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All Journal Sistemasi: Jurnal Sistem Informasi Sinkron : Jurnal dan Penelitian Teknik Informatika RABIT: Jurnal Teknologi dan Sistem Informasi Univrab IKRA-ITH Informatika : Jurnal Komputer dan Informatika JURIKOM (Jurnal Riset Komputer) EDUMATIC: Jurnal Pendidikan Informatika Journal of Information Systems and Informatics Journal of Innovation and Future Technology (IFTECH) REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer Jurnal Sistem Komputer dan Informatika (JSON) TIN: TERAPAN INFORMATIKA NUSANTARA Jurnal Teknik Informatika (JUTIF) INSERT: Information System and Emerging Technology Journal JOINTER : Journal of Informatics Engineering Journal La Multiapp Edutik : Jurnal Pendidikan Teknologi Informasi dan Komunikasi Indonesian Journal of Innovation Studies Ismart Edu: Jurnal Pendidikan Teknologi Informasi Jurnal Minfo Polgan (JMP) Jurnal Dinamika Informatika (JDI) Jurnal Locus Penelitian dan Pengabdian Prosiding Seminar Nasional Sisfotek (Sistem Informasi dan Teknologi Informasi) Jurnal Sains Informatika Terapan (JSIT) Journal of Artificial Intelligence and Digital Business Jurnal Ilmiah Teknik Informatika dan Komunikasi Innovative: Journal Of Social Science Research Jurnal Penelitian Teknologi Informasi dan Sains The Indonesian Journal of Computer Science semanTIK INOVTEK Polbeng - Seri Informatika Edutik : Jurnal Pendidikan Teknologi Informasi dan Komunikasi FIMERKOM: Journal of Information Systems and Technology Academia Open
Kristofel Santa
Universitas Negeri Manado
Aerospace Engineering Arts Humanities Automotive Engineering Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Dentistry Earth & Planetary Sciences Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Public Health Social Sciences Veterinary Other

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PENGGUNAAN ASYNCHRONOUS JAVASCRIPT AND XML (AJAX) PADA RANCANG BANGUN SISTEM E-LEARNING PENINGKATAN LITERASI SEJARAH DAN BUDAYA SULAWESI UTARA Stevanus Kembuan; Kristofel Santa
Journal of Innovation And Future Technology Vol. 7 No. 1 (2025): Vol 7 No 1 (Februari 2025): Journal of Innovation and Future Technology (IFTECH
Publisher : LPPM Unbaja

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47080/iftech.v7i1.3651

Abstract

Indonesia ranks low in global literacy, with various surveys indicating a very low level of reading interest. To address this, the Ministry of Education and Culture launched the National Literacy Movement (GLN) in 2016, which includes cultural literacy aimed at preserving culture and promoting tolerance among the Indonesian people. However, the lack of educational materials on cultural literacy could threaten these positive achievements, particularly in North Sulawesi, a region with a high religious harmony index. As time progresses, it is hoped that existing technology can be utilized to provide solutions to human challenges, including improving human resources and promoting cultural and historical development. Therefore, this study aims to design an AJAX-based e-learning sistem focused on the history and culture of North Sulawesi, featuring interactive elements such as learning modules, quizzes, and discussion forums. The sistem will integrate technology with local culture to ensure that younger generations do not lose their national identity and cultural heritage, even in the middle of technological advancements.
Support Vector Machine Algorithm for Classifying Public Satisfaction Index: Algoritma Mesin Vektor Dukungan untuk Klasifikasi Indeks Kepuasan Publik Efraim Ronald Stefanus Moningkey; Della Deviani Harisondak; Kristofel Santa
Academia Open Vol. 10 No. 2 (2025): December
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.10.2025.12697

Abstract

General Background: Evaluating public satisfaction with government services is vital to ensuring transparency and continuous improvement in public administration. Specific Background: At the Investment and One-Stop Integrated Services Office (DPMPTSP) of Minahasa Regency, satisfaction assessment has been limited by manual data processing and a lack of integrated systems, leading to inefficiencies in monitoring and classification. Knowledge Gap: Existing approaches to measuring the Public Satisfaction Index (IKM) have not effectively utilized machine learning to automate classification and provide real-time recommendations. Aims: This study aims to implement the Support Vector Machine (SVM) algorithm to classify public satisfaction levels and support service evaluation at DPMPTSP Minahasa. Results: Using 182 testing datasets, the system successfully categorized satisfaction into four levels—very satisfied, satisfied, less satisfied, and dissatisfied—with the majority of respondents classified as satisfied. The developed web-based system also provided actionable recommendations for each satisfaction level. Novelty: This study presents an integrated and automated framework that applies SVM to the public service domain, enabling efficient, accurate, and real-time evaluation. Implications: The findings demonstrate that machine learning can enhance public service management by facilitating data-driven decision-making and promoting service quality improvements. Highlight : The SVM algorithm effectively classifies public satisfaction levels into four categories. The web-based system improves efficiency and accuracy in service evaluation. Recommendations from the system support continuous service quality improvement. Keywords : Public Satisfaction Index, Support Vector Machine, Classification, Service Quality, DPMPTSP Minahasa
Spatial Clustering Of Tourism Investment Potential In Tomohon City: Klasterisasi Spasial Potensi Investasi Pariwisata Kota Tomohon Efraim R. S. Moningkey; Nelsi Timang; Kristofel Santa
Academia Open Vol. 11 No. 1 (2026): June
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/acopen.11.2026.13038

Abstract

General Background: Tourism represents a strategic driver of regional economic development that requires spatially grounded analytical approaches to support investment planning. Specific Background: Tomohon City, a volcanic tourism area in North Sulawesi, contributes substantially to regional economic output but experiences uneven spatial distribution of tourism investment due to accessibility and infrastructural variation. Knowledge Gap: Tourism investment planning in Tomohon has not previously integrated spatial clustering analysis with interactive geovisualization to classify investment potential systematically. Aims: This study aims to analyze and visualize tourism investment potential in Tomohon City using K-Means spatial clustering integrated into a WebGIS platform. Results: Based on 500 tourism sites and indicators including accessibility, visitor volume, supporting facilities, and estimated return on investment, three clusters were identified: high potential areas covering 28% of the region with ROI of 25–35%, medium potential areas covering 52% with ROI of 15–25%, and low potential areas covering 20% with ROI of 5–15%. Novelty: This research introduces an integrated spatial model combining K-Means clustering and WebGIS visualization for tourism investment assessment in a volcanic urban setting. Implications: The results provide a replicable spatial decision-support framework for tourism investment planning aligned with sustainable development objectives. Highlights • Tourism sites are spatially grouped into three investment potential categories• Central urban areas dominate high-return tourism zones• Web-based mapping supports structured spatial decision-making Keywords Spatial Analysis; Tourism Investment; WebGIS; K-Means Clustering; Tomohon City
A Digital Image Processing–Based Moler Disease Detection System for Shallot Leaves Reski Wahyuni; Alfiansyah Hasibuan; Kristofel Santa
Journal La Multiapp Vol. 7 No. 1 (2026): Journal La Multiapp
Publisher : Newinera Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37899/journallamultiapp.v7i1.2738

Abstract

This study aims to design and develop a leaf moler disease detection system on shallots (Allium cepa L.) based on digital image processing in Enrekang Regency, South Sulawesi. Moler disease caused by the fungus Fusarium oxysporum f. sp. cepae is one of the main factors that reduce the quality and productivity of shallots. So far, disease identification is still done manually through direct observation by farmers, which is subjective and time-consuming. To overcome this problem, this study applies the Convolutional Neural Network (CNN) algorithm to automatically classify shallot leaf images into two categories, namely healthy and infected with moler disease. The number of datasets used is 502 images, consisting of 251 healthy images and 251 infected images, with data division of 70% for training, 15% for validation, and 15% for testing. The CNN architecture used consists of convolution, pooling, flatten, and fully connected layers with ReLU and sigmoid activation functions in the output layer. The training process used the Adam optimizer with a learning rate of 0.001 and a binary cross-entropy loss function. Test results showed a training accuracy of 97.14%, a validation accuracy of 94.73%, and a testing accuracy of 97.37%, indicating the model has a good level of precision and generalization ability without overfitting. This system is implemented as a Flask-based web application that allows users to upload leaf images and obtain detection results instantly. This system is expected to help farmers detect diseases more quickly and increase shallot productivity in Enrekang Regency.
A Web-Based Disaster Report Recapitulation System Using the Simple Additive Weighting Method Fanuel Juventino Palandeng; Sondy Campvid Kumajas; Kristofel Santa
Journal of Information System and Informatics Vol 8 No 1 (2026): February
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/journalisi.v8i1.1410

Abstract

Many regional disaster management agencies still manage incident reporting through conventional, semi-manual workflows (e.g., spreadsheets and paper archives). These practices often create repetitive recapitulation tasks, increase the likelihood of data inconsistency, and produce reports that remain largely descriptive—limiting analytical support for timely, evidence-based decision-making. To address this limitation, this study develops a web-based disaster reporting and recapitulation system integrated with the Simple Additive Weighting (SAW) method to generate an event-level Impact Index for prioritization. The system is built using a Prototyping approach, enabling iterative refinement through user feedback to ensure operational fit. SAW is applied using weighted criteria—number of casualties, affected families, damage level, and disaster type—so that each recorded event can be scored and ranked automatically. In contrast to many prior disaster-related SAW applications that emphasize beneficiary selection or aid distribution, this research applies SAW for internal managerial evaluation, prioritizing disaster events themselves to support organizational review and mitigation planning. A case study at BPBD Minahasa Regency demonstrates the system’s feasibility and performance: Black Box Testing achieved a 100% functional success rate, and manual SAW verification confirmed that automated Impact Index outputs are mathematically consistent with theoretical calculations. Overall, the proposed application offers a structured and transparent analytical tool to standardize reporting, accelerate recapitulation, and strengthen decision support through objective impact-based ranking.
Implementasi Sistem Smartlamp untuk Menyalakan dan Mematikan Lampu Otomatis Berbasis IoT pada Ruangan Lab Komputer Cristy E. P. Bojoh; Jonathan Kowaas; Kristofel Santa; Nasib Marbun
Journal of Information Systems and Technology Vol. 2 No. 2 (2025): Desember 2025
Publisher : PT Katersi Minar Permata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66785/fimerkom.v2i2.150

Abstract

Perkembangan teknologi Internet of Things (IoT) memberikan peluang dalam penerapan sistem kendali perangkat elektronik jarak jauh yang lebih efisien dan fleksibel. Pada ruang laboratorium komputer, pengendalian lampu masih banyak dilakukan secara manual sehingga sering menimbulkan pemborosan energi ketika lampu tidak dimatikan setelah digunakan. Penelitian ini bertujuan untuk mengimplementasikan sistem kendali lampu berbasis IoT dengan memanfaatkan mikrokontroler ESP32, modul relay, serta aplikasi Blynk sebagai media pengontrolan jarak jauh melalui jaringan internet. Pada sistem ini, ESP32 berperan sebagai pengendali utama yang terhubung ke modul relay untuk mengatur aliran listrik menuju lampu. Aplikasi Blynk digunakan sebagai antarmuka pengguna untuk menyalakan dan mematikan lampu secara real-time melalui smartphone. Pengujian dilakukan untuk mengetahui tingkat respon sistem terhadap perintah ON/OFF melalui aplikasi serta kestabilan koneksi jaringan. Hasil pengujian menunjukkan bahwa sistem mampu bekerja dengan baik dan memberikan respon kendali yang cepat sesuai perintah dari aplikasi Blynk. Sistem ini memberikan kemudahan dalam memantau dan mengontrol kondisi lampu tanpa harus berada di lokasi ruangan laboratorium. Selain itu, implementasi sistem ini berpotensi mendukung efisiensi penggunaan energi dan pengelolaan ruang yang lebih efektif.
Sistem Pemantauan Suhu dan Aktivasi Cooler Otomatis Berbasis Internet of Things pada Ruangan Kelas Imanuel Hiskia Wagey; Arif Tegar Elgifari Arbie; Kristofel Santa
Journal of Information Systems and Technology Vol. 2 No. 2 (2025): Desember 2025
Publisher : PT Katersi Minar Permata

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.66785/fimerkom.v2i2.151

Abstract

Perubahan suhu pada ruang kelas yang tidak menentu sering menyebabkan kondisi belajar menjadi kurang nyaman dan menurunkan efektivitas pembelajaran. Untuk mengatasi masalah tersebut, penelitian ini mengembangkan sistem pemantauan suhu ruangan berbasis Internet of Things (IoT) menggunakan ESP32 dan platform ThingSpeak. Sensor suhu terpasang mengirimkan data secara real time ke ThingSpeak untuk ditampilkan dalam bentuk grafik sehingga dapat dipantau dari jarak jauh. Selain itu, sistem dirancang untuk mengaktifkan cooler secara otomatis ketika suhu ruangan melewati batas yang telah ditentukan, guna menjaga kenyamanan belajar dan meningkatkan efisiensi energi. Penelitian dilakukan melalui beberapa tahapan meliputi identifikasi kebutuhan, perancangan perangkat keras dan perangkat lunak, pengujian lapangan, serta analisis data. Hasil pengujian menunjukkan bahwa sensor mampu membaca suhu dengan baik, data dapat dikirim ke ThingSpeak secara real time, dan cooler dapat bekerja secara otomatis sesuai perubahan suhu ruangan. Implementasi sistem ini menunjukkan bahwa teknologi IoT dapat diterapkan secara efektif dalam pengelolaan ruang kelas yang lebih cerdas dan efisien.
Implementation of Random Forest for Predicting Complaint Handling Priorities at the Minahasa Education Office Sinta Tumbo; Medi Hermanto Tinambunan; Kristofel Santa
SISTEMASI Vol 15, No 3 (2026): Sistemasi: Jurnal Sistem Informasi
Publisher : Universitas Islam Indragiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32520/stmsi.v15i3.6060

Abstract

Public service delivery in the education sector requires government institutions to handle public complaints promptly and accurately. However, the Minahasa Regency Education Office still faces challenges in determining complaint handling priorities, which are often subjective and manually assigned. This condition may lead to delays in addressing urgent complaints. This study aims to implement the Random Forest algorithm to objectively predict complaint handling priorities based on data. The research methodology includes collecting a dataset of 500 public complaints with six attributes: complaint type, violation level, work unit, follow-up action, outcome, and priority. The process involves data preprocessing, splitting the dataset into training and testing sets, building the Random Forest model, and evaluating its performance. Data processing and modeling were conducted using Jupyter Notebook within the Anaconda environment. Model performance was evaluated using accuracy, confusion matrix, precision, recall, and F1-score metrics. The results show that the Random Forest algorithm achieved an accuracy of 100%, with precision, recall, and F1-score values of 1.00 across all priority classes. These findings indicate that the model demonstrates excellent and stable classification performance. Therefore, it can serve as a foundation for developing a decision support system to improve the effectiveness and quality of public service delivery at the Minahasa Regency Education Office.
Penerapan Teknik Google Dorking Untuk Identifikasi Kerentanan Sensitive Data Exposure Menggunakan Google Hacking Database (GHDB) Dengan Metode Focused Crawling: Studi Kasus Situs NASA Francesco Jeremy Topol; Quido C. Kainde; Kristofel Santa
Jurnal Sains Informatika Terapan Vol. 5 No. 2 (2026): Jurnal Sains Informatika Terapan (Juni, 2026)
Publisher : Riset Sinergi Indonesia (RISINDO)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62357/jsit.v5i2.1076

Abstract

Di era digital saat ini, kebocoran data sensitif (Sensitive Data Exposure) menjadi ancaman serius bagi integritas organisasi, sering kali disebabkan oleh kesalahan konfigurasi izin akses misalnya studi kasus ini yaitu pada layanan penyimpanan awan seperti Google Drive dan Spreadsheet. Penelitian ini bertujuan untuk merancang dan mengimplementasikan sistem audit keamanan otomatis bernama DorkWatch untuk mengidentifikasi potensi kebocoran data pada domain nasa.gov. Penelitian ini memanfaatkan sumber data primer berupa aset digital yang terindeks pada domain nasa.gov dan subdomain terkait, yang dikumpulkan secara real-time melalui pemanfaatan 5 kueri dork spesifik dari Google Hacking Database (GHDB) yang menargetkan ekosistem Google Workspace. Dalam proses pengujian yang dilakukan, dengan limit 25 hasil pencarian sistem berhasil mengekstraksi dataset yang mencakup tautan layanan penyimpanan awan publik (Google Drive dan Docs) dari konten HTML serta metadata file PDF menggunakan Regular Expression (Regex) dengan metode Focused Crawling. Dataset yang dihasilkan kemudian diklasifikasikan secara otomatis ke dalam 2 kategori utama, yaitu Docs Exposure dan Drive Exposure. Sistem ini dibangun menggunakan bahasa pemrograman Python dengan kerangka kerja Flask, dan menerapkan teknik Google Dorking berbasis Google Hacking Database (GHDB) untuk pencarian dokumen publik dan metode Focused Crawling untuk penelusuran aset digital secara lebih terarah, serta melakukan analisis risiko otomatis berdasarkan validasi status HTTP dan deteksi kata kunci sensitif. Hasil pengujian menunjukkan bahwa sistem DorkWatch efektif dalam menemukan dan mengklasifikasikan aset NASA yang terekspos ke publik, termasuk tautan file Google Docs serta folder dan file Google Drive yang tidak muncul pada hasil pencarian standar, sehingga membuktikan bahwa integrasi metode ini efisien dalam memitigasi risiko kebocoran informasi.
BM25 Algorithm for Improving Academic Website Search Accuracy: Algoritma BM25 untuk Meningkatkan Akurasi Pencarian di Situs Web Akademik Glenn David Paulus Maramis; Marthasya Chantika Putri Ranti; Kristofel Santa
Indonesian Journal of Innovation Studies Vol. 27 No. 1 (2026): January
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/ijins.v27i1.1799

Abstract

General Background: The increasing volume of digital information in academic environments requires search systems that can deliver accurate and relevant results. Specific Background: The Faculty of Engineering UNIMA website still relies on simple keyword matching, which often produces irrelevant outputs and reduces the effectiveness of information access. Knowledge Gap: Although the BM25 algorithm is widely recognized for its superior relevance scoring in information retrieval, its application in faculty-level academic portals remains limited. Aims: This study aims to implement the BM25 algorithm using Meilisearch integrated with Laravel and Filament to improve search relevance, speed, and data management efficiency. Results: The implemented system successfully ranks the most relevant documents at the top with response times measured in milliseconds, and automatic index synchronization ensures consistent and up-to-date search results. Novelty: This research presents one of the first BM25-based search implementations within an Indonesian faculty website, integrating Laravel, Meilisearch, and Filament into a cohesive architecture. Implications: The findings show that BM25 significantly enhances the quality of search services and user experience, providing a scalable model for academic institutions seeking effective information retrieval solutions. Highlights: Enhances search relevance and speed on a faculty academic website using BM25. Integrates Laravel, Meilisearch, and Filament into a unified, easy-to-manage system. Offers a scalable model for improving information access in higher education portals. Keywords: BM25, Information Retrieval, Meilisearch, Laravel, Academic Website
Co-Authors Agnia Paputungan Agniya Algifahri Aldo Napu Alfiansyah Hasibuan Alfiansyah Hasibuan Amran Panjaitan Andi R. Widyastuti Archangela G. Repi Arif Tegar Elgifari Arbie Arsila Duaulu Athik Gelamona Atuna, Annisa Salsabilah Audy Aldrin Kenap Basilius Mario Vikranta Rahanubun Ben Shalom Manopo Chelsea Aprilia Tendean Chris Terok Christenia Tagah Cristy E. P. Bojoh Daeng, Mushendra Dani Orlando Daniel Riano Kaparang Della Deviani Harisondak Detuage, Rivni Djami Olii Efraim R. S. Moningkey Enjelita Radjakore Ezra Matthew Warouw Runturamby Fanuel Juventino Palandeng Ferdinan I. Sangkop Ferjenia Feybelia Filisia R. Terok Francesco Jeremy Topol Geralda Lucia Rumondor Gitarosalina Sibarani Gladly Caren Rorimpandey Glenn D. P. Maramis Gratia Whaitney Injili Dotulong Hanni Tompunu Harisondak, Della Deviani Imanuel Hiskia Wagey Inda, Inda Indi Rahayu Ningsi Inggried Rillya Sondakh Irene Realyta Halldy Trosi Tangkawarow Irwan Irwan Jessa V Komaling Jonathan Kowaas Joy C. Rampi Julio Tabea Kambey, Waraney Maurits Kevin Mclaren Pandoh Kezya Tjanahu Krina Crisila T. Mawuntu Lisa Menden Lorentza Claudia Rianti Peres Tawaa Maria Rina Rumengan Mario Trinto Risky Rettob Marthasya Chantika Putri Ranti Martina Lorensa Medi Hermanto Tinambunan Medi Hermanto Tinambunan Melati Roring Moningkey, Efraim Ronald Stefanus Muhammad Lukmansyah Sulaiman Nanda, Agus Estepen Nasib Marbun Nelsi Timang Olivia Kembuan Pagala, J. Rifaldo parabelem tinno dolf rompas Peggy Veronica Togas Pesik, Luisa Maria Preisya Yunita Toar Prillya Chrisanta Esthefania Kawuwung Qnardo Delon Pateh Quido Conferti Kainde Rafter Johanes Karouw Rahellea Joiby Onibala Ratu, Regina Gloria Ravila Putri Pangalila Reski Wahyuni Rikna Aresta Lahutung Romeo Fernando Mikhael Dendeng Rumayar, Eroldy Saknohsiwy, Lorida Julensa Holiba Semuel Fendy Ngalo Sinta Tumbo Sondakh, Inggried Rillya Sondy C. Kumajas Sondy C. Kumajas Sondy Campvid Kumajas Stevanus Kembuan Stiven Panambunan Syalomita Cinta Tendean, Chelsea Aprilia Tiara Pongmangatta Tinambunan, Medi Hermanto Tiwi, Heri Susan Tresya Veronika Deil Tular, Feonri Vivi Peggie Rantung Waraney Maurits Kambey Wayne Kemur Wilma Wijayanti Wowor, Hanna Elisabeth Yosita Rante Tando