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INDONESIA
JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI
Published by STMIK Global Informatika MDP
ISSN : 24074322     EISSN : 25032933     DOI : -
Core Subject : Science,
Computer Science & IT
JATISI bekerja sama dengan IndoCEISS dalam pengelolaannya. IndoCEISS merupakan wadah bagi para ilmuwan, praktisi, pendidik, dan penggemar dalam bidang komputer, elektronika, dan instrumentasi yang menaruh minat untuk memajukan bidang tersebut di Indonesia. JATISI diterbitkan 2 kali dalam setahun (September dan Maret), makalah yang diterbitkan JATISI minimal terdiri dari 60% dari luar Sumatera Selatan, dan 40% dari Sumatera Selatan. Makalah yang diterbitkan melalui tahap review oleh reviewer yang berpengalaman dan sudah memiliki makalah yang diterbitkan di jurnal internasional yang terindeks SCOPUS.
Arjuna Subject : -
Articles 1,216 Documents
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Perancangan Website Pertolongan Pertama “LifeSaver” Menggunakan Metode Design Thinking Amelia, Dwi
JATISI Vol 11 No 2 (2024): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v11i2.7987

Abstract

Kecelakaan atau keadaan darurat kesehatan dapat terjadi dimanapun dan kapanpun, namun seringkali respons cepat dan tepat dalam pemberian pertolongan terabaikan disebabkan banyak faktor. Pertolongan pertama merupakan langkah penting dan memerlukan perhatian khusus. Kurangnya pengetahuan dan ketidakpercayaan diri dalam memberikan pertolongan pertama sering menjadi penghambat bagi sebagian besar orang. Untuk mengatasi permasalahan tersebut, diperlukan sistem informasi berbasis website yang dapat memberikan informasi dan edukasi seputar pertolongan pertama. ”LifeSaver” dirancang menggunakan metode design thinking. Melalui website ini pengguna dapat dengan mudah mencari nomor telepon penting, mempelajari cara penanganan yang tepat dalam situasi darurat, membantu menemukan rumah sakit terdekat, serta mendapatkan sertifikasi yang relevan. Dalam perancangan UI/UX dengan menerapkan metode design thinking, tahapan yang dilalui yaitu empathize, define, ideate, prototype, dan test. Dengan menggunakan metode ini, dapat menghasilkan solusi yang dapat mengatasi permasalahan yang dihadapi dalam memberikan pertolongan pertama. Melalui uji coba dengan 10 responen, terbukti bahwa desain UI/UX ini dapat dijalankan sesuai dengan skenario yang diberikan. Hal tersebut menunjukan bahwa perancangan yang dilakukan berhasil.
Implementasi Metode K-Nearest Neighbor dalam Menentukan Waktu Optimal Penarikan Pesanan Driver Ojol Prasetiyo, Anton
JATISI Vol 11 No 2 (2024): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v11i2.7995

Abstract

App-based transportation companies are propelling technological advancements in the services provided to every user and online motorcycle taxi partner. Online motorcycle taxis currently represent the most popular and widely used mode of transportation. Thanks to the application system's ability to enable online motorcycle taxi partners to work from anywhere and at any time, an increasing number of individuals are expressing interest in becoming such partners. However, this surge in interest has led to new challenges, particularly regarding income from orders within the competitive landscape of online motorcycle taxi partnerships. Therefore, the author aims to address these issues through this research. Classification algorithms are employed to analyze the optimal timing for processing order requests. This study seeks to develop a classification model using the K-Nearest Neighbor method to determine the optimal timing based on label classes. K-Nearest Neighbor involves identifying k target members in the training data closest to the target in the testing or new data. The dataset utilized in this research is sourced from three online motorcycle taxi driver accounts, comprising a total of 1941 datasets. The classification results using the K-Nearest Neighbor method yielded excellent outcomes, achieving an accuracy level of 99%. Subsequently, testing with a value of k=9 and an 80:20 ratio resulted in an average f1-score of 99.33%.
Sistem Informasi Praktik Kerja Lapangan (SIPRAKLAP) Pada SMK Berbasis Web Menggunakan Metode Waterfall Taufik, Andi
JATISI Vol 11 No 2 (2024): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v11i2.8003

Abstract

Field Work Practice is a form of activity to achieve the mission of Vocational High Schools (SMK) that produce graduates to be absorbed in the world of work. With the increasing acceptance of students every year, more and more students have to do PKL activities. However, when carrying out the PKL registration process, the lack of information about PKL received by students so that they do not get a quota for PKL places, the management of PKL activity data is still carried out manually by the hubin so that the hubin requires time in checking the status of students who have not, are and have done PKL, assessment of street vendors and print certificates To overcome these problems, a web-based Field Work Practice Information System (SIPRAKLAP) was created, which makes it easy to find PKL information, PKL reports, assessments and print PKL certificates. The System Development Model used in this study uses a waterfall model, starting from the System Needs Analysis Stage, System Design, Application of Coding, Testing, and Support. And it uses MySQL database and PHP programming language.
Perancangan Desain Aplikasi Mobile Untuk Pendukung Kinerja Imunisasi Posyandu Ijlal, Muhammad Yusuf Luthfi
JATISI Vol 11 No 2 (2024): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v11i2.8012

Abstract

Peningkatan kesehatan anak usia balita di Indonesia dilakukan melalui layanan imunisasi. Namun, akses dan efektivitas layanan ini masih terbatas terutama di daerah pedesaan. Oleh karena itu, diperlukan upaya optimalisasi, salah satunya melalui pendisiplinan imunisasi dan perbaikan sistem administrasi. Penelitian ini bertujuan merancang aplikasi mobile sebagai solusi pemberitahuan jadwal imunisasi. Survei dilakukan pada kalangan wanita dalam rentang usia bawah 40 tahun yang memiliki anak balita dan bekerja penuh waktu. Hasil analisis menunjukkan bahwa pemberitahuan jadwal imunisasi menjadi masalah utama. Oleh karena itu, aplikasi ini dirancang untuk memberikan notifikasi secara otomatis guna meningkatkan efektifitas imunisasi. Prototipe aplikasi dibuat untuk menguji kegunaan dan keberhasilan aplikasi melalui metode Usability Testing dan System Usability Scale (SUS). Hasilnya menunjukkan bahwa aplikasi ini dapat meningkatkan efektivitas notifikasi dan kemudahan akses layanan imunisasi, dengan rating kepuasan masuk kedalam kategori good.
Klasifikasi Penyakit Antraknosa Citra Cabai Rawit Dengan Metode Convolutional Neural Network (CNN) Setiono, Mukti
JATISI Vol 11 No 2 (2024): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v11i2.8039

Abstract

Abstract Indonesia, as an agricultural country, has a very vital agricultural sector, including the cultivation of cayenne pepper. Cayenne peppers are often infected with anthracnose disease caused by the fungus Colletotrichum sp., causing significant economic losses. This research aims to develop a Convolutional Neural Network (CNN) model for classifying anthracnose in images of cayenne pepper, in order to increase the effectiveness of disease diagnosis. Image data was obtained from chili gardens in Savanajaya Village, Buru Regency, with a total of 1000 images, which were divided into 500 images of healthy chilies and 500 images of infected chilies. The data is processed and labeled manually, then resized for consistency. CNN was trained using the Adam optimizer, RMSprop, and SGDM, with test results showing that the Adam optimizer provided the highest accuracy of 93.25%. The implementation of CNN has proven effective in classifying anthracnose, helping farmers in making timely decisions for disease control, thereby increasing productivity and reducing economic losses. This research emphasizes the importance of choosing the right optimizer and dataset quality in developing image-based plant disease classification models.
Sistem Diagnosa Stunting Menggunakan Teorema Bayes Kamto, Kevin Arsan; Purnomo, Agus Sidiq
JATISI Vol 11 No 2 (2024): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v11i2.8040

Abstract

Stunting is a chronic nutritional problem that impacts children's physical and cognitive growth. This research develops an expert system based on Bayes' Theorem to diagnose stunting, and utilizes artificial intelligence (AI) technology. The Bayes Theorem method is used for its ability to overcome data uncertainty and produce more accurate decisions. Data was collected through interviews with pediatricians and medical records from posyandu. The system was designed using flowcharts and DFD, then implemented and tested with samples of 30 children from the Kaligrenjeng Village Posyandu. The results of the diagnosis showed a 100% accuracy rate. Validation of the results shows the expert system according to the expert's diagnosis.
The CLASSIFICATION OF STROKE PREDICTION USING THE SUPPORT VECTOR MACHINE (SVM) METHOD Wulandari, Erika; Witanti, Arita
JATISI Vol 11 No 3 (2024): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v11i3.8044

Abstract

Stroke is a dangerous disease that can take someone's life, regardless of age. Several factors can cause a stroke, such as diabetes, hypertension, smoking, obesity, and other stroke factors. Therefore, understanding stroke is crucial for everyone to anticipate and prevent this disease. This stroke classification prediction research aims to determine the results of classification and the accuracy level of the data collected through the Support Vector Machine (SVM) method and SMOTE technique. Support Vector Machine (SVM) is an algorithm used to map information with minimal risk by separating hyperplanes. Before the testing phase, data balancing is also performed first using the SMOTE technique to ensure more accurate data processing. This research uses a dataset of 5,110 data points with 12 records. The classification results using the SVM method with the SMOTE technique yielded a good level of accuracy. Specifically, this research uses two ratios: 80:20 with an accuracy result of 85.45% and 70:30 with an accuracy result of 85.24%.
Analisis Kepuasan Pelanggan Terhadap Kinerja Layanan Air Bersih Menggunakan Metode TOPSIS (Studi Kasus PDAM Wilayah Pontianak) Marsela, Dwi; Purnomo, Agus Sidiq
JATISI Vol 11 No 3 (2024): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Regional Drinking Water Company (PDAM) has an important role in providing clean water services for the community. Customer satisfaction is a crucial aspect that needs to be considered to improve PDAM performance. This research aims to analyze customer satisfaction with PDAM performance in Pontianak area and optimize clean water service by using Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method in decision support system. The TOPSIS method is a multi-criteria decision-making method that can evaluate alternatives based on established criteria. Customer satisfaction data will be collected through surveys and processed using the TOPSIS methodology to produce an alternative ranking of service improvements. The results of this study are expected to provide recommendations for PDAM in optimizing performance and improving the quality of clean water services in Pontianak area based on customer preferences
SPK Rekomendasi Platform E-Commerce terbaik Menggunakan Metode (SAW) saputra, made okta
JATISI Vol 11 No 3 (2024): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v11i3.8055

Abstract

The rapid advancement of technology has significantly transformed modern economic life, particularly through e-commerce, which leverages digital tools and internet access. In Indonesia, e-commerce began in 1999 and experienced substantial growth in 2019 due to increased internet usage and smartphone adoption. Despite offering numerous benefits, users face challenges such as product price variations, product mismatches, and delivery issues. Decision Support Systems (DSS) using the Simple Additive Weighting (SAW) method have been proposed to determine the best alternative e-commerce platform. These systems provide accurate recommendations based on predefined criteria. The final scores indicate that the comparison between the system’s calculations and Microsoft Excel calculations showed 100% similarity. Shopee ranked first with a score of 0.95, making it the most suitable e-commerce platform solution
SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN BANTUAN BEASISWA TIDAK MAMPU DENGAN METODE SAW (Studi Kasus SD Muara Mea) Wulandari, Lasri
JATISI Vol 11 No 3 (2024): JATISI (Jurnal Teknik Informatika dan Sistem Informasi)
Publisher : Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jatisi.v11i3.8060

Abstract

Scholarships are financial support provided by various parties such as governments, private companies, embassies, universities, and educational institutions, rather than coming from personal or parental sources. In order for scholarship distribution to be carried out more precisely, the selection of scholarship recipients by educational institutions must be improved. One of the methods used is Simple Additive Weighting (SAW), where this method involves summing the weights of the ratings on each alternative. This study aims to build a decision support system in the selection of recipients of scholarship assistance at SD Muara Mea using the Simple Additive Weighting (SAW) method. Based on testing done using 15 data, it produces a system accuracy value with a percentage of 66%.

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