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Sistem Pendukung Keputusan Penerimaan Anggota Tagana pada Kantor Dinas Sosial Kabupaten TTU Menggunakan Metode Topsis Berbasis Website Nikolas Abi; Yoseph P.K Kelen; Krisantus Jumarto Tey Seran; Leonard Peter Gellu
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 8, No 5 (2025): Oktober 2025
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v8i5.9803

Abstract

Abstrak - Penelitian ini bertujuan mengembangkan Sistem Pendukung Keputusan (SPK) untuk seleksi penerimaan anggota Taruna Siaga Bencana (TAGANA) pada Kantor Dinas Sosial Kabupaten Timor Tengah Utara (TTU) menggunakan metode Technique for Order Preference by Samerity to Ideal Solution (TOPSIS) berbasis website. Proses seleksi anggota TAGANA yang selama ini dilakukan secara manual memerlukan waktu dan ketelitian yang cukup lama, sehingga dibutuhkan sistem yang dapat mempercepat dan mempermudah pengambilan keputusan. Sistem yang dikembangkan menerapkan metode TOPSIS untuk melakukan perhitungan berdasarkan kriteria seperti usia, ijazah terakhir, pengalaman kerja, domisili, kesehatan mata, kepemilikan kendaraan pribadi, status, dan dokumen administrasi. Pengumpulan data dilakukan dari calon anggota yang terdaftar, kemudian sistem memproses dan menampilkan hasil perhitungan serta pemeringkatan secara otomatis. Hasil penelitian menunjukkan bahwa penerapan metode TOPSIS dalam SPK berbasis website ini dapat membantu Dinas Sosial Kabupaten TTU dalam mengoptimalkan proses penerimaan anggota TAGANA, menjadikan proses seleksi lebih obyektif, cepat, dan efisien. Sistem ini juga mampu menyajikan informasi hasil seleksi secara transparan dan mudah diakses melalui platform online yang disebut SPEKTA.Kata kunci: Sistem Pendukung Keputusan; TOPSIS; Taruna Siaga Bencana; penerimaan anggota; berbasis website; Abstract - research aims to develop a Decision Support System (SPK) for the selection of admission of members of the Disaster Preparedness Cadets (TAGANA) at the North Central Timor Regency Social Service Office (TTU) using the website-based Technique for Order Preference by Samerity to Ideal Solution (TOPSIS) method. The selection process for TAGANA members, which has been carried out manually, takes a long time and precision, so a system is needed that can speed up and facilitate decision-making. The system developed applies the TOPSIS method to perform calculations based on criteria such as age, last diploma, work experience, domicile, eye health, personal vehicle ownership, status, and administrative documents. Data collection is carried out from registered prospective members, then the system processes and displays the results of calculations and rankings automatically. The results of the study show that the application of the TOPSIS method in this website-based SPK can help the TTU Regency Social Service in optimizing the process of accepting TAGANA members, making the selection process more objective, fast, and efficient. This system is also able to present information on the results of the selection in a transparent and easily accessible manner through an online platform called SPEKTA.Keywords: Decision Support System; TOPSIS; Disaster Preparedness Cadets; member admission; website-based;
Rancang Bangun M-Commerce untuk Pemasaran Daging Sapi di Kabupaten Timor Tengah Utara Bertha Virginia Rusae; Darsono Nababan; Krisantus Jumarto Tey Seran
Jurnal Nasional Komputasi dan Teknologi Informasi (JNKTI) Vol 8, No 1 (2025): Februari 2025
Publisher : Program Studi Teknik Komputer, Fakultas Teknik. Universitas Serambi Mekkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32672/jnkti.v8i1.8489

Abstract

Abstrak - Perkembangan Teknologi Informasi dan Komunikasi (TIK), khususnya Mobile Commerce (M-Commerce), telah membawa perubahan signifikan dalam bisnis dan pemasaran. Aplikasi mobile mempermudah transaksi jual beli tanpa batasan waktu dan tempat. Di Kabupaten Timor Tengah Utara (TTU), sektor pertanian dan peternakan masih menghadapi tantangan dalam penerapan pemasaran digital. Untuk itu, dikembangkan Aplikasi Pemasaran Daging Sapi (APDAS) berbasis Android, yang memfasilitasi transaksi antara penjual dan pembeli dengan fitur harga, stok, pemesanan, dan pembayaran langsung. Aplikasi ini dibangun dengan Metode Prototype, yang memungkinkan interaksi antara pen dan pengguna, memastikan hasil akhir sesuai kebutuhan. Pengujian sistem dilakukan dengan melibatkan 3 orang (admin, penjual, pembeli), yang menunjukkan bahwa APDAS dapat berfungsi dengan baik dan siap digunakan. Diharapkan, aplikasi ini dapat meningkatkan efisiensi pemasaran produk daging sapi di TTU.Kata kunci: Pemasaran, Daging Sapi, Metode Prototype, M-Commerce. Abstract - The rapid development of information and communication technology (ICT), particularly mobile commerce (m-commerce), has significantly transformed business and marketing. Mobile applications facilitate transactions without time and location constraints. In Timor Tengah Utara (TTU) Regency, the agriculture and livestock sector still faces challenges in implementing digital marketing due to limited knowledge. To address this, the Beef Marketing Application (APDAS) based on Android was developed to facilitate transactions between sellers and buyers with features such as price, stock, ordering, and direct payment. This application was developed using the Prototype method, which allows interaction between developers and users, ensuring the final product meets user needs. System testing was conducted involving 3 participants (admin, seller, buyer), demonstrating that APDAS functions well and is ready for use. It is expected that this application will improve the efficiency of beef marketing in TTU.Keywords: Marketing, Beef, Prototype Method, M-Commerce.
Penerapan Metode Forward Chaining dalam Mediagnosis Penyakit pada Ternak Babi Ullu, Hevi Herlina; Tey Seran, Krisantus Jumarto
Jurnal Informatika Universitas Pamulang Vol 10 No 3 (2025): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32493/jiup.v10i3.35317

Abstract

The The pig population in North Central Timor (TTU) Regency in 2025 reached 111,704, making pig farming one of the main sources of livelihood for the local community. However, farmers often experience substantial losses due to high livestock mortality rates during disease outbreaks. This situation is largely attributed to the limited knowledge of pig farmers regarding disease symptoms and types, as well as limited access to information on early disease management. This study aims to develop a pig disease diagnostic application capable of identifying disease types based on observable symptoms and providing recommendations for initial treatment and preventive measures. The application was developed using the Rapid Application Development (RAD) method to accelerate system design and implementation. Meanwhile, the Forward Chaining method was applied as a fact-finding technique to infer accurate conclusions regarding disease types based on symptoms. The results of this study include a web-based pig disease diagnostic application that implements symptom tracking using forward chaining, enabling farmers to independently identify pig diseases more quickly and accurately. The developed application is expected to help reduce pig mortality rates and improve the efficiency of livestock production, particularly pig farming in TTU Regency.
Decision support system for superior livestock commodities in North Central Timor using Fuzzy Topsis method Taek, Sisilia Novita Aryenny; Kelen, Yoseph Pius Kurniawan; Tey seran, Krisantus Junarto
Jurnal Simantec Vol 14, No 1 (2025): Jurnal Simantec Desember 2025
Publisher : Universitas Trunojoyo Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21107/simantec.v14i1.30059

Abstract

The livestock sector plays a crucial role in supporting regional economic development, including in North Central Timor (TTU) Regency, East Nusa Tenggara. Currently, the selection of superior livestock commodities in this area is still carried out manually, which results in slow, inefficient, and error-prone decision-making processes. Therefore, a system is needed to assist in making decisions more accurately and objectively. This study aims to develop a web-based Decision Support System (DSS) to analyze and determine superior livestock commodities in TTU Regency using the Fuzzy Technique for Order Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) method. The system was developed using the Waterfall model and implemented with PHP and MySQL. The decision criteria include productivity, market potential, production cost, environmental sustainability, and infrastructure support. The livestock alternatives considered in the analysis are cattle, goats, pigs, chickens, sheep, and horses. The implementation results show that beef cattle achieved the highest preference score of 0.76, making it the most superior livestock commodity in the region. This system provides easy access to accurate and real-time data for users and facilitates more effective and efficient decision-making. It also minimizes human error and speeds up the analysis process. With this system, stakeholders and livestock-related agencies can make better-informed decisions, improve resource management, and support sustainable development in the local livestock sector.Keywords: Decision Support System, Leading Commodities, Livestock, Fuzzy TOPSIS
Sistem Pakar Diagnosa Tingkat Depresi Mahasiswa Tugas Akhir dengan Algoritma Teorema Bayes Krisantus Jumarto Tey Seran; Hevi Herlina Ullu
Progresif: Jurnal Ilmiah Komputer Vol 21, No 1 (2025): Februari
Publisher : STMIK Banjarbaru

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35889/progresif.v21i1.2454

Abstract

Students at Timor University consistently face the challenge of Final Projects. This presents a unique hurdle, and a significant number of students experience depression during this phase. Consequently, this impacts the smooth progression of guidance and the graduation rate for each semester. Therefore, early detection and prevention measures are crucial for students in the final project phase. This effort involves developing a web-based expert system to facilitate the identification of depression levels in students by their supervisors. The expert system utilizes Bayes' Theorem to provide an accuracy rating for the level of depression experienced by a student based on observable symptoms. The system development employs the Rapid Application Development (RAD) methodology. The research data comprises 28 symptom data points and three levels of depression (Mild, Moderate, Severe). System testing results demonstrate its effectiveness in measuring the depression levels of students at Timor University with an accuracy rate of 84%.Keywords: Student; Depression; Expert System; Theorem Bayes   AbstrakMahasiswa Universitas Timor selalu dihadapkan dengan persoalan Tugas Akhir. Hal ini tentunya menjadi tantangan sehingga mengakibatkan mahasiswa mengalami depresi pada saat melaksanakan tugas akhir. Akibatnya, berpengaruh dalam kelancaran proses bimbingan serta persentase kelulusan untuk setiap periode wisuda kampus. Untuk itu perlu dilakukan pencegahan (deteksi) dini bagi mahasiswa yang sedang dalam periode tugas akhir. Upaya yang dilakukan adalah dengan membangun sistem pakar berbasis website yang mempermudah dosen pembimbing dalam mendeteksi tingkat depresi yang dialami seorang mahasiswa. Sistem pakar yang dibangun menggunakan Teorema Bayes untuk memberikan nilai akurasi pada tingkatan mana seorang mahasiswa berada berdasarkan gejala yang terlihat dan Metode RAD dalam pengembangan sistem. Data penelitian yang digunakan adalah 28 data gejala dan tiga tingkatan depresi (Ringan, Sedang, Tinggi). Hasil pengujian sistem membuktikan bahwa sistem ini dapat digunakan untuk mengukur tingkat depresi mahasiswa di Universitas Timor dengan tingkat persentase 84%. Kata kunci: Mahasiswa; Depresi; Sistem Pakar; Teorema Bayes