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All Journal Jurnal Simantec Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer Justek : Jurnal Sains Dan Teknologi Jurnal Saintek Lahan Kering Jurnal Informatika Universitas Pamulang Jurnal Nasional Komputasi dan Teknologi Informasi Progresif: Jurnal Ilmiah Komputer Zonasi: Jurnal Sistem Informasi JATI EMAS (Jurnal Aplikasi Teknik dan Pengabdian Masyarakat) BERNAS: Jurnal Pengabdian Kepada Masyarakat Bakti Cendana: Jurnal Pengabdian Masyarakat Aiti: Jurnal Teknologi Informasi Jurnal Pengabdian kepada Masyarakat Nusantara Jurnal Generic Jurnal Restikom : Riset Teknik Informatika dan Komputer Journal Social Science And Technology For Community Service HOAQ (High Education of Organization Archive Quality) : Jurnal Teknologi Informasi Journal Of Information And Technology Unimor (JITU) Jurnal Sains Teknologi dan Sistem Informasi JURNAL REKAYASA INFORMASI SWADHARMA (JRIS) Adopsi Teknologi dan Sistem Informasi SisInfo : Jurnal Sistem Informasi dan Informatika Majalah Ilmiah METHODA Prosiding Seminar Riset Mahasiswa Journal of Informatics and Computing JIKTEKS : Jurnal Ilmu Komputer dan Teknologi Informasi Jurnal Informasi Ilmu Komputer (JIIK)
Tey Seran, Krisantus Jumarto
Program Studi Teknologi Informasi, Universitas Timor
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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.
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  
Analisis Perbandingan Algoritma K-Means dan K-Medoids dalam Penentuan Status Gizi Balita Krisantus uamrto Tey Seran; Jefania Tilman Soares; Fetronela Rambu Bobu; Debora Chrisinta
JIKTEKS : Jurnal Ilmu Komputer dan Teknologi Informasi Vol. 4 No. 02 (2026): April
Publisher : Faatuatua Media Karya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70404/jikteks.v4i02.648

Abstract

Nutritional status in toddlers is an important indicator in determining child growth and development quality. Inaccurate classification of nutritional status can affect early intervention efforts. This study aims to compare the performance of K-Means and K-Medoids algorithms in clustering toddler nutritional status data at Puskesmas Betun. The dataset consists of 1,036 toddler records with variables including age, weight, height, and mid-upper arm circumference (MUAC). Data preprocessing was conducted through normalization before clustering. The performance of both algorithms was evaluated using the Davies Bouldin Index (DBI). The results show that K-Means converged in 24 iterations with a DBI value of 1.0281, while K-Medoids converged in 6 iterations with a DBI value of 1.1236. Based on the DBI evaluation, K-Means produced better clustering performance compared to K-Medoids. Therefore, K-Means is more suitable for determining toddler nutritional status in this study.
Penerapan Metode Forward Chaining dalam Mediagnosis Penyakit pada Ternak Babi Hevi Herlina Ullu; Krisantus Jumarto Tey Seran
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.
KLASTERISASI MODEL PEMBELAJARAN DI UNIVERSITAS TIMOR MENGGUNAKAN METODE K-MEANS: CLUSTERING OF LEARNING MODELS AT UNIVERSITAS TIMOR USING THE K-MEANS METHOD Seran, Krisantus Jumarto Tey; Fallo, Glorita D.R.M; Ludji, Dian Grace; Chrisinta, Debora
HOAQ (High Education of Organization Archive Quality) : Jurnal Teknologi Informasi Vol. 17 No. 1 (2026): Jurnal HOAQ - Teknologi Informasi
Publisher : STIKOM Uyelindo Kupang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52972/hoaq.vol17no1.p121-130

Abstract

Penelitian ini bertujuan untuk mengidentifikasi pola model pembelajaran di Universitas Timor menggunakan metode K-Means. Lima variabel utama yang digunakan dalam klasterisasi meliputi metode pembelajaran, jenis evaluasi, ketersediaan sumber daya, tingkat kepuasan, dan fleksibilitas waktu belajar. Data primer diperoleh dari 1.018 mahasiswa aktif melalui kuesioner skala Likert. Jumlah klaster optimal ditentukan menggunakan metode Elbow, yang menghasilkan dua klaster utama. Klaster 1 didominasi oleh mahasiswa yang memilih pembelajaran offline dengan pendekatan diskusi dan evaluasi berupa tugas individu. ketersediaan sumber daya masih terbatas, tingkat kepuasan tinggi dan fleksibilitas waktu belajar sangat baik. Klaster 2 juga menunjukkan preferensi terhadap pembelajaran offline dengan metode pendekatan dosen berupa diskusi jenis evaluasinya tugas individu. Sumber daya baru sebagian yang terpenuhi , dengan tingkat kepuasan yang baik dan fleksibilitas waktu belajar yang cukup baik. Evaluasi kualitas hasil klaster menggunakan metode Silhouette Coefficient menghasilkan nilai 0,3377, yang termasuk dalam kategori Weak Structure. Hasil penelitian ini diharapkan dapat menjadi bahan pertimbangan dalam pengembangan kebijakan pembelajaran dan penyusunan kurikulum yang lebih sesuai dengan karakteristik mahasiswa.   This study aims to identify learning pattern types at the University of Timor using the K-Means clustering method. Five main variables were used in the clustering process, including learning method, type of evaluation, availability of resources, student satisfaction, and time flexibility. Primary data were obtained from 1,018 active students through a Likert-scale questionnaire. The optimal number of clusters was determined using the Elbow method, which resulted in two main clusters. Cluster 1 is dominated by students who prefer offline learning with a discussion-based approach and individual task evaluation. Resource availability is still limited, but the level of satisfaction is high, and learning time flexibility is considered very good. Cluster 2 also shows a preference for offline learning with a discussion-based teaching approach and individual task evaluation. However, resource availability is only partially met, with good satisfaction levels and fairly good time flexibility. The quality of the clustering results was evaluated using the Silhouette Coefficient method, which produced a score of 0.3377, categorized as a Weak Structure. The results of this study are expected to serve as a consideration in developing learning policies and curriculum planning that better align with student characteristics.
Co-Authors Abi, Maria Oktavian Achmad Fariz Amsikan, Dionisius K. Anastasia Kadek Dety Lestari Bana, Yoseph Arianto Banusu, Lusitania Baso, Budiman Bertha Virginia Rusae Blegur, Willem Amu Chrisinta, Debora Da Conceicao, Fedelia Da Debora Chrisinta Dewi Kristiani Asuat Dian Grace Ludji Dionisius K. Amsikan Fallo, Glorita D.R.M Fallo, Kristoforus Fetronela Rambu Bobu Fetronela Rambu Bobu Fried Markus Allung Blegur Gelu, Leonard Peter Hevi Herlina Ullu Hevi Herlina Ullu Isto, Kristoforus Boik Tani'i Jefania Tilman Soares Knaofmone, Maria Letitia Kristoforus Fallo Lake, Delviana Leonard Peter Gellu Mammi Sarlota Bana Margaretha Baria Maria Grestiana Sani Maria Ilona Silab Maria Yosefa Sena Marjeni Liana Nino Martins, Alfiana Fontes Matute, Alejandro Jr. V. Mau, Lidia Marselina Mirja Hoar Moensaku, Emanuel Nababan, Darsono Nahak, Agustinus Yasvin Nahak, Maria Selviyanti H Nahak, Roswita R.K. Natalia Karmila Ketmoen nggadas, carles Nikolas Abi Nurliah Apryanti Oktavianus Klau Lekik Patricia Gertrudis Manek Risald Sae, Ina Rai Salu, Yoana Fransiska De Cantal Sesfao, Yusmiati Farida severinus ponis Spanyoli Muriano Fuel Stefanus Lau Manek Taek, Sisilia Novita Aryenny Taitoh, Rosalinda Hoar Usnaat, Sonya Oktavia Victoria Nova Naiheli Willem Amu Blegur Willem Amu Blegur Yasinta O.L Rema Yeni M Kabnani Yoseph P. K. Kelen Yoseph Pius Kurniawan Kelen Yuliana A.T Naitkakin Yulsiani Sanam