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Model Prototype Aplikasi Monitoring Tugas Akhir (MonTA) Mahasiswa pada STTI NIIT Ristasari Dwi Septiana; Fajar Septian
Jurnal Informatika Universitas Pamulang Vol 4, No 2 (2019): JURNAL INFORMATIKA UNIVERSITAS PAMULANG
Publisher : Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (329.448 KB) | DOI: 10.32493/informatika.v4i2.2825

Abstract

Services for students' final tasks are very important to increase the number of graduates to be achieved by Universities. The problem faced is knowing the progress of the students' final task. The objective of this research was to build an application for monitoring the students' final task using a prototype model at STTI NIIT. The Prototype model in this research used to identify what services should be given to users. The collection of user needs is done by using the business model analysis technique to see the business processes that are occurring. Then build the prototype application model based on the requirements analysis. Function testing in this application is done by black-box testing, all of which functions can run well. Prototype this application can monitor the progress of students' final task. This application also can present consulting services for students' final task.
Klasifikasi Anomali Intrusion Detection System (IDS) Menggunakan Algoritma Naïve Bayes Classifier dan Correlation-Based Feature Selection Saipul Anwar; Fajar Septian; Ristasari Dwi Septiana
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol 2, No 4 (2019): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (347.383 KB) | DOI: 10.32493/jtsi.v2i4.3453

Abstract

Intrusion Detection System (IDS) is useful for detecting an attack or disturbance on a network or information system. Anomaly detection is a type of IDS that can detect a deviate attack on the network based on statistical probability. The increasing use of the internet also increases interference or attacks from intruders or crackers that exploit weak internet protocols and application software. When many data packets arrive, a problem arises that needs to be analyzed. The right technique to analyze the data package is data mining. This study aims to classify IDS anomalies using the Naïve Bayes classification algorithm from the results of attribute selection with correlation-based feature selection. This study uses a UNSW-NB15 intrusion detection system data collection consisting of 49 attributes and 321,283 data records. Performance measurements are based on accuracy, precision, F-Measure and ROC Area. The results of attribute selection with correlation-based feature selection leave 4 attributes. The results of the evaluation of IDS anomaly classification using the naïve Bayes algorithm without the precedence of the attributes selected by the correlation technique obtained an accuracy rate of 71.2%. While the classification results if preceded by the attributes selected by the correlation technique obtained an accuracy of 74.8%. Classification with the naïve Bayes algorithm can be improved its accuracy which is preceded by the selection of attributes with correlation techniques.
Analisis Sentimen Vaksinasi Covid-19 Pada Twitter Menggunakan Naive Bayes Classifier Dengan Feature Selection Chi-Squared Statistic dan Particle Swarm Optimization Ristasari Dwi Septiana; Agung Budi Susanto; Tukiyat Tukiyat
Jurnal SISKOM-KB (Sistem Komputer dan Kecerdasan Buatan) Vol. 5 No. 1 (2021): Volume V - Nomor 1 - September 2021
Publisher : Teknik Informatika

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47970/siskom-kb.v5i1.228

Abstract

Tingginya penyebaran Covid-19 semakin berdampak pada bidang kesehatan, ekonomi, bahkan bidang pendidikan di Indonesia, sehingga pemerintah Indonesia melakukan tindakan vaksinasi Covid-19 guna menekan tingkat penyebaran Covid-19 di Indonesia. Namun hal tersebut dinilai kotroversial sehingga menarik perhatian masyarakat untuk memberikan opini di berbagai media seperti media sosial twitter. Sehingga membutuhkan analisa sentimen masyarakat terhadap upaya pemerintah pada tindakan vaksinasi Covid-19 untuk mencapai hasil prediksi dengan nilai akurasi paling optimal. Proses crawling secara otomatis menggunakan tools Rapidminer akan mengambil data tweets yang mengandung 5 (lima) kata kunci, yaitu “Vaksin Sinovac”, “Vaksin Astrazeneca”, “Vaksin Moderna”, “Vaksin Merah Putih”, dan “Vaksinasi Covid-19”. Dataset tweets didapatkan dari tanggal 4 Agustus 2021 sampai 12 Agustus 2021. Dataset diperoleh sejumlah 2060 tweets dan diberi label secara manual didapatkan jumlah tweet sebanyak 1193 sentimen positif, 73 negatif, dan 794 netral. Data tersebut dianalisa dengan menggunakan Metode Feature Selection Chi-Squared Statistic dan Particle Swarm Optimization (PSO) untuk mengurangi atribut yang kurang relevan pada saat proses klasifikasi dengan algoritma Naive Bayes Classifier (NBC). Hasil pengujian menunjukan bahwa Algoritma Naive Bayes Classifier (NBC) tanpa Feature Selection mendapatkan nilai akurasi 63,69%. Hasil penelitian menunjukkan bahwa Algoritma Naive Bayes Classifier (NBC) dengan Feature Selection Chi-Squared Statistic mempunyai tingkat akurasi 69,13%. Sedangkan hasil pengujian algoritma Naive Bayes Classifier (NBC) dengan Particle Swarm Optimization mempunyai tingkat akurasi 66,02%. Dengan demikian hasil seleksi fitur Chi-Squared Statistic mendapatkan nilai akurasi yang lebih baik jika dibandingkan dengan Particle Swarm Optimization untuk proses klasifikasi algoritma Naive Bayes Classifier (NBC) dengan selisih akurasi 3,11%.
Implementasi Algoritma Greedy dan Algoritma A* Untuk Penentuan Cost Pada Routing Jaringan Ristasari Dwi Septiana; Dimas Abisono Punkastyo; Nurhasan Nugroho
KLIK: Kajian Ilmiah Informatika dan Komputer Vol. 3 No. 2 (2022): Oktober 2022
Publisher : STMIK Budi Darma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30865/klik.v3i2.576

Abstract

The current increase in internet development raises new problems in terms of path optimization on the internet. This makes network path optimization a major problem in choosing the shortest route. The purpose of this research is to understand and compare the process of finding the shortest route using two algorithms, namely Greedy and A*. The A* algorithm has an advantage in overcoming network workloads compared to the Greedy algorithm. In implementation, both algorithms have the same results in determining the delivery path. However, the A* algorithm is more effective for use on large and complex networks because it has more certain and accurate calculations. From the test results, it was found that the A* algorithm has better performance than the greedy algorithm in the test. Where the final cost value of the greedy algorithm is 49, while for the A* algorithm is 48
PENYULUHAN DAN LAYANAN DETEKSI DINI PENYAKIT TIDAK MENULAR BAGI MASYARAKAT KELURAHAN ROA MALAKA Sucahyo, Nur; Artini, Ni Made; Tatyana, Tatyana; Darwanti, Dhenok; Rochendi, Teddy; Broto, Satrio; Sari, Jamah; Kurniati, Ike; Dharmalau, Andy; Sopian, Adi; Septiana, Ristasari Dwi
SWADIMAS: JURNAL PENGABDIAN KEPADA MASYARAKAT Vol 2, No 1 (2024): SWADIMAS EDISI JANUARI 2024
Publisher : Institut Teknologi dan Bisnis Swadharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56486/swadimas.vol2no1.443

Abstract

In Indonesia, the mortality rate due to non-communicable diseases (NCDs) is increasing. Non-communicable diseases (NCDs) are types of diseases that are not caused by germ infections. It is a chronic or catastrophic disease that can cause economic disruption for the sufferer due to the length of treatment and can cause limb disabilities. Various non-communicable diseases like heart disease, cancer, diabetes, stroke, and others. Routine basic health checks are one way to prevent non-communicable diseases. The community service program provides free basics health services in collaboration with the Puskesmas of Roa Malaka village by providing health services including checking blood pressure, blood sugar, uric acid, and cholesterol. The results of this community service activity carried out by ITB Swadharma are beneficial for the Roa Malaka health center to detect diseases that may appear in the community so that preventive action can be taken by providing various drugs needed.Di Indonesia, angka kematian akibat dari penyakit tidak menular (PTM) semakin meningkat. Penyakit tidak menular (PTM) merupakan jenis penyakit yang bukan disebabkan oleh infeksi kuman. Penyakit ini termasuk kronik atau katastropik yang dapat menyebabkan gangguan ekonomi bagi penderitanya karena lamanya perawatan dan dapat menyebabkan cacat pada anggota tubuh. Macam penyakit tidak menular seperti penyakit jantung, kanker, diabetes, stroke dan lain lain. Pemeriksaan kesehatan dasar secara rutin, merupakan salah satu cara pencegahan berbagai macam penyakit tidak menular. Program pengabdian kepada masyarakat yang dilakukan menyediakan layanan kesehatan dasar secara gratis bekerja sama dengan Puskesmas kelurahan Roa Malaka dengan memberikan layanan kesehatan diantaranya pengecekan tekanan darah, gula darah, asam urat, dan kolesterol. Hasil kegiatan pengabdian kepada masyarakat yang dilakukan oleh ITB Swadharma ini sangat membantu puskesmas Roa Malaka untuk mendeteksi penyakit yang kemungkinan muncul di masyarakat, sehingga dapat diambil tindakan preventif dengan menyediakan berbagai obat yang dibutuhan.
Sistem Pendukung Keputusan Pemilihan Software House Menggunakan Pendekatan Additive Ratio Assessment Septian, Fajar; Septiana, Ristasari Dwi; Setiyani, Hari; Arisantoso
JURNAL FASILKOM Vol. 14 No. 2 (2024): Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
Publisher : Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37859/jf.v14i2.7255

Abstract

Dalam era digital yang semakin maju, kebutuhan akan perangkat lunak berkualitas tinggi menjadi sangat penting bagi organisasi untuk mendukung operasi bisnis, meningkatkan efisiensi, dan menyediakan solusi inovatif. Pemilihan software house yang tepat menjadi keputusan strategis yang krusial namun menantang karena banyaknya pilihan yang tersedia. Kesalahan dalam pemilihan dapat berdampak negatif, seperti penundaan proyek dan overbudget. Penelitian ini bertujuan untuk pengembangan Sistem Pendukung Keputusan (SPK) untuk pemilihan software house menggunakan pendekatan Additive Ratio Assessment (ARAS). Metode ARAS dipilih karena keunggulannya dalam mengevaluasi berbagai kriteria secara menyeluruh dan simultan. Penelitian ini menghasilkan sistem yang dapat menilai alternatif berdasarkan kriteria yang telah ditentukan, memberikan bobot sesuai tingkat kepentingan, dan menghasilkan peringkat untuk memudahkan pengambil keputusan. Hasil output sistem untuk studi kasus ini diperoleh nilai tertinggi yaitu JMC Indonesia (A3) dengan skor tingkat relatif kinerja yaitu 0,9041. Hasil tersebut sama dengan perhitungan manual, Ini menunjukkan bahwa SPK yang dibangun menunjukkan kevalidan dalam perhitungannya. Selain itu, pada uji usability menunjukkan bahwa SPK yang dikembangkan memiliki skor usability rata-rata 88,75%, yang masuk dalam kategori "Excellent", menandakan sistem ini intuitif dan mudah digunakan.
Sistem Pendukung Keputusan Pemilihan Perumahan Menggunakan Kombinasi Metode ROC dan ARAS Septiana, Ristasari Dwi; Herdiansah, Arief; Septarini, Ri Sabti; Irfan, Muhammad
FORMAT Vol 14, No 2 (2025)
Publisher : Universitas Mercu Buana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22441/format.2025.v14.i2.005

Abstract

Selecting a suitable house is a multifaceted process that involves several considerations, including cost, location, available facilities, security, and access to transportation. Because decisions are often made subjectively, there is a risk of inefficiency, which highlights the need for a structured decision-making approach. This study presents the development of a web-based decision support application that combines the Rank Order Centroid (ROC) method for assigning criterion weights based on their priority order, and the Additive Ratio Assessment (ARAS) method for evaluating and ranking housing alternatives based on relative utility scores. The system was implemented using PHP and MySQL, incorporating modules for managing criteria, alternatives, inputting evaluations, and generating automated calculations and visual outputs. A case study with five housing options and five main evaluation criteria was conducted. The research employed a structured methodology involving problem identification, criteria selection, weight calculation using ROC, alternative evaluation using ARAS, system development, and black-box testing for validation. The findings revealed that Taman Permata achieved the highest utility score of 0.8616, placing it as the top-ranked alternative. Functional testing through a black-box approach verified that all components operated as intended. Overall, the system offers a transparent and effective tool to support users in identifying the most appropriate housing option according to their individual needs and priorities.
APLIKASI PEMBAYARAN UANG SEKOLAH PADA SEKOLAH RAINBOWS BERBASIS ANDROID Nurlaela, Lela; Septiana, Ristasari Dwi; Oktaviani, Rahayu
JEIS: Jurnal Elektro dan Informatika Swadharma Vol 4, No 1 (2024): JEIS EDISI JANUARI 2024
Publisher : Institut Teknologi dan Bisnis Swadharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56486/jeis.vol4no1.452

Abstract

SPP is one of the obligations of every student who is still actively studying at the school. Recording tuition payments at Rainbows School is inefficient because it still uses a manual system that requires a lot of paper. The research aims to design an application that can upload proof of payment online, record tuition bills, and facilitate administrators in making payment reports. Methods or procedures carried out in collecting data by conducting field studies. The data collection technique is to conduct interviews with those who directly handle existing student data to obtain information about payment data, the process of storing reports from parents, and parents who want to provide proof of transactions regarding payments at school. The result is the android application of a tuition payment application at Rainbows School with a code that uses block programming so that the tuition payment process becomes more efficient and practical. After testing the system made runs well and smoothly.SPP merupakan salah satu bentuk kewajiban setiap siswa yang masih aktif disekolah tersebut. Pencatatan pembayaran SPP pada Sekolah Rainbows yang tidak efisien, disebabkan masih menggunakan sistem manual sehingga membutuhkan banyak kertas. Tujuan penelitian untuk merancang aplikasi yang mampu mengupload bukti pembayaran secara online, mencatat tagihan uang sekolah, serta memudahkan administrator dalam membuat laporan pembayaran. Metode atau prosedur yang dilakukan dalam melakukan pengumpulan data dengan melakukan studi lapangan. Teknik pengumpulan data adalah dengan melakukan wawancara dengan yang menangani secara langsung data-data siswa yang ada untuk mendapat informasi tentang data pembayaran, proses penyimpanan laporan dari orang tua murid, dan juga orang tua yang ingin memberikan bukti transaksi perihal pembayaran di sekolah. Hasilnya sebuah aplikasi berbasis android untuk pembayaran uang sekolah pada Sekolah Rainbows dengan kodular yang menggunakan block programming sehingga proses pembayaran uang sekolah menjadi lebih efisien dan praktis. Setelah melakukan uji coba sistem yang dibuat berjalan dengan baik dan lancar.
Klasifikasi Anomali Intrusion Detection System (IDS) Menggunakan Algoritma Naïve Bayes Classifier dan Correlation-Based Feature Selection Anwar, Saipul; Septian, Fajar; Septiana, Ristasari Dwi
Jurnal Teknologi Sistem Informasi dan Aplikasi Vol. 2 No. 4 (2019): Jurnal Teknologi Sistem Informasi dan Aplikasi
Publisher : Program Studi Teknik Informatika Universitas Pamulang

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

Abstract

Intrusion Detection System (IDS) is useful for detecting an attack or disturbance on a network or information system. Anomaly detection is a type of IDS that can detect a deviate attack on the network based on statistical probability. The increasing use of the internet also increases interference or attacks from intruders or crackers that exploit weak internet protocols and application software. When many data packets arrive, a problem arises that needs to be analyzed. The right technique to analyze the data package is data mining. This study aims to classify IDS anomalies using the Naïve Bayes classification algorithm from the results of attribute selection with correlation-based feature selection. This study uses a UNSW-NB15 intrusion detection system data collection consisting of 49 attributes and 321,283 data records. Performance measurements are based on accuracy, precision, F-Measure and ROC Area. The results of attribute selection with correlation-based feature selection leave 4 attributes. The results of the evaluation of IDS anomaly classification using the naïve Bayes algorithm without the precedence of the attributes selected by the correlation technique obtained an accuracy rate of 71.2%. While the classification results if preceded by the attributes selected by the correlation technique obtained an accuracy of 74.8%. Classification with the naïve Bayes algorithm can be improved its accuracy which is preceded by the selection of attributes with correlation techniques.
PEMBUATAN VIDEO KEGIATAN TIM PENGERAK PKK KELURAHAN ROA MALAKA Fitriansyah, Ahmad; Nurlaela, Lela; Trilaksono, Agustinus Rio; Septiana, Ristasari Dwi
SWADIMAS: JURNAL PENGABDIAN KEPADA MASYARAKAT Vol 3, No 1 (2025): SWADIMAS EDISI JANUARI 2025
Publisher : Institut Teknologi dan Bisnis Swadharma

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56486/swadimas.vol3no1.710

Abstract

This community service activity aims to publish and document the activities of the PKK (Family Welfare Movement) team of Roa Malaka Village. Using the Service Learning (SL) method, ITB Swadharma students provide services to the community as part of their learning process. Through a participatory and collaborative approach, the activities were carried out in stages: Problem and Need Identification, Activity Planning, Activity Implementation, and Activity Evaluation. The results of the activities are in the form of two videos. The first video features the PKK of Roa Malaka sub-district engaging in a simulation game of Child and Adolescent Parenting Patterns (PAAR), and the second video is a documentation of activities from working group one to working group four and the secretary. The results of these activity videos were then uploaded to the YouTube page to promote the activities of the PKK Roa Malaka Village.Kegiatan pengabdian masyarakat ini bertujuan untuk melakukan publikasi dan dokumentasi terhadap kegiatan-kegiatan yang dilakukan oleh tim pengerak PKK Kelurahan Roa Malaka. Menggunakan metode Service Learning (SL) dimana mahasiswa ITB Swadharma dilibatkan dalam memberikan pelayanan kepada masyarakat sebagai bagian dari pembelajaran mahasiswa tersebut. Melalui pendekatan partisipatif dan kolaboratif, kegiatan dilakukan dengan tahapan Identifikasi Masalah dan Kebutuhan, Perencanaan Kegiatan, Pelaksanaan Kegiatan, dan  Evaluasi Kegiatan. Hasil kegiatan berupa dua buah video, video pertama berisi tayangan tim pengerak PKK kelurahan Roa Malaka yang melakukan permainan simulasi Pola Asuh Anak dan Remaja (PAAR) dan video kedua adalah video dokumentasi kegiatan dari pokja satu sampai pokja empat dan sekretaris. Hasil video kegiatan ini kemudian diunggah ke laman Youtube untuk mempromosikan kegiatan tim penggerak PKK Kelurahan Roa Malaka