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Front Matter and Back Matter

Pertanian kota dengan metode hidroponik saat ini menjadi solusi untuk mensiasati permintaan pasar terhadap sayur dan buah lokal yang dijual dengan harga relatif lebih murah dan hasil pertanian yang lebih sehat. Lahan kota yang terbatas, pilihan sayur yang sesuai, kondisi tanah, pupuk yang digunakan, gangguan hama, dan minat masyarakat terhadap sayur hidroponik atau keunggulan hidroponik, merupakan faktor – faktor yang mempengaruhi para petani sayur hidroponik di Pangkalpinang. Kondisi multi kriteria dan multi alternatif yang ada dalam pertanian kota dengan metode hidroponik ini membuat penelitian ini menggunakan metode Decision Support System (DSS) Analytical Hierarchy Process (AHP). AHP menyusun secara hirarki semua kriteria pendukung pengambilan keputusan, dan menghitung dengan matriks perbandingan berpasangan hasil penilaian responden ahli yang terlibat. Hasil pengolahan gabungan responden menunjukkan kriteria keunggulan hidroponik adalah faktor pendukung tertinggi dengan bobot 19,9% dan jenis sayur yang paling diminati adalah sawi putih dengan bobot 36,4%. Sistem pendukug keputusan ini mendorong petani sayur di Pangkalpinang untuk memiih bercocok tanam dengan metode hidroponik dengan mempertimbangkan kriteria –kriteria berikut, keungulan hidroponik, media tanam, hama, pertumbuhan usia panen, benih, dan pupukKata kunci: Pertanian Kota, Hidroponik, DSS, AHP Abstract[Urban Farming Decisions Support System of Narrow Lands in Pangkalpinang City Using Hydroponics Using Analytical Hierarchy Process Method] City agriculture with hydroponic methods is currently a solution anticipate market demand for local vegetables and fruits that are sold at relatively lower prices and healthier agricultural products. Limited urban land, suitable vegetable choices, soil conditions, fertilizers used, pest disorders, and community interest in hydroponic vegetables or hydroponic superiority are factors that influence the farmers of hydroponic vegetables in Pangkalpinang. The multi-criteria and multi alternative conditions that exist in urban agriculture with this hydroponic method make this research use the Analytical Hierarchy Process (AHP) Decision Support System (DSS) method. AHP arranges in a hierarchy all the decision support criteria and calculates with a paired comparison matrix of the assessment results of the expert respondents involved. The results of the combined processing of respondents showed the hydroponic superiority criteria was the highest supporting factor with a weight of 19.9% , and the most popular vegetable type was chicory with a weight of 36.4%. This decision support system encourages vegetable farmers in Pangkalpinang to choose to grow crops using the hydroponic method by considering the following criteria, hydroponic benefits, planting media, pests, growth of harvest age, seeds, and fertilizers.Keywords: City Agriculture, Hydroponics, DSS, AHP

Jamur memiliki kebutuhan tumbuh dengan suhu 16-22ºC dan kelembaban 80-90%, Jawa Barat merupakan sentra jamur karena di dataran tinggi seperti Pangalengan, Lembang, Cisarua, dan Cipanas, kawasan ini merupakan kawasan yang sangat baik untuk budidaya jamur tiram. Sedangkan daerah lain dapat berkembang menjadi tempat budidaya sebagai faktor lingkungan sesuai dengan pertumbuhan dan perkembangannya. Faktor lingkungan yang menentukan tanaman disekitarnya yaitu kelembaban media tanam, kelembaban relatif, kecepatan angin, suhu media tanam, dan unsur hara. Wajib dilakukan untuk mengatur suhu dan kelembaban yang membutuhkan biaya yang tidak sedikit. Solusi untuk masalah ini adalah menggunakan perangkat keamanan dan kelembaban dengan Raspberry pi. Raspberry merupakan komputer mini yang hanya membutuhkan daya hingga 10 Watt. Raspberry memiliki fasilitas IO port yang dapat dipasang dengan sensor suhu dan kelembaban. Selanjutnya dapat diukur suhu dan kelembaban yang terjadi dengan sensor tersebut. Pada penelitian ini dibuat sistem kendali suhu dan kelembaban dengan menyemprotkan air secara otomatis pada saat suhu dan kelembaban tinggi. Tujuan penelitian ini membuat sistem pengatur suhu yang dikembangkan dengan menggunakan bahasa pemrograman Python dan Android. Pengujian sistem kendali suhu dan kelembaban dilakukan dengan metode Black Box yaitu pengujian dengan melihat hasil sistem apakah keluaran dari sistem sesuai dengan yang diharapkan atau tidak. Hasil dari penelitian ini adalah sebuah alat yang dapat mengontrol suhu kumbung sesuai dengan kebutuhan tumbuh jamur sehingga meningkatkan hasil panen petani jamur dua kali atau lebih terutama pada musim kemarau.Kata kunci: Jamur Tiram, Raspberry, Metode Black Box Abstract[Raspberry Pi Development for Monitoring Temperature and Humidity to Increase Yields in Oyster Mushroom Cultivation]Mushrooms have growing requirements with temperatures of 16-22ºC and humidity of 80-90%, West Java is a mushroom center because in highlands such as Pangalengan, Lembang, Cisarua, and Cipanas, this area is a very good area for growing oyster mushrooms. While other areas can develop into a place of cultivation as an environmental factor in accordance with growth and development. While the environmental factors that determine the surrounding plants, the planting medium humidity, relative humidity, wind speed, temperature of the planting media, and nutrients. Required is done to regulate temperature and humidity which requires little cost. The solution to this problem is using a safety and humidity device with Raspberry pi. Raspberry is a mini-computer that only requires power up to 10 Watts. Raspberry has an IO port facility that can be installed with temperature and humidity sensors. Furthermore, it can be measured temperature and humidity in progress with these sensors. In this research, a temperature and humidity control system is created by spraying water automatically when the temperature and humidity are high. The purpose of this research is to make a temperature control system developed using the Python and Android programming languages. Testing of the temperature and humidity control system is carried out by the Black Box method, namely testing by seeing the system results whether the output from the system is as expected or not. The results of this study are a tool that can control the temperature of the lumbung according to the needs of growing mushrooms, thereby increasing the yield of mushroom farmers twice or more, especially in the dry season.Keywords: Oyster Mushroom, Raspberry, Black Box method

Corona virus (COVID-19) merupakan jenis virus baru yang ditemukan pada manusia di propinsi Wuhan, Cina pada bulan Desember 2019. Virus ini dapat menular dari manusia ke manusia melalui tetesan kecil (droplet) dari hidung atau mulut pada saat batuk, bersin, atau berbicara. Oleh karena itu, di masa pandemi ini sangat penting untuk menjaga jarak dengan orang lain dan menghindari wilayah dengan persebaran COVID-19 yang tinggi. Pada penelitian ini dilakukan klasterisasi persebaran virus Corona di DKI Jakarta dengan menerapkan metode data mining. Pengelompokan dilakukan berdasarkan parameter jumlah ODP, PDP, kasus Positif, pasien sembuh dan pasien meninggal. Pada penelitian ini, untuk melakukan klasterisasi data digunakan metode K-Means dan metode pengukuran jarak Euclidean. Penelitian ini menghasilkan prototipe aplikasi pengelompokan data persebaran pasien Covid-19. Berdasarkan pengujian, jumlah klaster yang direkomendasikan adalah 9 klaster. Hasil penelitian ini diharapkan dapat membantu pemerintah DKI Jakarta dalam mengambil keputusan strategis dalam mengurangi persebaran virus Corona di DKI Jakarta.Kata kunci: corona, Jakarta, klasterisasi, k-means Abstract[Corona Virus (Covid-19) Clustering in Jakarta using K-Means Method] Coronavirus (COVID-19) is a new type of virus found in humans in the province of Wuhan, China in December 2019. This virus can be transmitted from person to person through small droplets from the nose or mouth when coughing, sneezing, or talking. Therefore, during this pandemic, it is very important to keep your distance from other people and avoid areas with a high spread of COVID-19 In this study, the distribution of the Coronavirus in DKI Jakarta was clustered by applying the data mining method. The clustering was carried out based on the parameters of the number of ODP, PDP, positive cases, patients recovered and patients died. In this study, to perform data clustering, the K-Means method, and the Euclidean distance measurement method were used. This study produced a prototype application for the distribution of Covid-19 patient distribution data. Based on the test, the recommended number of clusters is 9 clusters. The results of this study are expected to help the DKI Jakarta government in making strategic decisions in reducing the spread of the Coronavirus in DKI Jakarta.Keywords: corona, Jakarta, clustering, k-means

Saham merupakan salah satu bentuk investasi yang mana merupakan surat berharga yang menjadi bukti kepemilikan seseorang atas suatu perusahaan. Pergerakan saham dari waktu ke waktu relatif tidak menentu dan tidak pasti, namun masih dapat diprediksi. Prediksi harga saham ini akan sangat berguna bagi investor untuk mengetahui bagaimana alur investasi bekerja pada setiap harga pada masing-masing harga saham yang berubah dari waktu ke waktu. Model prediksi pergerakan harga saham yang akurat dapat membantu para investor dalam pertimbangan pengambilan keputusan transaksi saham karena pergerakan harga saham yang cenderung non linier ini akan menyulitkan investor dalam melakukan prediksi. Dalam penelitian ini dilakukan prediksi harga saham PT. Telekomunikasi Indonesia menggunakan metode algoritma Support Vector Machine yang ditingkatkan kinerjanya menggunakan kernel RBF. Dari hasil pengujian dengan metode Support Vector Machine dihasilkan tingkat akurasi sebesar 0.9641 dan RMSE sebesar 0.0932. Pengujian juga dilakukan menggunakan algoritma k-Nearest Neighbors dengan tingkat akurasi sebesar 0.945 dan RMSE sebesar 0.1162. Dengan itu diketahui bahwa algoritma SVM memiliki tingkat akurasi yang lebih tinggi dan tingkat error yang lebih rendah dibangdingkan metode KNN.Kata kunci: prediksi, harga saham, support vector machine. Abstract[Stock Price Prediction Analysis of PT. Indonesian Telecommunications Using Methods Support Vector Machine] Stock is a form of investment which is a form of securities which is a proof of someone's ownership of a company. The movement of shares from time to time is relatively uncertain, but still predictable. This stock price prediction will be very useful for investors to find out how the flow of investment works at each price on each stock price that changes from time to time. An accurate prediction model of stock price movements can help investors in considering the decision of stock transaction because the stock price movements that tend to be non-linear will make it difficult for investors to make predictions. In this research a prediction of the stock price of PT. Telekomunikasi Indonesia uses the Support Vector Machine algorithm method which is improved in performance using the RBF kernel. From the results of testing with the Support Vector Machine method the accuracy level is 0.9641 and the RMSE is 0.0932. Tests are also carried out using the k-Nearest Neighbors algorithm with an accuracy level of 0.945 and an RMSE of 0.1162. Therefore, it is known that the SVM algorithm has a higher level of accuracy and a lower error rate than the KNN method.Keywords: prediction, stock price, support vector machine.

Identifikasi kebutuhan dalam pengembangan perangkat lunak merupakan langkah awal yang dilakukan dan mempengaruhi terhadap tahapan-tahapan pengembangan selanjutnya. Dalam tahap ini terdapat proses penentuan kebutuhan mengenai apa yang akan dibuat. Dalam tahap ini terdapat salah satu metode yang digunakan, yaitu User Persona. Teknik Personas yang dikembangkan oleh human-computer interaction (HCI) mengumpulkan data-data tentang pengguna, memperoleh pemahaman tentang kriteria mereka serta dapat mengetahui apa yang dibutuhkan oleh user pada system. Penelitian ini bertujuan menggunakan pendekatan pesona untuk mengetahui kebutuhan dan menganalisa keberagaman user yang memiliki perbedaan dari segi umur, jenis kelamin dan pengetahuan sehingga dapat dijadikan acuan dalam pengembangan sistem. Penggunaan pendekatan persona untuk menyelesaikan permasalahan dalam penyusunan materi modul praktikum dengan kemampuan mahasiswa agar dapat mengurangi kasus plagiasi source code pada waktu praktikum. Dari penelitian ini bahwa pengambilan data menggunakan pendekatan persona selanjutnya di analisis sesuai kebutuhan user, dan menghasilkan perangkat lunak yang dapat mengelola modul praktikum. Perangkat lunak ini memberikan akses bagi dosen, asisten laboratorium dan mahasiswa untuk dapat membagikan modul praktikum, mengerjakan soal latihan yang disesuaikan dengan Rencana Pelaksanaan Pembelajaran sebelum mengerjakan soal-soal praktikum dan menerima hasil praktikum lebih efektif dan mengurangi plagiarisme diantara mahasiswa.Kata Kunci – Persona, Metode, User Persona, HCI Abstract[Identification of Software Requirements using a Qualitative Study of the Persona User approach (Case Study: The Process of Making a Practicum Module with the Ability of Students to Reduce the Case of Source Code Plagiarism)] - Identification of requirements in software development is a very important initial stage and influences the subsequent stages of development. In this stage there is a process of determining the needs of what will be made. The method that will be used in this stage is User Persona. The Personas technique developed by human-computer interaction (HCI) collects data about users, obtains an understanding of their criteria and can find out what is needed by the user on the system. This study aims to use the charm approach to determine the needs and analyze the diversity of users who have differences in terms of age, gender and knowledge so that it can be used as a reference in system development. The use of a persona approach to solving problems in the preparation of practical module materials with the ability of students to reduce the case of source code plagiarism at the time of practicum. From this study the data collection by using the persona approach will be analyzed according to user needs, and produces software that could manage practice module. The purpose of this software is to provide access for lecturers, laboratory assistants, and students to be able to distribute practicum modules, do the excercises that are adjusted to the Learning Implemantation Plan before working on practicum questions and receive practical results more efectively, and reduce plagiarism among students.Keywords: Persona, Metode, User Persona, HCI

Indonesia merupakan negara hukum. Sebagai negara hukum, tentunya pembangunan terhadap substansi hukum perlu dilakukan, yaitu menunjukkan eksistensi hukum. Salah satu hal yang bisa dilakukan untuk menunjukkan eksistensi tersebut yaitu dengan melakukan dokumentasi terkait informasi hukum dengan membentuk Jaringan Dokumentasi dan Informasi Hukum (JDIH). Anggota JDIH tersebut terdiri dari berbagai macam instansi pemerintahan, salah satunya yaitu Kementerian. Di era Industri 4.0 saat ini tentunya adanya peraturan terkait teknologi informasi menjadi penting adanya. Namun, belum ada pengelompokan yang jelas untuk membagi berbagai peraturan masing-maisng kementerian menjadi beberapa peraturan yang serupa. Penelitian ini bertujuan untuk membuat clustering dari JDIH masing-masing kementerian dengan menggunakan parameter peraturan terkait teknologi informasi. Metode clustering yang digunakan yaitu metode K-Means Clustering. Dataset peraturan diambil dari website JDIH masing-masing kementerian dengan menggunakan kata kunci peraturan terkait teknologi informasi. Dari hasil analisis didapatkan bahwa JDIH Kementerian bisa dikelompokkan menjadi 4 cluster dari total 28 JDIH Kementerian. Cluster pertama berisi 12 kementerian, Cluster kedua berisi 13 Kementerian, Cluster ketida berisi 2 Kementerian, dan Cluster keempat berisi 1 Kementerian. Hal tersebut menggambarkan bahwa masing-masing JDIH Kementerian yang masuk dalam 1 cluster yang sama memiliki keterkaitan dan kesamaan.Kata kunci: Jaringan Dokumentasi dan Informasi Hukum, K-Means Clustering, Kementerian, Teknologi Informasi. Abstract[Analysis of the Network of Documentation and Legal Information of the Ministry about Information Technology Using the K-Means Clustering Method] Indonesia is a state of law. As a state of law, the development of the legal substance needs to be carried out, that is, to show the existence of law. One of the things that can be done to demonstrate that existence is to do documentation related to legal information by forming a Legal Documentation and Information Network (JDIH). JDIH members consist of various government agencies, one of which is the Ministry. In the current era of Industry 4.0, the existence of regulations related to information technology becomes essential. However, there has not been a clear grouping to divide the various regulations of each Ministry into several similar regulations. This study aims to make the clustering of JDIH of each Ministry by using regulatory parameters related to information technology. This research uses the K-Means for the clustering method. The regulatory dataset is taken from the JDIH website of each Ministry by using regulatory keywords related to information technology. From the results of the analysis, it was found that JDIH Ministries can be grouped into 4 clusters from a total of 28 JDIH Ministries. The first cluster contains 12 ministries, the second cluster contains 12 Ministries, the third cluster contains 2 Ministries, and the fourth cluster contains 1 Ministry. This illustrates that each JDIH Ministry that falls into the same 1 cluster has interrelations and similarities.Keywords: Documentation Network and Legal Information, Information Technology, K-Means Clustering, Ministry

Penjurusan siswa di suatu sekolah merupakan suatu proses penempatan siswa ke dalam jurusan tertentu sesuai dengan kemampuan dan keinginan siswa. Madrasah Aliyah Al-Falah (MA Al-Falah) merupakan sekolah yang sederajat dengan Sekolah Menengah Atas (SMA) dan memiliki tiga jurusan yaitu Ilmu-ilmu Keagamaan (IIK), Matematika dan Ilmu Alam (MIA), dan Ilmu-ilmu Sosial (IIS). Saat ini proses penjurusan di MA Al-Falah dilakukan dengan melakukan empat jenis tes yaitu matematika, bahasa Indonesia, bahasa Inggris, dan keagamaan terhadap siswa. Hasil tes tersebut dijadikan dasar penentuan jurusan siswa. Permasalahan yang dihadapi oleh pihak sekolah adalah kesulitan dalam mengklasifikasikan siswa berdasarkan hasil tes penjurusan tersebut. Saat ini teknik penjurusan yang dilakukan sekolah hanya mengandalkan pengolahan data dan pengurutan dengan Microsoft Excel. Pada penelitian ini, dilakukan penerapan metode Naïve Bayes Classifier untuk melakukan klasifikasi nilai tes dan menghasilkan rekomendasi jurusan siswa. Sistem klasifikasi penjurusan siswa yang dikembangkan dapat membantu proses penjurusan siswa dengan lebih mudah, cepat, dan akurat. Berdasarkan pengujian yang telah dilakukan sistem penjurusan siswa dapat memberikan rekomendasi jurusan siswa dengan nilai akurasi sebesar 33,34%.Kata kunci: penjurusan siswa, naïve bayes, sistem klasifikasi Abstract[The Implementation of Naïve Bayes Classifier Method for Student Majorization at Madrasah Aliyah Al-Falah Jakarta] Student majorization in a school is a process of placing students into certain majors according to their abilities and desires. Madrasah Aliyah Al-Falah (MA Al-Falah) is a school equivalent to High School and has three majors namely Religious Sciences (IIK), Mathematics and Natural Sciences (MIA), and Social Sciences (IIS). Currently the majors at MA Al-Falah are carried out by carrying out four types of tests namely mathematics, Indonesian, English, and religion on students. The test results are used as the basis for determining student majors. The problem faced by the school is the difficulty in classifying students based on the results of the majors test. Currently the majors that schools use rely solely on data processing and sequencing with Microsoft Excel. In this study, the Naïve Bayes Classifier method was implemented to classify test scores and produce recommendations for student majors. The student majors classification system developed can help students' majors process more easily, quickly, and accurately. Based on the testing that has been done the student majors system can provide student majors recommendations with an accuracy value of 33,34%.Keywords: student majors, naïve bayes, classification system

Di Indonesia khususnya di Provinsi DKI Jakarta sampai saat ini Demam Berdarah Dengue masih merupakan masalah kesehatan masyarakat yang utama. Meski sudah ada beberapa langkah untuk mengatasi penyebaran penyakit Demam Berdarah Dengue (DBD), namun harus ada metode analisis untuk melakukan peramalan terhadap kasus DBD menggunakan serangkaian data yang ada, dan memperkirakan nilai data dimasa yang akan datang. Penelitian ini bertujuan untuk membuat model forecasting peningkatan jumlah kasus Demam Berdarah Dengue menggunakan algoritma regresi linear dan melakukan analisis pengaruh dari temperatur, kelembapan dan curah hujan dalam kanaikan kasus penyakit Demam Berdarah Dengue di Provinsi DKI Jakarta dari model regresi yang dibuat. Data DBD yang digunakkan merupakan dataset pemantauan penyakit endemik yang diperoleh dari Dinas Kesehatan DKI Jakarta sedangkan data cuaca merupakan dataset yang didapat dari Dinas Lingkungan Hidup DKI Jakarta. Dari model regresi yang dibuat diperoleh nilai R2 sebesar 0.3622, hal tersebut menunjukan presentase pengaruh variabel predictor terhadap kasus demam berdarah sebesar 36.22%, sedangkan 63.78% dipengaruhi oleh faktor lain diluar variabel independen tersebut.Setelah melakukan uji simultan, dapat disimpulkan bahwa temperatur, kelambapan, dan curah hujan secara bersama-sama berpengaruh terhadap kenaikan jumlah kasus demam berdarah di Provinsi DKI Jakarta. Selanjutnya uji parsial membuktikan bahwa, kelembapan dan curah hujan memiliki pengaruh signifikan terhadap kenaikan kasus demam berdarah, sedangkan untuk variabel bebas, temperatur terbukti tidak memiliki pengaruh yang signifikan terhadap kenaikan kasus demam berdarah dengue di Provinsi DKI Jakarta.Kata kunci: Data Mining, Predictive Mining, Regresi Linier, Demam Berdarah Dengue Abstract[Forecasting Model of Dengue Hemorrhagic Fever in DKI Jakarta Using Linear Regression Algorithm to Know Trends of Predictor Variable Value for Case Increasing] In Indonesia specifically in DKI Jakarta Province, Dengue fever is still the main public health problem. Although there are already several steps to overcome the spread of Dengue Fever (DHF), there still needs to be an analytical method to forecast the increase dengue cases using and estimated data values in the future. This study aims to make a forecasting model for increasing the number of cases of Dengue Fever using a linear regression algorithm and analyzing the effect of temperature, humidity and rainfall in the case of Dengue Hemorrhagic Fever in DKI Jakarta Province from a regression model made. The DHF data used is an endemic disease monitoring dataset obtained from the DKI Jakarta Health Office while the weather data is a dataset obtained from the DKI Jakarta Environmental Service. From the regression model made, the value of R2 is 0.3622, it shows the percentage of the influence of temperature, humidity and rainfall on cases of dengue fever is 36.22%, while 63.78% is influenced by other factors outside the independent variable. After conducting a simultaneous test, it can be concluded that temperature, humidity and rainfall together, influence the increase in the number of dengue cases in DKI Jakarta Province. Then the partial test proves that humidity and rainfall have a significant influence on the increase in dengue cases, whereas for temperature independent variables proved that no significant effect on the increase in cases of dengue hemorrhagic fever in DKI Jakarta Province.Keywords: Data Mining, Predictive Mining, Linear Regression, Dengue Fever (DHF)

Penggunaan media sosial semakin hari semakin meningkat. Salah satu media sosial yang popular saat ini adalah Twitter. Menjelang pemilihan Presiden Republik Indonesia semakin banyak tweet yang membahas tentang kegiatan tersebut. Hal ini menyebabkan topik kampanye pemilu memiliki peluang yang baik untuk dilakukan proses analisis sentimen. Saat ini, mayoritas analisis sentimen di Indonesia dilakukan hanya menilai sentimen dari kalimat tanpa mengetahui apa entitas yang ada dalam kalimat. Tujuan penelitian ini yaitu melakukan analisis sentimen dengan pendekatan berbasis ontologi. Ontologi digunakan dalam menyaring data yang akan digunakan. Ontologi dalam penelitian ini adalah ekonomi dengan atribut finansial, lapangan kerja, dan kesejahteraan. Proses analisis sentimen dilakukan dengan metode Lexicon-based dan Support Vector Machine (SVM). Proses akuisisi data diperoleh sejumlah 700.000 tweet. Koleksi tersebut diseleksi berdasarkan ontologi ekonomi menghasilkan 16.998 tweet dan dilakukan pelabelan manual sebanyak 1.600. Kemudian dilakukan pengolahan data hingga diperoleh dataset final sejumlah 1.050 tweet. Berdasarkan hasil penelitian yang dilakukan akurasi yang diperoleh berdasarkan metode Lexicon-based adalah 39% dan metode SVM sebesar 83%. Dari penelitian ini diketahui bahwa SVM mempunyai performa yang lebih baik dibandingkan dengan Lexicon-based. Hasil Lexicon-based menunjukkan bahwa sentimen pada mayoritas atribut berupa netral. Sedangkan hasil SVM menunjukkan bahwa sentimen pada mayoritas atribut (finansial dan kesejahteraan) berupa positif, sisanya (lapangan kerja) berupa netral. Selanjutnya, proses ekstraksi dan pembuatan ontologi Bahasa Indonesia secara semi-otomatis pada dataset perlu untuk dikembangkan pada penelitian berikutnya untuk menyempurnakan ontologi.Kata kunci: Analisis Sentimen, Twitter, Ontology, SVM, Lexicon Abstract[Comparison of the Lexicon-based and SVM Method for Ontology-Based Analysis of the 2019 Presidential Election Campaign on Twitter] The use of social media is increasing. One of the most popular social media is Twitter. Towards the election of the President of the Republic of Indonesia, election topic tweets discussed almost every day. Hence, it is suitable for the sentiment analysis process. Nowadays, the sentiment analysis is only evaluating the sentence without knowing what the entity is in the sentence. To overcome this drawback, we propose a sentiment analysis based on ontology. Ontology is used to filter the data to be used. The ontology used in this study is economics with attributes, i.e., financial employment, and welfare. The sentiment analysis process is carried out using the Lexicon and Support Vector Machine (SVM) based methods. The process of acquiring data obtained 700,000 tweets. The collection was selected based on economic ontology to produce 16,998 tweets, and 1,600 manual labels were labelled. Then, the number of the final dataset is 1,050 tweets. The results show that the accuracy of the Lexicon-based method is 39%, and the SVM method is 83%. The SVM has better performance than Lexicon-based. Lexicon-based results show that the sentiment on the majority attributes is neutral. While the SVM results show that the sentiment on the majority attributes (financial and welfare) is positive, the rest (employment) is neutral. A semi-automatic ontology extraction and development for Bahasa Indonesia is necessary for the future works to make a comprehensive ontology and provide better results. Keywords: Sentiment Analysis, Twitter, Ontology, SVM, Lexicon

Peminatan studi pada STMIK Amik Riau merupakan pilihan minat berdasarkan kemampuan khusus dan ketertarikan mahasiswa. Program studi Teknik Informatika STMIK Amik Riau memiliki dua bidang peminatan, yaitu bisnis dan jaringan. Peminatan disesuaikan dengan kemampuan dan ketertarikan dari mahasiswa serta harus dipilih dengan baik dan tepat. Pengambilan peminatan sangat berpengaruh terhadap tugas akhir dan tingkat kelulusan mahasiswa. Pemilihan peminatan studi oleh mahasiswa saat ini hanya mengikuti teman dan tidak berdasarkan kemampuan, sehingga sebuah Sistem klasifikasi peminatan merupakan salah satu solusi untuk menyelesaikan permasalahan pemilihan peminatan pada program studi karena dianggap mampu memberikan rekomendasi pemintan yang baik dan tepat. Algoritma K-Nearest Neighbor (K-NN) merupakan algoritma klasifikasi yang dapat digunakan sebagai solusi dalam pengelompokan data. Pada penelitian ini data yang digunakan diperoleh dari nilai mata kuliah prasyarat selama semester satu hingga semester lima. Data diolah dengan membangun aplikasi yang menerapkan algoritma K-NN menggunakan PHP dan MySQL. Hasil keluaran sistem memiliki akurasi 100% dibandingkan hasil perhitungan manual menggunakan Ms. Excel. Pengujian menggunakan tools RapidMiner untuk mengukur performa algoritma. Hasil pengujian yang dilakukan terhadap 183 data latih dan 100 data uji menyatakan algoritma K-NN memiliki performa dengan hasil Acuracy, Recall, Precision, F Measure, dan Clasificassion Error dengan nilai 98%, 100%, 100%, 91.67%, dan 2%. Penelitian ini dapat memberikan rekomendasi peminatan studi kepada mahasiswa Teknik Informatika STMIK Amik Riau.Kata kunci: Peminatan studi, klasifikasi, algoritma K-NN Abstract[Implementation of K-Nearest Neighbor Algorithm For Determining Concentration of Study at Informatics Engineering Program of STMIK AMIK RIAU] Concentration of study at STMIK Amik Riau is a choice of interests based on special abilities and student interests. Informatics Engineering Program at STMIK Amik Riau has two subjects of interest, namely business and networking. The study concentration is tailored to the abilities and interests of students and must be chosen properly and correctly because it is very influential on the final assignment and graduation level of students. The classification system of interest is one of the solutions to solve the problem of choosing a concentration in the study program because it is considered capable of providing good and appropriate spinning recommendations. K-Nearest Neighbor (K-NN) is one of classification algorithm that can be used as a solution in classifying data. In this study, the data used was obtained from the value of prerequisite courses during semester one to semester five. Data is processed by building applications that implement the K-NN algorithm using PHP and MySQL. The output of the system has 100% accuracy compared to the results of manual calculations using Microsoft Excel. The Testing process used RapidMiner software to measure algorithm performance. The results of the tests carried out on 183 training data and 100 test data stated that the K-NN algorithm had a performance with the results of Accuracy, Recall, Precision, Measure, and Classification Error with values of 98%, 100%, 100%, 91.67%, and 2 %. This study can provide a system that can help to give some study concentration recommendations to the student of Informatics Engineering Program at STMIK Amik Riau.Keywords: Study Interest, Classification, K-Nearest Neighbor (K-NN) Algorithm

The success of the implementation of smart villages is based on the success of the village in carrying out digital transformation with Information and Communication Technology (ICT) as the driver. As a result, villages need an ICT development center which is better known as telecentre. Telecentres contribute to the social and economic development of villages with ICT as the key. In Indonesia, the establishment of telecentres is increasingly prevalent, but until now it was felt that it still did not show its success. The difficulties that arise are, constraints on information and financial management to pay for connectivity, equipment maintenance and telecentre staff salaries. The purpose of this study is to provide a telecentre development model in the form of a Village-Owned Enterprise based on hybrid organizational theory. This research approach was carried out qualitatively with a case study of Lamahu Village, Bone Bolango, Gorontalo. The process of collecting data through interviews, and the results of interviews were analyzed by interpretation into hybrid organizational theory. The results showed that the telecentre development needs to review 3 aspects, namely (1) the establishment of telecentres must have a mission as a social enterprise engaged in the implementation of ICT-based appropriate technology, (2) telecentres in the form of a legal entities Village Owned Enterprise so that they have the opportunity to obtain financial resources from external (CSR) and internal (village funds) and finally (3) telecentre human resources must involve the village community from origin so that they can help the effectiveness of interaction and ensure the sustainability of ICT adoption.

Rough set theory is one of the mathematical models for dealing with a vague, imprecise, and fuzzy knowledge that has been successfully used to handle incomplete information systems. Since, in fact in the real-world problems, often found the conditions that are the user can not provide all the necessary preference values. In this research, an implementation of extension technique of rough set theory that called limited tolerance relation is used to overcome incomplete information systems in student data at Telkom University. Based on the obtained results, the limited tolerance relation technique successfully used to handle that problem. The results show that the technique achieved the accuracy of 96.04% with an execution time of 3.1830 seconds.

Lectures schedule management in campus is an important aspect that must be implemented in every period. The schedule will be managed well if avoided from collision of the room, time, and lecturer. To overcome collision problem it's necessary to make mitigate system to avoid schedule changes frequently caused by collision of room, time, and lecturer. Thus, the author design and build SIM-DRaW (Sistem Informasi Manajemen Dosen, Ruang, dan Waktu) web-based to fulfill needs and overcome schedule management system. The final result of the design and build SIM-DRaW is implemented information system that can help schedule manager to avoid collision earlier.

One indicator of college efficiency is the study period of the students. It is important for university managers to improve the ratio of students who graduate on time. This research aims to analyze the characteristics that affect the study period of students from academic data. The methods used are association rule mining (ARM) and clustering. We propose a framework to analyze academic data using ARM dan clustering method. ARM method is a method to find association rules that meet minimum support and minimum confidence. The algorithm used is Apriori. While clustering using Simple Expectation-Maximization (EM-clustering) algorithm. Simple EM is a model-based algorithm that searches for maximum likelihood estimation in the probability model. The variables analyzed were student achievement index, province of the students, and type of high school. The analysis is done using WEKA. Research begins with the collection of data from the primary source of the Biro Administrasi Akademik (BAA) Universitas Muhammadiyah Malang (UMM). Then, we do the data cleaning and transformation. Analyzing process is done in two step. First, do a rule search using Apriori algorithm. The regulated parameters are the minimum support and minimum confidence value. Second, we use Simple EM algorithm for the clustering process. The experiments were conducted to find the clustering result with the largest log likelihood value. Based on the experiment, the method used successfully describes the characteristics based on the study period.

The problems office in the utilization of wireless technology has widely used but sometimes without take into the number of users, so it is not mangkus. The networking system for small office can be use wireless simple system. Most of the office has applied hotspot but that is old system, one account for all people using internet access. Single sign-on is a system services of hotspot, this system verifying an account for each user so people have different and username dan a password. The methodology used is literature review, analysis, design, implementation, testing and analysis of the data transfer rate. The hotspot with a single sign-on system using mikrotik, and access point, the connected with networking devices in the office. Winbox tools is used to configuration. Testing with the user had been connected to the hotspot system single sign on. Methods of test to user login on the system single sign-on is the black box texting. Testing the speed of data transfer is used staff user and guest user who uploaded three types of files to the drive with diffrent bandwidth. Then the network sniffing is used tools wireshark. The results from this study is simple hotspot service with single sign-on system for office and from the analysis of the data transfer rate was known the data transfer rate on the staff user and guest user to the three types of file is a type of word files greater than PDF and PPT.

A word processor is a tool used for writing text in which a word processing application has a function can perform text editing and printing. In making the word processing application is used programming languages C ++ Builder 5.0. The logic flow of this first-word processing application user will be presentedwith a form where there is a place to write the text. Within these forms are also several main menus in which there is a menu that is used to create new documents, the menu is used to edit the text, the menuis used for printing, as well as a menu that is used to store documents that support the format: txt, rtf, doc.

Sistem navigasi digunakan sebagai penunjuk arah suatu tempat. Namun, penggunaan navigasi pada smartphone dapat memberikan dampak pada kurangnya kefokusan dan konsentrasi khususnya pengendara motor roda dua. Hal ini telah tertuang dalam UU No. 22 Tahun 2009 menjelaskan tentang Lalu Lintas dan Angkutan jalan mengenai berkendara dengan penuh konsentrasi. Melihat fenomena tersebut, penulis menemukan inovasi baru yang menggunakan NodeMCU yang digunakan dalam menjalankan modul speaker yang akan digunakan untuk sistem navigasi menggunakan suara pada helm. Suara yang dikeluarkan berasal dari Google Maps yang digunakan untuk menunjukkan arah (navigasi) pada helm. Penelitian ini menggunakan platform berbasis IoT dan menggunakan modul Wi-Fi sebagai penghubung antara aplikasi google maps dan smartphone. Hasil ujicoba alat kepada lima orang pengguna diperoleh hasil bahwa 80% pengendara yang mengunakan helm dengan sisten navigasi mengunakan suara lebih fokus dan juga lebih akurat dibandingkan pengendara yang menggunakan GPS melalui layar smart phone.Kata Kunci: NodeMCU, Sistem Navigasi, Smart Helm, Google Maps Abstract[Design and Build Navigation System Using Sound on Helmet] The navigation system is used as a direction to a place. However, navigation on a smartphone can have a slight impact on focusing and give the two wheels a professional feel. It has been stated in Law no. 22 of 2009 describes road traffic and transportation about driving with full concentration. Seeing this phenomenon, the authors found an innovation that uses Node NodeMCU, which is used in running the speaker module used for navigation systems using sound on the helmet. The sound emitted comes from Google Maps which is used to show the direction (navigation) on the helmet. This study uses an IoT-based platform and uses a Wi-Fi module to link the google maps application and a smartphone. Testing the tool to five people showed that 80% of users who use helmets with navigation use a more focused voice and are also more accurate than users who use GPS through a smartphone screen.Keywords: NodeMCU Nodes, Navigation Systems, Smart Helmet

PT Indo Cafco adalah sebuah perusahaan penampung biji kopi robusta dari para petani kopi, khususnya di daerah kabupaten Lampung Barat. Dari hasil penampungan biji kopi robusta akan dipasarkan kepada para konsumen, baik dalam perdagangan nasional ataupun perdagangan internasional (ekspor) berdasarkan nilai mutunya. Akan tetapi tidak dapat dipungkiri bahwa dalam menentukan kualitas biji kopi masih banyak masalah atau kendala yang akan dihadapi. Pemilihan nilai mutu kopi robusta setidaknya dilakukan dalam waktu 5 jam dalam sekali uji nilai mutu dengan menguji maksimalnya 10 karung pada setiap uji, sehingga pemilihan biji kopi robusta dapat berlangsung berhari-hari. Fokus dari penelitian ini adalah mengembangkan sistem pendukung keputusan dengan menerapkan metode TOPSIS dalam pemilihan biji kopi robusta yang bernilai mutu ekspor. Metode TOPSIS dipilih karena metode ini menggunakan prinsip bahwa alternatif yang terpilih harus mempunyai jarak terdekat dari solusi ideal positif dan terjauh dari solusi ideal negatif, sehingga kinerja alternatif dapat terukur. Penelitian ini menghasilkan apliasi pendukung keputusan pemilihan biji kopi bermutu ekspor yang mempermudah pengambil keputusan karena dilengkapi dengan rekomendasi hasil dan perengkaingan kelayakan kopi. Berdasarkan pengujian akurasi dengan membandingkan hasil analasis dari pakar dengan sistem mendapatkan tingkat akurasi 84% dan tergolong kriteria baik.Kata kunci: topsis, kopi robusta, sistem pendukung keputusan Abstract[Implementation of the TOPSIS Method in Decision Support Systems Selection of Robusta Coffee Beans with Value of Export Quality (Case Study: PT. Indo Cafco Fajar Bulan Lampung)] PT Indo Cafco is a Robusta coffee bean storage company from coffee farmers, especially in West Lampung regency. From the results of Robusta coffee beans will be marketed to consumers, both in national trade and international trade (exports) based on quality value. However, it cannot be denied that in determining the quality of coffee beans there are still many problems or obstacles that will be faced. The selection of Robusta coffee quality values is done at least within 5 hours in one test of the quality value by testing a maximum of 10 sacks in each test, so that the selection of Robusta coffee beans can last for days. The focus of this research is to develop a decision support system by applying the TOPSIS method in the selection of robusta coffee beans with export quality value. The TOPSIS method was chosen because it uses the principle that the chosen alternative must have the shortest distance from the positive ideal solution and the farthest from the negative ideal solution, so that alternative performance can be measured. This research resulted in an application of decision support for the selection of export quality coffee beans that made decision makers easier because it was equipped with recommendations on the results and competitiveness of coffee. Based on testing the accuracy by comparing the results of analysis from experts with the system get an accuracy rate of 84% and classified as good criteria.Keywords: topsis, robusta coffee, decision support system

Perkuliahan yang ditempuh 4-5 tahun mempengaruhi perkembangan fisik. Penelitian ini menggunakan data video digital mahasiswa. Hasil rekaman video digunakan untuk data set menentukan ciri tertentu yang dimiliki mahasiswa nantinya tersimpan dalam katalog database file digital. Dimulai dari konversi video .mp4 menjadi format .AVI. Algoritma CAMShift menggunakan dasar warna HSV untuk pelacakan posisi wajah (tracking) dan mengenal wajah (recognition). Video durasi 1-2 detik menghasilkan 45-200 frame format PNG. Algoritma CamShift melakukan penghitungan nilai Hue data sample. Hasil seleksi area bounding box disimpan dalam database wajah. Tracking wajah menggunakan Meanshift switching Matlab–OpenGL. Penelitian bertujuan mendokumentasikan profil wajah berbentuk digital berdasarkan warna dominan kulit. Hasil uji pencocokan wajah dilakukan pada beberapa video play, keberhasilan deteksi: 100% terseleksi, 45%-60%, 80-90%, disimpulkan sekitar 50%-100% berhasil. Gerakan wajah akan tertangkap centroid bounding box, bila warna wajah dominan Hue.Kata kunci: Algoritma Camshift; Database Wajah; Real Time; Seleksi Wajah; Warna Hue; Abstract[Real Time for Digital Face Database Selection Using Camshift Algorithm] Education taken 4-5 years affects physical development. This study uses student digital video data. The recording results are used to identify certain characteristics possessed by a student later stored in the digital file database catalog. The stages of the study consisted of identification, recognition and matching of faces. It starts from converting .mp4 videos to .AVI format. The CAMShift algorithm uses basic HSV colors for tracking face position (tracking) and faces recognition. 1-2 seconds video produces 45-200 frames PNG file. The research aims to document the digital profile of a face based on the dominant color of the skin. The face matching test results were carried out on several video play, the success of detection: 100% selected, 45%-60%, 80-90%, concluded around 50%-100% successful. Face movements will be caught by the centroid bounding box, if the color of the face is dominant in HueKeywords: Camshift Algorithm, Database Faces Face Selection; Hue Color; Real Time

Untuk mematuhi Peraturan Presiden No. 95 Tahun 2019 tentang Sistem Pemerintahan Berbasis Elektronik(SPBE), Pemerintah Kabupaten Bandung Barat harus mampu menyelaraskan layanan bisnis dengan teknologi informasi yang ada, khususnya pada fungsi promosi Dinas Pariwisata dan Kebudayaan. Enterprise Architecture merupakan salah satu metode yang dapat digunakan untuk menyelaraskan strategi bisnis dengan teknologi informasi dan mendukung program SPBE. Dalam melakukan perancangan EA dibutuhkan framework arsitektur untuk mengembangkan lingkup pembahasan secara luas dari sisi bisnis, aplikasi, data, dan teknologi. Framework yang digunakan pada perancangan ini adalah TOGAF ADM yang terdiri dari 9 fase. Pada penelitian ini, peneliti mengambil studi kasus pada Fungsi Promosi dengan menjadikan Government Service Bus (GSB) sebagai teknologi utama. Enterprise Architecture yang diharapkan dapat mempermudah pencapaian tujuan strategis, peningkatan proses bisnis, sistem informasi, dan teknologi informasi yang digunakan. Dari penelitian ini akan dihasilkan output berupa cetak biru dari rancangan enterprise architecture fase information system pada fungsi promosi Dinas Pariwisata dan Kebudayaan. Penilitian ini dapat menjadi referensi untuk pengembangan lebih lanjut hingga fase change management architecture.Kata kunci: SPBE, Enterprise Architecture, TOGAF ADM, GSB Abstract[Information System Architecture Analysis and Design Using TOGAF ADM in Promotion Function (Case Study: Department of Tourism and Culture in Bandung Barat Government)]. To approve Presidential Regulation No. 95 of 2019 concerning Electronic Based Government Systems (SPBE), the Government of West Bandung Regency must provide aligning business services with existing information technology, specifically in the promotion function of the Office of Tourism and Culture. Company architecture is one method that can be used to align business strategies with information technology and support the SPBE program. In designing an EA, an architectural framework is needed to develop broader, business, application, data and technology approvals. The framework used in this design is TOGAF ADM which consists of 9 phases. In this study, researchers took a case study on the Promotion Function by making the Government Service Bus (GSB) the main technology. The company architecture is expected to achieve strategic objectives, business process improvement, information systems, and information technology used. This research will produce output in the form of a blueprint of the architecture of the enterprise information system phase of the promotion of the Department of Tourism and Culture. This research can be a reference for further development until the phase of management architecture change TOGAF ADM.Keywords: SPBE, Enterprise Architecture, TOGAF ADM, GSB

Racing video game genre was still being popular today. One way to develop racing games quickly is by using a template or kit that is on the game engine. Racing Game Starter Kit (RGSK) was being the most popular racing game template for Unity game engine. However, there was problem in racing game’s NPC especially in RGSK related to NPC vehicle’s braking decision. The commonly used method is the Brake Zone, but the developers must manually place the zone themselves in the designated locations for braking. The solution that can be applied for that problem is see the angle formed by the vector of the NPC vehicle with the vector from 2 next following waypoint then determine the best configuration angle threshold for NPC braking, but this also has its shortcoming in which to get the best result, a proper threshold configuration is needed in each track. To resolve the problem, researcher proposed the method of machine learning, Naïve Bayes for the braking decision. Naïve Bayes uses two output classes (brake or no brake) in which the data will be obtained from the player. We use data from players who can control racing car games well or have never hit a wall and have fast lap times. The purpose of this study is to provide an alternative braking method to RGSK that can provide fast lap times but does not affect the game's FPS and without the need to determine or change any parameters on each track. The test result using RGSK v1.1.0a in Unity Game Engine showed that the proposed method can be an alternative method in RGSK braking decisions. Our NPC has faster lap time and was able to prevent the vehicle from crashing with the outer wall without dropping the game’s FPS (Frames per Second).Keywords: Braking Decision, Racing Game Starter Kit, Naïve Bayes, Machine learning, Unity engine AbstrakGenre video gim balap masih populer saat ini. Salah satu cara untuk mengembangkan game balap dengan cepat adalah menggunakan template atau kit yang ada di game engine. Racing Game Starter Kit (RGSK) adalah templat game balap paling populer pada Unity Game Engine. Namun, terdapat permasalahan NPC pada gim balapan terutama di RGSK terkait dengan keputusan pengereman kendaraan NPC. Metode yang digunakan untuk eksperimen jenis ini adalah Zona Rem. Namun, pengembang harus secara manual menempatkan zona tersebut di lokasi tertentu pada setiap lintasan. Solusi dari masalah ini yang sudah diterapkan pada RGSK v1.1.0a yaitu dapat menggunakan sudut yang dibentuk oleh vektor kendaraan NPC dengan vektor dari 2 titik arah berikutnya, kemudian menentukan ambang sudut terbaik untuk pengereman NPC, tetapi ini juga memiliki masalah yaitu untuk mendapatkan hasil putaran terbaik atau cepat, perlu menentukan konfigurasi ambang batas yang tepat di setiap trek. Untuk mengatasi masalah tersebut, peneliti mengusulkan metode pembelajaran mesin, Naïve Bayes untuk keputusan pengereman. Naïve Bayes menggunakan dua kelas output (rem atau tidak ada mengerem) di mana data akan diperoleh dari pemain. Kami menggunakan data dari pemain yang dapat mengontrol permainan mobil balap dengan baik atau tidak pernah menabrak tembok dan memiliki waktu putaran yang cepat. Tujuan dari penelitian ini adalah untuk memberikan metode pengereman alternatif untuk RGSK yang dapat memberikan waktu putaran yang cepat namun tidak mempengaruhi FPS game dan tanpa perlu menentukan atau mengubah parameter apa pun di setiap trek. Hasil pengujian menggunakan RGSK v1.1.0a di Unity Game Engine menunjukkan bahwa metode yang diusulkan dapat menjadi metode alternatif dalam keputusan pengereman RGSK. NPC kami mempunyai waktu putaran yang lebih cepat dan mampu mencegah kendaraan agar tidak menabrak dinding luar tanpa menjatuhkan FPS game (Frame per Detik).Kata kunci: Keputusan Pengereman, Racing Game Starter Kit, Naïve Bayes, Pembelajaran Mesin, Unity Engine

STMIK Amik Riau menggunakan sistem informasi akademik dalam memberikan pelayanan terhadap mahasiswa dan kegiatan akademik lainnya seperti e-KRS, e-EDOM, Labkom, e-library, e-ktm, e-BAAK, PMB, dan lain sebagainya. Evaluasi sistem merupakan salah satu cara untuk mengetahui sistem dapat berjalan dengan baik dan optimal dalam memberikan layanan yang lebih efektif dan efisien. Audit TI digunakan untuk mengukur tingkat kematangan (maturity level) dari SIASAR dan memberikan rekomendasi terhadap sistem. Penelitian berfokus pada terhadap mahasiswa sehingga framework audit Information Technology Infrastucrure Library (ITIL) v3 sesuai karena terdapat domain khusus yang dapat mengukur tingkat kematangan dari SIASAR yaitu Domain Service Operation. Analisa berupa penyebaran kuisioner kepada pengguna atau yang terlibat dengan sistem secara langsung SIASAR. Berdasarkan perhitungan sistem SIASAR masih pada level 2 (repeatable) dengan nilai 1,78 dimana sistem SIASAR saat ini sudah memiliki sebuah tingkat kedisiplinan dan kepatuhan terhadap peraturan dan standar operasional yang berlaku. Rekomendasi yang dapat diberikan berupa peningkatan proses pendokumentasian, standarisasi, dan pengukuran serta pencatatan pada seluruh unit yang ada pada STMIK Amik Riau.Kata kunci: STMIK Amik Riau, ITIL V3, Maturity Level, Service Operation Abstract[Maturity Level Analysis of Academic Information Systems STMIK Amik Riau using ITIL V3 Domain Service Operation] STMIK Amik Riau uses academic information systems in providing services to students and other educational activities such as e-KRS, e-EDOM, Labkom, e-library, e-KTM, e-BAAK, PMB, and so on. System evaluation is one way to find out the system can run well and optimally in providing more effective and efficient services. IT audits are used to measure the maturity level of SIASAR and provide recommendations on the system. The research focuses on students so that the Information Technology Infrastructure Library (ITIL) v3 audit framework is appropriate because there is a unique domain that can measure the maturity level of SIASAR, namely Domain Service Operation. The analysis is in the form of distributing questionnaires to users or those involved with the SIASAR system directly. Based on the calculation, the SIASAR system is still at level 2 (repeatable) with a value of 1.78 where the SIASAR system currently has a level of discipline and compliance with applicable regulations and operational standards. Recommendations can be given in the form of improving the process of documentation, standardization, and measurement and recording of all units in STMIK Amik Riau.Keywords: STMIK Amik Riau, ITIL V3, Maturity Level, Service Operation

The use of data that has long stored in the information system can be utilized to know information that supports decision-making activities. One of them is sales transaction data. During this time, the case of sales transaction data is rarely analyzed to be taken into consideration when taking a decision, such as analyzing the transaction data. The prediction analysis of the transaction should analyze the inflation factors that affect earnings. It is predicted that inflation will lead to an increase in the price of basic necessities which can also lead to employers tend to raise the price of products to be sold. Therefore, this research focuses to analyze sales transaction data at a restaurant. Where the data used is data that has been stored for 3 years within the period 2015-2017. The purpose of this study is to determine the quality comparison of sales predictions of sales between years with regard to inflation based on changes in selling prices. The result of the study is known that the prediction of goods sold with actual data in the following year is quite significant and the prediction of income is not affected by the inflation based on price comparison.

In most organizations, candid moments on held events should be captured as images for administrative purposes. For instance, if an event is sponsored by third parties, it is necessary to send some images capturing moments on that event to them. However, human resources are required to capture such images, resulting additional operational cost. This paper proposes a method to capture candid moments without human intervention. Unique to this method, daily device (i.e., mobile phone) is used to replace human resource with the help of a phone holder and a dedicated mobile application. Prior capturing images, given mobile application should be installed to the mobile phone and such phone should be attached to the phone holder that is aimed at event area. Candid images can be then automatically collected by running installed mobile application. According to our evaluation, such method can replace human resource for capturing candid moments using daily device. Further, it is more efficient than video recording (i.e., an alternative to capture candid moments) in terms of used battery power and memory.

Android Malware has grown significantly along with the advance of the times and the increasing variety of technique in the development of Android. Machine Learning technique is a method that now we can use in the modeling the pattern of a static and dynamic feature of Android Malware. In the level of accuracy of the Malware type classification, the researcher connect between the application feature with the feature required by each type of Malware category. The category of malware used is a type of Malware that many circulating today, to classify the type of Malware in this study used Support Vector Machine (SVM). The SVM type will be used is class SVM one against one using the RBF Kernel. The feature will be used in this classification are the Permission and Broadcast Receiver. To improve the accuracy of the classification result in this study used Feature Selection method. Selection of feature used is Correlation-based Feature Selection (CFS), Gain Ratio (GR) and Chi-Square (CHI). A result from Feature Selection will be evaluated together with result that not use Feature Selection. Accuracy Classification Feature Selection CFS result accuracy of 90.83%, GR and CHI of 91.25% and data that not use Feature Selection of 91.67%. The result of testing indicates that permission and broadcast receiver can be used in classifying type of Malware, but the Feature Selection method that used have accuracy is a little below the data that are not using Feature Selection.

Health services are basic services whose implementation is protected and guaranteed by the government. The existence of BPJS makes health services easier, more secure, and reachable to all levels of society. When a patient's health condition requires a higher facility, patients are generally referred to a higher-level health facility. In the province of Bangka Belitung currently stands several hospitals with various levels and completeness of facilities, ranging from provincial public hospitals, local public hospitals, to private hospitals. Patients who need referral can adjust the choice of the hospital with their health condition. The diverse needs of referral health care services and the diversity of hospitals with their services make decision making difficult. This study focuses on analyzing what factors are the basis of patient consideration in choosing a referral hospital. To support the multicriteria and multi-alternative selection process, this study uses the Analytical Hierarchy Process (AHP). The results of data processing showed that the most important criterion for patients when choosing a referral hospital was a health service attribute weighing 19.2% and the patients referred to were mostly referral patients in wards of wards with a weight of 24.2%.

Use of information technology facility as supporting support vision mission university need to be proven to prove, only with any of the measurement. Infrastructure audit of information technology on online test information system (SIUJO) faculty of technique is a form of measurement the maturity level in formation technology which the purpose is identifying the early possible risk so the process of faculty's bussiness is not trouble. Doing infrastructure audit of information technology using framework cobit 4.1 focus on subdomain AI3 and AI5 with respondent according to RACI. Audit of information technology infrastructure SIUJO shows the result that the maturity level is still on the current level 1. It is necessary for gradual improvement efforts between three years to maturity level 3 to 4. By doing audit earlierly, bussiness process expected to support the faculty.

Language center of state Polytechnic of cilacap is an english language training institution, and one of them is TOEFL test. Academic data processing of Language Center still uses conventional ways. Some of them are registering and data processing of participants. The result of TOEFL test is still conducted using microsoft excel. The growth of education and technology is demanding the language center to make innovation in improving service and interaction that can be accepted well. The system will be developed by using based web and dekstop that function to quicken registering process, performance, and eficiency in administration data processing and scoring TOEFL in Language Center. By internet/intranet media, it will ease in registering process and data processing through dekstop without having a need many conventional activities.

Decision making by considering is very important in an institution. Generally, in choosing a solution of the problem is only take from a meeting, discussion or vote among the leader of each division. But it usually needs more time if the problems are the repetitive and less measurable, then it takes an application so that decision-making to be effective, efficient, systematic and measurable. This application use decision table method to classifies each risk by considering the scale of likelihood and consequence, then of both these parameters will be taken risk management matrix that will determine the best solution. This application not absolutely and only help to give the recommendation with the minimum value, so on each solution and risk have a value and the test results of the respondents indicated that the application is able to assist institutions in decision-making as much as 50 percent.

The use of surveillance cameras are commonly used in place or room that is considered vulnerable, not only monitor but also can provide a sense of security for its users. This study discusses concerning fire detection and motion detection using a webcam for security room. Fire detection using the method of fire threshold RGB values by comparing each frame images captured by the webcam as data input, at the motion detection algorithm using blob calculation. Warning system used SMS gateway and sent to the specified server. The results show the value range RGB flame 218-248, 240-250, 242-252 and the use of motion detection complementary security systems built.