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All Journal Syntax Jurnal Informatika CommIT (Communication & Information Technology) Scan : Jurnal Teknologi Informasi dan Komunikasi Proceeding International Conference on Information Technology and Business Jurnal Teknologi Informasi dan Ilmu Komputer International conference on Information Technology and Business (ICITB) Jurnal Sistem Informasi dan Bisnis Cerdas Informatika Mulawarman: Jurnal Ilmiah Ilmu Komputer INTEGER: Journal of Information Technology JIEET (Journal of Information Engineering and Educational Technology) Pendas : Jurnah Ilmiah Pendidikan Dasar JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Jutisi: Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Jurnal Informatika dan Rekayasa Elektronik bit-Tech Journal of Appropriate Technology for Community Services JATI (Jurnal Mahasiswa Teknik Informatika) CICES (Cyberpreneurship Innovative and Creative Exact and Social Science) Jurnal Layanan Masyarakat (Journal of Public Service) Jifosi Nusantara Science and Technology Proceedings KERNEL: Jurnal Riset Inovasi Bidang Informatika dan Pendidikan Informatika Abdimas Altruis: Jurnal Pengabdian Kepada Masyarakat Jurnal Informatika Dan Tekonologi Komputer (JITEK) East Asian Journal of Multidisciplinary Research (EAJMR) Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Teknik Informatika dan Teknologi Informasi Jurnal Krisnadana JUSIFOR : Jurnal Sistem Informasi dan Informatika Jurnal Pepadu Jurnal Ilmiah Teknik Informatika dan Komunikasi Jurnal Krisnadana Jurnal Informatika Polinema (JIP) Horizon: Indonesian Journal of Multidisciplinary Router : Jurnal Teknik Informatika dan Terapan Bridge: Jurnal Publikasi Sistem Informasi dan Telekomunikasi Repeater: Publikasi Teknik Informatika dan Jaringan Prosiding Seminar Nasional Ilmu Teknik Router : Jurnal Teknik Informatika dan Terapan Jurnal Informatika Dan Tekonologi Komputer
Henni Endah Wahanani
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PEMBERDAYAAN PEREMPUAN WIRAUSAHA BERBASIS INOVASI DAN TEKNOLOGI DIGITAL UNTUK PENGUATAN EKONOMI LOKAL DI DESA JABUNG, KECAMATAN PANEKAN, KABUPATEN MAGETAN, JAWA TIMUR Henni Endah Wahanani; Swasti, Ika Korika; Sholihatin, Endang; Affro, Salma; Arimawan, Kesya Sakha Nesya
Jurnal Pepadu Vol 6 No 3 (2025): Jurnal Pepadu
Publisher : Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/pepadu.v6i3.8197

Abstract

ABSTRACT This community engagement initiative aims to empower women entrepreneurs in Jabung Village, Panekan Subdistrict, Magetan Regency, East Java, through the implementation of product innovation and the utilization of digital technology to strengthen the local economy. The primary challenges faced by the target group include limited knowledge of digital marketing, poor packaging quality, and restricted market reach. The program was executed through a series of activities comprising training sessions, technology transfer, demonstrations, and intensive mentoring, involving 15 women entrepreneurs as core partners. A participatory approach based on Participatory Rural Appraisal (PRA) was employed, enabling active involvement of participants in every stage of the program. The outcomes indicate a significant improvement in the participants' ability to manage digital business accounts on platforms such as Tokopedia, Instagram Business, Facebook Business, and TikTok Business, with an average understanding increase of 73%, as measured by pre- and post-test evaluations. Furthermore, 85% of participants successfully created and managed online business accounts, 75% consistently uploaded product content with enhanced appeal, and 80% actively utilized social media for promotional purposes. Innovation was also evident in packaging design, with 85% of participants developing brand-identified labels, thereby enhancing consumer perception and market appeal. The tangible impacts of the program include an average sales increase of 25%, expansion of market reach beyond the village, and a rise in women's contribution to household income from 10–15% to 25–30%. These findings underscore that MSME digitalization through training, technology transfer, and branding enhancement can significantly improve women's economic independence while sustainably strengthening the local economy. Keywords: women empowerment, entrepreneurship, digitalization, product innovation, branding, local economy.
Sistem Pendukung Keputusan Eligible Seleksi Nasional Berdasarkan Prestasi (SNBP) Menggunakan Metode Additive Ratio Assessment (ARAS): Studi Kasus: SMAN 8 Surabaya Rhiziqo Adjie Syahputra; Henni Endah Wahanani; Budi Mukhamad Mulyo
Prosiding Seminar Nasional Ilmu Teknik Vol. 2 No. 2 (2025): Desember: Prosiding Seminar Nasional Ilmu Teknik
Publisher : Asosiasi Riset Ilmu Teknik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/prosemnasproit.v2i2.205

Abstract

The selection process for students eligible for the National Selection Based on Achievement (SNBP) requires objective and structured assessment because it involves various academic and non-academic criteria. This study aims to develop a Decision Support System (DSS) to determine the ranking of SNBP eligible students at SMAN 8 Surabaya using the Additive Ratio Assessment (ARAS) method. The ARAS method is used to evaluate student alternatives based on their report card scores for semesters 1-5, academic ability tests (TKA), academic achievements, non-academic achievements, discipline, organizational activity, and attendance through a normalization process to obtain relative Ki values. The results of the study show that the system is capable of producing objective student rankings with relative utility values (Ki) ranging from 95.15 to 89.38, where the highest value indicates the best alternative from all alternatives. The application of ARAS-based DSS can improve the efficiency, transparency, and consistency of the SNBP student selection process.
An Adaptive DTN Routing Protocol Using a Q-Learning Framework for Archipelagic Emergency Networks Agussalim Agussalim; Henni Endah Wahanani; Andreas Nugroho Sihananto
CommIT (Communication and Information Technology) Journal Vol. 20 No. 1 (2026): CommIT Journal (in press)
Publisher : Bina Nusantara University

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Natural disasters in archipelagic regions often disrupt communication networks, particularly in geographically isolated islands where terrestrial infrastructure is limited and highly vulnerable. Hence, adaptive, infrastructure-independent solutions are required to maintain connectivity during emergencies. The research proposes an adaptive routing protocol for Delay Tolerant Network (DTN), named Q-learning-based Forwarding Routing (QFR), designed to enhance data delivery performance in disaster scenarios characterized by intermittent connectivity and constrained resources. QFR employs a lightweight, tabular Q-learning framework to make intelligent forwarding decisions based on real-time state information, including buffer occupancy, encounter history, and local node density. The protocol further integrates adaptive replica control and prioritybased scheduling mechanisms to regulate congestion and optimize bandwidth and buffer utilization. Performance evaluation is conducted using the ONE Simulator with realistic maritime mobility traces derived from vessel movement patterns around Madura Island, Indonesia, representing inter-island emergency communication conditions. The results indicate that QFR consistently outperforms benchmark protocols such as Epidemic and PRoPHETv2, particularly in maintaining a high delivery ratio under heavy traffic loads while keeping routing overhead moderate and latency stable. Time-series analysis further demonstrates QFR’s ability to improve its performance over time as the agent learns. The key finding is that a lightweight, adaptive algorithm based on a tabular Q-learning framework provides a practical and effective solution for reliable communication in resource-constrained emergency networks, avoiding the computational complexity of deep reinforcement learning approaches.
LSTM with Attention Optimization for IDR-USD Exchange Rate Forecasting Muhammad Abdullah Hafizh; Anggraini Puspita Sari; Henni Endah Wahanani
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.3131

Abstract

This study proposes the application of the LSTM-Attention model to forecast the IDR exchange rate against the USD. Exchange rate stability is an important element in national and international economic resilience systems, as currency fluctuations can have a significant impact on trade, investment, banking, and household consumption. In the case of Indonesia, which is highly dependent on imported goods, exchange rate fluctuations cause an increase in import costs, rising inflation, and a decline in the competitiveness of export products in the global market, making accurate forecasting of exchange rate movements essential for economic policy, business strategy, and risk management. Statistical models such as ARIMA have been widely applied in exchange rate forecasting, but they have difficulty capturing the nonlinear of time series data. In recent years, machine learning methods such as Long Short-Term Memory (LSTM) have demonstrated their ability to handle timeseries data. Previous studies have shown that LSTM models generally outperform traditional methods, but they still face limitations in identifying important features across time steps. To overcome this problem, the Attention mechanism allows the model to focus on the most informative parts of the input sequence, thereby improving prediction accuracy. Experimental results show that the LSTM-Attention achieves MAPE of 1.28% and R2 of 0.97 and runtime 45% faster than BiLSTM. While BiLSTM achieved slightly higher accuracy, it’s required nearly twice the training time. Findings indicates that the proposed model offers practical choice for real-time exchange rate forecasting.
Fuzzy C-Means Clustering of Regencies and Cities Based on Total Sanitation Society Ananda Azra Razali; Eva Yulia Puspaningrum; Henni Endah Wahanani
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.3180

Abstract

The Community Based Total Sanitation (STBM) program is a national initiative designed to enhance public health by promoting clean and healthy living habits. However, its implementation in several regions, including East Java Province, continues to encounter a number of challenges, as several sanitation indicators have yet to reach the desired targets. This study aims to group the sanitation performance of regencies and cities in East Java using the Fuzzy C Means (FCM) algorithm and visualize the outcomes through thematic maps to provide clearer and more informative spatial insights. Six key indicators. Six key indicators CTPS, PAMMRT, PSRT, PLCRT, PKURT, and Healthy Home Access were analyzed as percentages, with variable selection and normalization conducted using the Min Max Scaler to ensure comparable value ranges across datasets. The clustering validity was assessed using the Davies Bouldin Index (DBI), where the lowest value of 0.9134 was achieved for three clusters, indicating the most optimal grouping configuration. The resulting clusters represent regions with high, medium, and low sanitation achievement levels, while spatial visualization reveals that lower-performing regions are largely concentrated in the eastern part and the Madura area. From a practical standpoint, the findings of this study can serve as a foundation for policy formulation, intervention prioritization, and more efficient resource allocation to improve regional sanitation performance in a focused and sustainable manner.
Implementation of Facebook Prophet Algorithm in Population Prediction Raditya Dimas Libriawan; Anggraini Puspitasari Sari; Henni Endah Wahanani
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.3190

Abstract

The number of populations in a country is a very important aspect because it has a direct effect on various aspects of life. Indonesia is in the fourth position of the country with the largest population in the world. It is recorded in the Indonesian Central Statistics Agency (BPS) that by mid-2024, the population in Indonesia will reach 281.603.800 people. The ever-increasing population will drive increased energy demand. Therefore, monitoring and controlling population growth is a crucial and indispensable step, one of which is by utilizing machine learning to conduct time series forecasting. This study contributes by optimizing FB Prophet’s parameter configuration for population forecasting in Indonesia, achieving improved accuracy compared to traditional models. The purpose of this study is to determine the level of accuracy and error of the model with evaluation metrics such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE). The results obtained from forecasting using the Prophet algorithm were that Indonesia increased by 1.5% by the end of 2025, with the value of the MAE evaluation metric of 0.0244, RMSE of 0.0256, and MAPE of 2.65%, which indicates a highly accurate prediction level for annual population data.
Optimizing the ResNet50 Model with Five Optimizers for Detecting Rice Leaf Diseases Muchammad Syamsu Huda; Henni Endah Wahanani; Fetty Tri Anggraeny
bit-Tech Vol. 8 No. 2 (2025): bit-Tech
Publisher : Komunitas Dosen Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32877/bt.v8i2.3232

Abstract

Rice (Oryza sativa) productivity is frequently threatened by foliar diseases such as Bacterial Leaf Blight, Brown Spot, Blast, and Tungro, which are often visually indistinguishable. This study achieved a high classification accuracy of 97.05% in detecting these diseases by optimizing the ResNet50 architecture with five optimizers Adam, Nadam, Adamax, RMSprop, and SGD and identifying Adamax as the most effective. Using transfer learning with ImageNet weights and data augmentation, the model was trained and validated on 4,400 labeled images from Kaggle, partitioned in a 70:20:10 ratio for training, validation, and testing. The methodological framework integrates three layers of innovation: (1) optimizing a deep residual CNN with comparative adaptive and non-adaptive optimizers; (2) employing transfer learning to accelerate convergence and reduce overfitting; and (3) deploying the best-performing model into an Android-based mobile application for real-time field detection. Results demonstrate that adaptive optimizers substantially enhance ResNet50’s learning stability and generalization compared to traditional methods. The Adamax variant exhibited the most stable convergence and minimal validation loss, proving effective for fine-grained visual differentiation between similar disease patterns. This research advances the current state-of-the-art in agricultural image classification by providing a systematic optimizer evaluation within a CNN transfer learning framework and extending its practical usability through mobile deployment. Future studies should address model compression, real-time inference optimization, and cross-crop generalization to strengthen the scalability of AI-assisted disease diagnosis in precision agriculture.
Penerapan Teknik Basis Path pada Pengujian White Box Sistem Informasi Perencanaan dan Penganggaran Responsive Gender di Diskominfo Kabupaten Jombang Putri, Della Atika; Wahanani, Henni Endah; Nurlaili, Afina Lina
JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Vol 10, No 3 (2025)
Publisher : STKIP PGRI Tulungagung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29100/jipi.v10i3.6338

Abstract

Sistem informasi merupakan media penting yang digunakan untuk menyediakan informasi secara akurat dan tepat waktu. Mengingat signifikansi sistem ini bagi organisasi, pengujian kualitas dan keandalan sistem menjadi krusial. Penelitian ini mengkaji sistem informasi perencanaan dan penganggaran responsif gender yang dikelola oleh Diskominfo Jombang dengan menerapkan teknik basis path dalam metode pengujian white box. Pengujian melibatkan pembuatan flowgraph, perhitungan cyclomatic complexity (CC), penentuan jalur independen, dan pembuatan test case. Teknik basis path digunakan untuk memastikan bahwa setiap jalur dalam program dapat dilalui sekali tanpa adanya jalan pintas atau perulangan, melalui analisis kode program sistem. Hasil pengujian menunjukkan bahwa dari empat fungsi yang diuji, satu fungsi memiliki prosedur yang terstruktur dengan baik dan konsisten, sedangkan tiga fungsi lainnya sederhana dan memiliki risiko rendah. Secara keseluruhan, sistem ini dinilai memiliki risiko rendah. Namun, evaluasi usability menggunakan metode SUS menunjukkan bahwa, meskipun sistem berfungsi dengan baik dari segi logika internal, antarmuka yang rumit, serta navigasi yang membingungkan menyebabkan skor SUS yang rendah. Hal ini menunjukkan bahwa sistem belum sepenuhnya ramah pengguna dan memerlukan perbaikan.
Implementasi Kerangka Kerja MITRE D3FEND dalam Mitigasi Serangan Ransomware LockBit 3.0 Syahbagus Radithya Haryo Santoso; Henni Endah Wahanani; Achmad Junaidi
Jutisi : Jurnal Ilmiah Teknik Informatika dan Sistem Informasi Vol 15, No 3 (2026): Juni 2026
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/jutisi.v15i3.3636

Abstract

Cybersecurity threats are escalating due to the evolution of LockBit 3.0 ransomware, which has disrupted national vital sectors. This study aims to demonstrate the implementation of the MITRE D3FEND framework to mitigate these attacks within a Windows 11 environment. An experimental method using a technical comparative analysis approach was applied and validated through 50 test iterations to ensure data reliability. The results indicate that the baseline unprotected system is completely vulnerable to the entire LockBit 3.0 attack chain. However, the deployment of MITRE D3FEND controls proactively enhances system resilience, achieving a 75% effectiveness score by successfully executing passive detection and real-time active blocking at critical attack vectors. This study concludes that a digital artifact-based defense strategy significantly hardens cyber infrastructure, while recommending future developments in artificial intelligence (AI) based adaptive mitigation automation.Kata kunci: MITRE D3FEND; LockBit 3.0; Cybersecurity; Ransomware; Mitigation AbstrakAncaman keamanan siber meningkat akibat evolusi ransomware LockBit 3.0 yang melumpuhkan berbagai sektor vital nasional. Penelitian ini bertujuan mendemonstrasikan implementasi kerangka kerja MITRE D3FEND dalam memitigasi serangan tersebut pada Windows 11. Metode eksperimen diterapkan melalui pendekatan analisis komparatif teknis yang divalidasi lewat 50 kali iterasi pengujian guna menjamin reliabilitas data. Hasil pengujian menunjukkan bahwa sistem standar tanpa proteksi sepenuhnya rentan terhadap seluruh rangkaian serangan LockBit 3.0. Namun, penerapan kontrol pertahanan MITRE D3FEND terbukti proaktif meningkatkan resiliensi sistem dengan skor efektivitas mencapai 75% melalui keberhasilan fungsi deteksi pasif serta pemblokiran aktif secara real-time di titik-titik krusial serangan. Penelitian ini menyimpulkan bahwa strategi pertahanan berbasis artefak digital secara signifikan memperkeras keamanan infrastruktur siber, sekaligus merekomendasikan pengembangan otomatisasi mitigasi adaptif berbasis kecerdasan buatan (AI) di masa depan. 
SISTEM INKUBATOR TELUR LEOPARD GECKO BERBASIS IOT DENGAN PID UNTUK ANAKAN BETINA Ahmad Anwar Saifurridzal; Mohammad Idhom; Henni Endah Wahanani
Jurnal Informatika Teknologi dan Sains (Jinteks) Vol 8 No 2 (2026): EDISI 28
Publisher : Program Studi Informatika Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51401/jinteks.v8i2.7293

Abstract

Perkembangan teknologi Internet of Things (IoT) telah mendorong penerapan sistem otomatis dalam bidang peternakan, termasuk pada proses penetasan telur reptil. Leopard Gecko (Eublepharis macularius) merupakan salah satu reptil yang proses penetasan telurnya sangat dipengaruhi oleh suhu, di mana perbedaan suhu inkubasi dapat menentukan jenis kelamin anakan yang dihasilkan. Namun, fluktuasi suhu lingkungan sering menjadi kendala bagi peternak, khususnya peternak rumahan, sehingga dapat menurunkan tingkat keberhasilan penetasan. Penelitian ini bertujuan untuk merancang dan mengembangkan sistem inkubator telur Leopard Gecko berbasis IoT dengan metode kontrol Proportional-Integral-Derivative (PID) guna menjaga kestabilan suhu secara otomatis. Sistem ini menggunakan sensor DHT22 sebagai pembaca suhu, modul peltier sebagai aktuator, serta mikrokontroler sebagai pengendali utama. Hasil yang diharapkan dari penelitian ini adalah terciptanya sistem inkubator yang mampu menjaga suhu sesuai setpoint untuk menghasilkan jenis kelamin betina secara optimal, serta memudahkan peternak dalam memantau kondisi inkubator secara real-time dan jarak jauh.
Co-Authors Abdi, Harris Cipta Abiyan Naufal Hilmi Achmad Junaidi Aditia Mieka Darminta Adityawati, Dewi Affro, Salma Agung Mustika Rizki Agung Mustika Rizki, Agung Mustika Agussalim Agussalim Agussalim, Agussalim Ahmad Anwar Saifurridzal Akbar, Fawwaz Ali Al Hamda, Veqqy Alfi Ramadhaniar Ananda Azra Razali Andreas Nugroho Sihananto Anggraini Puspita Sari Anggraini Puspitasari Sari Aniisah Eka Rahmawati Arif Saifudin, Muhamad Arimawan, Kesya Sakha Nesya Arrosyid, Muhammad Habib Arum Prabowo, Galih Bagus Satrio Wicaksono Bariq Satrio Yudoko Basuki Rahmat Basuki Rahmat Masdi Siduppa Belia Putri Salsabila Bregas Arya Bagaskara Budi Mukhamad Mulyo Budianto Budianto Chystia Aji Putra Darminta, Aditia Mieka Eka Zuni Selviana Ekamartha, Ken Narendra Endang Sholihatin Erlangga Wicaksono, Dewa Erlina Diah Karisma Eva Yulia Puspaningrum Fadhilasari, Annisa Fetty Tri Anggraeny Fikri Dwilaksono Firlie Aurellia Az-zahra Firza Prima Aditiawan Fitriansyah, Muhammad Daffa Hamzah Dimas Syah Reza Hermawan, Oky I Made Suartana I Nyoman Sujana idhom, Mohammad IMANDAYANTI, NUR EZA Intan Yuniar Purbasari Intan Yuniar Purbasari inthan anggraini, dieas Islah Rachmawati Lina Nurlaili, Afina M. Arif Made Hanindia Prami Swari Mandyartha, Eka Prakarsa Mohamad Ilham Prasetyo Raharjo Mohammad Idhom Mohammad Idhom Mohammad Idhom Muchammad Syamsu Huda Muhammad Abdullah Hafizh Muhammad Idhom Muhammad Muharrom Al Haromainy Muhammad Rizki Alamsyah Muhammad, rizal Muttaqin, Faisal Nafa Nabila El Indri naufal firdaus, ahmad Nugroho, Budi Nugroho, Budi Nugroho, Budi Nugroho, Budi Nurlaili, Afina Lina Nurlaili, Afina Lina Pelean Alexander Jonas Sitompul Phitria, Shaum Prakoso, Galih Indo Putra, Chrystia Aji Putra, Chystia Aji Putri, Della Atika Raditya Dimas Libriawan Rahmawati, Aniisah Eka Ramadhani, Muhammad Nabil Rayhan Rizal Mahendra Retno Mumpuni Retno Mumpuni Rhiziqo Adjie Syahputra Sandy Rizkyando Sandy, Aditya Noor Saputra, Wahyu S.J. Saputro, Fajar Arif Eko Shabika Aqmarina, Azzuraa Soedarto, Teguh Suartana, I Made Sugiarto Sugiarto - SUGIARTO - Sukirmiyadi, Sukirmiyadi Swasti, Ika Korika Syahbagus Radithya Haryo Santoso Thohir, A. Zaki Thomas Andrew Imanzaghi Vita Via, Yisti Wahono, Bari Hade Variant Yudha Asmara, I Wayan