ANALISIS DAN PERANCANGAN SISTEM INFORMASI REKAM MEDIS SEBAGAI SARANA PELAYANAN KESEHATAN PADA PUSKESMAS OESAPA KOTA KUPANG

Puskesmas merupakan instansi yang bergerak dibidang pelayanan jasa kesehatan masyarakat. Pada zaman sekarang telah banyak di bangun Rumah Sakit akan tetapi di daerah pelosok atau desa yang ada masih Puskesmas yang berfungsi sebagai usaha preventif (pencegahan) dan operatif (penanggulangan) terhadap upaya-upaya kesehatan masyarakat. Puskesmas Oesapa merupakan salah satu instansi pemerintahan di bidang kesehatan yang memiliki peranan sangat penting dalam meningkatkan kesehatan masyarakat di Kota Kupang. Masalah utama dalam penelitian ini adalah proses pelayanan yang ada di puskesmas Oesapa masih dilakukan secara manual. Dengan dibuatnya aplikasi system informsdi Rekam Medis diharapkan dapat meningkatkan kualitas pelayanan terutama Informasi data pasien, data rekam medis, data kunjungan pasien, data penerimaan obat, data pengeluaran obat, dan data dokter , data persediaan obat dapat dicari dengan mudah dan dengan waktu yang relatif singkat

Pengolahan Citra Digital Perbandingan Metode Histogram Equalization Dan Spesification Pada Citra Abu-abu

A digital image processing software has been successfully constructed. The software can increase image contrast using the histogram equalization method. The results given by the equalizaton histogram method can improve image quality, so that the information in the image is more clearly seen. But not all digital images have a visual display that satisfies the human eye. Dissatisfaction can arise due to noise, the lighting quality in digital images that are too dark or too bright. So that a method is needed to improve the quality of the digital image. To improve image quality in terms of color contrast, we can give treatment to the histogram. The treatment referred to in this article is an equalization histogram on grayscale images. Image histogram is said to be good if it is able to involve all possible levels or levels at the gray level. Of course the goal is to be able to display details on the image so that it is easy to observe. The process of segmenting and repairing digital images is done using MATLAB

PENGOLAHAN CITRA DIGITAL PERBANDINGAN METODE HISTOGRAM EQUALIZATION DAN SPESIFICATION PADA CITRA ABU-ABU

A digital image processing software has been successfully constructed. The software can increase image contrast using the histogram equalization method. The results given by the equalizaton histogram method can improve image quality, so that the information in the image is more clearly seen. But not all digital images have a visual display that satisfies the human eye. Dissatisfaction can arise due to noise, the lighting quality in digital images that are too dark or too bright. So that a method is needed to improve the quality of the digital image. To improve image quality in terms of color contrast, we can give treatment to the histogram. The treatment referred to in this article is an equalization histogram on grayscale images. Image histogram is said to be good if it is able to involve all possible levels or levels at the gray level. Of course the goal is to be able to display details on the image so that it is easy to observe. The process of segmenting and repairing digital images is done using MATLAB

Analisis Metode Cycle Crossover (Cx) Dan Metode Partial Mapped Crossover (Pmx) Pada Penyelesaian Kasus Traveling Salesman Problem (Tsp)

Travelling Salesman Problem (TSP) is a form of a problem in optimizing the search for the shortest route by passing through every city in exactly one time. The problem of searching the shortest route of a location can be solved by using many other optimizing algorithms. In this research, genetics algorithm was used by using two crossover methods namely cycle crossover and partial-mapped crossover. The parameters used were crossover probability and mutation probability, the sum of the city, maximum generation, the sum of the population and also threshold. In this research two testing models were used. In the first one, in order to get the generation and the best fitness it used the 80% consistency stopping criteria, and in the second one, in order to get the best testing time, it  used the 100 and 500 maximum generation stopping criteria. The result of the first test showed that PMX method is better than the CX one. This was shown through the 8 times of testing which the result was the best PMX generation was 104,0469 and the CX was 350,4563. The second test resulted that the best testing time of the PMX time was 1,1035 second and the CX method was 2,2374 second, thus, it can be concluded that the solution brought by the PMX method is considered better than the CX

Implementasi Sistem Pendukung Keputusan Pemilihan Lokasi Lahan Padi Sawah Tadah Hujan Menggunakan Metode Fuzzy Multi Attribute Decision Making (FMADM

Tujuan dari penelitian ini adalah membangun sistem pemilihan lokasi lahan sawah di Kabupaten Kupang Timur. Permasalahan tujuan penelitian adalah membuat sistem seleksi lokal lahan sawah di Kabupaten Kupang Timur. Hal itu menyebabkan petani di Kupang Timur kesulitan dalam menentukan lahan yang akan digunakan untuk menanam padi jenis ini. Sedangkan di wilayah Kupang Timur, pemilihan jenis lahan tetap dilakukan tanpa mengecek kesuburan tanah atau kondisi tanah. Dengan demikian, informasi pendukung keputusan untuk mendefinisikan sawah juga tidak akurat dan membuat petani di Kupang Timur terancam gagal panen. Oleh karena itu, penelitian ini menggunakan sistem pengambilan keputusan fuzzy multi-attribute decision-making (FMADM), yang memiliki 13 alternatif dan 7 kriteria, dimana nilai preferensinya adalah suhu 20%, curah hujan 20%, kelembaban 20%, drainase 13%, tekstur tanah. 13%, kedalaman tanah 7% dan pH H₂O 7%. Data lahan sebanyak 60 orang petani digunakan sebagai data uji untuk perhitungan dan diperoleh persentase tertinggi dari opsi terpilih yaitu lahan Cristovel Ullu dengan kode opsi Desa Oesao yang memiliki hasil tertinggi sebesar 0,966. Hasil pengujian UAT dilakukan terhadap 9 responden dengan total 5 pertanyaan untuk mengetahui kepuasan responden terhadap kegunaan fungsi, kesesuaian antarmuka sistem dan informasi yang disediakan oleh system dan hasilnya adalah 90,212 %

PENALARAN BERBASIS KASUS UNTUK MENDIAGNOSA PENYAKIT INFEKSI MENULAR SEKSUAL (IMS) MENGGUNAKAN ALGORITMA WEIGHTED EUCLIDEAN DISTANCE

Case-based reasoning is a methodology for solving problems by utilizing previous experience. In this study the authors apply case-based reasoning to diagnose sexually transmitted infection using the weighted Euclidean distance method. Source of the knowledge base was obtained by collecting medical record of patients with sexually transmitted infections in 2016-2017. The process of finding a solution starts with eliminating irrelevant data using the C4.5 method and continues with the calculation of the similarity value using the Weighted Euclidean Distance algorithm. This system can diagnose 5 types of sexually transmitted infections based on 123 existing symptoms. System result in the form of sexually transmitted infections based on symptoms experienced by the patient, treatment solution and presentation of similarities between new cases and old cases. Based on the result of testing with 127 cases of sexually transmitted infections obtained result: testing uses the K-Fold Cross Validation scenario, the total data is divided into 10fold and the testing process is divided into 2 parts, namely testing using indexing and testing without using indexing. For testing using the highest accuracy indexing obtained at 90.84% in the second fold, and the average accuracy of the entire fold is 88.55% with the average time generated 9498 ms (millisecond), while testing without using the highest accuracy indexing obtained by 63.03% in the second fold, and the average accuracy of the entire fold is 53.48% with the average time generated 9975 ms (millisecond).  Penalaran Berbasis Kasus adalah sebuah metedologi untuk penyelesaian masalah dengan memanfaatkan pengalaman sebelumnya. Pada penelitian ini penulis menerapkan penalaran berbasis kasus untuk mendiagnosa penyakit infeksi menular seksual menggunakan metode weighted euclidean distance. Sumber basis pengetahuan diperoleh dengan mengumpulkan berkas rekam medis pasien penyakit infeksi menular seksual pada tahun 2016-2017. Proses pencarian solusi dimulai dengan mengeliminasi data yang tidak relevan menggunakan C4.5 dan berlanjut dengan perhitungan nilai kemiripan menggunakan algoritma weighted euclidean distance. Sistem ini dapat mendiagnosis 5 jenis penyakit infeksi menular seksual berdasarkan 123 gejala yang ada. Hasil sistem berupa jenis penyakit infeksi menular seksual berdasarkan gejala yang dialami pasien, solusi pengobatan dan presentasi kemiripan kasus baru dengan kasus lama. Berdasarkan hasil pengujian dengan 127 kasus infeksi menular seksual (IMS) didapatkan hasil: Pengujian menggunakan skenario K-Fold Cross Validation, total data dibagi menjadi 10 fold dan proses pengujian dibagi menjadi 2 bagian yaitu pengujian menggunakan indexing dan pengujian tanpa menggunakan indexing. Untuk pengujian menggunakan indexing akurasi tertinggi yang didapat sebesar 90.84% pada fold ke-2, dan rata-rata akurasi dari keseluruhan fold adalah sebesar 88.55% dengan rata-rata waktu yang dihasillkan 9498 ms (milidetik) sedangkan pengujian tanpa menggunakan indexing akurasi tertinggi yang didapat sebesar 63.03% pada fold ke-2, dan rata-rata akurasi dari keseluruhan fold adalah sebesar 53.48% dengan rata-rata waktu yang dihasilkan 9975 ms (milidetik). &nbsp

DIAGNOSA HAMA DAN PENYAKIT PADA TANAMAN PADI MENGGUNAKAN METODE NAIVE BAYES DAN K-NEAREST NEIGHBOR

This study builds systems Case Based Reasoning (CBR) to diagnose pests and diseases in rice plants using Naïve Bayes algorithm and K-Nearest Neighbor. CBR is one method of solving the problem with new cases of decision making based on the solution of previous cases by calculating the degree of similarity (similarity), The case consists of 13 species and 10 types of disease pests of rice plants. The degree of similarity can be determined by indexing and nonindexing. Indexing is the process of grouping the cases by classes that have been determined, while nonindexing a process without grouping cases. Based on cross validation testing using average values obtained accuracy of 92.88% to 153 test data on testing using the indexing and the average value of 89.63% accuracy of the test data in the test 153 using nonindexing. Penelitian ini membangun sistem Case Based Reasoning (CBR) untuk mendiagnosis hama dan penyakit pada tanaman padi menggunakan algoritma Naïve Bayes dan K-Nearest Neighbor. CBR merupakan salah satu metode pemecahan masalah dengan pengambilan keputusan kasus baru berdasarkan solusi dari kasus–kasus sebelumnya dengan cara menghitung tingkat kemiripan (similarity). Kasus ini terdiri dari 13 jenis hama dan 10 jenis penyakit tanaman padi. Tingkat kemiripan dapat ditentukan dengan cara indexing dan nonindexing. Indexing merupakan proses pengelompokkan kasus yang ada berdasarkan kelas yang telah ditentukan, sedangkan nonindexing merupakan proses tanpa pengelompokkan kasus. Berdasarkan pengujian menggunakan cross validation didapatkan nilai rata-rata akurasi 92,88% terhadap 153 data uji pada pengujian menggunakan indexing dan nilai rata-rata akurasi 89,63% terhadap 153 data uji pada pengujian menggunakan nonindexing

Kombinasi Steganografi Bit Plane Complexity Segmentation (Bpcs) dan Kriptografi Data Encryption Standard (Des) untuk Penyisipan Pesan Teks pada Citra Bitmap Grayscale 8 Bit

Bit Plane Complexity Segmentation (BPCS) is steganography method that using uncapability of human\u27s vision in interpreting difficult biner form. Data Encryption Standard (DES) is cryptography algorhytm that is chiper block and changing data become blocks 64 bit and then using encryption key amount 56 bit. By combining steganography algorhytm and cryptography will increase quality of data security. In this research combination of BPCS and DES done by inserting text message into bitmap image, the increating text message restricted maximum 248 characteristic with the long of the key must 16 characteristic in hexsadecimal format. The result obtained by this system testing with image test about 30 images is the inserting text can be read again with the provision of using the same key for inserting process and reading text. This image of insertion result can\u27t stand to adding contrast operation (25%) and rotation (90 to the right, 90 to the left, 180) and cutting operation on the upper side dan left image, but if cutting on the lower side and right (image resolution > 100 piksel) the inserting text can be read again correctly. In image inserting result, will be found noise of the upper left side from image because these region is the initial region is inserted

ANALISIS METODE CYCLE CROSSOVER (CX) DAN METODE PARTIAL MAPPED CROSSOVER (PMX) PADA PENYELESAIAN KASUS TRAVELING SALESMAN PROBLEM (TSP)

Travelling Salesman Problem (TSP) is a form of a problem in optimizing the search for the shortest route by passing through every city in exactly one time. The problem of searching the shortest route of a location can be solved by using many other optimizing algorithms. In this research, genetics algorithm was used by using two crossover methods namely cycle crossover and partial-mapped crossover. The parameters used were crossover probability and mutation probability, the sum of the city, maximum generation, the sum of the population and also threshold. In this research two testing models were used. In the first one, in order to get the generation and the best fitness it used the 80% consistency stopping criteria, and in the second one, in order to get the best testing time, it  used the 100 and 500 maximum generation stopping criteria. The result of the first test showed that PMX method is better than the CX one. This was shown through the 8 times of testing which the result was the best PMX generation was 104,0469 and the CX was 350,4563. The second test resulted that the best testing time of the PMX time was 1,1035 second and the CX method was 2,2374 second, thus, it can be concluded that the solution brought by the PMX method is considered better than the CX

Multinomial Naive Bayes untuk Klasifikasi Status Kredit Mitra Binaan di PT. Angkasa Pura I Program Kemitraan

Status classification of partner acordiing to sector parimeter, loan disbursement, loan reimbursment, loan arrears, remaining loan and grace period is very important in anticipating the case in PT. Angkasa Pura I. Problematic credit is very unbeneficial for the PT. Angkasa Pura I because it will disturb the economy condition of a company and will affect the next small and medium enerprises (SME). To solve this, the reserch uses Multinominal Naive Bayes to method to classify the partners status in the PT. Angkasa Pura I according to the parimeter that is divided into 4 clases namely smooth class, less smooth class, doubted and jammed class. The process used was classification process where it calculated probability value and the atribute of the partner. The data used in this research is consisted of 148 that taken from 2012-2015. The final result, after the classification is done, the class probability value that was taken randomly is gained, with the resuld to system test with 5 times of testing data division that is taken randomly, it is gained the accuracy as big as 86,56%, precision is as big as 73%, recall is as big as 73% and F-1 Measure is as big as 73%