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Jambura Journal of Informatics
Published by Universitas Negeri Gorontalo
ISSN : 2656467X     EISSN : 26854244     DOI : 10.37905/jji
Core Subject : Science,
Computer Science & IT
Jambura Journal of Informatics (JJi) is a peer-reviewed open access journal published by Department of Informatics Engineering, Faculty of Engineering, Universitas Negeri Gorontalo (UNG), Indonesia. The journal is an archival journal serving the scientist and engineer involved in all aspects of computer science, information technology, information systems, software engineering and education of information technology. JJI publishes original research findings and high quality scientific articles that present cutting-edge approaches including methods, techniques, tools, implementations and applications.
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Articles 94 Documents
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Pengembangan Sistem Informasi Manajemen Konten Digital untuk UMKM (Studi Kasus: Kota Gorontalo) Amuda, Putra Anshori Arta; Koniyo, Moh. Hidayat; Dwinanto, Arif; Yusuf, Rampi; Dangkua, Eka Vickraien
Jambura Journal of Informatics VOL 7, N0 2: OKTOBER 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jji.v1i2.34752

Abstract

ABSTRACT. Micro, Small, and Medium Enterprises (MSMEs) in Gorontalo City have adopted social media for marketing purposes; however, its utilization remains suboptimal due to time constraints and a lack of strategic understanding regarding digital content management. Preliminary surveys indicate that many MSMEs lack a structured posting schedule and face difficulties in objectively measuring promotional effectiveness. As a practical solution, this research designs and develops a web-based Digital Content Management Information System. The primary contribution of this study is the provision of a centralized platform for MSMEs to plan and manage posting schedules, integrated with an innovative "Interaction Level Assessment" feature. This feature converts complex interaction metrics into simplified, easy-to-understand performance scores (Engagement Rate values and Grades A-D) and provides follow-up recommendations for each uploaded content. The system was developed using the Waterfall method (Pressman), involving systematic stages from requirements analysis through interviews and surveys, system design using Unified Modeling Language (UML), to code implementation. Functional testing was conducted using the Black Box Testing method, which confirmed that the system operates according to user requirements and planned specifications.ABSTRAK. Usaha Mikro, Kecil, dan Menengah (UMKM) di Kota Gorontalo telah mengadopsi media sosial untuk keperluan pemasaran, namun pemanfaatannya belum optimal akibat keterbatasan waktu dan kurangnya pemahaman mengenai strategi manajemen konten digital. Survei awal menunjukkan bahwa banyak pelaku UMKM tidak memiliki jadwal unggahan yang terstruktur dan kesulitan mengukur efektivitas promosi secara objektif. Sebagai solusi praktis atas permasalahan tersebut, penelitian ini merancang dan membangun Sistem Informasi Manajemen Konten Digital berbasis web. Kontribusi utama dari penelitian ini adalah penyediaan platform terpusat bagi UMKM untuk merencanakan dan mengelola jadwal unggahan, serta fitur inovatif "Interaction Level Assessment". Fitur ini mampu mengonversi metrik interaksi yang kompleks menjadi skor performa yang sederhana dan mudah dipahami (nilai Engagement Rate dan Grade A-D), serta memberikan rekomendasi tindakan lanjut bagi setiap konten yang diunggah. Pengembangan sistem menggunakan metode Waterfall (Pressman) yang meliputi tahapan sistematis mulai dari analisis kebutuhan melalui wawancara dan survei, perancangan sistem dengan Unified Modeling Language (UML), hingga tahap implementasi kode. Pengujian fungsionalitas sistem dilakukan menggunakan metode Black Box Testing, yang menunjukkan bahwa sistem telah berfungsi sesuai dengan kebutuhan pengguna dan spesifikasi yang direncanakan.
Evaluasi Algoritma KNN dan Naive Bayes untuk Analisis Sentimen Kebijakan Program Makan Bergizi Gratis Sakina, Nur; Wajidi, Farid; Rasyid, Muh. Rafli
Jambura Journal of Informatics VOL 7, N0 2: OKTOBER 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jji.v1i2.34418

Abstract

Social media has become a primary platform for the public to express opinions on government policies, including Indonesia’s Free Nutritious Meal (MBG) program. This study analyzes public sentiment toward MBG by comparing the K-Nearest Neighbor (KNN) and Naive Bayes algorithms. A total of 9,723 tweets were collected, and after removing the neutral category, 6,322 tweets remained (3,955 positive and 2,367 negative), indicating a dominance of positive opinions. The experimental results show that KNN performed best at k=9 with a 70:30 split, achieving an accuracy of 72.27% and an F1-score of 65.92%, with an average cross-validation accuracy of 73.30%. Naive Bayes with parameter α=0.5 consistently outperformed KNN, achieving an average accuracy of 79.61% and an F1-score of 77.33%, along with better precision–recall balance. The main contribution of this research is providing empirical evidence that Naive Bayes is more effective than KNN for sentiment analysis of Indonesian-language text with a large dataset, as well as offering a methodological framework applicable to the evaluation of other public policies.Media sosial menjadi ruang utama masyarakat untuk mengekspresikan opini terhadap kebijakan publik, termasuk Program Makan Bergizi Gratis (MBG) di Indonesia. Penelitian ini menganalisis sentimen publik terhadap MBG dengan membandingkan algoritma K-Nearest Neighbor (KNN) dan Naive Bayes. Data diperoleh dari 9.723 tweet, kemudian setelah penghapusan kategori netral tersisa 6.322 tweet (3.955 positif dan 2.367 negatif), yang menunjukkan dominasi opini positif. Hasil eksperimen menunjukkan bahwa KNN terbaik pada k=9 dengan rasio 70:30 menghasilkan akurasi 72,27% dan F1-score 65,92%, dengan akurasi rata-rata cross-validation 73,30%. Naive Bayes dengan parameter α=0,5 unggul dengan akurasi rata-rata 79,61% dan F1-score 77,33%, serta keseimbangan presisi dan recall yang lebih baik. Kontribusi penelitian ini adalah memberikan bukti empiris bahwa Naive Bayes lebih efektif dibandingkan KNN dalam analisis sentimen teks berbahasa Indonesia dengan dataset besar, serta menawarkan kerangka metodologis yang dapat diterapkan untuk evaluasi kebijakan publik lainnya.
Optimasi UI/UX Berbasis Design Thinking pada Sistem Informasi Keluarga (SIGA). Studi Kasus: BKKBN Provinsi Gorontalo Laot, Firman Syahputra; Katili, Muhammad Rifai; Lahay, Sri Nilawaty; Hadjaratie, Lillyan; A., Hermila
Jambura Journal of Informatics VOL 7, N0 2: OKTOBER 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jji.v1i2.33904

Abstract

The Family Information System (SIGA) is a strategic application of BKKBN in Gorontalo Province that supports national family data management. However, during implementation, it faces obstacles in the user interface (UI) and user experience (UX), which affect its effectiveness. This research aims to optimize the UI/UX SIGA design using the Design Thinking approach. This research method applies five stages (empathize, define, ideate, prototype, test) and evaluation of the System Usability Scale (SUS). The initial SUS test for the SIGA application yielded an average score of 41.84, indicating a very low level of usability (Grade F). After a design iteration based on user feedback, the new prototype was tested and showed a significant increase in SUS score to 88.36 (Grade A). These results show that the Design Thinking approach is practical in identifying problems and creating optimal UI/UX solutions. This research contributes practically to improving the usability of SIGA and academically to the Human-Computer Interaction (HCI) literature on public sector information systems.Sistem Informasi Keluarga (SIGA) merupakan aplikasi strategis BKKBN di Provinsi Gorontalo yang digunakan untuk mendukung pengelolaan data keluarga secara nasional. Namun, dalam implementasinya menghadapi kendala pada aspek antarmuka (UI) dan pengalaman pengguna (UX), yang berdampak pada efektivitas kerja. Penelitian ini bertujuan mengoptimalkan desain UI/UX SIGA menggunakan pendekatan Design Thinking. Metode penelitian ini menerapkan lima tahapan (empathize, define, ideate, prototype, test) dan evaluasi System Usability Scale (SUS). Hasil uji SUS awal pada aplikasi SIGA hanya mencapai skor rata-rata 41,84, yang menunjukkan tingkat usability sangat rendah (Grade F). Setelah dilakukan iterasi desain berdasarkan umpan balik pengguna, prototipe baru diuji dan menunjukkan peningkatan skor SUS signifikan menjadi 88,36 (Grade A). Hasil ini menunjukkan bahwa pendekatan Design Thinking efektif dalam mengidentifikasi masalah dan menciptakan solusi UI/UX yang optimal. Penelitian ini berkontribusi praktis pada perbaikan usability SIGA serta berkontribusi akademis pada literatur Human-Computer Interaction (HCI) untuk sistem informasi sektor publik.
Evaluasi Kualitas Sistem Informasi Akademik Terpadu (SIAT) Menggunakan ISO/IEC 25010 Nambo, Ilun; Pakaya, Nikmasari; Amali, Lanto Ningrayati; Olii, Salahudin
Jambura Journal of Informatics VOL 7, N0 2: OKTOBER 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jji.v1i2.33720

Abstract

The Integrated Academic Information System (SIAT) at Universitas Negeri Gorontalo has been widely used to support academic activities, but issues such as slow performance under heavy load, data security risks, and inconsistent interface design remain. Previous studies on academic information systems often focus on limited quality aspects or rely on single evaluation tools, leaving a research gap in providing a comprehensive quality assessment. This study aims to evaluate SIAT using the ISO/IEC 25010 standard with multi-tool approach, offering a replicable framework for system evaluation across higher education institutions. A quantitative descriptive method was applied, combining expert judgment for Functional Suitability, GTMetrix for Performance Efficiency, PowerMapper for Compatibility, SUS for Usability (30 respondents), WAPT for Reliability, Acunetix for Security, Land’s instrument for Maintainability, and cross-device/browser testing for Portability. The results show high scores in Functional Suitability (97.3%), Performance Efficiency (95.4%), Reliability (99.6%), and Portability (100%). Usability scored 68 (marginally acceptable), while Security revealed severe vulnerabilities, and Maintainability was hindered by interface inconsistencies and lack of formal testing. This research not only to evaluating SIAT but also to introducing a replicable multi-tool evaluation framework based on ISO/IEC 25010, which can inform improvements in similar systems at other universities.Sistem Informasi Akademik Terpadu (SIAT) di Universitas Negeri Gorontalo telah digunakan untuk mendukung aktivitas akademik, namun masih menghadapi masalah seperti kinerja yang lambat pada beban tinggi, kerentanan keamanan, dan inkonsistensi antarmuka. Penelitian sebelumnya umumnya hanya menilai sebagian aspek kualitas atau menggunakan satu alat uji, sehingga menimbulkan kesenjangan penelitian dalam penyediaan evaluasi kualitas yang menyeluruh. Penelitian ini bertujuan mengevaluasi SIAT berdasarkan standar ISO/IEC 25010 dengan pendekatan multi-tool, serta menawarkan kerangka evaluasi yang dapat direplikasi untuk sistem serupa di perguruan tinggi lain. Metode yang digunakan adalah kuantitatif deskriptif dengan kombinasi berbagai instrumen: penilaian ahli untuk Functional Suitability, GTMetrix untuk Performance Efficiency, PowerMapper untuk Compatibility, SUS untuk Usability (30 responden), WAPT untuk Reliability, Acunetix untuk Security, instrumen Land untuk Maintainability, serta pengujian lintas perangkat/browser untuk Portability. Hasil penelitian menunjukkan SIAT unggul pada Functional Suitability (97,3%), Performance Efficiency (95,4%), Reliability (99,6%), dan Portability (100%). Usability memperoleh skor 68 (cukup), sementara Security menunjukkan kerentanan tinggi, dan Maintainability masih terbatas karena inkonsistensi tampilan serta belum adanya pengujian formal. Penelitian ini tidak hanya dalam evaluasi SIAT, tetapi juga melalui pengusulan kerangka evaluasi multi-tool berbasis ISO/IEC 25010 yang dapat direplikasi dan bermanfaat untuk peningkatan sistem informasi akademik di universitas lain.
Integrasi IoT dan Sistem Informasi Produksi Berbasis Web Service dengan Load Cell untuk Otomatisasi Industri Kecil Safitri, Ramona Dyah; Alek, Alek; Rino, Rino
Jambura Journal of Informatics VOL 7, N0 2: OKTOBER 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jji.v1i2.34265

Abstract

Manual recording of production results in small and medium-sized industries (SMIs) often leads to errors and delays in reporting. This study proposes a solution in the form of an automated production information system based on a web platform, integrated with Load Cell sensors and the NodeMCU ESP8266 microcontroller, utilizing the Internet of Things (IoT). The developed system aims to improve efficiency and accuracy in the production data recording process by automating the measurement of weight and quantity of items in real-time. The methodology includes the design of the IoT system architecture, integration of the Load Cell sensor with NodeMCU ESP8266, development of a web service based on PHP/MySQL, and data validation through calibration and system testing. The testing results show that the system successfully records the weight and quantity of items automatically. In this research, the weight of the items is 5 grams and then stores data on the web server, and displays reports in real-time. The system is also effective in reducing human error and enhancing production efficiency. Further testing indicates that the sensor integration and web interface operate stably, with measurement accuracy reaching 99.5%, an error rate of 0.5%, and a response time of 0.2 seconds. Therefore, this system is suitable for implementation in small to medium-sized industries as a solution for more efficient and accurate production automation.Pencatatan hasil produksi secara manual di industri kecil dan menengah (IKM) sering kali menyebabkan kesalahan dan keterlambatan dalam pelaporan. Penelitian ini mengusulkan solusi berupa sistem informasi produksi otomatis berbasis web yang terintegrasi dengan sensor Load Cell dan mikrokontroler NodeMCU ESP8266, berbasis Internet of Things (IoT). Sistem yang dikembangkan bertujuan untuk meningkatkan efisiensi dan akurasi dalam proses pencatatan data produksi dengan mengotomatisasi pengukuran berat dan jumlah barang secara real-time. Metode yang digunakan mencakup perancangan arsitektur sistem IoT, integrasi sensor dengan NodeMCU ESP8266, pengembangan web service berbasis PHP/MySQL, serta validasi data melalui kalibrasi dan pengujian sistem. Hasil pengujian menunjukkan bahwa sistem mampu mencatat berat dan jumlah barang secara otomatis, pada penelitian ini berat barang dibatasi hanya 5 gram yang kemudian menyimpan data ke server web, serta menampilkan laporan secara real-time. Sistem ini juga terbukti efektif dalam mengurangi human error dan meningkatkan efisiensi proses produksi. Pengujian lebih lanjut mengindikasikan integrasi sensor dan antarmuka web berjalan stabil, dengan tingkat akurasi pengukuran mencapai 99,5%, error rate 0,5%, dan waktu respons 0,2 detik. Dengan demikian, sistem ini dapat diimplementasikan pada skala industri kecil hingga menengah sebagai solusi untuk otomatisasi produksi yang lebih efisien dan akurat.
Pengembangan Sistem Informasi Geografis Berbasis Web untuk Pendataan Kelompok Rentan dan Koordinasi Relawan Pakaya, Nikmasari; Syafiullah, Zaiem Athif; Tuloli, Mohamad Syafri; Takdir, Rahman; Ahaliki, Budiyanto; Dwinanto, Arif
Jambura Journal of Informatics VOL 7, N0 2: OKTOBER 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jji.v1i2.32455

Abstract

The manual process of collecting and distributing aid for persons with disabilities at Yayasan Putra Mandiri Gorontalo had faced challenges, including inefficiency, data inaccuracy, and weak coordination. These problems had impacted the accuracy and effectiveness of aid distribution. This study had offered a solution through a centralized web-based Geographic Information System (GIS) that integrated data, volunteer management, and location mapping. The contribution of this study was a system design that improved data accuracy and aid distribution effectiveness. The research used the Waterfall model, consisting of requirement analysis, system design with UML, implementation using PHP and MySQL, and black-box and white-box testing. The results showed that the system successfully performed CRUD operations, displayed interactive maps, and facilitated structured coordination. White-box testing indicated that the program logic complied with cyclomatic complexity. This system had supported better data quality and operational efficiency. The study concluded that the developed system was effective for managing aid distribution and could be further enhanced with automatic notification features
Analisis Sentimen terhadap Pemerintahan Prabowo–Gibran menggunakan IndoBERT dan LDA Ishak, Sahrial Ihsani; Arnilia, Okma; Widodo, Tri; Tatwa, I Gusti Nyoman Agung Bisma
Jambura Journal of Informatics VOL 7, N0 2: OKTOBER 2025
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jji.v1i2.34895

Abstract

This study analyzes public perception of the Prabowo–Gibran administration through online news coverage using a Natural Language Processing (NLP) approach. Data were collected from credible news portals such as Indonesia News and Detik, totaling 195 articles. The analysis was conducted in two stages: first, IndoBERT was used to classify the sentiment into positive, negative, and neutral; second, Latent Dirichlet Allocation (LDA) was applied to identify the main topics driving rage. Sentiment results showed that most topics, particularly those related to the economy, public policy, and governance, were dominated by negative sentiment (80%), while positive sentiment accounted for 15.9% and neutral sentiment for 4.1%. These findings indicate public criticism and concern regarding the effectiveness of policies and economic stability. The combined IndoBERT and LDA approach proved effective in providing a comprehensive understanding of public opinion dynamics in the digital era. It can serve as a consideration for the government in formulating more responsive and transparent communication strategies.Penelitian ini menganalisis persepsi publik terhadap kepemimpinan Prabowo–Gibran melalui pemberitaan media online menggunakan pendekatan Natural Language Processing (NLP). Data dikumpulkan dari portal berita kredibel seperti Antara News dan Detik dengan total 195 artikel. Analisis dilakukan dalam dua tahap: pertama, IndoBERT digunakan untuk mengklasifikasikan sentimen berita menjadi positif, negatif, dan netral; kedua, Latent Dirichlet Allocation (LDA) diterapkan untuk mengidentifikasi topik utama yang mendominasi pemberitaan. Hasil sentimen menunjukkan bahwa sebagian besar topik, terutama terkait ekonomi, kebijakan publik, dan pemerintahan, didominasi oleh sentimen negatif (80%), sedangkan sentimen positif tercatat 15,9% dan netral 4,1%. Temuan ini mengindikasikan adanya kritik dan keprihatinan publik terhadap efektivitas kebijakan dan stabilitas ekonomi. Hasil menunjukkan bahwa sebagian besar topik, terutama terkait ekonomi, kebijakan publik, dan pemerintahan, didominasi oleh sentimen negatif. Temuan ini mengindikasikan adanya kritik dan keprihatinan publik terhadap efektivitas kebijakan dan stabilitas ekonomi. Pendekatan kombinatif IndoBERT dan LDA terbukti efektif dalam memberikan pemahaman komprehensif mengenai dinamika opini publik di era digital, serta dapat menjadi bahan pertimbangan bagi pemerintah dalam merumuskan strategi komunikasi yang lebih responsif dan transparan.
Perbandingan SVM dan CNN MobileNetV2 untuk Klasifikasi Residu Insektisida pada Citra Buah Kakao Rahmawati, Rahmawati; Arifin, Nurhikma; Firgiawan, Wawan
Jambura Journal of Informatics VOL 8, N0 1: APRIL 2026
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jji.v8i1.37972

Abstract

The decline in cocoa production in West Sulawesi due to pest attacks and the use of insecticides that leave residues on the fruit surface has reduced visual quality and highlights the need for efficient automatic classification based on digital image processing. This study aims to classify cocoa fruit images into three classes (Normal, Insecticide-Treated, and Residue) and to compare the performance of Support Vector Machine (SVM) and Convolutional Neural Network (CNN) with the MobileNetV2 architecture. The dataset consists of 672 images divided into training and testing sets with an 80:20 ratio and evaluated under two training data conditions: imbalanced and balanced through rotation-based augmentation at an image size of 224×224 pixels. For SVM, color and texture features are extracted using Hue Saturation Value (HSV) and Local Binary Pattern (LBP), while the CNN model adopts MobileNetV2 with transfer learning and an adjusted fully connected layer. The results show that SVM with combined HSV and LBP features achieves an accuracy of 86.67%, whereas CNN attains 82.22% on data without augmentation and improves to 87.41% on augmented data. The McNemar test on the same test set yields p-values of 0.6171 and 1.0000 for the imbalanced and balanced training data conditions, indicating that the performance difference between the two methods is not statistically significant and that both models provide comparable classification capability.Penurunan produksi kakao di Sulawesi Barat akibat serangan hama dan penggunaan insektisida yang meninggalkan residu pada permukaan buah menurunkan kualitas visual dan menunjukkan perlunya metode klasifikasi otomatis berbasis pengolahan citra digital yang efisien. Penelitian ini bertujuan mengklasifikasikan citra buah kakao ke dalam tiga kelas (Normal, Berinsektisida, dan Residu) serta membandingkan kinerja Support Vector Machine (SVM) dan Convolutional Neural Network (CNN) dengan arsitektur MobileNetV2. Dataset terdiri atas 672 citra yang dibagi menjadi data latih dan data uji dengan rasio 80:20 dan dievaluasi pada dua kondisi data latih, yaitu tidak seimbang dan seimbang melalui augmentasi rotasi dengan ukuran citra 224×224 piksel. Pada SVM, fitur warna dan tekstur diekstraksi menggunakan Hue Saturation Value (HSV) dan Local Binary Pattern (LBP), sedangkan CNN menggunakan MobileNetV2 dengan pendekatan transfer learning dan penyesuaian fully connected layer. Hasil pengujian menunjukkan bahwa SVM dengan kombinasi fitur HSV dan LBP mencapai akurasi 86,67%, sedangkan CNN memperoleh akurasi 82,22% pada data tanpa augmentasi dan meningkat menjadi 87,41% pada data setelah augmentasi. Uji McNemar pada data uji yang sama menghasilkan nilai p-value 0,6171 dan 1,0000 untuk kondisi data latih tidak seimbang dan seimbang, yang menunjukkan bahwa perbedaan performa kedua metode tidak signifikan secara statistik sehingga keduanya memiliki kemampuan klasifikasi yang relatif sebanding.
Identification of Factors and Models of Knowledge Management Maturity: A Systematic Literature Review Abilowo, Krisanto; Sensuse, Dana Indra
Jambura Journal of Informatics VOL 8, N0 1: APRIL 2026
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jji.v8i1.37862

Abstract

Studies related to the knowledge management maturity (KMM) model in libraries have been successfully identified. However, the model is at risk of bias because, in these studies, the KMM assessment within the organization is based on the total score across all criteria/components/factors. This poses a risk of bias if one of the criteria required at the initial maturity level is not met. Therefore, this study aims to identify KMM factors and models from various sectors to support research on developing a KMM model in the library sector. In identifying KMM factors and models, the researchers will conduct a Systematic Literature Review (SLR). The method used in this SLR is the Kitchenham method. Of the 103 KMM factors, the most widely used in previous studies were in the process category, including organizational culture. Based on the factors that make up the KMM model, it can be seen that, among the 17 KMMs, those used in previous studies had the greatest advantages in the process category, such as the army KM3. In addition, based on the objectives of the KMM model, one model that assesses the maturity level of Knowledge Management (KM) implementation and serves as a guideline for KM implementation is the General KM Maturity Model (GKMMM). Based on the issues and results of the SLR conducted, the researchers plan to develop a knowledge management maturity model for the library sector in the next study.
Integrasi Best Worst Method dan MOORA dalam Sistem Pendukung Keputusan Orientasi Karir Siswa SMK Suma, Nur Alim M.; Hadjaratie, Lillyan; Pakaya, Nikmasari; Padiku, Indhitya R.
Jambura Journal of Informatics VOL 8, N0 1: APRIL 2026
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jji.v8i1.38415

Abstract

The career orientation process in vocational high schools was frequently constrained by student confusion and teacher subjectivity due to the absence of analytical guidelines. This study developed a decision support system to provide objective career recommendations. The main contribution of this research was the provision of an early-stage analytical guideline based on mathematical computation for students. The system development utilized the Waterfall method. For computation, the Best Worst Method (BWM) was used to calculate criteria weights based on expert preferences, which was combined with Multi-Objective Optimization on the basis of Ratio Analysis (MOORA) to rank alternatives. The computation results of the BWM vector successfully achieved a consistency ratio of 0.0468. The confusion matrix testing on 30 samples indicated an accuracy rate of 86.67% and the System Usability Scale (SUS) evaluation obtained a score of 72.2 (Acceptable). However, this study is limited by the small sample size and implementation scope within a single school. These findings indicate that the integration of BWM and MOORA can be used as an initial analytical guideline to support career guidance services in vocational high schools. Proses penentuan orientasi karir di SMK sering terkendala kebingungan siswa dan subjektivitas guru akibat ketiadaan pedoman analitis. Penelitian ini mengembangkan sistem pendukung keputusan untuk memberikan rekomendasi karir secara objektif. Kontribusi utama penelitian ini adalah penyediaan pedoman analitis awal berbasis komputasi matematis bagi siswa. Pengembangan sistem menggunakan metode Waterfall. Untuk komputasi, metode Best Worst Method (BWM) digunakan untuk menghitung bobot kriteria berdasarkan preferensi pakar, yang dipadukan dengan Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA) untuk merangking alternatif. Hasil komputasi vektor BWM sukses mencapai rasio konsistensi 0,0468. Pengujian confusion matrix pada 30 sampel menunjukkan tingkat akurasi 86,67% dan evaluasi System Usability Scale (SUS) memperoleh skor 72,2 (Acceptable). Meskipun demikian, penelitian ini memiliki keterbatasan pada ukuran sampel yang kecil dan cakupan implementasi yang masih terbatas di satu sekolah. Temuan ini menunjukkan bahwa integrasi BWM dan MOORA dapat digunakan sebagai pedoman analitis awal dalam mendukung layanan bimbingan karir di SMK.

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