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All Journal Jurnal Mantik Journal of Artificial Intelligence and Engineering Applications (JAIEA) Jurnal Aplikasi Bisnis dan Komputer Jurnal Teknologi dan Manajemen Industri Terapan ABDINE Jurnal Pengabdian Masyarakat Malcom: Indonesian Journal of Machine Learning and Computer Science J-Icon : Jurnal Komputer dan Informatika Jurnal Inovatif Wira Wacana AMMA : Jurnal Pengabdian Masyarakat
Arini Aha Pekuwali
Program Studi Teknik Informatika Universitas Kristen Wira Wacana Sumba
Humanities Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Nursing Public Health Other

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Pelatihan Sistem Informasi Manajemen Induk Sinode GKS Fajar Hariadi; Arini Aha Pekuwali; Yustina Rada; Desy Asnath Sitaniapessy; Rambu Yetti Kalaway; Raynesta Mikaela Indri Malo; Itha Priyasthiti; Pingky Alfa Ray Leo Lede; Reynaldi Thimotius Abineno; Leonard Marten Doni Ratu; Ferdian Fendi Djami; Umbu Theofilus Dendimara; Demaris Lemba Oy; Papy Rivandi Bara; Trisari D. N. B. Mira; Riwa Rambu Hada Enda
AMMA : Jurnal Pengabdian Masyarakat Vol. 4 No. 6 : Juli (2025): AMMA : Jurnal Pengabdian Masyarakat
Publisher : CV. Multi Kreasi Media

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

Abstract

Training on the Sistem Informasi Manajemen Induk Sinode GKS was conducted as part of the digitalization initiative for congregation and financial data management within Gereja Kristen Sumba (GKS), under the auspices of Sinode GKS. The training was attended by 83 participants, consisting of secretaries, church council working bodies, and treasurers responsible for managing congregation data as well as financial administration and reporting in GKS churches under the Sinode.  User evaluations (on a scale of 1 to 5) of the Sistem Informasi Manajemen Induk Sinode GKS (Simanis V.2) yielded a score of 3.95 for the congregation data management feature and 3.47 for the financial management feature. These results indicate that both the training and the Simanis application have supported the churches' needs in managing congregation and financial data, although improvements to certain features are still necessary.
Sistem Pemantauan Kualitas Air Kolam Berbasis Internet of Things (IoT) Untuk Mengurangi Kematian Ikan Nila Menggunakan Logika Fuzzy Mamdani Aristho umbu nggaba kaho; Arini Aha Pekuwali; Leonard Marten Doni Ratu
Jurnal Teknologi dan Manajemen Industri Terapan Vol. 1 No. 3 (2022): Jurnal Teknologi dan Manajemen Industri Terapan
Publisher : Yayasan Inovasi Kemajuan Intelektual

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55826/jtmit.v4i3.1010

Abstract

Penelitian ini bertujuan untuk mengembangkan sistem pemantauan kualitas air kolam ikan nila berbasis IoT dengan penerapan logika fuzzy Mamdani serta notifikasi Telegram bot untuk membantu peternak mengurangi potensi kematian ikan nila akibat penurunan kualitas air. Sistem menggunakan tiga parameter utama yaitu suhu, pH  dan tingkat kekeruhan air yang diukur secara real-time melalui sensor DS18B20, pH-4502C dan sensor turbidity. Data hasil pengukuran akan diproses menggunakan logika fuzzy Mamdani untuk menentukan kelayakan air dan dikirim ke pengguna melalui Telegram. Berdasarkan hasil pengujian menunjukkan bahwa sistem mampu membaca parameter air dengan baik, memproses data melalui logika fuzzy Mamdani secara akurat, serta mengirimkan notifikasi kepada pengguna secara real-time ketika kondisi air terdeteksi tidak ideal. Sistem diharapkan dapat membantu peternak ikan nila, khususnya di SMK Negeri 3 Pahunga  Lodu, dalam memantau kualitas air kolam dan mengambil langka antisipatif untuk mengurangi potensi kematian ikan secara massal.
Design of a Web Based Population Data Information System at Matawai Atu Village Office Jesika Prince Piri; Arini Aha Pekuwali
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 3 (2026): June 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i3.2334

Abstract

The development of information technology has greatly influenced many sectors, including village administration. The Matawai Atu Village Office, located in Umalulu Subdistrict, East Sumba Regency, still uses a manual system to record population data such as births, deaths, new residents, and relocations. Data is recorded in a main register book and then processed using Microsoft Word to create reports. This method causes several problems, including the risk of data loss, data entry errors, slow data searching, and delays in report preparation. To solve these problems, this study aims to design a web-based population data information system that is effective and efficient. The study uses the Waterfall method, which includes the stages of requirements analysis, system design, implementation, testing, and maintenance. The system is developed using PHP and a MySQL database. Data collection is carried out through interviews, direct observation at the research location, and literature study. System testing is conducted using Black Box Testing to ensure that all features work properly, and the System Usability Scale (SUS) to measure how easy the system is for users. The results show that the developed system can manage population data more accurately, quickly, and securely. The system also makes it easier for staff to search data, manage documents, and prepare reports. With this system, it is expected that public services at the Matawai Atu Village Office will improve and better support the work of village staff.
PREDIKSI HARGA BERAS DI SUMBA TIMUR MENGGUNAKAN ALGORITMA NEURAL NETWORK Renol Bulu Manggal; Arini Aha Pekuwali; Raynesta Mikaela Indri Malo
J-Icon : Jurnal Komputer dan Informatika Vol 14 No 1 (2026): March 2026
Publisher : Universitas Nusa Cendana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35508/jicon.v14i1.27555

Abstract

Fluctuations in rice prices in East Sumba Regency are an important issue that directly affects farmers, traders, and consumers. Unstable price changes are influenced by weather conditions, supply availability, distribution, and market dynamics. Therefore, a prediction method is needed that can provide accurate estimates of rice prices as a basis for decision making. This study aims to predict the price of medium rice in East Sumba Regency using the Neural Network algorithm, specifically Long Short-Term Memory (LSTM), which is effective in modeling time series data. The data used are monthly rice price data for the period January 2021 to December 2025 obtained from Perum BULOG Waingapu Branch Office, with data processing and analysis carried out after all 2025 data became available. The research stages include data collection, data preprocessing, normalization using Min-Max Scaling, time series dataset formation, division of training and testing data, LSTM model training, and model performance evaluation. The evaluation was carried out using the Root Mean Square Error (RMSE) metric. The results show that the LSTM model is able to predict rice prices with an RMSE value of 360.91 Rp/Kg or around 3.35% of the average rice price. This value indicates that the prediction error of the model is relatively small, so the model can be said to have good prediction performance. Therefore, the developed LSTM model is considered feasible to be used as a tool for predicting rice prices and is expected to help farmers and traders in planning sales and become a consideration for the local government in maintaining rice price stability in East Sumba Regency.
Co-Authors Adindarena, Vindya Donna Alfrian Carmen Talakua Andi Alex Aristho Umbu Nggaba Kaho Demaris Lemba Oy Desy Asnath Sitaniapessy Djadji, Osfred Umbu Fajar Hariadi Ferdian Fendi Djami Itha Priyasthiti Jesika Prince Piri Jimi Meha Milla Lede, Pingky Alfa Leonard Marten Doni Ratu Mega Peka Rihi Mesak Katanga Mulung Mikael Maga Muhammad Fauzi Hamdon Obed Hunggu Li Papy Rivandi Bara Pingky Alfa Ray Leo Lede Rambu Yetti Kalaway Raynesta Mikaela Indri Malo Renol Bulu Manggal Reynaldi Thimotius Abineno Riwa Rambu Hada Endah Salmon Pandarangga Trisari D. N. B. Mira Umbu Theofilus Dendimara Yustina Rada