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All Journal International Journal of Electrical and Computer Engineering TEKNIK INFORMATIKA Jurnal Simetris Bulletin of Electrical Engineering and Informatics Explore: Jurnal Sistem Informasi dan Telematika (Telekomunikasi, Multimedia dan Informatika) Jurnal Pengabdian Kepada Masyarakat Sakai Sambayan WARTA KLIK (Kumpulan jurnaL Ilmu Komputer) (e-Journal) Science and Technology Indonesia JOIV : International Journal on Informatics Visualization INTENSIF: Jurnal Ilmiah Penelitian dan Penerapan Teknologi Sistem Informasi Jurnal Komputasi Jurnal Teknoinfo Jurnal Tekno Kompak Journal of Electronics, Electromedical Engineering, and Medical Informatics Jurnal Pengabdian Kepada Masyarakat (JPKM) Tabikpun Buguh: Jurnal Pengabdian Kepada Masyarakat International Journal of Electronics and Communications Systems Jurnal Pepadun Journal of Data Science and Software Engineering Warta LPM Laporan Upaya Nyata Inovasi Ilmu Komputer (LUNIK) Integra: Journal of Integrated Mathematics and Computer Science

Lumbanraja, Favorisen R

Jurusan Ilmu Komputer, Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Lampung

Author-ID : 3250375

Agriculture, Biological Sciences & Forestry Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Materials Science & Nanotechnology Mathematics Medicine & Pharmacology Physics Social Sciences Other

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PREDIKSI JUMLAH PENDERITA PENYAKIT TUBERKULOSIS DI KOTA BANDAR LAMPUNG MENGGUNAKAN METODE SVM (SUPPORT VECTOR MACHINE) Favorisen R. Lumbanraja; Ira Hariati Br Sitepu; Didik Kurniawan; Aristoteles Aristoteles
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 7, No 3 (2020)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v7i3.350

Tuberkulosis (TB atau TBC) merupakan salah satu penyakit infeksi yang disebabkan oleh Bakteri Mycobacterium tuberculosis. Bakteri tersebut merupakan bakteri yang sangat kuat sehingga dalam pengobatannya memerlukan waktu yang cukup lama. Pengobatan penyakit tuberkulosis dilakukan selama 6-9 bulan secara rutin dengan sedikitnya 3 macam jenis obat. Saat ini kebanyakan masyarakat menganggap batuk dalam jangka waktu berbulan-bulan merupakan batuk biasa, jika dicermati salah satu gejala yang ditimbulkan penyakit tuberkulosis, yaitu batuk dalam jangka waktu yang panjang. Pada penelitian ini digunakan data penderita tuberkulosis di Kota Bandar Lampung, data cuaca dan matrix jarak antara kejadian penderita tuberkulosis yang satu dengan kejadian yang lainnya dalam lingkup kecamatan. Jumlah dari keseluruhan data sebanyak 600 data dengan 44 variabel. Penelitian ini juga menggunakan 3 kernel yaitu, Linear, Gaussian, dan Polynomial dengan menggunakan Metode SVM dengan kernel Linear mendapatkan nilai rata-rata R2 sebesar 51.43 %, pada percobaan dengan metode SVM dengan kernel Gaussian mendapatkan nilai rata-rata R2 sebesar 58.53 % dan pada percobaan dengan metode SVM dengan kernel Polynomial mendapatkan nilai rata-rata R2 sebesar 36.03 %.Kata Kunci : Prediksi penderita tuberculosis, tuberculosis, Machine Learning, Support Vector Machine.Tuberculosis (TB / TBC) is one of infectious disease caused by Mycobacterium tuberculosis bacteria. These bacteria are very strong bacteria so for the treatment takes a long time. Tuberculosis treatment is carried out for 6-9 months regularly with at least 3 types of drugs. Currently, most of people consider a cough for months is a common cough, if looked by one of the symptoms caused by tuberculosis, which is a cough for a long time. In this research, data on tuberculosis patients in the city of Bandar Lampung were used, weather data and the distance matrix between the case of tuberculosis patients with other case within the district. The total number of data is 600 data with 44 variables. This research also uses 3 kernels namely, Linear, Gaussian, and Polynomial by using the SVM method with the Linear kernel getting an average R2 value of 51.43%, in the experiment with the SVM method with a gaussian kernel getting an average R2 value of 58.53% and at Experiments with the SVM method with the Polynomial kernel obtained an average value of R2 of 36.03% .Keywords : Prediction of tuberculosis sufferers, tuberculosis, Machine Learning, Support Vector Machine.

KLASIFIKASI ABSTRAK JURNAL KOMPUTASI MENGGUNAKAN METODE TEXT MINING DAN ALGORITMA SUPPORT VECTOR MACHINE Eliza Fitri; Favorisen R. Lumbanraja; Ardiansyah Ardiansyah
Jurnal Pepadun Vol. 1 No. 1 (2020): December
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Lampung

The University of Lampung especially Computer Science Departement has an online journal that publishes various scientific articles written by researchers both students and lecturers. This scientific article is called the online Computating Journal which is published once every 6 months. But, this online Computating Journal has not been structured and classified into the category of science that more specific. Therefore, in this research the abstract Computating Journal will be classified using text mining techniques to process the abstract become more structured and retrieve information in it. Then, the information in the abstract is extracted as a feature by the TFIDF weighting technique. The proposed classification model uses the support vector machine algorithm that has strong consistency. The model classification will be validated by applying the 10-Fold Cross Validation technique.

IDENTIFIKASI KAIN TAPIS LAMPUNG MENGGUNAKAN EKSTRAKSI FITUR EDGE DETECTION (CANNY) DAN KLASIFIKASI PROBABILITY NEURAL NETWORK (PNN) Admi Syarif; M. Juandhika Rizky; Rico Andrian; Favorisen R. Lumbanraja
Jurnal Pepadun Vol. 2 No. 1 (2021): April
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Lampung

Tapis fabric is a Lampung tribe women's clothing in the form of a sarong made of woven cotton threads with a sugi motif or decoration, silver thread or gold thread with an embroidery system. Lampung tapis is the result of woven cotton threads with motifs, silver threads or gold threads and becomes the typical clothing of the Lampung tribe. Tapis fabric can be distinguished by shape and pattern, each type has its own special characteristics. This study aims to identify the tapis fabric using Edge Detection feature extraction and Probability Neural Network (PNN) classification. Experiments were carried out using 525 images data, 450 images became training data, while the other 75 images became test data consisting of 3 types of filters Bintang Perak, Gunung Beradu, and Sasab. The results of the experiment are quite good. The smoothing value applied to the PNN has an effect on the accuracy.

KLASIFIKASI KEJADIAN HIPERTENSI DENGAN METODE SUPPORT VECTOR MACHINE (SVM) MENGGUNAKAN DATA PUSKESMAS DI KOTA BANDAR LAMPUNG Indah Pasaribu; Favorisen Rosyking Lumbanraja; Dewi Asiah Shofiana; Aristoteles Aristoteles
Jurnal Pepadun Vol. 2 No. 2 (2021): August
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Lampung

Hypertension is a condition in which a person experiences an increase in blood pressure above the normal value which causes pain and even death. Normal human blood pressure is 120/80 mmHg. Patients with hypertension cannot be cured, but prevention and control can be done. The hypertension cases are always increasing in Indonesia. The Bandar Lampung City Health Service stated that hypertension is a disease that always ranks in the top ten diseases in Bandar Lampung City. Diagnosis of hypertension is currently manually performed by requiring a lot of energy, materials, and time. Based on the condition, there is an idea to apply the field of biomedical data analysis to help diagnosing hypertension using the support vector machine (SVM) method in Bandar Lampung City. This study classifies and measures the accuracy of the support vector machine method in hypertension. The data comes from five health centers in Bandar Lampung City from 2017 to 2019 with 10-fold cross validation data sharing. The kernels used are linear, gaussian, and polynomial kernels. This study successfully classifies hypertension sufferers in Bandar Lampung City. The result of the highest feature correlation analysis is 0.90. The results of the classification using the support vector machine method get the highest accuracy, which is 99.78% on the gaussian kernel.

CLUSTERING K-MEANS JENIS KATA PADA LAPORAN KEGIATAN KULIAH KERJA NYATA (KKN) UNIVERSITAS LAMPUNG MENGGUNAKAN WORD2VEC Kristina Ademariana; Aristoteles Aristoteles; Favorisen Rosyking Lumbanraja; Rico Andrian
Jurnal Pepadun Vol. 2 No. 2 (2021): August
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Lampung

Kuliah Kerja Nyata (KKN) is a form of student service activities for the community, requesting and developing science and technology carried out off-campus within a period, linking work, and special requirements managed by the Badan Pelaksana Kuliah Kerja Nyata (BP-KKN). While carrying out KKN activities, each group of students is required to upload a report of the activities carried out in the village. In uploading the report file, there are several categories in each activity, including socialization, training, and character development. To classify the results of uploading activities one of which can be done using clustering techniques. In this research, a clustering of discussion on KKN student activities will be conducted at the University of Lampung. The text mining method is used to process KKN student activities to be more structured. Information on the KKN student activities was obtained as a feature with the Word2Vec weighting technique. The algorithm used is the K-Mean algorithm which has a high accuracy of the size of the object, so this algorithm is relatively more measurable and efficient for processing large numbers of objects. From the results of research conducted, it has been found that apply the text mining process algorithm for clustering with the K-means method on the Unila KKN Student activity data produces a value of k = 2, a lot of filtered data in the preprocess is 6284 data, using this method has not yet gotten a good association analysis because the results of the second cluster do not show the general types of words, typos and reporting activities by students who are not specifically can affect the results of clustering that is not good.

Pelatihan Desain Grafis untuk Peningkatan Keterampilan SDM Bagi Perangkat Desa Tambah Dadi Purbolinggo Lampung Timur Bambang Hermanto; Favorisen Rosyking Lumbanraja; Tristiyanto Tristiyanto; Febi Eka Febriansyah
Jurnal Pengabdian Kepada Masyarakat (JPKM) TABIKPUN Vol. 1 No. 1 (2020)
Publisher : Faculty of Mathematics and Natural Sciences - Universitas Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/jpkmt.v1i1.6

Perkembangan teknologi yang semakin pesat perlu diimbangi dengan peningkatan keterampilan sumber daya manusia, sehingga dapat memanfaatkan teknologi secara maksimal dalam berbagai kepentingan termasuk bagi warga atau aparatur desa Tambah Dadi Lampung Timur dalam melakukan tugas pelayanan kepada masyarakat. Diantara keterampilan yang penting dimiliki adalah teknik praktis desain grafis. Saat ini belum banyak warga/aparatur desa Tambah Dadi Lampung Timur yang memiliki keterampilan komputer, khususnya bidang desain grafis, sehingga proses pelatihan terkadang mengalami hambatan, namun hal ini tidak membuat patah semangat untuk terus belajar dengan menyimak penyampaian materi oleh narasumber. Setelah mengikuti pelatihan berdasarkan hasil post test pada 15 orang peserta uji yang dipilih secara acak, diperoleh peningkatan hasil kemampuan sebesar 20%. Dengan bertambahnya keterampilan, warga juga memiliki peluang berwirausaha dibidang jasa desain grafis.

IMPLEMENTASI METODE SIMPLE ADDITIVE WEIGHTING (SAW) PADA SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN RUMAH BERBASIS ANDROID Admi Syarif; Qory Aprilarita; Muhammad Rizki; Favorisen R Lumbanraja
Jurnal Tekno Kompak Vol 14, No 2 (2020): AGUSTUS
Publisher : Universitas Teknokrat Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33365/jtk.v14i2.796

The process of selecting house is a difficult thing to do, because there are many alternatives offered by developers. The purpose of this research is to build an Android-based decision support system that can help selection process involving ten criteria. The criteria used in this research are house prices, building area, land area, electricity, water sources, distance from market, distance from university, number of bedrooms, number of bathrooms, and number of floors. The system built applies Simple Additive Weighting (SAW) method. SAW is one of the well-known methods and is often used for multiple attribute decision making because of its simplicity in providing alternatives during the decision making process. Based on system performance testing, the results of accuracy is 85,7%, which at this time has been categorized as very good. Based on the results of alpha testing and beta testing, it can be concluded that application has worked and meets the level of user satisfaction, with value that is categorized as very good

PENENTUAN GRADE BIJI KOPI ROBUSTA MENGGUNAKAN ANALYTICAL HIERARCHY PROCESS Aristoteles Aristoteles; Favorisen R. Lumbanraja; Astria Hijriani; Meria Nensi
KLIK- KUMPULAN JURNAL ILMU KOMPUTER Vol 9, No 2 (2022)
Publisher : Lambung Mangkurat University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20527/klik.v9i2.470

Coffee beans are one of the raw materials as well as a result of planting by farmers which provides special benefits for the survival of the Indonesian people. Coffee is used as a refreshing drink ingredient and in today's life, coffee drinks have become a lifestyle for millennial people. The type of coffee that is widely cultivated is the robusta coffee bean type, because this robusta coffee is mostly produced in Indonesia, reaching 87.1% of the total coffee production in Indonesia. One of the largest producers of robusta coffee in Indonesia is the Dempo Pagar Alam Mountain Slope Coffee Plantation, South Sumatra. Therefore in this study using the type of robusta coffee beans which grade or quality will be determined according to the applied criteria. This study aims to determine the grade of robusta coffee beans in the Dempo Pagar Alam Mountain Slope Coffee Plantation in South Sumatra using the AHP (Analytical Hierarchy Process) method.The stages in this research are the preparation of research data collection, namely primary and secondary which are stored in a text file (.txt) with tens of data and the second stage is determining criteria and alternatives, compiling a hierarchical structure, compiling a paired comparison matrix, looking for priority vector values and eigen vectors, alternative ranking results, and accuracy testing. The results of this study are expected to provide benefits to see the results of the robusta coffee bean grade ranking in the Slope Coffee Plantation of Mount Dempo Pagar Alam, South Sumatra by using the AHP method. Keywords : Coffe Beans,Grade, AHP (Analytical Hierarchy ProcessBiji kopi merupakan salah satu bahan baku sekaligus sebagai hasil dari penanaman oleh petani yang memberikan manfaat tersendiri bagi kelangsungan hidup masyarakat Indonesia. Kopi dijadikan sebagai bahan minuman penyegar dan di kehidupan sekarang ini minuman kopi telah menjadi gaya hidup bagi masyarakat milenial. Adapun jenis kopi yang banyak dibudidayakan yaitu jenis biji kopi robusta, karena kopi robusta ini paling banyak diproduksi di Indonesia mencapai 87,1% dari total keseluruhan produksi kopi di Indonesia. Salah satu daerah penghasil jenis kopi robusta terbesar di Indonesia yaitu Perkebunan Kopi Lereng Gunung Dempo Pagar Alam Sumatera Selatan. Oleh karena itu dalam penelitian ini menggunakan jenis biji kopi robusta yang akan ditentukan grade atau kualitasnya sesuai dengan kriteria yang diterapkan.Penelitian ini memiliki tujuan untuk menentukan grade biji kopi robusta di Perkebunan Kopi Lereng Gunung Dempo Pagar Alam Sumatera Selatan dengan menggunakan metode AHP (Analytical Hierarchy Process). Tahapan dalam penelitian ini yaitu persiapan pengumpulan data penelitian yaitu primer dan sekunder yang disimpan di dalam file teks (.txt) dengan jumlah data puluhan dan tahap kedua adalah menentukan kriteria dan alternatif, penyusunan struktur hierarki, menyusun matriks perbandingan berpasangan, mencari nilai priority vector dan eigen vector, hasil perangkingan alternatif, dan pengujian akurasi. Hasil penelitian ini diharapkan dapat memberikan manfaat melihat hasil perangkingan grade biji kopi robusta yang ada di Perkebunan Kopi Lereng Gunung Dempo Pagar Alam Sumatera Selatan dengan merepakan metode AHP.Kata Kunci : Biji Kopi, Grade, AHP (Analytical Hierarchy Process)

RUMAH BELAJAR LANSIA: PUSAT PENGEMBANGAN DAN PENINGKATAN POTENSI LANJUT USIA DI KELURAHAN BUMI WARAS KOTA BANDAR LAMPUNG Aristoteles Aristoteles; Rinaldo Adi Pratama; Tiyara Saghira; Syangap Diningrat Sitompul; Ahyarudin; Jihan Aferiansyah; Aulia Putri Ariqa; Aflaha Asri; Admi Syarif; Kurnia Muludi; Favorisen R. Lumbanraja
BUGUH: JURNAL PENGABDIAN KEPADA MASYARAKAT Vol. 2 No. 2 (2022)
Publisher : Badan Pelaksana Kuliah Kerja Nyata Universitas Lampung

The neglected elderly is one of the impacts of the existing poverty problem, where poverty is not only limited to economic inability, but also the failure to fulfill basic rights and differences in treatment of a person or group of people in living a decent and dignified life. The method of writing this article uses a qualitative-descriptive approach to provide an overview as well as a description of the implementation of the team-based project “Rumah Belajar Lansia”. The implementation project of Rumah Belajar Lansia is focuses on providing benefits for all elderly residents on Jalan Skip Rahayu, Bumi Waras Village, which was welcomed and enthusiastically by involving the role of institutions and the community in its implementation which consists of several programs, namely, re-establishing the Posyandu for the Elderly, implementing ergonomic gymnastics for the elderly, and providing socialization or counseling on physical and psychological health of the elderly. This article is limited to the implementation of the Pejuang Muda Bandar Lampung City program in 2021.

IMPLEMENTASI SUPPORT VECTOR MACHINE DALAM MEMPREDIKSI HARGA RUMAH PADA PERUMAHAN DI KOTA BANDAR LAMPUNG Favorisen Rossyking Lumbanraja; Reza Aji Saputra; Kurnia Muludi; Astria Hijriani; Akmal Junaidi
Jurnal Pepadun Vol. 2 No. 3 (2021): December
Publisher : Department of Computer Science, Faculty of Mathematics and Natural Sciences, University of Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23960/pepadun.v2i3.90

Machine Learning has been widely used in terms of predictions for analyzing datasets. One method of Machine Learning is Support Vector Machine (SVM). The house has an important role in the survival of human beings. With the times, many developers are competing to build housing. The purpose of this study is to predicted the housing cost using Support Vector Machine. The data in this research used the data of house in Bandar lampung, the price, the location and the building specification. The amount of data used 51 datas and 33 variables with regression and classification, also used 3 kernels and it's model, 12 times first trial and next 6 experiments done with fitur selection. The trial result was kernel regression polynomial model reached the highest R 2 that was 95,99% linear kernel and gaussian kernel reached R 2 90,99% and 81,43% each. While in accuration classification model trial is obtained in 8 class of gaussian kernel as big as 91,18%, and linear kernel and polynimonal kernel get an accuracy of 90,20% and 89,90%.

Co-Authors - Damayanti Adawiyah, Laila Admi Syarif Aflaha Asri Ahyarudin Akbar, Mohammed Raihan Akmal Junaidi Amelia Jasmine Andrian, Rico Annisa Rizqiana Ardiansyah Ardiansyah Aristoteles, Aristoteles Asmiati Asmiati Astria Hijriani Astria Hijriani Aulia Putri Ariqa Ayu Amalia Bambang Hermanto Damayanti Damayanti Danu Sasmita Desti Fatmalasari Destian ade anggi Sukma Dian Kurniasari Didik Kurniawan Dwi Kartini, Dwi Dwi Sakethi Dwi Sakethi, Dwi Eliza Fitri Elly Lestari Rusitati Erdi Suroso Fanni Lufiana Fanni Lufiana Farida Ariyani Febi Eka Febriansyah Fitriyana, Silfia Hadi, Normi Abdul Hamim Sudarsono . Hdiana, Yazid Zinedine Heningtyas, Yunda Ilman, Igit Sabda Indah Pasaribu Ira Hariati Br Sitepu Irawati, Anie Rose Jasmine, Amelia Jihan Aferiansyah Junaidi Junaidi Junaidi Junaidi Kristina Ademariana Kurnia Muludi Kurnia Muludi Kurnia Muludi Lilies Handayani M. Juandhika Rizky Machudor Yusman Manurung, Yunita Rosalina Megawaty, Dyah Ayu Meria Nensi Muhammad Reza Faisal, Muhammad Reza Muhammad Rizki Muhaqiqin, Muhaqiqin Muliadi Mustofa Usman Nadila Rizqi Muttaqina Naurah Nazhifah Nirwana Hendrastuty Nova Ayu Lestari Siahaan Nugroho Susanto, Gregorius Nuning Nurcahyani Nurdin, Muhaymi Nurhasanah Nurhasanah Parabi, M. Iqbal Parjito , Parjito Prabowo, Rizky Pratama, Rinaldo Adi Priyambodo Priyambodo Priyambodo Priyambodo Qory Aprilarita Rahmat Safe'i Rangga Agustiantino Reza Aji Saputra RM Sulaiman Sani Rosdiana, Siti Rudy Herteno Rudy Herteno Rusitati, Elly Lestari Saragih, Triando Hamonangan Shofiana, Dewi Asiah Sholehurrohman, Ridho Sintiya Paramitha Siti Aisyah Solechah Siti Rosdiana Su'admaji, Arif Susanto, Gregorius Nugroho Sutyarso Sutyarso Sutyarso, - Syangap Diningrat Sitompul TANJUNG, AKBAR RISMAWAN Tiyara Saghira Tristiyanto Tristiyanto Wamiliana Wamiliana Wamiliana Warsono Warsono Warsono Warsono Warsono YOHANA TRI UTAMI, YOHANA TRI Zaenal Abidin Zuliana Nurfadlilah

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