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Tri A. Sundara
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The Indonesian Journal of Computer Science
Published by STMIK Indonesia Padang
ISSN : 25497286     EISSN : 25497286     DOI : https://doi.org/10.33022
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering Engineering
The Indonesian Journal of Computer Science (IJCS) is a bimonthly peer-reviewed journal published by AI Society and STMIK Indonesia. IJCS editions will be published at the end of February, April, June, August, October and December. The scope of IJCS includes general computer science, information system, information technology, artificial intelligence, big data, industrial revolution 4.0, and general engineering. The articles will be published in English and Bahasa Indonesia.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 1,127 Documents
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Scrum-Based Mobile Application Development for Patient Satisfaction Assessment in Class 'B' Hospitals in Padang Nabilla, Regina; Dian, Yulef; Idris, Iswandi
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4506

Abstract

The assessment of patient satisfaction is a critical aspect of healthcare services, providing valuable insights into the quality of care and service delivery. In Padang's Class "B" hospital, traditional satisfaction assessment methods are inefficient and time-consuming. This research explores the implementation of the Scrum methodology in the development of a mobile application for real-time patient satisfaction assessment. The objective is to enhance feedback collection, improve service quality, and provide hospital management with actionable insights. The mobile application allows patients to rate services on various parameters instantly, enabling quicker responses and continuous improvement of hospital operations. This study discusses the technical implementation, the advantages of using Scrum in the development process, and the potential impact on service quality in the hospital
Analysis of General Election Campaign Topics of Candidates for President and Vice President of the Republic of Indonesia Using Lattent Dirichlet Allocation on Social Media Data Ericko Rinanto Pratama
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4508

Abstract

The election of the President and Vice President of the Republic of Indonesia 2024 is an important moment for the Indonesian people in determining future leaders. Social media plays a major role as a platform used to deliver campaign programs by presidential and vice presidential candidates. In conducting social media analysis, one approach that can be used is using topic modeling. Topic modeling produces output in the form of topics of conversation from a document, one of the models is Latent Dirichlet Allocation (LDA). In previous research, LDA has been widely used to search for topics of conversation on social media. This research analyzes the campaign programs of the 2024 Presidential and Vice Presidential Candidates of the Republic of Indonesia on social media using the Latent Dirichlet Allocation (LDA) method for intent classification in campaign program detection and sentiment analysis to check sentiment analysis. Data from the Twitter social media platform during the campaign period was processed and analyzed with LDA to understand the trend of campaign topics.
Comparison of Support Vector Machine and Random Forest Methods on Sentinel-2A Imagery for Land Cover Identification in Banda Aceh City Using Google Earth Engine Safira; Amiren, Muslim; Nazhifah, Sri Azizah; Rusdi, Muhammad; Nizamuddin; Misbullah, Alim
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4510

Abstract

Land cover is a physical feature of the earth that illustrates the relationship between natural processes and social processes. Over time, there has been a lot of land conversion, where initially open land is now built-up land. This is due to the large-scale development in Banda Aceh City. Therefore, this study aims to compare the performance of two classification methods, namely using Support Vector Machine (SVM) and Random Forest in identifying land cover in Banda Aceh City using Sentinel-2A imagery via the Google Earth Engine platform. As for data recording, it starts from January 1 to December 31, 2023. There are 4 classes used in this study, namely vegetation, water bodies, built-up land, and open land. The classification results show that the Support Vector Machine and Random Forest methods have been successfully applied to identifying land cover in Banda Aceh City using Sentinel-2A imagery. The accuracy results show that the Support Vector Machine method has a higher accuracy value of 90.5% compared to the Random Forest method of 85.7%.
Analisis Kepuasan Pengguna Aplikasi LinkAja Menggunakan Metode TAM dan EUCS Nisa', Sayyidatun; Megawati; Zarnelly; Permana, Inggih; Marsal, Arif
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4511

Abstract

Aplikasi LinkAja banyak digunakan karena memudahkan bertransaksi. Namun banyak pengguna mengalami kendala seperti, tidak dapat melakukan pembayaran QRIS, transaksi gagal namun saldo sudah terpotong, dan kesulitan mengupgrade ke LinkAja full service. Penelitian ini bertujuan menganalisis tingkat kepuasan pengguna aplikasi LinkAja dengan mengintegrasikan metode Technology Acceptance Model (TAM) dan End User Computing Satisfaction (EUCS). Berdasarkan perhitungan Lemeshow, responden dalam penelitian ini sebanyak 100 orang. Pengumpulan data dilakukan dengan menyebarkan kuesioner kepada pengguna aplikasi LinkAja. Temuan penelitian menunjukkan bahwa 5 hipotesis diterima, yaitu persepsi kemanfaatan, isi, akurasi, bentuk, dan sikap terhadap penggunaan. Sementara 3 hipotesis ditolak, yaitu persepsi kemudahan penggunaan, kemudahan penggunaan, dan ketepatan waktu. Hasil PLS-SEM menunjukkan bahwa kepuasan pengguna memiliki pengaruh positif. Ditunjukkan oleh korelasi kuat antara tiap variabel, dengan nilai R-Square kepuasan pengguna sebesar 84,6%. Ini menunjukkan bahwa aplikasi LinkAja menjalankan fungsinya dengan baik sehingga pengguna merasa puas ketika menggunakannya.
Implementasi Sistem Pemantauan Kelayakan Kapal Pada Proses Pengujian Kapal Menggunakan Teknologi Internet of Things Pristovani, Dimas; Abu Jami’in, Muhammad; Singgih Setiyoko, Annas; Toto Wibowo, Alvalo; Leonard, Rikky
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4512

Abstract

A new ship must doing a sea trial inspection before handover to the owner based on International Maritime Organization regulation under Resolution MSC.137. Currently, these inspections are conducted manually. So, the Ship Qualification and Clasification System using Internet of Things (IoT) technology are highly needed. This system made up of hardware connected to an Android application and a web-based application that monitors real-time data on position, speed, inclination, wind speed, and time. Data logger are performed simultaneously on the hardware, Android app, and web-based app, creating redundancy in data logging. In practice, The results of these trials ensure that the ship's technical specifications comply with agreed standards, as well as strengthening the confidence of all parties involved in the testing project. With this success, an IoT-based monitoring and analysis system can be a reliable solution for operational needs and evaluating ship performance
Metode Ekstraksi Fitur Canny, GLCM dan Segmentasi Warna Menggunakan K-Means Clustering Dalam Peningkatan Motif Batik Zain, Ruri Hartika; Sumijan
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4514

Abstract

Batik merupakan salah satu hasil seni budaya Indonesia berupa kain cetak yang dibuat dengan teknik tertentu. Motif motif bunga melambangkan keindahan dan kebahagiaan. Peneliti mengusulkan metode ekstraksi fitur Canny, GLCM dan segmentasi warna menggunakan k-means clustering dalam peningkatan motif batik. Dengan mengekstraksi fitur dari citra batik yang sudah ada, dapat dihasilkan citra batik dengan motif warna yang lebih banyak. Terlihat dari motif batik yang memiliki tekstur, tekstur dapat dijadikan sebagai salah satu unsur pembeda batik satu dengan yang lain. Penelitian ini juga mengimplementasikan metode Canny, GLCM dan LBP untuk ekstraksi fitur tekstur, HSV colour moment untuk ekstraksi fitur warna, sedangkan metode k-means clustering untuk mengklasifikasikan citra batik dan mengidentifikasi citra batik pewarna alam dan citra batik pewarna sintetis berdasarkan warna. Tujuan dari penelitian ini adalah untuk menggabungkan pola pada data yang sudah ada dengan pola baru. K-means clustering untuk mengelompokkan piksel citra batik digital berdasarkan warna. Hasil penelitian ini menunjukkan bahwa k-means clustering dapat meningkatkan desain batik baru dengan pola dan warna yang berbeda.
Measuring mobile banking service quality using Topic Modeling and Term Ranking: A case study of an Indonesian digital bank Anggraini, Veny; Budi, Indra; Santoso, Aris Budi; Putra, Prabu Kresna
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4517

Abstract

The rapid expansion of digital transactions in Indonesia is driving the transformation of both traditional and digital banks. Since digital banks operate without physical branches, all banking services are via mobile banking apps. This study examines mobile banking service quality using text mining techniques like topic modeling and term ranking to analyze 11,815 user reviews from app stores and assess customer satisfaction through ratings. The research involves extracting and preprocessing reviews, identifying key topics, and linking them to satisfaction levels. Seven service dimensions were found: customers were satisfied with Enjoyment, Debit Card Delivery, and Feature-Free Transactions but dissatisfied with Accessibility, Data Privacy, Loan Services, and Touchless Customer Support. Debit Card Delivery and Feature-Free Transactions were highlighted as significant factors in Indonesia's digital banking market. With limitations in analyzing user reviews in Bahasa Indonesia, the findings are specific to the Indonesian digital banking context and may not be applicable elsewhere.
Klasifikasi Status Gizi Bayi Menggunakan Algoritma K-NN Pada Puskesmas Talise Palu Hernita, Ayu; Yulandari, Anisa; Sri Khaerawati Nur
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4518

Abstract

Nutrition is a human's physical condition resulting from the balance of energy supplied and then released by the body. Nutrition is important to support the growth and development of babies. The period of toddlerhood is a very important period, because if the nutritional status of young children is inadequate then complications can arise in their health. The system used to determine children's nutrition is the K-nearest neighbor (KNN) method. This technique is a way to classify or group several test data whose classes are not yet known. This system uses variables based on anthropometric data or the baby's body sequence, namely childhood, child's weight, height and child's condition. The algorithm used in this research is K-NN in the child nutritional status classification system which determines whether the child's status is normal or not. The system development method used is Waterfall. According to the results of accuracy measurements, the success rate for determining the nutritional status of toddlers using this system was 79.17%
Pengembangan Aplikasi Presensi Pengenalan Wajah Untuk Mahasiswa Menggunakan Convolutional Neural Network Yulanda; Sutarman
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4520

Abstract

Dalam dunia pendidikan, kehadiran mahasiswa dalam pembelajaran di kelas sering dianggap sebagai syarat dan standar untuk penilaian mahasiswa. Namun, masih ada beberapa universitas yang melakukan presensi secara manual kemudian direkap ke sistem oleh dosen dan ada juga presensi menggunakan tanda tangan sebagai sistem konvensional. Hal tersebut dapat dimanfaatkan oleh mahasiswa yang nakal untuk selalu titip absen, sehingga proses ini kurang efektif, memakan waktu yang lama dan kurang terorganisir. Dan oleh karena itu, untuk mengatasi masalah tersebut peneliti membuat sistem absensi dengan pengenalan wajah atau face recognition, sehingga dapat meminimalisir waktu absensi. Dalam penelitian, metode yang digunakan adalah Convolutional Neural Network. Hasil dari pengujian aplikasi menyatakan bahwa aplikasi dapat berjalan sesuai dengan fungsinya dan kebutuhannya. Hasil penelitian menunjukkan bahwa model Convolutional Neural Network, memiliki akurasi 100% dan loss 0.0097. Percobaan dilakukan secara berulang-ulang, dan meskipun nilai loss mengalami fluktuasi, akurasi model tetap konsisten.
The Identifikasi Tren Risiko Keamanan Siber dan Mitigasinya dalam Pembangunan Smart city: Identifikasi Tren Risiko Keamanan Siber dan Mitigasinya dalam Pembangunan Smart city Adi Pratama, Yoga; Dana Indra Sensuse; Franky Juhar
The Indonesian Journal of Computer Science Vol. 13 No. 6 (2024): The Indonesian Journal of Computer Science (IJCS)
Publisher : AI Society & STMIK Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33022/ijcs.v13i6.4524

Abstract

Pembangunan smart city Ibu Kota Nusantara (IKN) menghadirkan tantangan baru dalam menjaga keamanan siber. Penelitian bertujuan untuk mengidentifikasi tren risiko keamanan siber sekaligus mitigasi risiko keamanan siber pada smart city dengan menggunakan metodologi Systematic Literature Review (SLR). Framework TOE (Technology, Organization, Environtment) digunakan untuk menghasilkan daftar risiko keamanan siber yang komprehensif berdasarkan kategori teknologi, organisasi, dan lingkungan. Hasil penelitian menunjukkan terdapat 58 risiko keamanan siber yang didominasi oleh risiko keamanan siber teknologi yaitu 81%. Mitigasi risiko keamanan siber dikelompokkan juga berdasarkan kategori teknologi, organisasi dan lingkungan. Standar internasional ISO 27002: 2022 digunakan sebagai metode validasi kontrol keamanan atas mitigasi risiko yang diidentifikasi sebagai bentuk best practice. Hasil penelitian ini memberikan rekomendasi kepada pemerintah dalam menyusun kebijakan keamanan dengan mendorong penggunaan kriptografi secara efektif, menyelaraskan dengan standar kebijakan yang aman dan audit berkala, serta selalu meningkatkan kualitas SDM keamanan siber sehingga dapat membantu pengembangan smart city IKN yang aman dan berkelanjutan.

Page 84 of 113 | Total Record : 1127

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