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All Journal IJCCS (Indonesian Journal of Computing and Cybernetics Systems) Jurnal Teknologi Informasi dan Ilmu Komputer Syntax Literate: Jurnal Ilmiah Indonesia PROCESSOR Jurnal Ilmiah Sistem Informasi, Teknologi Informasi dan Sistem Komputer Jurnal Ilmiah Media Sisfo Jurnal Nasional Komputasi dan Teknologi Informasi GERVASI: Jurnal Pengabdian kepada Masyarakat Psikostudia : Jurnal Psikologi JSR : Jaringan Sistem Informasi Robotik INFORMASI (Jurnal Informatika dan Sistem Informasi) JOURNAL OF INFORMATION SYSTEM MANAGEMENT (JOISM) Diseminasi : Jurnal Pengabdian kepada Masyarakat TIN: TERAPAN INFORMATIKA NUSANTARA Cakrawala Repositori Imwi Jurnal Pengabdian kepada Masyarakat Nusantara Brilliance: Research of Artificial Intelligence Jurnal Teknologi Sistem Informasi Jurnal Nasional Teknik Elektro dan Teknologi Informasi Jurnal Pemberdayaan: Publikasi Hasil Pengabdian kepada Masyarakat (JPM ITTC ) Jurnal Pengabdian Kolaborasi dan Inovasi IPTEKS International Journal of Electrical Engineering, Mathematics and Computer Science Akademika Jurnal TAM (Technology Acceptance Model)
Abidin, Zainil
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Penerapan K-Means Clustering untuk Pengelompokan Data Industri Kecil Menengah di Provinsi Jambi Ariansah, Bimo; Khaira, Ulfa; Abidin, Zainil
Jurnal Teknologi Sistem Informasi Vol 6 No 2 (2025): Jurnal Teknologi Sistem Informasi
Publisher : Program Studi Sistem Informasi, Universitas Multi Data Palembang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35957/jtsi.v6i2.13553

Abstract

Industri Kecil dan Menengah (IKM) memiliki peran penting dalam perekonomian daerah, namun di Provinsi Jambi masih terdapat ketimpangan antarwilayah. Penelitian ini menerapkan algoritma K-Means Clustering untuk mengelompokkan data IKM periode 2021–2023 berdasarkan nilai investasi, jumlah produksi, dan nilai produksi. Data diproses melalui pembersihan, normalisasi, serta deteksi outlier. Evaluasi menggunakan Elbow Method, Silhouette Coefficient, dan Davies-Bouldin Index menunjukkan bahwa dua cluster merupakan hasil optimal dengan Silhouette 0,70 dan DBI 0,47.Hasilnya terbentuk dua kelompok utama. Cluster 1 merepresentasikan IKM Belum Berkembang dengan investasi dan produksi rendah, dominan di Tanjung Jabung Barat, Bungo, dan Kerinci. Cluster 2 menunjukkan IKM Berkembang dengan investasi tinggi serta kontribusi ekonomi signifikan, ditunjukkan oleh Kota Jambi, Sarolangun, dan Merangin. Visualisasi peta interaktif dan barchart memperjelas distribusi spasial dan tren antar tahun.Penelitian ini menegaskan bahwa mayoritas IKM di Jambi masih tergolong belum berkembang. Oleh karena itu, diperlukan intervensi berupa peningkatan akses permodalan, pelatihan, dan penguatan infrastruktur agar sektor IKM dapat tumbuh lebih merata.
Penerapan Random Oversampling dan Principal Component Analysis untuk Meningkatkan Akurasi Prediksi Kebangkrutan Perusahaan di Indonesia dengan Model Machine Learning Abidin, Zainil; Suratno, Tri; Fadhila Putri, Mutia
Jurnal Teknologi Informasi dan Ilmu Komputer Vol 12 No 5: Oktober 2025
Publisher : Fakultas Ilmu Komputer, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25126/jtiik.2025125

Abstract

Prediksi kebangkrutan menjadi penting untuk memberikan peringatan dini bagi manajemen dan pemangku kepentingan agar dapat mengambil tindakan preventif. Penelitian ini menguji penerapan metode Random Oversampling dan Principal Component Analysis (PCA) dalam model machine learning untuk meningkatkan akurasi prediksi kebangkrutan perusahaan. Penelitian ini menggunakan dua dataset yaitu data Taiwanese Bankruptcy Prediction dari UCI Machine Learning Repository sebanyak 6.891 data dan data primer berupa data kebangkrutan perusahaan Indonesia dari Bursa Efek Indonesia (BEI) dari tahun 2021-2023 sebanyak 2.703 data. Total keseluruhan dataset yang digunakan sebanyak 9.594 data. Empat algoritma klasifikasi—KNN, Naïve Bayes, SVM, dan Decision Tree—diuji sebelum dan sesudah penerapan metode tersebut. Hasil menunjukkan bahwa kombinasi PCA dan Random Oversampling meningkatkan recall kelas minoritas (kebangkrutan) secara signifikan. SVM menjadi algoritma terbaik dengan precision 0,86, recall 0,76, dan F1-score 0,80, sementara Decision Tree mengalami overfitting setelah oversampling. PCA berhasil mereduksi dimensi dataset hingga 98,87% varian tetap terjaga, dan Random Oversampling menyeimbangkan distribusi kelas.   Abstract Bankruptcy prediction is crucial for providing early warnings to management and stakeholders to take preventive actions. This study examines the application of Random Oversampling and Principal Component Analysis (PCA) in machine learning models to improve the accuracy of corporate bankruptcy prediction. The study uses two datasets: the Taiwanese Bankruptcy Prediction data from the UCI Machine Learning Repository (6,891 data points) and primary data on Indonesian company bankruptcies from the Indonesia Stock Exchange (IDX) for 2021–2023 (2,703 data points), totaling 9,594 data points. Four classification algorithms—K-Nearest Neighbors (KNN), Naïve Bayes, Support Vector Machine (SVM), and Decision Tree—were tested before and after applying these methods. The results show that the combination of PCA and Random Oversampling significantly improved the recall of the minority class (bankruptcy). SVM emerged as the best-performing algorithm with a precision of 0.86, recall of 0.76, and F1-score of 0.80, while the Decision Tree experienced overfitting after oversampling. PCA successfully reduced the dataset’s dimensions while retaining 98.87% of the variance, and Random Oversampling balanced the class distribution.
Sentiment Analysis of Indonesian National Team in 2024 AFF Using Naive Bayes and KNN Adrian, Rahmad; Aryani, Reni; Abidin, Zainil
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.7111

Abstract

Social media platforms like Twitter (now X) serve as key channels for public opinion on major events, including sports tournaments such as the AFF Cup, where sentiments reflect nationalism, criticism, and support. Prior studies have highlighted varying accuracies in sentiment classification for Indonesian football contexts, prompting comparisons of algorithms like Naive Bayes and K-Nearest Neighbors (KNN). This research aims to analyze public sentiment directions towards the Indonesian National Team during the 2024 AFF Cup and compare the performance of Naive Bayes and KNN algorithms. Data comprised 1,918 tweets collected from December 8, 2024, to January 8, 2025, reduced to 1,598 unique entries after preprocessing (cleaning, case folding, tokenizing, filtering, stemming). Sentiments were labeled as positive, negative, or neutral by linguistic experts. TF-IDF vectorized features, and SMOTE addressed class imbalance. Models were trained on 90:10 data splits and evaluated using accuracy, precision, recall, and F1-score, with visualizations including frequency diagrams and word clouds. Neutral sentiments dominated at 49.6%, followed by negative (27.3%) and positive (23.2%). Naive Bayes with SMOTE achieved 79.38% accuracy, outperforming KNN (50-53%). Word clouds revealed supportive terms in positives ("garuda", "semangat"), critical in negatives ("kalah", "pecat"), and factual in neutrals ("indonesia", "piala"). Naive Bayes proves more effective for this dataset, offering insights for team management. Future work should explore advanced models like SVM or BERT and expand data sources for broader generalization.
UI/UX Design of the Bangkitku Waste Bank Information System in Jambi City Using Design Thinking Sopia Ranty; Reni Aryani; Zainil Abidin; Noneng Marthiawati; Winny Laura
International Journal of Electrical Engineering, Mathematics and Computer Science Vol. 2 No. 1 (2025): March : International Journal of Electrical Engineering, Mathematics and Comput
Publisher : Asosiasi Riset Teknik Elektro dan Infomatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/ijeemcs.v2i1.310

Abstract

Waste management is increasingly critical due to the rising waste generated by community activities driven by a consumptive lifestyle. A key solution to this issue is the implementation of waste bank programs, though community participation and operational efficiency remain challenges, as seen with the Bangkitku Waste Bank in Jambi City. This study focuses on designing the user interface for the Bangkitku Waste Bank Information System using the design thinking method and evaluating the usability of the prototype. The design process followed the five stages of design thinking: empathize, define, ideate, prototype, and test, with data collected through interviews and observations. The analysis involved tools such as empathy maps, user personas, sitemaps, and user flows, with prototypes created using Figma. Usability testing was conducted with 10 participants, including administrators and customers, resulting in high usability scores—98 for administrators and 97 for customers. The majority of participants found the system easy to use, as indicated by responses on the Single Ease Question (SEQ) survey. The prototype met key usability criteria, improving both operational efficiency and community engagement in waste bank management. The findings demonstrate the system's potential to foster sustainable environmental practices and enhance the effectiveness of waste bank management.
Stress Among Psychologist Candidates Rachmawati, Arini; Abidin, Zainil
Psikostudia : Jurnal Psikologi Vol 13, No 3 (2024): Volume 13, Issue 3, September 2024
Publisher : Program Studi Psikologi, Fakultas Ilmu Sosial dan Ilmu Politik, Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30872/psikostudia.v13i3.15290

Abstract

There were five participants in this study. The results indicate that the majority of participants showed negative emotional reactions, such as increased anxiety leading to a desire to avoid academic situations. Physical reactions also emerged, such as fatigue, sleep disturbances, and headaches. Some participants attempted to cope with stress by engaging in enjoyable activities or exercising, but some still struggled to cope with stressful conditions and felt desperate about academic demands. A psychology graduate must complete a professional psychology education program to be considered a psychologist. The existence of several requirements and responsibilities to be fulfilled in pursuing education as a psychologist candidate, along with obligations outside the academic scope, can increase the risk of stress. This research is a descriptive qualitative study aimed at illustrating the stress experienced among psychologist candidates. The participants in this study were five graduate students from various universities enrolled in a Master of Professional Psychology program. The research instrument used in this study was an interview guide based on the Perceived Stress Scale (PSS) questionnaire and the data analysis method applied was thematic analysis. The results showed that overall, the participants perceived the demands they faced as psychologist candidates to be stressful situations. Stress reactions included the emergence of negative emotions such as increased anxiety, as well as physical reactions such as fatigue, sleep disturbances, and headaches. Some participants attempted to cope with stress by engaging in enjoyable activities or exercising. However, some participants still had difficulty managing their stress, leading to feelings of hopelessness regarding academic demands. The findings of this study are expected to serve as a reference in developing intervention programs to address stress, particularly among students in professional psychology programs.Sarjana psikologi harus menyelesaikan program pendidikan profesi psikologi untuk dapat dikatakan sebagai psikolog. Adanya sejumlah persyaratan dan tanggung jawab yang harus dipenuhi dalam mengikuti pendidikan sebagai calon psikolog, bersama dengan kewajiban di luar lingkup akademis, dapat meningkatkan risiko stres. Penelitian ini merupakan penelitian kualitatif deskriptif dengan tujuan untuk menjelaskan gambaran stres pada calon psikolog. Partisipan dalam penelitian ini berjumlah lima orang mahasiswa Magister Psikologi Profesi dari beberapa universitas. Instrumen penelitian yang digunakan dalam penelitian ini adalah panduan wawancara yang disusun berdasarkan pada kuesioner Perceived Stress Scale (PSS) dan metode analisis data yang diterapkan dalam penelitian ini adalah analisis tematik (thematic analysis). Hasil penelitian menunjukan bahwa secara keseluruhan, para partisipan mempersepsikan tuntutan yang mereka hadapi sebagai calon psikolog merupakan situasi yang memicu terjadinya stres. Muncul reaksi stres berupa adanya emosi negatif seperti kecemasan yang meningkat dan juga terdapat reaksi fisik seperti kelelahan, gangguan tidur, serta sakit kepala. Beberapa partisipan mencoba mengatasi stres dengan melakukan kegiatan yang digemari atau dengan berolahraga. Namun, sebagian partisipan masih mengalami kesulitan dalam mengatasi kondisi stres tersebut hingga memunculkan perasaan putus asa terhadap tuntutan akademis. Temuan penelitian ini diharapkan dapat menjadi referensi dalam pengembangan program intervensi untuk mengatasi stres, khususnya di kalangan mahasiswa program pendidikan profesi psikologi.
Analisis Penerapan Metode User-Centered Design pada Augmented Reality (AR) dengan Marker Based Tracking Zainil Abidin; Daniel Arsa; Yolla Noverina
Jurnal PROCESSOR Vol 19 No 1 (2024): Jurnal Processor
Publisher : LPPM Universitas Dinamika Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33998/processor.2024.19.1.1640

Abstract

This research investigates the use of Augmented Reality (AR) technology in the context of higher education faculty promotion. The main focus of this research is to design and test an AR application that uses a marker in the form of a QR-Code placed on the faculty study program brochure. This AR application aims to provide prospective students with an interactive experience in exploring the facilities, study programs and academic potential of the faculty. The location of the research was at the Faculty of Science and Technology, Jambi University. The method for designing faculty promotional tools in the form of AR uses the UCD (User-Centered Design) method. This research includes the design stage, AR application development, as well as functionality testing and application performance evaluation. Performance testing is carried out based on the distance between the user's device and the QR-Code marker. Performance testing aims to understand the extent to which an application can function in various usage situations. The results of this study provide in-depth insight into the potential of AR as a faculty promotion tool, considering the advantages and limitations of marker-based tracking methods. These findings strengthen understanding of how AR technology can add value to prospective student recruitment efforts and guide the development of more effective AR applications in the future
Comparison of SVM and KNN Methods for the Integratin of MyIndiHome into MyTelkomsel Application Siagian, Harul Risina; Setiawan, Dedy; Abidin, Zainil
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.7234

Abstract

This study aims to analyze user sentiment toward the merger of the MyIndiHome application into the MyTelkomsel platform conducted by PT Telkom Indonesia. In the digital era, the integration of these two customer service applications represents a strategic step to create a unified digital ecosystem. However, this merger has also generated diverse user responses, reflected in various reviews on the Google Play Store. To analyze these opinions, 1,556 user reviews were collected using the web scraping technique. The preprocessing stage included cleaning, tokenizing, filtering, normalization, stemming, and the application of the Synthetic Minority Over-Sampling Technique (SMOTE) to address class imbalance. Two machine learning algorithms, Support Vector Machine (SVM) and K-Nearest Neighbor (KNN), were applied to classify sentiments into positive, negative, and neutral categories. The experimental results showed that SVM achieved higher accuracy (86.2% before SMOTE and 84.9% after SMOTE) compared to KNN (83.7% before SMOTE and 67.6% after SMOTE). These results indicate that SVM performs more effectively and consistently in handling high-dimensional text data than KNN. Therefore, SVM is considered a more reliable algorithm for sentiment classification in this context. The findings provide valuable insights for PT Telkom Indonesia in understanding user perceptions, improving service quality, and enhancing user experience following the digital integration of MyIndiHome into MyTelkomsel.
Application of Visual Data Mining for Visualization of UKBI Achievement Data Yolanda, Ketri genes; Utomo, Pradita Eko Prasetyo; Abidin, Zainil
Brilliance: Research of Artificial Intelligence Vol. 5 No. 2 (2025): Brilliance: Research of Artificial Intelligence, Article Research November 2025
Publisher : Yayasan Cita Cendekiawan Al Khwarizmi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47709/brilliance.v5i2.7409

Abstract

The current visualization of Adaptive Indonesian Language Proficiency Test (UKBI Adaptif) results in Jambi Province is suboptimal, often relying on static, basic charts, which hinders transparency and the effective formulation of evidence-based language policies. This research aims to address this critical gap by developing an interactive, data-driven system to analyze the language proficiency profile of UKBI participants in Jambi from 2021 to 2024. The research objective is to accurately map regional competence, identify hidden patterns, and provide actionable intelligence to the Jambi Language Center. The study adopts the Visual Data Mining (VDM) methodology, integrating interactive visualization with the K-Means clustering algorithm. This method allowed for the normalization and grouping of over 10,000 participant data points, with the optimal number of clusters determined by the Silhouette Score. The research results successfully established three distinct proficiency clusters, including a "Listening Struggler Group" dominated by non-education professions, exhibiting significantly low scores in the Listening section. Furthermore, geographical analysis revealed a disparity where Jambi City—the region with the highest participation—maintained an average proficiency at the lower boundary of the Intermediate category, while smaller regions like Muaro Jambi showed higher rates of Superior and Exceptional achievement. The conclusion is that the VDM-based interactive dashboard is a validated and effective tool that successfully provides micro-level insights, supporting the strategic allocation of resources and the design of targeted intervention programs to address specific skill weaknesses, such as listening comprehension.
PERANCANGAN UI/UX SISTEM MANAJEMEN BISNIS PADA UMK PAWON3D MENGGUNAKAN METODE USER CENTERED DESIGN Wafi, Akhdan Al; Firdaus, Muhammad Iqbal; Saputra, Edi; Abidin, Zainil
Journal of Information System Management (JOISM) Vol. 7 No. 2 (2026): Januari (On Progress)
Publisher : Universitas Amikom Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24076/joism.2026v7i2.2461

Abstract

UMKM merupakan pilar penting perekonomian Indonesia dengan kontribusi 61% terhadap PDB dan penyerapan 97% tenaga kerja. Pawon3D, sebagai UMKM khususnya usaha mikro di bidang roti dan kue, telah memanfaatkan media sosial untuk memperluas jangkauan pasar, namun masih menghadapi kendala dalam pengelolaan kasir, produksi, dan inventori yang bergantung pada pencatatan fisik. Kondisi ini menyebabkan ketidakefisienan, kesalahan data, dan pengambilan keputusan yang kurang akurat. Untuk mengatasi permasalahan tersebut, dirancang sistem manajemen bisnis berbasis web yang mengintegrasikan ketiga aspek utama operasional. Metode User Centered Design (UCD) digunakan agar pengembangan sistem berfokus pada kebutuhan pengguna. Evaluasi dilakukan melalui Usability Testing dan System Usability Scale (SUS), yang menunjukkan hasil positif di hampir seluruh bagian, meskipun masih terdapat ruang perbaikan pada modul kasir dan produksi. Secara keseluruhan, rancangan UI/UX yang dihasilkan dinilai layak digunakan dan mampu meningkatkan efisiensi serta kualitas manajemen Pawon3D.
Sistem Informasi Layanan Teknologi Informatika dan Komunikasi Berbasis Web Akbartio, Candra Dwi; Setiawan, Dedy; Abidin, Zainil
INFORMASI (Jurnal Informatika dan Sistem Informasi) Vol 17 No 2 (2025): INFORMASI (Jurnal Informatika dan Sistem Informasi)
Publisher : LPPM STMIK Indonesia Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37424/informasi.v17i2.446

Abstract

Proses pengelolaan layanan teknologi informasi di Dinas Komunikasi dan Informatika (DISKOMINFO) Kota Jambi sebelumnya masih dilakukan secara manual, seperti pencatatan permohonan layanan, pengajuan aplikasi baru, serta proses tindak lanjut melalui komunikasi langsung atau pesan pribadi. Hal ini menyebabkan beberapa kendala, di antaranya keterlambatan penanganan permohonan, data permohonan yang tidak terintegrasi, dan sulitnya melakukan pemantauan status layanan. Penelitian ini bertujuan untuk merancang dan mengembangkan Sistem Informasi Layanan Teknologi Informatika dan Komunikasi berbasis web yang dapat membantu proses pengelolaan layanan teknologi informasi secara lebih efektif, efisien, dan terintegrasi. Metode yang digunakan dalam penelitian ini adalah Rapid Application Development (RAD) yang meliputi tahapan requirements planning, workshop design, dan implementation system. Dalam pengembangannya, sistem ini dibangun menggunakan bahasa pemrograman PHP, basis data MySQL, dan framework Laravel. Sistem SILANTIK menyediakan berbagai fitur utama seperti pengajuan permohonan layanan aplikasi, permintaan jaringan, pengelolaan subdomain, pemantauan status permohonan, serta pengelolaan data oleh admin DISKOMINFO. Hasil pengujian menggunakan metode black box testing menunjukkan bahwa seluruh fungsi sistem berjalan sesuai dengan kebutuhan dan spesifikasi yang telah ditentukan. Implementasi sistem ini mampu meningkatkan efisiensi dalam pengelolaan permohonan layanan teknologi informasi, mempercepat proses verifikasi, dan meminimalkan kesalahan pencatatan data. Kesimpulannya, pengembangan Sistem Informasi Layanan Teknologi Informasi dan Komunikasi (SILANTIK) berbasis web dengan metode RAD berhasil memberikan solusi digital yang efektif bagi DISKOMINFO Kota Jambi dalam mendukung layanan teknologi informasi yang lebih terstruktur dan transparan.
Co-Authors Adrian, Rahmad Akbartio, Candra Dwi Alfajri, Willy Bima Andre Rabiula Apresto, Muhammad Haikal Ariansah, Bimo Arsa, Daniel Aryani, Reni aSaputra, Zaqib Benedika Ferdian Hutabarat Budi Jejen Zaenal Abidin Daniel Arsa Dedy Setiawan Deni Erpian Edi Saputra EDI SAPUTRA Indra Weni Jefri Marzal Khaira, Ulfa Kosasih, Raihan Surya Ramadhan Listiani Safitri, Devi Mh. Khathamy Fhadlullah Haq Syahlevy Mohamad Ilham Muhammad Iqbal Firdaus, Muhammad Iqbal Muhammad Naufal Muhammad Razi A mutia fadhila putri, mutia fadhila Noneng Marthiawati Norman Syarief Noverina, Yolla Novitayanah, Elisa Putri Z., Khairin Nisa Rachmawati, Arini Rahman, Reyvi Rizqa Raaiqa Bintana Saputra, Dandi Juan Saputri, Yosika Dian Siagian, Harul Risina Sopia Ranty susilawati rahman, ledisma Tri Suratno Ulfa Khaira, Ulfa Utomo, Pradita Eko Prasetyo Wafi, Akhdan Al Winny Laura Yolanda, Ketri genes Yolla Noverina Yolla Noverina Yosi Riduas Hais