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All Journal Gaung Informatika Jurnal Edukasi dan Penelitian Informatika (JEPIN) Jurnal Varidika CESS (Journal of Computer Engineering, System and Science) JOIV : International Journal on Informatics Visualization JITK (Jurnal Ilmu Pengetahuan dan Komputer) Jurdimas (Jurnal Pengabdian Kepada Masyarakat) Royal Jurnal Pelayanan dan Pengabdian Masyarakat (Pamas) Abdihaz: Jurnal Ilmiah Pengabdian pada Masyarakat Jurnal Tekinkom (Teknik Informasi dan Komputer) Indonesian Journal of Data and Science TEPIAN Dewantara Journal of Technology Jurnal Pengabdian Teknologi Tepat Guna Amarasi : Jurnal Desain Komunikasi Visual prosiding seminar nasional JOMLAI: Journal of Machine Learning and Artificial Intelligence Engineering and Technology International Journal (EATIJ) Journal of Economics, Entrepreneurship, Management Business and Accounting Journal Of Informatics And Busisnes Jurnal Pengabdian Masyarakat Indonesia Sejahtera Scientica: Jurnal Ilmiah Sains dan Teknologi Jurnal Pengabdian Masyarakat dan Riset Pendidikan Journal of Innovative and Creativity ADIMA Journal of Information System and Application Development Router : Jurnal Teknik Informatika dan Terapan Journal of Engineering and Science Application Research of Scientia Naturalis Router : Jurnal Teknik Informatika dan Terapan Jimstek
Dahlan Susilo
Universitas Sahid Surakarta
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Perbandingan Kinerja Klasifikasi Sentimen Ulasan Aplikasi Over the Top di Google Play Store Tutus Pandam Pradipta; Sri Huning Anwariningsih; Dahlan Susilo
CESS (Journal of Computer Engineering, System and Science) Vol. 11 No. 1 (2026): Januari 2026
Publisher : Universitas Negeri Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24114/cess.v11i1.70832

Abstract

Persaingan ketat layanan Over The Top (OTT) di Indonesia menuntut pemahaman terkait kepuasan pengguna sebagai kunci retensi pelanggan. Ulasan Google Play Store menjadi sumber data penting untuk klasifikasi sentimen. Meskipun metode SVM dan Naive Bayes populer untuk klasifikasi, tetapi perbandingan keduanya untuk klasifikasi sentimen layanan OTT masih terbatas. Penelitian ini membandingkan kinerja keduanya untuk klasifikasi ulasan Aplikasi OTT berbahasa Indonesia. Selain itu, dilakukan validasi eksternal terhadap rating Aplikasi untuk mengidentifikasi metode dan rasio data optimal, serta menganalisis korelasi antara kinerja sentimen positif dengan rating tersebut. Tahapan perbandingan dilakukan melalui metode KDD meliputi pengumpulan data, text preprocessing, transformasi data, hingga klasifikasi dengan pengujian pembagian data training dan testing (70:30, 80:20, dan 90:10) untuk mendapatkan model yang optimal. Klasifikasi diuji menggunakan berbagai matrik evaluasi yaitu Akurasi, Presisi, Recall, dan F1-Score. Model optimal kemudian divalidasi menggunakan koefisien korelasi Pearson antara F1-Score sentimen positif dan rating Aplikasi. Hasil kesimpulan dari perbandingan kedua metode menunjukkan bahwa SVM secara konsisten mengungguli Naive Bayes di seluruh skenario pengujian. Model SVM dengan rasio 90:10 adalah model optimal dengan akurasi rata-rata 75%. Model ini kuat pada sentimen negatif (F1-Score=0,91) namun menunjukkan kegagalan kritis pada sentimen netral (F1-Score=0,00). Analisis korelasi Pearson menghasilkan nilai r = 0,538, mengindikasikan adanya korelasi positif sedang antara sentimen positif dengan popularitas aplikasi. Implikasi penelitian ini adalah model optimal ini dapat digunakan sebagai alat Business Intelligence meskipun perlu pengembangan lanjutan untuk mengatasi imbalance data pada kelas netral.
Analisis Sentimen Ulasan Pengguna Aplikasi Kredivo menggunakan Algoritma Naive Bayes dan Logistic Regression Diki Dwi Anggara; Farid Fitriyadi; Dahlan Susilo
Dewantara Journal of Technology Vol. 7 No. 1 (2026)
Publisher : Akademi Teknologi Industri Dewantara Palopo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59563/djtech.v7i1.386

Abstract

Perkembangan pesat industri Financial Technology (Fintech) Buy Now Pay Later (BNPL) di Indonesia mendorong tingginya akumulasi ulasan pengguna pada aplikasi Kredivo di Google Play Store. Ulasan tersebut memuat data opini yang sangat berharga terkait tingkat kepuasan, keandalan sistem, maupun keluhan layanan, namun volumenya yang besar menyulitkan evaluasi secara manual. Penelitian ini bertujuan untuk mengidentifikasi sentimen publik serta membandingkan performa algoritma Multinomial Naive Bayes dan Logistic Regression dalam mengklasifikasikan sentimen ulasan pengguna Kredivo. Dataset sebanyak 17.212 ulasan terfilter periode Januari 2021 hingga Januari 2026 diproses melalui tahapan preprocessing (cleansing, case folding, tokenizing, normalisasi kata Indo-Normalizer, stopword removal, dan stemming sastrawi) hingga menghasilkan 10.798 data ulasan bersih. Pelabelan otomatis berbasis rating dengan verifikasi manual pada rating 3 menghasilkan distribusi sentimen yang tidak seimbang, yaitu 80,55% positif dan 19,45% negatif. Pembobotan kata menggunakan Term Frequency-Inverse Document Frequency (TF-IDF) menghasilkan 4.558 fitur kata. Untuk mengatasi ketidakseimbangan kelas tanpa memicu data leakage, teknik Synthetic Minority Oversampling Technique (SMOTE) diterapkan secara terisolasi pada data latih di setiap fold menggunakan 5-Fold Cross Validation. Hasil eksperimen menunjukkan Logistic Regression unggul secara konsisten dibanding Naive Bayes dengan menggapai rata-rata akurasi sebesar 90,14%; precision 91,43%; recall 90,14%; dan F1-score 90,52% pada 5-Fold Cross Validation. Pada pengujian akhir menggunakan 20% data uji murni (2.160 ulasan), Logistic Regression kembali membuktikan daya generalisasi terbaik tanpa overfitting dengan akurasi 90,42% dan F1-score 90,74%. Analisis Word Cloud mengungkapkan bahwa kepuasan pengguna didominasi oleh efisiensi pencairan dana dan kemudahan aplikasi, sedangkan keluhan terfokus pada penolakan limit transaksi mendadak serta mekanisme penagihan.
Perancangan Website Manajemen Stok di Toko Istana Murah Ocky Rafni Juliansyah; Dahlan Susilo; Firdhaus Hari Saputro Al Haris
Router : Jurnal Teknik Informatika dan Terapan Vol. 4 No. 3 (2026): September : Router : Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Profesi Telekomunikasi dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v4i3.1023

Abstract

Inventory management is a critical operational aspect for small retail businesses, yet many of them still rely on manual bookkeeping that is prone to recording errors and slow report preparation. This study aims to design and build a web-based stock management system for Istana Murah Store, a clothing retailer located in Beru Village, Jereweh District, West Sumbawa Regency, which still records its inventory in a paper stock book. The research applied the prototype development method, with data collected through observation, an interview with the store owner, and a literature review. The system was modelled using the Unified Modeling Language, covering use case, activity, sequence, class, component, and deployment diagrams, and was implemented using the PHP programming language with a MySQL database. System validation employed black box testing on the login, registration, and administrator modules, followed by a Mean Opinion Score evaluation involving twenty respondents. Black box testing confirmed that all tested functions behaved as designed, while the Mean Opinion Score reached 4.70 on a five-point scale, which falls into the excellent category. The findings indicate that the developed system accelerates the recording of incoming and outgoing goods, reduces recording errors, and provides accurate, real time stock information to support managerial decisions.
Perancangan Website Manajemen Stok di Toko Istana Murah Ocky Rafni Juliansyah; Dahlan Susilo; Firdhaus Hari Saputro Al Haris
Router : Jurnal Teknik Informatika dan Terapan Vol. 4 No. 3 (2026): September : Router : Jurnal Teknik Informatika dan Terapan
Publisher : Asosiasi Profesi Telekomunikasi dan Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62951/router.v4i3.1023

Abstract

Inventory management is a critical operational aspect for small retail businesses, yet many of them still rely on manual bookkeeping that is prone to recording errors and slow report preparation. This study aims to design and build a web-based stock management system for Istana Murah Store, a clothing retailer located in Beru Village, Jereweh District, West Sumbawa Regency, which still records its inventory in a paper stock book. The research applied the prototype development method, with data collected through observation, an interview with the store owner, and a literature review. The system was modelled using the Unified Modeling Language, covering use case, activity, sequence, class, component, and deployment diagrams, and was implemented using the PHP programming language with a MySQL database. System validation employed black box testing on the login, registration, and administrator modules, followed by a Mean Opinion Score evaluation involving twenty respondents. Black box testing confirmed that all tested functions behaved as designed, while the Mean Opinion Score reached 4.70 on a five-point scale, which falls into the excellent category. The findings indicate that the developed system accelerates the recording of incoming and outgoing goods, reduces recording errors, and provides accurate, real time stock information to support managerial decisions.
Peningkatan Kualitas Akses Infrastruktur WiFi Sekolah untuk Mendukung Kelas Berbasis E-Learning di SMK Sahid Surakarta Dahlan Susilo; Diyah Ruswanti; Astri Charolina; Herlina Dwi Anggraheni; Faritza Putri Ayuk Natasya; Agus Kristianto
Jurnal Pengabdian Masyarakat Indonesia Sejahtera Vol. 5 No. 3 (2026): September: Jurnal Pengabdian Masyarakat Indonesia Sejahtera
Publisher : STAI YPIQ BAUBAU, SULAWESI TENGGARA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59059/jpmis.v5i3.3432

Abstract

The development of information technology has increased the importance of internet networks in supporting learning and administrative activities in schools. SMK Sahid Surakarta has provided WiFi facilities on each building floor; however, initial observations identified several issues, including uneven signal quality, weak signal areas, and the absence of documented network evaluation. This community service activity aims to analyze the WiFi network conditions at SMK Sahid Surakarta and provide recommendations for optimization. The activities involved observation, access point mapping, signal strength measurement using the NetSpot application, and documentation of measurement results. The results showed that SMK Sahid Surakarta has 11 access points distributed across four floors, consisting of three access points on the first floor, three on the second floor, two on the third floor, and three on the fourth floor. Signal strength measurements indicated several areas with reduced quality due to access point distance, building obstacles, and uneven signal distribution. Optimization recommendations include improving access point placement, expanding coverage, and adding access points in areas with inadequate signal quality. These results are expected to support improvements in WiFi services for more effective learning, administrative, and technology-based activities.
Pengembangan Sistem Informasi Kasir SPP Menggunakan Metodologi Agile Scrum Di Sekolah Menengah Kejuruan Dahlan Susilo; Astri Charolina; Diyah Ruswanti; Agus Kristianto; Daniel Christian Santosa; Alfiansyah Mahendra Pradapa; Raffael Agung Christriano Putro; Kurnia Galih Mahendra
Journal Of Informatics And Busisnes Vol. 4 No. 3 (2026): Oktober - Desember
Publisher : CV. ITTC INDONESIA

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47233/jibs.v4i3.5249

Abstract

The management of the administration of the payment of Education Development Contributions (SPP) at SMK Sahid Surakarta is still carried out manually using the Microsoft Excel application, so that various obstacles are still encountered such as the risk of human error, loss of data, and difficulties in recapitulating tuition arrears per student. These problems encourage the need for an information system that is able to manage student tuition payment data centrally, efficiently, and transparently. This research aims to build an SPP Cashier System that integrates tuition fee payment history, tuition arrears, and tuition fee reports in an integrated manner. This research uses survey and documentation methods for data collection and system development methods are carried out using Agile Scum which is divided into five 5 iterative stages (Sprint), including Foundation & Authentication, Data Management & Tuition Bills, Payment & Receipt Transactions, Reports & Exports, to Testing & Finalization, with a total allocation of 62 Story Points. The SPP Cashier Information System provides an information dashboard in the form of real-time payment recapitulation and implements a transaction module that makes it easier for cashiers to record payments and identify student arrears in the current month. The results of the study show that the SPP Cashier Information System was successfully designed and implemented as a web-based school financial administration digitization solution that runs in an XAMPP/LAN environment with a centralized MySQL database, and is able to replace the manual recording process at SMK Sahid Surakarta. The resulting system can include all core modules, namely Dashboard, Student Data, Tariff & Generate bills, Transactional Cashier Mode, Reports in the form of Excel, and Carry-Over arrears as well as a professional user interface so that it can be operated by administrative staff comfortably.
DEEP LEARNING ALGORITHMS FOR PRECISION AGRICULTURE USING HIGH-RESOLUTION MULTISPECTRAL REMOTE SENSING SATELLITE IMAGERY Han Jiwon; Seo Jiwo; Dahlan Susilo
Research of Scientia Naturalis Vol. 3 No. 5 (2026)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/scientia.v3i5.4483

Abstract

Precision agriculture increasingly depends on reliable interpretation of high-resolution multispectral satellite imagery to monitor crop variability, detect stress, and support site-specific management. This study aimed to evaluate deep-learning architectures for crop-stress classification and determine whether spectral-spatial integration improves predictive robustness and agronomic interpretability. A quantitative experimental design compared a conventional convolutional neural network, ResNet, Vision Transformer, and hybrid CNN-Transformer using parcel-level training, validation, internal testing, and external spatial-temporal holdout data. Spectral ablation and explainable artificial intelligence analyses were also conducted to assess band importance and model attention. The hybrid CNN-Transformer achieved the highest internal accuracy, macro F1-score, and AUC, while maintaining the strongest performance under external domain shift. Near-infrared and red-edge bands contributed most substantially to classification, particularly for distinguishing intermediate crop-stress conditions. Explainability analysis showed that the best-performing model focused predominantly on canopy regions and vegetation-sensitive spectral information rather than irrelevant background features. The study concludes that reliable precision-agriculture intelligence requires more than high internal accuracy. Integrating local spatial features, broader contextual relationships, multispectral information, external validation, and interpretable model behavior provides a stronger foundation for transferable satellite-based crop monitoring and decision support across heterogeneous agricultural environments. This framework can improve timely intervention, resource allocation, and field-level management decisions.
Co-Authors ., palgunadi A.A. Ketut Agung Cahyawan W Abdush Shomad, Abdush Achmad Syah, Elvandec Rizky Aditya Dwi Jatmiko, Aditya Dwi Agung Nurmansyah Agus Kristianto Agus Kristianto Agus Purwo Handoko Akhmad Syukron Alfiansyah Mahendra Pradapa Amri Eka Widayanto Angga Kusuma Dawami Angky Sudarmono, Angky Anwariningsih , Sri Huning Ari Wibowo Ari Wibowo Arif Yulianto Arif Yuliyanto Ariwibowo, Heru Ashsidiq, Muhammad Fadhlan Ravi Astri Charolina Astri Charolina Bayu Tri Haryanto Budi Prabowo Cristya, Arkha Daniel Christian Santosa Destina Paningrum Diki Dwi Anggara Diyah Ruswanti Dwi Retnoningsih Erwin Kartinawati Faritza Putri Ayuk Natasya Firdhaus Hari Saputro Al Haris Fiska Kusuwawati Fitriani, Nisa Fitriyadi, Farid Fitriyadi, Farid Hadi Pratikno Han Jiwon Harry Abri Anto Henny Tri Hastuti Hasana Heri Kusharyanto Heribertus Ary Setyadi Herlina Dwi Anggraheni Indah Puspita Mutiara Indriastiningsih, Erna Iqbal Aditya Ferryanto Joko Cahyono Keristiawan, Subakti Khoirul Huda Khusnuliawati, Hardika Kristiawan, Ade Kuncoro, Isnu Kurnia Galih Mahendra Kusuwawati, Fiska Lina Sulistyani Mochtar Yunianto Muhammad Arya Priasatama Putra Muhammad Dwi Nugroho Muhammad Dwi Nugroho Muhammad NR Hidayatullah Murni Murni Mutiara, Indah Puspita nisa fitriani Norman Duma Sitinjak Nugroho, Moh Andi Setyo Nurul Pradana Ratmawati Ocky Rafni Juliansyah Omega, Yuseva Kristine Palgunadi . Permana, Tatok Andri Pranowo Setiaji Pratikno, Hadi Prawesti, Nindia Fika Rizky Purnama, Christian Roy Putra, Adi Wijaya Putra, Muhammad Arya Priasatama Raffael Agung Christriano Putro Ratmawati, Nurul Pradana Retnoningsih , Dwi Riskyanto Pangemanan Role, Vinsensius Sony rudi pranoto, rudi Rusnandari Retno Cahyani Ruswanti, Diyah Salsabila, Afrida Nur Salsabila, Unik Hanifah Seo Jiwo Setiawan, Gigih Setiawan, Sukawati Novy Siti Zubaidah Sri Ernawati Sri Huning Anwariningsih Sukawati Novy Setiawan Sulistyani, Lina Supriyanta Supriyanta Supriyanta Supriyanta Tutus Pandam Pradipta Vinsensius Sony Role Wahyudi . Wahyuningsih, Dwi Prastiwi Wawan Nugroho Widayanto, Amri Eka Yunitasari, Veronica Sri Yusuf Sutanto