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Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi
Published by Sekolah Tinggi Manajemen Informatika dan Komputer Banjarbaru
ISSN : 20893787     EISSN : 26850893     DOI : -
Core Subject : Science,
Computer Science & IT
Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi adalah Jurnal Ilmiah bidang Teknik Informatika dan Sistem Informasi yang diterbitkan secara periodik tiga nomor dalam satu tahun, yaitu pada bulan April, Agustus dan Desember. Redaksi Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi menerima sumbangan tulisan hasil penelitian atau atau artikel konseptual bidang Teknik Informatika dan Sistem Informasi.
Arjuna Subject : -
Articles 951 Documents
 92   93   94   95   96 
Implementasi Teknologi Geolocation Pada Sistem Pelaporan Parkir Liar Berbasis Web Prayata, Aldo Yusran; Romli, Moh. Ali
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 3: Desember 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i3.3362

Abstract

This study is motivated by the low effectiveness of reporting illegal parking violations in urban and tourist areas, where the current manual reporting process often leads to delays in handling incidents and difficulties in accurately identifying the location. To address these issues, this research aims to develop an information system for reporting illegal parking based on web and mobile platforms by utilizing geolocation technology to make the reporting process faster, more accurate, and easier for the public to use. The system was developed using the Waterfall model, which includes the stages of requirements analysis, design, implementation, and testing using the Black-box method. It integrates the Google Maps API to automatically detect the reporter’s location and uses PostgreSQL as the main database for storing reports. The testing results indicate that all system features operate according to user requirements and accurately display incident locations, enabling more efficient reporting, assisting officers during verification processes, and supporting the digitalization of public services in the transportation sector.Keywords: Reporting System; Geolocation; API; Web Base AbstrakPenelitian ini dilatarbelakangi oleh rendahnya efektivitas pelaporan pelanggaran parkir liar di kawasan wisata dan perkotaan, di mana proses pelaporan yang masih dilakukan secara manual menyebabkan keterlambatan penanganan serta kesulitan dalam menentukan lokasi kejadian secara tepat. Untuk mengatasi masalah tersebut, penelitian ini bertujuan mengembangkan sistem informasi pelaporan parkir liar berbasis web dan mobile dengan memanfaatkan teknologi geolokasi agar proses pelaporan menjadi lebih cepat, akurat, dan mudah diakses oleh masyarakat. Sistem dikembangkan menggunakan model Waterfall yang meliputi tahap analisis kebutuhan, perancangan, implementasi, dan pengujian menggunakan metode Black-box. Sistem ini terintegrasi dengan Google Maps API untuk mendeteksi lokasi pelapor secara otomatis dan menggunakan PostgreSQL sebagai basis data penyimpanan laporan. Hasil pengujian menunjukkan bahwa seluruh fitur sistem telah berfungsi sesuai kebutuhan pengguna dan mampu menampilkan lokasi kejadian dengan akurat, sehingga sistem yang dibangun dapat meningkatkan efisiensi pelaporan, membantu proses verifikasi petugas, serta mendukung digitalisasi layanan publik di sektor transportasi. 
Analytical Hierarchy Process Method of Prosthetic and Orthotic Materials for Patient Needs Nurkholiza, Rahmiyana; Beng, Jap Tji; Wasino, Wasino; Tiatri, Sri; Sam, Toong Hai; Anolin, Ann G.; Castillo, Sheryll Ann M.; Dinatha, Vienchenzia Oeyta Dwitama
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 3: Desember 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i3.3159

Abstract

This study highlights the importance of optimising assistive devices for people with disability, as the law says in Law No. 8 of 2016. Ligar Mandiri Prosthetics and Orthopaedics Clinic offer related services, where choosing the right materials is getting more complicated because of fast tech advances and lots of options like carbon fibre, plastic, and titanium. This study aims to develop a Decision Support System (DSS) to assist practitioners in selecting materials based on quality, cost, and production time criteria. The alternatives evaluated include local, semi-imported, and imported materials. Using the Analytic Hierarchy Process (AHP) method, the analysis shows that imported materials received the highest ranking (0.54708), followed by local materials (0.24157) and semi-imported materials (0.21155). The DSS developed in this study has enhanced the accuracy, efficiency, and transparency of decision-making, thereby supporting practitioners in providing effective and reliable prosthetic and orthotic solutions. 
Analisis Pembangunan Knowledge Management System Pada Unit Kerja Asdep Dumas Kemensetneg RI Dengan Framework COBIT 5.0 Novryzal, Andress; Pranoto, Edi
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 3: Desember 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i3.3148

Abstract

The very rapid development of information technology in the era of disruption has changed various work processes, including the management of public complaints at the Ministry of State Secretariat of the Republic of Indonesia, the number of which continues to increase every year. To increase the speed and accuracy of analysis, the Assistant Deputy for Public Complaints developed a Knowledge Management System as a means of accessing and managing case references. This research evaluates the suitability of system development to organizational needs and assesses the maturity level of IT processes using a COBIT 5-based audit. The approach used is a mixed method through literature study, distributing questionnaires to 15 Dumas analysts, and interviews with relevant officials. The research results show that the maturity level is at level 4 (managed), while the organization's target is level 5. The gap value found in EDM02 was 0.9, EDM04 was 0, APO04 was 0.67, and APO12 was 0.89, indicating the need for process improvement to achieve the expected maturity level.Keywords: Cobit 5.0; Knowledge Management System; Maturity level; Dumas AbstrakPerkembangan teknologi informasi yang sangat pesat pada era disrupsi telah mengubah berbagai proses kerja, termasuk pengelolaan pengaduan masyarakat di Kementerian Sekretariat Negara RI yang jumlahnya terus meningkat setiap tahun. Untuk meningkatkan kecepatan dan ketepatan analisis, Asisten Deputi Pengaduan Masyarakat mengembangkan Knowledge Management System sebagai sarana akses dan pengelolaan referensi kasus. Penelitian ini mengevaluasi kesesuaian pengembangan sistem dengan kebutuhan organisasi serta menilai tingkat kematangan proses TI menggunakan audit berbasis COBIT 5. Pendekatan yang digunakan merupakan metode campuran melalui studi pustaka, penyebaran kuesioner kepada 15 analis dumas, dan wawancara dengan pejabat terkait. Hasil penelitian menunjukkan tingkat kematangan berada pada level 4 (managed), sementara target organisasi adalah level 5. Nilai kesenjangan yang ditemukan EDM02 sebesar 0,9, EDM04 sebesar 0, APO04 sebesar 0,67, dan APO12 sebesar 0,89 mengindikasikan perlunya peningkatan proses untuk mencapai tingkat kematangan yang diharapkan. 
Machine Learning Classification of Insomnia Using Multidimensional Features and SMOTE Novanza, Trional; Ramadhan, Mgs. M. Luthfi; Caryn, Femilia Hardina; Passa, Rahma Satila; Iqrom, Redho Aidil; Seftianto, Ferlian; Hardoni, Andre; Baturohmah, Habi
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 3: Desember 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i3.3372

Abstract

Sleep disorders, especially insomnia, are common among adolescents and negatively affect health. Early detection is crucial for appropriate treatment. This study aims to classify insomnia severity in adolescents using a Machine Learning (ML) model and multidimensional features derived from 19 questionnaire instruments. The dataset consists of 95 adolescents aged 16–19 years, categorized into Insomnia, Subclinical Insomnia, and Control classes. The modeling process includes reducing multicollinearity, class balancing with SMOTE, and hyperparameter optimization using GridSearchCV and StratifiedKFold. Feature importance analysis was conducted using decision tree-based methods and permutation importance. The results show that SMOTE improves SVM performance from 0.690 to 0.793 and positively affects Random Forest. Logistic Regression performs best without SMOTE (accuracy 0.759), while XGBoost shows the lowest accuracy (0.614) even with SMOTE. A total of 11 features consistently contribute to all models. In conclusion, ML models, particularly SVM, are effective for classifying insomnia severity in adolescents. 
Pengembangan Model Long Short-Term Memory Berbasis MediaPipe Pose untuk Klasifikasi dan Penilaian Gerakan Push-Up Artha, I Kadek Bayu Danu; Arthana, I Ketut Resika; Suputra, Putu Hendra
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 3: Desember 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i3.3363

Abstract

The counting and assessment of push-up movements are often inaccurate and subjective because they are done manually. Existing automated approaches generally only consider the top and bottom positions. This makes the assessment incomplete, so that imperfect movements can be counted as correct. This study aims to develop a Long Short-Term Memory (LSTM) model using MediaPipe Pose landmark extraction to detect and classify push-up movements based on the overall movement pattern. Data was collected in the form of videos validated by experts and processed into 3,600 video data sets with 10 movement classes. The video data was extracted to produce normalized keypoint coordinates and joint angles, and padding was added to equalize the data length. The model was trained using the K-Fold Cross Validation method with eight different architectures. The results showed that the best model achieved an average testing accuracy of 92.35% and an F1-Score of 92.53%. These findings indicate that the combination of MediaPipe Pose and LSTM can effectively recognize and classify push-up movements.Keywords: MediaPipe Pose;Llong short-term memory; Classification; Push-up; Time seriesAbstrakPenghitungan dan penilaian gerakan push-up sering tidak akurat serta bersifat subjektif akibat dilakukan secara manual. Pendekatan otomatis yang ada umumnya hanya mempertimbangkan posisi atas dan bawah. Hal ini membuat penilaian tidak secara keseluruhan sehingga gerakan yang tidak sempurna dapat terhitung benar. Penelitian ini bertujuan mengembangkan model Long Short-Term Memory (LSTM) dengan memanfaatkan ektraksi landmark MediaPipe Pose untuk mendeteksi dan mengklasifikasi gerakan push-up berdasarkan keseluruhan pola gerakan. Data dikumpulkan dalam bentuk video yang divalidasi oleh ahli dan diolah hingga mejadi 3.600 data video dengan 10 kelas gerakan. Data video diektraksi hingga menghasilkan koordinat keypoint dan sudut sendi yang dinormalisasi, serta ditambahkan padding untuk menyamakan panjang data. Model dilatih dengan metode K-Fold Cross Validation dengan delapan arsitektur berbeda. Hasil penelitian menunjukkan performa model terbaik memperoleh rata-rata akurasi testing 92,35% dan F1-Score 92,53%. Temuan ini menunjukkan kombinasi MediaPipe Pose dan LSTM dapat dengan baik mengenali dan mengklasifikasi gerakan push-up. 
Analisis Pola Penjualan Menu Makanan Dengan Metode Regresi Linier Dan Visualisasi Interaktif Kuswandi, Olivia; Dharmawan, Alexander; Bakti, Cristeddy Asa
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 3: Desember 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i3.3198

Abstract

Micro, small, and medium enterprises (MSME) often face difficulties in analyzing sales data to support accurate business planning. This study aims to identify sales patterns and forecast demand for the MSME Bakmi Ceria using the linear regression method. The dataset consists of monthly online sales records from Gojek and Grab platforms for four main menus: Mie Ayam, Mie Bakso, Mie Pangsit, and Mie Komplit. The independent variable analyzed is time (month), while the dependent variable is the sales quantity of each menu. Model performance was evaluated using Mean Absolute Percentage Error (MAPE) and the coefficient of determination (R²). Results show that three menus exhibited upward trends, while Mie Komplit declined. MAPE values ranged from 2.55% to 6.98%, with R² reaching 0.99, indicating high model accuracy. These findings confirm that linear regression effectively supports stock planning, promotion strategies, and data-driven decision-making for MSMEs. Keywords: Micro, small, and medium enterprises; Sales pattern; Linear regression; Prediction, Python AbstrakUMKM sering menghadapi kendala dalam menganalisis data penjualan untuk merencanakan strategi bisnis secara tepat. Penelitian ini bertujuan untuk mengidentifikasi pola penjualan dan memprediksi permintaan pada UMKM Bakmi Ceria dengan metode regresi linier. Data yang digunakan berupa catatan penjualan bulanan dari platform Gojek dan Grab terhadap empat menu utama: Mie Ayam, Mie Bakso, Mie Pangsit, dan Mie Komplit. Variabel independen yang dianalisis adalah waktu (bulan), sedangkan variabel dependen berupa jumlah penjualan tiap menu. Model diuji menggunakan Mean Absolute Percentage Error (MAPE) dan koefisien determinasi (R²) untuk menilai akurasi. Hasil menunjukkan tiga menu mengalami tren kenaikan, sedangkan Mie Komplit menurun. Nilai MAPE berkisar 2,55%–6,98% dengan R² mencapai 0,99, menunjukkan tingkat akurasi yang tinggi. Temuan ini menegaskan bahwa regresi linier efektif dalam mendukung perencanaan stok, promosi, dan pengambilan keputusan berbasis data pada UMKM. 
Implementasi Forward Chaining Dalam Sistem Pakar Untuk Menentukan Dosis Pemupukan Tahunan Kelapa Sawit Ramadhan, Rayka Mulya; Waluyo, Anita Fira
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 3: Desember 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i3.3357

Abstract

Proper fertilization of oil palm is crucial for increasing plant productivity, however farmers often face challenges in determining the correct fertilizer dosage based on plant conditions and soil types. This study aims to develop an expert system using the forward chaining method to determine the annual fertilizer dosage for oil palm. The forward chaining method was chosen due to its ability to draw conclusions progressively based on initial data (soil type and plant age). The system operates by applying pre-programmed rules to generate accurate fertilizer dosage recommendations. Testing results show that the system can provide precise dosages based on the age category and soil type of the oil palm. The implementation of this system is expected to assist oil palm farmers in improving agricultural efficiently.Keywords: Forward chaining; Expert system; Oil palm; Fertilizer dosageAbstrakPemupukan kelapa sawit yang tepat sangat penting untuk meningkatkan produktivitas tanaman, namun sering kali petani kesulitan dalam menentukan dosis pupuk yang sesuai dengan kondisi tanaman dan jenis tanah. Penelitian ini bertujuan untuk mengembangkan sistem pakar berbasis metode forward chaining dalam menentukan dosis pemupukan tahunan pada kelapa sawit. Metode forward chaining dipilih karena kemampuannya dalam menarik kesimpulan secara bertahap berdasarkan data awal (jenis tanah dan umur tanaman). Sistem ini bekerja dengan cara mengaplikasikan aturan (rule) yang sudah diprogramkan untuk menghasilkan rekomendasi dosis pupuk yang tepat. Hasil pengujian menunjukkan bahwa sistem dapat memberikan dosis yang akurat sesuai dengan kategori umur dan jenis tanah kelapa sawit. Dengan implementasi sistem ini, diharapkan dapat membantu petani kelapa sawit dalam meningkatkan hasil pertanian secaraefisien.
Pengembangan Aplikasi Pengaduan dan Monitoring Fasilitas Umum Zuliyanto, Andika Fajar; Asriningtias, Yuli
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 3: Desember 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i3.3290

Abstract

Public facilities such as roads, street lights and drainage channels are vital elements that support the comfort and safety of the community. However, damage to these facilities is often not repaired immediately due to the lack of an integrated reporting and monitoring system. This study aims to design and develop a mobile and web-based public facility complaint and monitoring application that allows the community to report damage directly, along with the location, description, and photos. The system was developed using the Waterfall method, which includes needs analysis, design, implementation, testing, and maintenance. Testing results using Black Box Testing show that all features function according to specifications, including location-based reporting and real-time status monitoring. Keywords: Public facilities; Reporting system; Mobile application; Digitization of public services; Monitoring. AbstrakFasilitas umum seperti jalan, lampu penerangan, dan saluran drainase merupakan elemen vital yang menunjang kenyamanan dan keselamatan masyarakat. Namun, kerusakan pada fasilitas tersebut sering kali tidak segera diperbaiki karena belum adanya sistem pelaporan dan pemantauan yang terintegrasi. Penelitian ini bertujuan untuk merancang dan mengembangkan aplikasi pengaduan dan monitoring fasilitas umum berbasis mobile dan web yang memungkinkan masyarakat melaporkan kerusakan secara langsung disertai lokasi, deskripsi, dan foto. Pengembangan sistem dilakukan menggunakan metode Waterfall yang meliputi analisis kebutuhan, perancangan, implementasi, pengujian, dan pemeliharaan. Hasil pengujian menggunakan Black Box Testing menunjukkan bahwa seluruh fitur berfungsi sesuai spesifikasi, termasuk pelaporan berbasis lokasi dan pemantauan status secara real-time. 
Klasifikasi Tujuan Penggunaan AI Oleh Mahasiswa Dengan Algoritma K-Nearst Neighbor Karoh, Sabilatul Isti; Waluyo, Anita Fira
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 3: Desember 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i3.3348

Abstract

Artificial intelligence (AI) technology is developing rapidly, particularly through platforms like ChatGPT and Gemini AI, which are widely used by students for various purposes. This fact highlights the importance of a more in-depth analysis of students' AI usage patterns. This study aims to classify the purposes of AI use by students using the K-Nearest Neighbor (K-NN) algorithm. The study was conducted using two classification approaches: multi-class classification and binary classification. Data were obtained from questionnaires with 305 respondents and processed using Python on the Google Colab platform using preprocessing, normalization, and data encoding stages. Test results show that the K-NN algorithm achieved a high accuracy of 77% in the binary classification scenario (Productive/Career and Entertainment/Personal), while in the multi-class classification scenario the highest accuracy only reached 34%. This finding indicates that K-NN performance is strongly influenced by the complexity of the number of classes and is more optimally applied to classifications with a limited number of classes.Keywords: K-Nearest Neighbor; AI usage classification; students; Binary Classification; Multi-class Classification.AbstrakTeknologi kecerdasan buatan ataupun Artificial Intelligence (AI) berkembang pesat, terutama melalui platform seperti ChatGPT dan Gemini AI yang banyak digunakan oleh mahasiswa untuk berbagai tujuan. Fakta ini menunjukkan pentingnya analisis yang lebih mendalam mengenai pola penggunaan AI oleh mahasiswa. Penelitian ini bertujuan untuk mengklasifikasikan tujuan penggunaan AI oleh mahasiswa memakai algoritma K-Nearest Neighbor (K-NN). Penelitian dilakukan melalui dua pendekatan klasifikasi, yaitu multi-class classification dan binary classification. Data didapatkan dari kuesioner terhadap 305 responden dan diolah memakai Python pada platform Google Colab menggunakan tahap pra-pemrosesan, normalisasi, dan pengkodean data. Hasil pengujian menunjukan algoritma K-NN mencapai akurasi tinggi yaitu 77% pada skenario klasifikasi biner (Produktif/Karir dan Hiburan/Personal), sementara pada skenario klasifikasi multi-kelas akurasi tertinggi hanya mencapai 34%. Temuan ini menandakan bahwa kinerja K-NN sangat dipengaruhi oleh kompleksitas jumlah kelas dan lebih optimal diterapkan pada klasifikasi dengan jumlah kelas yang terbatas. 
Desain User Interface Pendaftaran Akta Kelahiran Dan Kartu Identitas Anak Pada Data Kependudukan Pambudi, Aji Indra; Cahyono, Ariya Dwika
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 14, No 3: Desember 2025
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v14i3.3166

Abstract

Efficient and easy-to-understand public services are a primary demand in today’s digital era. One essential service that needs improvement is the registration system for birth certificates and Child Identity Cards (KIA). This study aims to design an efficient and user friendly user interface (UI) to facilitate online registration for the public. The Design Thinking method is used as the main approach in this research, consisting of five stages: empathize, define, ideate, prototype, and test. Through interviews and observations involving users and civil registration officers (Disdukcapil), several challenges were identified, such as long queues and the perception of excessive documentation required for registering birth certificates and KIAs. The ideation and prototyping process resulted in a simpler and more understandable UI design. Testing of the prototype showed a significant improvement in users’ understanding of the registration process and their overall satisfaction. Therefore, the Design Thinking approach has proven effective in producing a UI design that meets user needs and enhances the efficiency of digital public services.Keywords: Design user interface; Design Thinking; Birth certificate registration; Child identity card registrationAbstrakPelayanan publik yang efisien dan mudah dipahami merupakan tuntutan utama dalam era digital saat ini. Salah satu layanan penting yang perlu ditingkatkan adalah sistem pendaftaran akta kelahiran dan Kartu Identitas Anak (KIA). Penelitian ini bertujuan untuk merancang antarmuka pengguna (UI) yang efisien dan user-friendly guna mempermudah masyarakat dalam melakukan pendaftaran secara daring. Metode Design Thinking digunakan sebagai pendekatan utama dalam penelitian ini, yang terdiri dari lima tahap: empathize, define, ideate, prototype, dan test. Melalui wawancara dan observasi terhadap pengguna serta petugas Disdukcapil, ditemukan berbagai kendala seperti antrian yang panjang serta dokumen yang dianggap banyak dalam mengurus pendaftaran akta kelahiran dan Kartu Identitas Anak (KIA). Hasil dari proses ideasi dan prototyping menghasilkan desain UI yang lebih sederhana, dan mudah dipahami. Pengujian terhadap prototype menunjukkan peningkatan signifikan dalam pemahaman alur pendaftaran dan kepuasan pengguna. Dengan demikian, pendekatan Design Thinking terbukti efektif dalam menghasilkan desain UI yang mampu menjawab kebutuhan pengguna serta meningkatkan efisiensi layanan publik digital. 

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