The aim of the study was to make mortar with a fiber mixture that utilizes band strapping waste. The selection of strapping band material as fiber since this material is not environmentally friendly, the benefits of this research can reduce band strapping waste and increase the economic value of band strapping waste. This research was conducted to determine the optimum fiber concentration value which resulted in the value of split tensile strength, compressive strength of maximum mortar, fiber strapping band with a length of 50 mm and width of 2.5 mm in the composition of 0%, 1.25%, 2.5%, 3.75%, 5%. The size of the specimen is 150 mm in diameter and 300 mm in height for the split tensile strength test and the object size is 100 mm in diameter and 200 mm in height for the compressive strength test. The number of specimens is 35 pieces, with each composition as many as 3 samples. For compressive strength test using 15 test specimens and split tensile strength test using 15 test specimens. From the test results, the optimum composition occurs in 5% fiber strapping band with a maximum increase in compressive strength of 29.67% (40.3 Mpa), split tensile strength of 60.94% (1.03 Mpa). For volume weight of 100 × 200 mm decreased by 7.58% (1.955 gr / cm3) while for weight volume 150 × 300 mm decreased by 3.62% (1.868 gr / cm3). Due to the increased split tensile strength, this mortar mixture is suitable for the manufacture of plastering or mortar on the surface of the wall especially the outer wall.

The purpose of this study was to analyze the technical performance of team performance in an event of the main division in Indonesia. The sample of this study was the players’ performance of the winning team. The data were collected using the Volleyball Tactical Information Skill (VTIS) software which is originally developed by the researcher based on the Volleyball Information System (VIS). The data collected using the VTIS includes service, ball receive, attack, toss, block, and dig that was performed by each player throughout the game. The statistical data is presented on average and percentage. The statistical data obtained from VTIS has been proven to be useful and provides valuable information for the team's technical performance.

Underprivileged scholarships are assistance provided by government or institutions to students from poor families. Scholarships can be given to all students at the education level from elementary school to higher education with certain conditions and criteria. However, in reality many scholarships are given that are not on target. This is because of the number of students who register as scholarship recipients. Therefore, it is necessary to have a decision support system in order to aid the selection process. This study aims to find appropriate system to aid the underprivileged scholarship selection. This study proposed a system which was built using PHP for programming languages and using MySQL as its database using the Simple Additive Weighting method. Data is taken from SMK Sultan Agung 1 Jombang. Data is then analyzed and tested using the Blackbox testing method. Results of this research obtained a list of the best ranks of prospective scholarship recipients which are result of processing from system. The results obtained from system will be validated by means of comparisons with manual calculations as in Table 1. The validation results show same results, so that system can be said to be valid and can replace process that is done manually.

Waste has become a problem that is really worrying everywhere. If you pay close attention, there are indeed a number of factors that cause waste problems to become serious. First, population growth. Second, more and more instant food with plastic packaging. Third, the habit of littering, the habit of consuming instant food in packaging, to the habit of throwing garbage without sorting between organic and non-organic waste will damage the ecosystem. The same problem is also experienced by Berbek Village in Sidoarjo Regency, the problem of waste and flooding that is always faced by the city cannot only be the responsibility of the government, but the community as one of the producers of household waste should always help reduce the amount of waste. Thisneeds to provide an understanding to the community of environmental concerns, especially regarding household waste management and water conservation for the future based on water conservation. The results achieved from this activity are that the village community is aware of and understands the importance of a clean environment, there is no garbage scattered, puddles or floods can be reduced, and are able to practice independent waste management methods.

Diabetes adalah penyakit yang tidak menular dan termasuk cukup serius bagi manusia dikarenakan pankreas tidak mampu menghasilkan insulin secara optimal. Internasional Diabetes Federation (IDF) memperkirakan sedikitnya terdapat 463 juta orang pada usia 20-79 tahun di dunia menderita diabetes. Prevelensi diabetes diperkirakan meningkat seiring penambahan umur penduduk menjadi 19,9% juta pada tahun 2030 dan 700 juta pada tahun 2024. Oleh karena itu dibutuhkan sistem yang bertujuan untuk mendeteksi penderita penyakit diabetes. Penelitian ini menggunakan dua algoritma yaitu KNN dan Naive Bayes. Hal ini untuk memandingkan kedua algoritma yang memiliki tingkat akurasi yang terbaik. Algoritma KNN adalah algoritma yang digunakan untuk mengklasifikasi objek baru berdasarkan objek terdekatnya. Adapun Algoritma Naive Bayes adalah salah satu algoritma yang digunakan untuk klasifikasi sistematika yang dapat digunakan untuk memprediksi probabilitas keanggotaan dalam suatu class. Pada penelitian ini proses klasifikasi dilakukan dengan cara memasukkan data ke dalam tools Jupyter Notebook dan membuat rancangan proses penelitian. Dataset yang diambil oleh ibu Saptarum di Klinik Bidan Saptarum Maslahah Kabupaten Jombang dengan jumlah 50 data akan diolah dengan Algoritma KNN dan Naive Bayes. Tahap akhir menjadikan file dalam bentuk Data Pickle agar dapat direalisasikan kedalam sistem. Adapun hasil nilai akurasi Algoritma KNN dengan K=3 memiliki nilai sebesar 93%, sedangkan algoritma Naïve Bayes memiliki akurasi sebesar 95%.