Katolik Indonesia Atma Jaya Jakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25170/charitas.v4i02.6168

Abstract

The Electrical Engineering study program of the Faculty of Engineering, Atma Jaya Catholic University of Indonesia has been collaborating with Harapan Bagi Bangsa Christian Middle School, Cilincing, North Jakarta for several years in an extracurricular program for junior high school students, as a form of community service from Electrical Engineering lecturers. The extracurricular activity program implemented is in the form of basic electronics training. The theme of the activity varies, according to the requests and needs of the partner schools. The first activity is to provide basic electronics skills training to students. This program received a very positive response from teachers and students. From the evaluation results of previous activities, all students wanted training activities with advanced materials. The training provided is an introduction to basic Arduino Uno microcontrollers using Tinkercad simulation software. The purpose of this activity is to conduct training on the introduction and how to program the Arduino Uno microcontroller to turn on Light Emitting Diodes (LEDs). The training was carried out at Harapan Bagi Bangsa Christian Middle School. The training began by assembling the resistor and LED components on the project board. After all the components were installed, an Arduino Uno microcontroller program was created to turn on the LEDs alternately according to the order of the program created. The training used Tinkercad simulation software and the Arduino Uno microcontroller board. From the results of the student evaluation, 92.2% of students gave good and excellent ratings, while 7.8% gave neutral ratings for this training.
Co-Authors Adiguna, Brian Adyana, Gede Bagia Wijaya Alexander, Justin Ali, Puti Retno ALIWARGA, CINTHIA Aloysius Adya Pramudita Asmaralda, Naftalia Bachri, Karel Octavianus Bachtiar, Marsellinus Bellachintya Reira Christata budi Cahyono Catherine Olivia Sereati Christine Natalia Edmund, Kyle Enny Widawati Gideon Manalu, Ferry Rippun Goenawan, Stephanus Ivan Hendrik Yusmanto Hotma Antoni Hutahaean Inna Kholidasari Iryanto, Mokhamad Trihandoyo Jayawarsa, A.A. Ketut Julius Bata Kartika Suhada Kurniawan Kurniawan Mamok Andri Senubekti Marsellinus Bachtiar Marsellinus Bachtiar W Marvin Chandra Wijaya Melisa Mulyadi Muda, Yosef Norbertus Tembu Nova Eka Budiyanta Osmond, Edbert Rainisa Maini Heryanto Rexivio, Derys Christian Rizani, Miftahul Fahriyyah Rizki Surya Permana Ronald Sukwadi Ronald Sukwadi SANTOSO SANTOSO Silalahi, Agustinus Stania Vandika Stanislaus S. Uyanto Sutanto, Daniel Denis Theresia Ghozali TIrtaulima, Chelsea Naomi Trifenaus Prabu Hidayat Uyanto, Stanislaus Suryadi Veronica Windha Mahyastuty Vivi Arisandhy Wijayanti, Linda Yanto`, Budi Yunita, Ika